Rationality Concepts in Environmental Valuation

Frör, Oliver Book — Digitized Version Rationality Concepts in Environmental Valuation Hohenheimer volkswirtschaftliche Schriften, No. 58 Provided in Cooperation with: Peter Lang International Academic Publishers Suggested Citation: Frör, Oliver (2007) : Rationality Concepts in Environmental Valuation, Hohenheimer volkswirtschaftliche Schriften, No. 58, ISBN 978-3-631-75515-0, Peter Lang International Academic Publishers, Berlin, https://doi.org/10.3726/b14029 This Version is available at: https://hdl.handle.net/10419/182961 Standard-Nutzungsbedingungen: Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden. Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen. 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If the documents have been made available under an Open Content Licence (especially Creative Commons Licences), you may exercise further usage rights as specified in the indicated licence. https://creativecommons.org/licenses/by/4.0/ Rationality Concepts in Environmental Valuation HOHENHEIMER VOLKSWIRTSCHAFTLICHE SCHRIFTEN Oliver Frör Survey based valuation techniques like the Contingent Valuation Method (CVM) rely particularly on the premise of respondents‘ rationality when answering willingness to pay (WTP) questions. Results of CVM surveys have repeatedly put this fundamental assumption into question. This study adopts a more realistic view of rationality accounting for respondents‘ limited capacities to process information. Based on cognitive psychology a technique to detect and analyze the bounds of rationality inherent in WTP statements is developed. Using an empirical example, the influence of bounded rationality on the validity of CVM results is analyzed. It is shown that individual differences in information processing play a major role. From these results recommendations for future survey design are developed. Oliver Frör; 1998 Degree of a Diplom-Geoökologe, University of Bayreuth; 2000 M.A. in Economics, State University of New York at Albany, NY; 2000–2001 Consultant at the New York State Department of Economic Development; 2001 Adjunct faculty at Siena College in Loudonville, NY; since 2001 Scientific Assistant at the Department of Economics, especially Environmental Economics, Regulatory and Consumer Policy at the University of Hohenheim; 2007 Doctoral degree. HOHENHEIMER VOLKSWIRTSCHAFTLICHE SCHRIFTEN Oliver Frör Rationality Concepts in Environmental Valuation Rationality Concepts in Environmental Valuation Hohenheimer Volkswirtschaftliche Schriften Herausgegeben von Prof. Dr. Michael Ahlheim, Prof. Dr. Thomas BeiBinger, Prof. Dr. Ansgar Belke, Prof. Dr. Rolf Caesar, Prof. Dr. Harald Hagemann, Prof. Dr. Klaus Herdzina, Prof. Dr. Walter Piesch, Prof. Dr. lngo Schmidt, Prof. Dr. Ulrich Schwalbe, Prof. Dr. Peter Spahn, Prof. Dr. Jochen Streb, Prof. Dr. Gerhard Wagenhals, Banctss ~ PETER LANG Frankfurt am Main •Berlin• Bern •Bruxelles• New York• Oxford . Wien Oliver Fror Rationality concepts in Environmental Valuation £ PETER LANG Frankfurt am Main. Berlin. Bern• Bruxelles• New York• Oxford• Wien Open Access: The online version of this publication is published on www.peterlang.com and www.econstor.eu under the international Creative Commons License CC-BY 4.0. Learn more on how you can use and share this work: http://creativecommons. org/licenses/by/4.0. This book is available Open Access thanks to the kind support of ZBW – Leibniz-Informationszentrum Wirtschaft. ISBN 978-3-631-75515-0 (eBook) Bibliographic Information published by the Deutsche Nationalbibliothek The Deutsche Nationalbibliothek lists this publication in the Deutsche Nationalbibliografie; detailed bibliographic data is available in the internet at <http://www.d-nb.de>. :£ Zugl.: Hohenheim, Univ., Diss., 2007 D 100 ISSN 0721-3085 ISBN 978-3-631-57336-5 © Peter Lang GmbH lnternationaler Verlag der Wissenschaften Frankfurt am Main 2007 All rights reserved. All parts of this publication are protected by copyright. Any utilisation outside the strict limits of the copyright law, without the permission of the publisher, is forbidden and liable to prosecution. This applies in particular to reproductions, translations, microfilming, and storage and processing in electronic retrieval systems. Printed in Germany 1 2 3 4 5 7 www.peterlang.de Acknowledgments The work on this dissertation has been a long journey and during its course many people kept me company and have contributed to its completion in one way or many others. Most importantly, I would like to thank my first adviser and academic mentor Prof. Dr. Michael Ahlheim who guided my work in many lateevening discussions and provided invaluable advice and support. I am also indebted to my second adviser Prof. Dr. Dr. h.c. Franz Heidhues for numerous helpful discussions and important comments and suggestions on earlier versions of this dissertation. Special thanks shall be given to my former colleague at the institute Dr. Ulrike Lehr who was never too busy to listen to my unfinished thoughts and who was always available for comments, consultation and consolation, if needed. During the final phase of my work, my colleagues Isabell Benignus and Andreas Zahn took over some of my duties, for which I am very grateful. I am especially indebted to my family and my parents who never ceased to believe in my ideas and supported my work with a lot of understanding despite the long evenings and weekends I had to take off for this purpose. The completion of this work is certainly as much a relief for them as it is for me. I would also like to thank the team of the Sonderforschungsbereich 564, both in Germany and in Thailand, whose support in all matters of the research project was of great help. In Thailand, special thanks shall be given to my colleague and fellow researcher Nopasom Sinphurmsukskul, as well as to his assistant Ailada Yathuam. Without their ceaseless help the research project on which my dissertation is based would simply not have been possible. Finally, I would like to thank the Deutsche Forschungsgemeinschaft DFG who funded the research project and provided for this particularly rich and interesting time. V ii List of Tables 3-1 The development of the Bounded Rationality field from 18401995 ·································································································· 62 3-2 Features of the four elementary dual-process designs ..................... 83 4-1 The Rational Experiential Inventory . . . . . . . . . . . . . ... . . .. .. . . . . . . . ... . . ... . . . . . . . .. .. 111 4-2 Task independent scale -the question items ................................... 118 4-3 Task dependent scale -the question items .................... .................. 119 4-4 Bid design of the DC and the PC elicitation question formats ........ 129 4-5 Distribution ofresponses in the split-sample design ....................... 132 4-6 Values of household size, age and income....................................... 133 4-7 Average household WTP for the tap water improvement scenario.. 136 4-8 Parameter estimates of the explanatory variables (covariates) of WTP for the DC and for the PC samples ......................................... 140 4-9 Factor loadings of the task independent bounded rationality scale ... 143 4-10 Factor analytical results of the REI items only ................................ 145 4-11 Results of the single question items of question 18 ... .. .... ...... .......... 146 4-12 Factor loadings of the task dependent bounded rationality scale (DC) ...................................................................................................... 148 4-13 Factor loadings of the task dependent bounded rationality scale (PC) ...................................................................................................... 150 4-14 Correlations among the task independent factors (TIF) and the task dependent factors (TDF) ........................................................... 152 4-15 Bounded rationality scales as explanatory factors of WTP for the DC dataset . . . .. .. ... . . . . ... . . . . . . . . . . . .. . . .. . . . . . . . . . . . . . ... .. . .. . . . . . .. . . .. .. . .. .. . . ... . . . . .. . . . . 161 4-16 Bounded rationality scales as explanatory factors ofWTP for the PC dataset .. .. . . . .. . . .. . . .. . . . . . . . . . . . . . . . . . . . . . . . . . . .. .. .. .. . .. . . . . . . . . . . . .. . . . . . . . . . .. . . . . . . . . . . . 163 4-17 Number of respondents classified in each cognitive type factor (DC format) ... ................................................................ ................... 165 4-18 Number ofrespondents classified in each cognitive type factor (PC format) ....................................................................................... 165 4-19 Determination of the starting point bias for the DC format .... ......... 168 4-20 Determination of the anonymity and range biases .................. .. ....... 169 XIII iii ABM ABCM cdf CEST CRT CV CVM DBDC DC EBA EEG ELM EV FI fMRI FtF HPM HSM MBDC MRWW MS NFC NOAA OE PC PET PVM REI List of Abbreviations Averting Behavior Method Attribute Choice Modelling cumulative (probability) distribution function Cognitive-Experiential-Self Theory Cognitive Reflection Test Hicksian Compensating Variation Contingent Valuation Method Double-Bounded Dichotomous Choice Dichotomous Choice Elimination By Aspects heuristic Electro Encephalography Elaboration Likelihood Model Hicksian Equivalent Variation Faith-in-Intuition functional Magnet Resonance Imaging Face-to-Face Hedonic Pricing Method Heuristic Systematic Model Multiple-Bounded Dichotomous Choice Mae Rim Water Works Mail Survey Need-for-Cognition National Oceanographic and Atmospheric Administration Open Ended format Payment Card Positron Emission Tomography Participatory Valuation Method Rational Experiential Inventory xv REil REI2 RUM SBDC SFB TCM TDF TDFl DC TDF2 DC TDF3 DC TDFl PC TDF2 PC TDF3 PC TDF4 PC TIF TIFl TIF2 TIF3 TIF4 w. r. t. WTA WTP XVI Intuitive-experiential REI Analytical-rational REI Random Utility Model Single-Bounded Dichotomous Choice Collaborative Research Center (Sonderforschungsbereich) Travel Cost Method Task Dependent Factor Uncertain TDF for the DC respondents Analytical TDF for the DC respondents Elimination TDF for the DC respondents Uncertain TDF for the PC respondents Analytical TDF for the PC respondents Equal TDF for the PC respondents Elimination TDF for the PC respondents Task Independent Factor Intuitive-experiential TIF Analytical-rational TIF Cautious TIF Cognitive miser TIF with respect to Willingness-to-Accept Compensation Willingness-to-Pay 1 Introduction 1.1 Motivation and scope The use of economic valuation methods has become a regular instrument for the assessment of the desirability of public investment projects aiming at the improvement or conservation of environmental goods. This tendency reflects the understanding that the existence of environmental goods or amenities on the one hand has a beneficial impact on various functions in society as well as in the economy, however, on the other hand comes at the cost of forgone economic possibilities or at additional public funds to be expended for conservation or rehabilitation efforts. The improvement of urban air quality through a reduction of particle emissions or the conservation of natural areas by preventing industrial development, for example, require considerations regarding the expected benefits from such measures in relation to the costs to be incurred by society as a whole. Especially in times of increasing fiscal constraints it is of particular importance to possess reliable and transparent indicators for changes in society's well-being resulting from such environmental projects for the process of public policy decision making. The special properties of environmental goods, however, pose a number of problems for the measurement of benefits they generate for society. In principle, environmental goods belong to the so called non-market goods. Examples of such environmental goods are the possibility to breathe clean air or the knowledge of the existence of certain biological plant and animal species. As in the latter example, environmental goods often have the character of pure public goods characterized by non-excludability and non-rivalry in consumption. For non-market goods a number of difficulties with respect to the assessment of the benefits they provide to society are generally encountered. The assessment of such benefits becomes relevant in case projects are carried out that go along with changes in the quality or the quantity of environmental goods provided. As is well known in the case of market commodities for which excludability from consumption holds the minimum benefit an individual derives from the consumption of such a good can easily be inferred from its price. An individual will only consume a commodity if the benefit from consuming it makes up at least for the costs of purchasing it, otherwise he would not be willing to pay the price asked. The absence of market prices for environmental commodities, therefore, constitutes the main difficulty of assessing the benefits derived from their existence or consumption, or, in case of a public project resulting in a change of their quantity or quality, of assessing the change of benefits to society. The aim of assessing such social benefits from a project producing or conserving an environmental good is the determination of some figure that enables a comparison of derived benefits against incurred costs. Since costs are in general conveniently measured in monetary terms it has proven useful to develop methods that are able to express the economic value of the provision of environmental goods in monetary units, as well. From this perspective it is not surprising that methods for the valuation of environmental goods were developed much in analogy to established methods of market-good valuation where the price of the good serves as the measuring rod of benefits. The most prominent and most widely used method for the assessment of changes in social well-being due to changes in environmental goods is the Contingent Valuation Method (CVM) (see Mitchell and Carson 1989 for a detailed review of the method). This method constitutes the particular focus of this study. In principle, it aims at the elicitation of households' utility changes from some envisaged or planned environmental project. Its main feature is the creation of a hypothetical market which functions in analogy to a real market in which economic agents are given the possibility to purchase the environmental good under consideration. The CVM is based on surveying a representative sample of a population that is likely to be affected by some proposed environmental change scenario. During these interviews which can be carried out as face-to-face, mail or telephone interviews the selected respondents are confronted with a specific scenario of a change in the level of an environmental good and, e. g. in the common case of an environmental improvement, are then asked a monetary amount they would be willing to pay for this improvement to actually take place. In the case of a proposed environmental deterioration respondents would either be asked their willingness-to-pay (WTP) to prevent the deterioration and stay in the present state or, alternatively, their willingness-to-accept-compensation (WTA) for their loss in well-being if the deterioration actually took place. The WTP (or in the case of a perceived deterioration the WTA) is generally interpreted as the economic agent's Hicksian Compensating Variation (CV), a theoretical measure for individual welfare changes which represents the maximum amount of money which could be extracted from an agent so that he is not worse off after the change than before. The main advantage of the CVM, however, the simulation of a market for environmental goods where in fact no such market exists, is at the same time the method's weak point. Usually, in a market households reveal their preferences by making a purchase decision and paying for the purchased good in return. As stated above, it can therefore be inferred that the value they attribute to the purchased good is at least what they have paid for it. At the same time, in a market households usually participate actively, i. e. they play an active part in searching for commodities they desire, acquire information regarding their 2 characteristics and also decide about the time when they purchase these goods. It is obvious, therefore, that the decision situation constructed in a CVM interview is quite different from what a respondent is used to when purchasing real commodities. He plays no active role in a CVM interview, rather he is approached by an interviewer at a time he cannot determine and has to make a decision whether or how much to pay for an environmental good that he usually has not much knowledge of. Furthermore, if he feels that he needs more information to make a well-reflected decision he cannot postpone that decision to some later point in time when he will have. acquired sufficient information. The only consolation to a respondent in such a situation is that he is not required to give up money right away but that the cost of the project will come from some increased tax, higher prices or mandatory payments into a project-specific fund in the future. A WTP statement in a CVM interview, thus, resembles only moderately the situation of a purchase decision in a real market. Still, despite these shortcomings of the simulated market of a CVM interview as compared to a real market this method emulates such a market situation as closely as possible. The alternatives to the CVM would be to use only the various existing indirect valuation methods like the travel cost and the hedonic pricing methods that rely on real market actions but can capture only the use values of environmental goods or to revert entirely to expert valuations. As shown in the literature, these alternatives are not attractive. However, the above mentioned distinctions between real and simulated markets need to be addressed when interpreting the WTP statements of CVM respondents as measures of their welfare changes resulting from a change in an environmental good. Certainly, one of the consequences is not to take the rationality of such WTP statements as given but to scrutinize in detail whether this necessary assumption of rationality is sufficiently fulfilled in practical CVM surveys. Numerous theoretical and practical studies regarding the Contingent Valuation Method have revealed that the rationality of respondents is indeed a problem and that reduced rationality leads to systematic distortions or biases of CVM results. Famous biases reflecting problems of reduced rationality are among others the embedding effect, anchoring effects, social desirability effects caused by the presence of an interviewer and framing effects, just to name a few. In theory, a rational response to a WTP question in a CVM interview requires that the respondent correctly perceives the proposed environmental change scenario including the consequences for his personal life, that he evaluates this scenario in the light of his personal preferences and states a WTP that reflects his evaluation in monetary terms. Ideally, his WTP statement should neither depend on the format of the WTP elicitation question, i. e. whether he himself states an amount or has to accept or reject a proposed amount, nor on the payment vehicle or the interview form. In short, the WTP response should not depend on the specific question format or interview procedure, i. e. it should be 3 procedure invariant. In practice, however, it was often demonstrated that such procedural invariance is elusive. So far, a number of explanations for an often perceived irrationality of CVM responses have been proposed. However, it appears that until to date little is known about the thought processes that actually take place inside a respondent's head when confronted with a WTP question for an environmental change scenario. One key problem with this task for respondents in a CVM interview appears to be that they are confronted with a decision situation which is unfamiliar to them. Often, two aspects of unfamiliarity are encountered: first, respondents might be unfamiliar with the particular good to be valued, i. e. they might have heard of the good or of the issue but have no or only little personal experience with it. Unlike with market goods, where a respondent could always be given a sample product to try out its features and functionality and gain some initial experience to get an idea of its utility, this is usually not possible with environmental goods. As a consequence, the respondent remains in a state of uncertainty with respect to the utility that he will finally receive from the proposed environmental change. The expected change in utility will, therefore, be just an estimate or vague expectation. Second, respondents might be unfamiliar with the task of assigning a monetary value to something they have never associated with money before because they consider it a public property as is the case with most environmental goods and amenities. Decisions about the provision of environmental goods and trade-offs between environmental quality and other economic amenities are usually taken on a higher political or administrative level. In practice, CVM respondents face an additional difficulty: in a typical CVM interview situation, at least in a face-to-face or telephone situation, the respondent will initially be given some considerable amount of information and is then expected to state his WTP within a very short period of time, usually on the spot. A typical CVM face-to-face interview usually lasts between 20 and 40 minutes, and during this little time the respondent needs to assimilate the given information, assess it in the light of his own personal context, generate an expectation of what this new proposed situation would feel like, put this in relation to the loss of possible market consumption resulting from the required payment and, finally, answer a number of personal questions. Typically, the time span between the point at which the respondent first realizes that most likely the interview will require him to make a monetary consideration and the point where he is actually asked to state his WTP is very short. Thus, little time is available to process rather large amounts of new information and to assess the consequences of an environmental change scenario in monetary terms. The cognitive burden in a CVM interview may be quite large and prevent the respondent from fully processing the given information, a situation which is expected to put bounds on the respondent's rationality of decision making. 4 In a world of perfect rationality where individuals are perceived as rather abstract utility maximizers with unlimited cognitive abilities these cognitive burdens play no role since once the scenario information is given the individual should be able to state a WTP conforming to his personal preferences. In the real world, however, CVM respondents will be limited by their personal cognitive capacities and capabilities and will, thus, find the task of evaluating the scenario information and stating a WTP rather stressful. Moreover, they perceive that the decision cannot be postponed, there will be no second chance to express their valuation for the proposed project. Respondents will search for ways of how to best deal with the complex decision situation in which they are required to consider and process large amounts of new and often unfamiliar information in a short period of time. Are respondents willing and able to consider all information provided thoroughly or will they rather try to find ways to avoid the employment of too many cognitive resources? What are respondents' strategies to cope with such situations? Recent research on human information processing and reasoning conducted in the field of cognitive psychology suggests that while people certainly aim at making good and rational decisions they try to make these decisions using as little cognitive effort as possible. Some tasks and decisions require the use of analytical information processing characterized by sequential and logical reasoning, i. e. on conscious thought. For many other tasks, however, the individual has learned that good or at least satisfactory outcomes can be achieved also by limited information processing, e. g. by relying on analogies to previous situations or habits or by focusing only on parts of the available information and thereby neglecting information considered to be less important for the task at hand. Often, key words or "heuristic cues" contained in the formulation of the task or the information provided lead to an activation of a particular strategy to save cognitive resources. Such strategies are often termed "heuristics", i.e. rules of thumb using simplified information processing in order to circumvent cognitively effortful analytical thinking. For the individual, the importance of the task as well as the structure of the information provided decide on the cognitive processes to be employed to solve the task using the least amount of cognitive resources. Such behavior characterized by economizing on cognitive resources can, therefore, be characterized as "economy of cognition". Since this behavior will rarely achieve optimal outcomes the rationality concept underlying such limited information processing resulting in suboptimal decisions is termed "bounded rationality", contrasting the idealized world of perfect rationality. Consequently, in the real world respondents in a CVM survey must be expected to often deviate from the perfectly rational response behavior mentioned above and to employ strategies of information processing to economize on their scarce cognitive resources, instead. Therefore, it appears 5 necessary to perceive respondents as boundedly rational information processors and decision makers. This new perspective on the rationality of respondents allows to analyze and explain the often inconsistent results in CVM surveys. The focus on information processing opens a whole new toolbox for analyzing respondents' use of cognitive resources and, thus, may shed light on ways respondents become victims of their own reasoning and thinking. Biases in the CVM may be the result of respondents' strategies to cope with a complex decision situation by finding appropriate ways to limit the amount of cognitive resources to be invested into decision making. Respondents may use their realworld experience that it is often sufficient for achieving a satisfactory outcome to focus their attention on the most prominent features of a problem or to avoid particularly unwanted outcomes etc. It is reasonable to expect that people's ways of information processing and decision making in a CVM interview are influenced by those experiences of what usually works well. For the analysis of CVM responses, however, this perspective has not yet been adopted. Furthermore, it is to be expected that people differ in their ways to process complex information and make decisions. Some respondents may be more capable to analyze large amounts of information and evaluate a complex environmental change scenario while others are struggling with such a task and feel overloaded. Such respondents will be more likely to employ strategies that make the decision problem simpler and, thus, may be more susceptible to exhibit the kinds of inconsistent response behavior often found in empirical CVM studies. Recent research in the field of cognitive psychology supports this expectation that individual differences exist in the kinds of information processing generally used. Therefore, the concept of bounded rationality to be adopted here is quite multi-faceted in contrast to the usual assumption of perfect rationality. It incorporates a continuum of people's information processing strategies when facing complex tasks ranging from rather analytical to various kinds of spontaneous and simplified reasoning. The adoption of the perspective of boundedly rational respondents in CVM surveys, therefore, promises an explanation of different kinds of response behavior that allows new insights into the problems of this method, i.e. where systematically distorted responses might be rooted. Such insights may help to improve the performance of the CVM. The objective of this study, therefore, is to scrutinize respondents' rationality in CVM surveys by contrasting the concept of bounded rationality as the main paradigm of behavioral economics and cognitive psychology against the concept of perfect rationality. The particular interest of this scrutiny is to analyze the explanatory power of this alternative rationality concept for often found inconsistent response patterns in CVM surveys. Furthermore, it shall be attempted to derive recommendations of how the design and the administration of CVM surveys could be improved so that the decisions taken in the simulated 6 "pure" option value as "quasi" option value (cf. Arrow and Fisher 1974). In addition to this option value, Krutilla ( 1967) pointed to the existence value describing the utility derived from the pure knowledge of the existence of environmental goods, e. g. certain plant and animal species or entire ecosystems, that an individual will most likely never see himself but nevertheless perceives as important to preserve. Krutilla also introduced the bequest value referring to the utility one derives from leaving an intact environment, or at least a particular amenity, to future generations. Since these additional categories of value are clearly components of the well-being of society they must be considered as elements of the benefit-cost framework mentioned above. Therefore, in the environmental economics literature it is now common to use the concept of total economic value that considers all kinds of ways in which human beings derive value from an environmental good (cf. Nunes 2002: 4). This concept differentiates on a first level between use values and non-use values. Use values comprise the value derived from direct consumption (direct use values) and from ecosystem functions (indirect use values) as well as the "pure" option value. Non-use values that are also often termed passive use values comprise the existence value and the bequest value described above. Additionally, the "quasi" option value is usually classified as a non-use value, however, it might as well be considered a use value. Since this distinction is of no practical importance it shall not be elaborated on here. It can be argued that within the concept of total economic value the intrinsic values mentioned above are to some extent subsumed in Krutilla's existence value since it comes closest to the environment having a value regardless of its use to man. When, however, intrinsic values imply a complete lack of substitutability between environmental and produced goods such values cannot be dealt with in an economic approach. Figure 2-1: The concept of total economic value TOT AL ECONOMIC VALUE Direct use value Use values Indirect use value Pure option value Existence value Non-use values Bequest value Quasi option value The concept of total economic value with its distinction in use values and nonuse values has important implications for the practical methods of environmental valuation. Before the presentation and discussion of these methods, however, the theory of environmental valuation and benefit-cost analysis in neoclassical 13 economics shall be dealt with in the following section in order to derive theoretically consistent measures of value that can then form the reference base for the methods of practical assessment. 2.1.2 Environmental valuation and benefit-cost analysis in neoclassical economics The following section 2.1.2 is largely based on Ahlheim (2003) and Stephan and Ahlheim (1998). For the presentation of the theoretical foundations of environmental valuation let's for simplicity consider a public project aiming at some improvement of the state of the environment. Typically, such a project leads to a number of effects that are important from an economic perspective and, therefore, must be dealt with here since they affect the well-being of the households considered. The desired effect of such a project is the improvement of the environment which is denoted as i here, where k E {0, l}. Specifically, z0 stands for the state of the environment before the project, i. e. the initial situation, and z1 refers to the state after the project has been carried out. Since the financing of such a project usually requires government to raise additional funds, e. g. in the form of increased taxes, it is plausible to assume a change in the households' income levels when the project is implemented. Thus, I~ denotes household h's income in environmental state k. Additionally, it must be expected that the consumption of market goods xh = { xh, 1, xh, 2, ••• , xh,N} changes since the improvement of the environment might lead to more consumption of some goods, e. g. hiking boots, and less of others, e. g. computer games, which has effects on the relative prices of market goods. Let, therefore, p~ denote the market price of commodity n in environmental state k. In cost-benefit analysis we are generally interested in the change of welfare, i.e. well-being, of society resulting from such a public project. We, therefore, aim at finding an indicator from which we can unambiguously tell whether society is better or worse off after the project implementation and financing. In democratic states, to which this theoretical approach refers, society is generally perceived as consisting of individual persons whom economics usually classifies in households since members of one household are for simplicity assumed to make consumption decisions with a joint budget. Thus, social welfare can be expressed formally as where a¼uh ~ 0 V h. (2-1) Therefore, the problem of the assessment of the welfare change resulting from the considered project can be divided into a first step of determining the changes 14 in utility of each household in society, the so-called identification problem, and a second step of aggregating all individual household changes in order to determine the overall welfare change, the so-called aggregation problem. Each of these problems will be dealt with in turn. Let us consider the household's direct utility function that depends on the consumption of market commodities, the vector xh, and the state of the environment z so that (2-2) It is assumed that the direct utility function is monotonically increasing in z so that environmental quality is indeed considered as a good. The change in utility of the household due to the implementation of the project can then be defined as the utility difference between the initial situation k = 0 and the situation k = 1 after the implementation of the project LiU~ 1 = U~ - U~ = uh ( x~, z1) - uh ( x~, z0 ). (2-3) However, as mentioned above, along with an implementation of the environmental project and its financing by government, the consumption of market commodities must be expected to change due to changes in incomes, for instance. Therefore, it is more convenient to employ the indirect utility function, instead, which depends on prices, incomes and the state of the environment. The indirect utility function results from the maximization of the direct utility function subject to a given budget, prices and state of the environment. It symbolizes the maximum level of utility that can be attained given these parameters. vh(p,z\Ih) = max u(xh,z) s.t. lh=p·xh; z=zk X i.e. (2-4) The expression x • (p, zk, Ih) represents the Marshallian demand functions resulting from the described utility maximization problem of the household, i. e. the optimal consumption quantities of x given p, zk and lh. With this definition of the indirect utility function the utility difference stated in 2-3 can now be written as (2-5) 15 However, it is well known that neither the direct nor the indirect utility functions are observable due to their ordinal nature. It is, therefore, necessary to define a measure of individual welfare £\h that is based on the theoretical expression in 25 and that is in principle accessible to observation and can be computed using econometric techniques. In general, such a welfare measure needs to satisfy the so-called indicator condition according to which the measure must be able to unambiguously indicate whether an individual household is better or worse off after a change from situations k = 0 to k = 1, i.e. > > £\ 0 h 1 = O)h ( ut u~) = 0 <=> u~ = u~ . (2-6) < < In order to derive a welfare measure both satisfying the indicator condition and being observable in principle the concept of the expenditure function will be employed. Taking into account the existence of environmental goods the expenditure function defines the minimum expenditure that is necessary for a household to attain a given utility level U when prices p and the environmental state z are given, i. e. e(p,z,U}= min p·x, xeU(U) U(U) = { xi u(x,z) 2:: U}. (2-7) As desired, the expenditure function is strictly monotonically increasing in the utility level U since when prices and the state of the environment are given any increase in U is necessarily accompanied by an increase in expenditure for market goods creating this utility. Due to this strict association of money and utility level the expenditure function is termed "money-metric utility function". Since we are interested in measuring utility changes the expenditure function can be used to define utility differences in monetary terms as the difference between two expenditures necessary to attain two different and predefined levels of utility when prices and environmental state are kept constant. These utility difference measures are based on John Hicks (cf. Hicks 1939, 1942). In the literature two such measures feature very prominently differing only in the chosen level of prices and environmental state to be kept constant ( cf. Stephan and Ahlheim 1996: l 72t). In the situation under consideration where there is an initial state, i. e. before the project, and a final state, i. e. after project implementation, it is plausible to either choose the prices and environmental state at the initial situation or at the final situations as reference levels of the expenditure functions for the welfare measure. Choosing the initial level as reference gives rise to a welfare measure called Hicksian Equivalent Variation defined as 16 Evt = eh (p 0, z0, U~ ) - eh (p 0, z0, U~ ) = eh (p 0, z0, U~ ) - I~ , (2-8) since the expenditure necessary to attain U~ at prices p0 and environmental state z0 equals just the income of household h in the initial situation I~ . As a monetary expression for the difference in utility between an initial situation and a final situation Evi 1 can be interpreted in two directions. On the one hand Evi 1 denotes the minimum amount of money that must be given to household h for his utility to remain unchanged ifhe were to forego an environmental project that would increase his level of utility from U~ to U~. In this case Evi 1 is commonly interpreted as willingness to accept compensation (WT A). On the other hand Evi 1 denotes the maximum amount of money that could be extracted from household h if the implementation of a project that would decrease his level of utility from U~ to U~ were prevented. In this case EVt is commonly interpreted as willingness to pay (WTP). In the first case, an environmental improvement, Evi 1 would be positive whereas in the second case, an environmental deterioration, Evi 1 would be negative. In case the final situation, i. e. k = 1, is chosen as reference level in the expenditure function, the Hicksian Compensating Variation is obtained which can be defined formally as cvi 1 = eh (p1, z1, u~) - eh (p1, z1, u~) = I~ - eh (p1, z1, Un . (2-9) Again, the expenditure necessary to attain utility level U~ giv.en p1 and z1, eh (p 1, z1, U~ ), equals just household h's income in the final situation I~. In analogy to the Equivalent Variation, the Compensating Variation can assume two states: in case it assumes a negative value, i. e. cvt < 0, it denotes the minimum amount of money that must be given to the household to compensate him for a loss in utility from U~ to U~, commonly interpreted as WTA. In case cvi 1 > 0, however, the Compensating Variation stands for the maximum amount of money that could be extracted from the household and still leave him as well off as before if the environmental project were to be implemented. This latter case where cvi 1 is commonly interpreted as WTP is most frequently used in environmental valuation since it describes the natural situation where a 17 household is asked to give up some monetary equivalent for an environmental improvement to occur. Thus, in the following, only the Compensating Variation will be used as a measure of utility differences resulting from environmental changes. In its formulation in 2-9 cvi1 can still not be computed since while the household income I~ is observable the expenditure term eh (p 1, z1, U~ ) refers to a hypothetical situation since it denotes expenditure necessary to attain the initial level of utility under the final situation of prices and environmental state. Such an expenditure is entirely abstract and can, therefore, not be elicited from the household. In order to render the expression for cvi1 observable it is necessary to transform it into three separate utility differences by adding zeros to equation 2-9 (cf. Stephan and Ahlheim 1996: 175f) yielding cvi1 = eh (p1, z1, u~) - eh (p 0, z0, u~) + eh (po' ZO' U~ ) - eh (pl' ZO' U~ ) + eh (p1, z0, U~ ) - eh (p1, z1, U~ ) . The notation of the augmented expression in 2-10 can be simplified to cv 01 - cv1° 1 + CVp 01 + CVz 01 h - h h h• (2-10) (2-11) i.e. the Compensating Variation for the utility change from U~ to U~ can be separated into three expressions referring respectively to the change in utility from changes in household incomes, CVI~ 1, the change in utility from the changes in prices, CVp~ 1, and the change in utility from the change in the environmental state, CVz~ 1• The advantage of such a separation into single utility changes is that there exist methods of measurement for each of them. CVI~ 1 simply refers to the change in the income level of the household, i.e. I~ - I~. This income change is in principle observable from household census data. For the computation of CVp~ 1 there exists a well-established procedure of measurement (cf. Vartia 1983) which is based on an approximation procedure aiming at computing an integral over Hicksian demand functions when only the respective Marshallian demand functions are known ( cf. Ahlheim and Wagenhals 1988). With this procedure any level of accuracy can be achieved depending only on the effort expended. Finally, the expression CVz~ 1 is the one being most important for environmental valuation since it represents the utility 18 change that is generated for the household by the change of the state of the environment alone. In theory, this expression represents the integral over the shadow prices for the environment between the initial state (without the project) and the final state (after project implementation). Since, however, these shadow prices are not observable from household data, other methods have been developed for an approximate computation of this measure in practice. These methods aim at the elicitation of individual households' WTP for the project under consideration since, as mentioned above, the CV for a utility increasing project is commonly interpreted as the WTP for that project. In a next step, the problem of aggregating the individual welfare changes needs to be addressed since it is the aim to derive a valid measure for changes in social welfare. An environmental economic policy maker would hardly be able to recommend the implementation of a public project on the basis of countless figures of individual WTP. The aggregation of individual welfare measures, however, poses a fundamental theoretical problem in economics since it involves interpersonal comparisons of utility which is not compatible with ordinal utility theory. In addition, it was demonstrated by Arrow's Impossibility Theorem (cf. Arrow 1950) that no social preference ordering can be constructed on the basis of individual preferences that fulfills certain desirable conditions. Therefore, it is necessary to revert to weaker forms of aggregation for practical purposes. In reality, a policy maker would like to base the decision concerning some publicly funded project on the assessment of whether society as a whole will be better or worse off after the implementation of the project. Such an assessment can at least be approximated by determining whether it is possible for the winners of such a project to compensate the losers and still not be worse off than without the project. This criterion for preference aggregation is known as the Hicks-Kaldor potential Pareto criterion (cf. Cullis and Jones 1998: 29). Despite its theoretical shortcomings it has been widely accepted as one possible and transparent way of deriving a social benefit-cost measure from measures of individual welfare change. Using the derived measure of individual welfare changes on the basis of the Hicksian Compensating Variation above yields the following expression for the Hicks-Kaldor criterion in our case: > > H H H H I,cvi1 = ICVl~ 1 + ICVp~ 1 + ICVz~ 1 = 0 • W1 = w0 (2-12) h=l h=l h=l h=l < < where W\ k E { 0, 1} denotes social welfare at situation k. Separability of the three components of the individual welfare measure cvi1 implies that the aggregated CV can simply be obtained by summing the individual components 19 over all households. For further discussion of the Hicks-Kaldor criterion in the literature see e. g. Johansson ( 1994 ). In practical applications, however, it will not be viable to apply the HicksKaldor criterion fully as specified above. In order to compute a numerical value for the social value of an environmental project it would, thus, be necessary to know the income changes of all households, to estimate the entire demand system of society and the utility changes resulting from the environmental improvement using suitable empirical methods. Therefore, in practice, a simpler approach is usually chosen that relies on a comparison of the costs necessary to implement the project versus the aggregated individual benefits from the intended environmental improvement yielding the following benefit-cost expression H BC01 = ICVz~I -q1. Y, h=I (2-13) where y denotes the vector of the quantities of input factors necessary for the implementation of the project and q I denotes the vector of the respective factor prices. If BC 01 is positive the implementation of the project under consideration is recommended, if it turns out to be negative the proposed project should be scrapped. For the conditions under which this approximation of the benefit-cost measure is reasonable see Hanusch (1994: 57) and Ahlheim (2003: 27ft). Therefore, the focus of empirical methods of environmental valuation is directed H on the assessment of the term L CVz~1 , i. e. on the assessment of household's h=l WTP for the project under consideration as a common interpretation of the Compensating Variation in practice. The methods currently available for this task shall be described and discussed in the following section. 2.1.3 Methods of environmental valuation Since the theoretically correct assessment of the individual welfare change CVz~1 by computing the integral over the compensated shadow price function of environmental states is not possible in practice it is necessary to employ empirical methods that allow to deduce the value that households attribute to a particular environmental change from data that are observable from these households. As mentioned above, willingness to pay for an environmental improvement or for preventing an environmental deterioration is usually considered as a suitable proxy for the associated utility change of the household due to the economic trade-off involved in the decision of how much money, i.e. market consumption, should be sacrificed in return for an environmental good. 20 This consideration gives rise to two fundamentally different approaches for the elicitation of WTP. The first approach makes use of the weak complementarity between some market goods and environmental goods and bases WTP elicitation on households' observed consumption behavior of these goods. This implies that the value of the environmental good is assessed indirectly through the consumption of its complementary market goods. Therefore, the methods relying on observed market behavior of such goods are usually called indirect methods of environmental valuation. Alternatively, since they require the households to reveal their preferences for environmental goods through the consumption of market goods they are often called revealed-preference methods. Weak complementarity between a market good and an environmental good exists whenever consumption of a good is positively associated with an environmental good, i. e. when ceteris paribus the existence, the level or the quality of an environmental good leads to a higher consumption of those market goods or if prices of market goods are positively influenced by the environmental good (cf. Stephan and Ahlheim 1996: 154, Maler 1974). However, the indirect methods can only assess that part of the value attributed to the environment which is directly associated with its use since the use of the environment determines the consumption of the market goods that are related to it by weak complementarity. Therefore, the indirect methods are only of limited use for environmental valuation. When it is expected that an environmental good creates considerable non-use values as described in 2.1.1 the so-called direct valuation methods have to be employed. These methods are based on direct questioning of households concerning the value they attribute to some environmental improvement. The idea of the direct methods is to simulate a market situation for environmental goods where the household is given the opportunity to "buy" the environmental good in question. From the household's behavior in this simulated, or hypothetical, market situation his willingness to pay for the environmental good in question can be inferred. Since these methods rely on households' direct statements of value in a hypothetical situation rather than on true market behavior, they are often called stated-preference methods. Since the research in this study focuses on stated-preference methods they will be discussed in greater detail in 2.1.3.2. For completeness sake, however, a brief overview of the most prominent revealed-preference, or indirect, methods shall be given here. 2.1.3.1 Indirect methods The three most prominent indirect valuation methods are the travel cost method, the hedonic-pricing method and the averting behavior method. The travel cost method (TCM) dating back to Clawson (1959) is usually applied if the use value of some recreational site, e. g. a natural park or a lake, is to be valued. Its basic 21 premise is that this value can be inferred from the expenditures on consumption goods related to the use of the recreation site and the time invested for using it. Certain market goods like e. g. transportation, hiking equipment, bathing suits, barbecue equipment etc. are necessary for and closely associated with the use of the site under consideration for recreation. The minimum value of the site for a specific household would then equal the expenditures for the associated market goods plus the valuation of the time spent for travel and recreation. However, in practice it proves to be difficult to determine the share of the expenditure on market goods that is exclusively related to the use of the specific site, e. g. bathing suits can also be used at other sites. Equally, the value of time is not so straightforward since in most cases the opportunity cost of time in people's freetime cannot simply be equated to foregone earnings in their jobs. Most people do not work on weekends and on holidays anyway, so that it seems impossible to value time in monetary terms in this case. Nevertheless, the travel cost method is still often used due to its computational simplicity, sometimes even in conjunction with direct valuation methods. The main idea underlying the hedonic-pricing method (HPM) dating back to Ridker ( 1967) is the assumption that the price of a market commodity that is weakly complementary to an environmental good contains as a part the value the consumer attributes to this environmental good. In other words, the consumer is willing to pay a higher price for a certain market commodity if it is positively associated with an environmental good. The standard example is the supposed influence of environmental amenities like e. g. a scenic view or a natural recreation area on property values or rents in the housing market ( cf. Rosen 1974, Bartlik and Smith 1987, Freeman 1993, Palmquist 2004 for detailed reviews of theory and practical applications of the hedonic-pricing method). The same, but opposite, influence on property values can be observed for environmental disamenities like e. g. the proximity to environmentally hazardous sites ( cf. Kohlhase 1991, Cameron 2006 for the influence of Superfund sites in the USA on regional property values). From the variation of property values of houses with the same characteristics differing only in the environmental attribute (scenic view, distance to hazardous sites etc.) the share of the commodity's price pertaining to the environmental attribute can be determined and, under certain conditions, a WTP for an environmental change can be computed (cf. Horowitz 1984). However, there exist a number of theoretical concerns that question the validity of WTP estimates derived from the hedonic-pricing method ( cf. Freeman 1993: 680f, Palmquist 1991 ). While, in principle, it is argued that indirect methods can only assess direct use values, the hedonic-pricing method could also, in special cases, elicit indirect use values and even non-use values like the existence value. The indirect use value of ecosystem services, for example the protection of settlements from landslides in mountainous regions by natural forest 22 up bid than when this lower bid is the first bid, was not found to be as strong. DeShazo (2002) explains this asymmetric anchoring effect with prospect theory ( cf. Kahneman and Tversky 1979) according to which people are loss averse, i. e. inclined to reject a higher follow-up bid perceived as a loss in comparison to the first bid, and risk seeking, i. e. trying their luck even further when offered the lower follow-up bid. Due to these consistent shortcomings of the DBDC format DeShazo (2002) developed a DC format where the respondent is asked a follow-up bid only in case he has already rejected the first bid. It was shown, and could be replicated in the empirical example underlying this study (see chapter 4 ), that this DeShazo format yields WTP estimates practically identical to those of the SBDC format while being statistically more efficient due to the larger amount of information extracted per respondent as a result of the lower follow-up bid. Cooper et al. (2002) attribute the anchoring effects found in DeShazo (2002) to the surprise that respondents feel when a follow-up bid, especially a higher one, is presented to them. The authors propose to modify the DBDC format by announcing to the respondent prior to the WTP question a range in which the project costs will most likely lie. Respondents are then either asked a bid at the upper end of that range and asked a follow-up bid, the amount of the lower bound of the announced range, whenever the first bid was rejected. Or, alternatively, the lower amount is asked first, followed by the upper bound of the range in case the first bid was accepted. Cooper et al. (2002) call this format the one-and-one-half-bounded DC (OOH). However, it was shown by Bateman et al. (2004b) that this approach is itself highly vulnerable to the specific range presented to the respondents so that strong anchoring effects cannot be avoided by this format, either. Thus, at the moment the DeShazo format seems to be the most desirable format out of the set of possible DC formats. In empirical comparisons between WTP results obtained from open-ended formats like the OE or the PC format with those from the DC formats many studies report systematic differences ( cf. Ready et al. 1996, Herriges and Shogren 1996, Boyle et al. 1996, Frew et al. 2003, Ryan et al. 2004, Champ and Bishop 2006). The WTP estimates from open-ended formats are consistently below those from dichotomous choice formats. While the controversy w. r. t. the "correct" question format cannot be settled by such a comparison due to the lack of a valid reference point on which the performance of the formats can be compared the consistent findings of starting point bias and anchoring effects in the DC format and only few proofs of statistically significant range biases ( cf. Whynes et al. 2004) in the PC format put considerable doubt on recommendations to use the DC format in order to make use of its direct analogy to the purchase of market goods. In case the DC format is chosen for a study, the literature suggests that it is very advisable, however, to avoid bids in the upper tail of the expected WTP distribution. The bid design, i. e. the choice of the 29 different bid values should be based on pretests using open-ended formats in order to avoid bid designs that are already biased upwards (cf. Kanninen 1993, Boyle et al. 1998). After the WTP elicitation question the interview proceeds to the final step where a number of attitudinal, socio-economic and demographic questions are asked. The purpose of the elicitation of this kind of information is threefold: first, the socio-economic and demographic information about the sample can be used to check whether the WTP estimates are gained from a representative selection out of the entire population and, thus, forms a suitable basis for the computation of an aggregated welfare estimate. Second, these variables can be used in econometric models as explanatory variables, i. e. as variables that are systematically associated with the observed WTP. This analysis can serve as a plausibility test of the WTP responses obtained in the survey since there exist a number of a priori expectations w. r. t. the association of some of these variables with WTP. For example, it is reasonable to expect that WTP increases systematically with the level of household income, often also with education and the level of worry w. r. t. the environmental good under consideration. If these prior expectations are verified in the dataset the credibility of the validity of the WTP is reinforced. Third, the found systematic relationships between socioeconomic and demographic variables and WTP represent an important information for policy makers who will be able to assess which group of the population would benefit most from the planned project and which group(s) might be expected to lose. These considerations are very important for practical environmental policy. Apart from personal interviews at a household's home, a number of alternative interview forms have been proposed for CVM interviews like mail surveys, telephone interviews or mall-stop interviews in large shopping malls or streets. Mall-stop and telephone interviews are usually regarded less reliable than personal and mail surveys. Mall-stop samples are hardly representative in the first place and there is usually very little time available for the interview so that a thorough consideration of the proposed scenario cannot be expected. While it is easier to obtain a representative sample in telephone interviews the possibilities for a detailed presentation of the valuation scenario are scarce since neither written nor graphical material can be employed. Thus, currently only face-to-face and mail interviews are judged to lead to fairly reliable WTP estimates. Nevertheless, CVM studies using mail surveys (MS) are often considered less reliable than studies using face-to-face interviews (FtF) due to low return rates associated with self-selection of respondents returning the questionnaires ( cf. Whitehead et al. 1993 ), limited possibilities to convey a complex valuation scenario to the respondent and less possibilities to force respondents to strictly follow the standardized order of questions in the questionnaire (cf. Cameron et al. 1999, Ethier et al. 2000). On the other hand, 30 however, MS have a number of advantages that make their employment attractive: respondents are much more likely to respond truthfully to personal questions so that the problem of social desirability and interviewer biases, a well known problem of FtF surveys, can be avoided ( cf. Krysan 1994 ). Also, respondents can take as much time as they need to think about the proposed scenario and their answer to the WTP elicitation question ( cf. Dillman 1978). Last but not least, mail surveys are generally considerably less expensive than FtF surveys. As a result of the described procedural shortcomings of both interview forms widely divergent estimates of project benefits for FtF surveys as compared to MS are reported in the literature where FtF surveys are usually regarded as the interview form leading to more reliable results (cf. NOAA 1994). Recent findings of the comparison of the performance of face-to-face versus mail surveys are reported for a CVM study in Thailand of which the empirical research of this study is a part (cf. Ahlheim et al. 2007). After this detailed description of the general CVM procedure and the discussion of its main practical problems two further direct methods of environmental valuation shall be briefly described in the following sections. The Participatory Valuation Method (PVM) One of the main criticisms of the CVM often voiced in the literature is that respondents in the traditional face-to-face CVM setting have little time to perceive and process the information of the valuation scenario, have no possibility to acquire additional information if they feel it is necessary and lack the chance to discuss their views with other people in order to reflect on the task at hand more thoroughly. This criticism is based on the view that in most CVM studies respondents will not have clearly defined preferences for the environmental good to be valued that they are able to readily express in monetary terms. Rather, it is sometimes argued that preferences for more or less unfamiliar goods or goods that are usually not perceived to have value in monetary terms need to be constructed by the respondent during the valuation task ( cf. Payne and Schkade 1999, Bettman et al. 1998, Payne et al. 1992 ). This view contrasts the prevailing notion in the valuation literature that well-defined preferences for environmental goods exist which simply need to be unveiled by a suitable valuation method. If preferences are not so readily available and the construction of preferences is initiated only when respondents are confronted with a specific valuation task great care must be laid into this construction process in order to avoid manipulation of the respondents into one direction or another. Several authors have proposed valuation techniques based on the interaction of respondents in group meetings, so-called participatory valuation techniques (cf. Macmillan et al. 2002, Philip and Macmillan 2005). 31 Usually, this Participatory Valuation Method (PVM) is based on the CVM (see, however, Alvarez-Farizo and Hanley 2006 and Powe et al. 2005 for participatory valuation techniques in the ABCM setting presented below). Unlike the traditional individual-based interviews groups of respondents, e. g. 10 to 15 people, are formed that meet for two or more moderated sessions. The purpose of these sessions is to provide respondents with the opportunity to actively learn more about the valuation scenario, to ask questions and obtain more information on the issue at hand if they wish and to enable them to share their opinions and views on the project so that they can reflect and deliberate on the proposed environmental project as deeply as possible. In this process, expert information should be presented, ideally from different sources and angles in order to avoid undue manipulation of the participants. At the end of the sessions, participants are given a CVM questionnaire containing the WTP elicitation question that they can fill out in private and anonymously. While this approach to environmental valuation seems very promising since it enables respondents to invest great effort into the detection of their "true" WTP for the project a number of critical issues need to be addressed briefly. From a practical point of view this method requires a lot of effort for the organization and moderation of the group meetings. The overall sample size will necessarily remain limited so that the WTP estimates are rather inefficient from a statistical point of view. Furthermore, it is doubtful whether the preferences toward the specific environmental project will really represent the preferences of the general population should the project be implemented since the general population will hardly ever attain the level of information on the project that the participants of the group meetings had when stating their WTP (cf. Ahlheim and Fror 2003). Thus, the PVM is clearly not sufficient as a stand-alone technique for assessing environmental values but it appears to be a promising tool for complementing the traditional survey methods based on representative samples of respondents. Attribute Based Choice Modelling (ABCM) Unlike in the CVM the respondents in a survey employing Attribute Based Choice Modelling (ABCM) are not simply confronted with the task of valuing a project scenario in relation to some status quo but can make choices among various alternative combinations of valuation scenarios. The ABCM which is closely related to Conjoint Analysis commonly employed in marketing research is based on Lancaster's (1966) characteristics theory of value according to which the value of a commodity is determined by the specific combination of the characterics, i.e. the attributes, which in conjunction define that commodity. An environmental good, therefore, is seen to consist of a number of attributes, e. g. area of a nature preserve, endangered plant and animal species, water quality of 32 the rivers etc. Combining these attributes with different levels yields a set of possible environmental goods to be valued. The aim of the ABCM is the valuation of the aggregate environmental goods in relation to the status quo as well as of the single attributes of which the good consists. In practice, respondents are successively presented a number of choice sets consisting usually of two alternative combinations of attributes as well as the status quo. Each of the two alternatives contains a cost attribute which states the monetary amount that the respondent would have to pay if that particular alternative were implemented. The respondent is then asked to select between the three combinations presented, i. e. the two project alternatives and the status quo. From the successive choices among different such choice sets both a WTP estimate for every possible combination of attributes as well as for discrete changes of the levels of the attributes can be obtained. The ABCM has already been applied in many empirical valuation studies ( cf. Stevens et al. 1997, Garrod and Willis 1997, Adamowicz et al. 1998, Foster and Mourato 2000, Haefele and Loomis 2001, Hanley et al. 2001). The ABCM approach is certainly a valuable extension of the CVM technique whenever it is possible to create meaningful environmental goods by combinations of different attribute values. The advantage of this method is the simultaneous valuation of a number of alternative project scenarios which allows a policy maker who is not already committed to some fixed and unchangeable environmental project to determine among an entire set of possible projects the one that exhibits the most favorable ratio of social benefits to costs of the project. Thus, the ABCM, whenever applicable, seems a powerful tool for environmental policy making. Summarizing the discussion of practical methods of environmental valuation it becomes obvious that rationality plays quite a different role for direct methods in comparison to indirect methods. Since indirect valuation methods are based on people's observed market choices where money is actually expended for environmental goods the assumption of rational, i. e. utility maximizing, behavior is already implied. In neoclassical economics it is generally presumed that people can be trusted when it comes to deciding which goods will generate the highest utility for the available budget. 1 At the same time it must be assumed that before purchasing a good people have gathered information about the good they consider sufficient for making that purchase decision. In simulated markets as generally used in the context of direct valuation methods, however, the situation is different. First, economic choices of respondents are not real, i. e. people do not sign a binding contract to purchase an environmental good for money. However realistically a payment scenario may be crafted, statements of WTP will merely remain announcements of what respondents would pay for an environmental good in case they would have to do so in the future. Second, 1 Sometimes, however, this assumption is questioned as will be discussed in chapter 3. 33 respondents cannot search actively for the information they require to make a good WTP statement, they are left with what is provided to them in the course of the interview. These two distinctions show that it cannot be taken for granted that choices made in the course of a CVM, PVM or ABCM interview are perfectly rational since the very context of the interview, i. e. degree of realism, elicitation question format, type and quality of provided information etc., bears the potential to influence stated WTP. Such biases of WTP as already briefly discussed in the preceding section shall be addressed in more detail in 2.1.5 below. 2.1.4 Statistical estimation models for the CVM The aim of this section is to provide a brief overview of the statistical estimation approaches commonly used for the analysis of CVM response data. These comprise models for the estimation of WTP as the main objective of the CVM and for the estimation of the determinants of WTP used for plausibility tests and as information for policy makers. This overview is based mainly on Haab and McConnell (2002) with some useful modifications in notation as well as on Hanemann (1984) and Hanemann et al. (1991) where further details w. r. t. the estimation of dichotomous choice models can be found. For the open-ended question format the estimation of WTP is very simple since direct and precise figures of WTP are obtained from each respondent. From these responses mean WTP can be computed as the arithmetic mean over all individually stated WTP figures. Mean WTP serves as the basis for an aggregation of WTP to the whole population affected by the project under consideration by simply multiplying this estimate by the number of households affected. For the mean WTP 95%-confidence intervals as a measure for the estimation error can be computed using the standard textbook procedures ( cf. Griffiths et al. 1993: 143). Similarly, the median WTP can be directly obtained from the open-ended responses indicating the WTP stated by at least 50% of the households. Median WTP indicates the amount for which exactly 50% of the households would have voted in a referendum on the proposed project and would, therefore, serve as a useful figure for environmental policy makers in case households were obliged to pay this amount as a result of project implementation. In general, median WTP was found to be considerably lower than mean WTP for open-ended data since, as mentioned above, the answers are not symmetrically distributed and exhibit a spike of responses at "zero". In addition, very high WTP statements contribute to the tendency of higher means. Due to the regularly observed mass of "zero" responses regression models using ordinary least squares (OLS) estimation for the analysis of determinants of WTP would yield biased parameter estimates of the explanatory variables (cf. 34 Maddala 1983). Thus, censored regression models like the tobit model are commonly used for an analysis of WTP determinants ( cf. Tobin 1958, Halstead et al. 1991 ). The estimation of WTP from dichotomous choice and payment card responses, however, is more complicated since responses are given only in the form of intervals of WTP. Since these responses are to be interpreted as the result of a rational, i. e. utility maximizing, choice it is necessary to derive a suitable statistical model from an economic model of utility maximization. Therefore, the derivation of the model starts with the following consideration. If a utility maximizing respondent h agrees to pay a monetary amount A in return for an environmental project proposed in a CVM interview the following weak inequality must hold (2-14) where v h ( ·) denotes the household's indirect utility function when market prices are held constant and sh denotes the vector of the household's socioeconomic and demographic characteristics as well as personal attitudinal variables. Thus, the household will only agree to pay Ah if he is at least as well off with the project as without it but not having to pay Ah. Since v h ( •) is not observable and its true functional form is unknown this expression has to be separated into a deterministic term v h ( ·) that represents the researcher's model of household h's preferences and a stochastic term E~: (2-15) The deterministic part of v h ( ·) is based on the observable characteristics of the household, including his income I~, the particular environmental state zk and the household's behavior w. r. t. the WTP question, i. e. whether he accepts or rejects the proposed bid. The error term E~ represents all unobservable characteristics of the household, e. g. personal and only privately known situational factors or preference uncertainty (see below). For the observer vh ( •) is, therefore, a random variable so that utility as specified here belongs to the socalled Random Utility Models (RUM) for which a well-developed framework of statistical analysis exists (cf. McFadden 1974). For the analysis ofCVM interval data it is useful to derive an expression for the probability to accept the proposed bid, i. e. to say "yes" to the WTP question, using the above random utility specification: Pr{yesh} = Pr{vh(z\Ih -Ah,sh) ;;:: vh(z 0,Ih,sh)} 35 = Pr{vh(z 1 ,Ih -Ah,sh) + e~ ~ vh(z 0 ,Ih,sh) + e~} = Pr{vh(z 1 ,Ih -Ah,sh)- vh(z 0 ,Ih,sh) ~ e~ - e~} (2-16) Thus, in other words, the probability that household h experiences no loss in utility if he has to pay Ah for the environmental project is simply the probability that the difference of the observable utility change is at least as great as the difference of the unobservable error terms. 2-16 shows the necessary rationality assumption inherent in this formulation of the statistical model. A respondent's "yes"-response implies that he is able to perfectly observe whether he will be at least as well of with the project as without it. Whenever a rational response is not guaranteed, however, i. e. whenever the response is not in congruence with the respondent's "true" utility difference, the statistical model will necessarily fail to estimate this "true" WTP. Defining the utility difference Li vh = vh ( z1, Ih -Ah, sh)- vh ( z0, Ih, sh), 17 = e~ - e~ and FT\ ( ·) as the cumulative distribution function (cdf) of 17 the probability to accept the bid can be written as (2-17) i. e. the larger the deterministic utility difference Li v h the larger the probability that this difference exceeds the error term 17 and the larger the probability to accept the proposed bid A. In order to operationalize this expression for an estimation model of WTP both the deterministic component Li v h and the stochastic component F Tl ( • ) , i. e. the distribution of the error term 17, must be specified. A simple and commonly employed specification of the utility difference Li v h is the linear utility model Livh = v~ - v~ = (a 1 +~(Ih-AJ - (a 0 +~Ih) (2-18) (2-19) where a = a 1 -a O subsumes the observable characteristics sh. A more detailed explanatory model will be used below. Alternative specifications for the utility difference where the influence of household income on WTP is modeled more realistically have been proposed (cf. Hanemann and Kanninen 1999), however, in this study the commonly employed simple model specified in 2-19 will be used throughout. 36 The stochastic specification depends on the assumption of the distribution of the error terms E~ • The assumption of independently and normally distributed errors leads to F 11 ( d \\ ) = <t> (d vh) where <t> ( •) denotes the standard normal cumulative distribution function resulting in a probit model for WTP estimation. In the probit model, errors are assumed to be distributed standard normal with a mean of 0 and variance cr 2 of 1, i.e. E~ ~ N (0, 1). Since the errors E~ are N (0, cr 2) distributed the parameters a and ~ need to be normalized to ! and ! for statistical estimation. Thus, in the probit model the probability to say "yes" becomes <t>(-;-¾Ah). The same applies to the commonly used logit model where the assumption of an independent and identical extreme value distribution of errors leads to the logistic distribution F 11 ( d vh ) = (l-e6 "h r1• Since the standard normal and the standard logistic distributions differ merely by the latter assuming higher probability density in the tails of the distribution there is only a slight difference between probit and logit models in practice. For further specification of the stochastic part of the model assuming asymmetric distributions and taking account of the fact that WTP should be strictly nonnegative see Hanemann and Kanninen (1999). From the parametric specification in 2-19 a welfare measure based on WTP can be obtained directly by assuming that d v h = 0 exactly if Ah = WTPh, thus for the probit and the logit model it must hold thatO = a - ~ WTPh so that (2-20) Due to the symmetry of the standard normal and standard logistic distributions the resulting welfare measure represents both mean and median WTP. Alternative specifications of the stochastic part of utility based on asymmetric probability density distributions lead to different expressions for the welfare estimate where the mean and the median differ. For the estimation of the parameters a and ~ in expression 2-20 it is convenient to use the Maximum Likelihood technique now commonly available in econometric software packages like LIMDEP (cf. Greene 2002). For the single-bounded dichotomous choice interval data the log-likelihood function using the probit model is specified as In L( a,~ I Ah) = IYesh -in[ <t>(-;-¾Ah )]+ ( 1Yesh)-ln[ 1 - <t>(-;-¾Ah )] h~l (2-21) 37 where Y esh indicates whether household h has accepted (Yesh = 1) or rejected (Yesh = 0) the proposed bid Ah. For the DeShazo interval data where information on three WTP intervals is obtained the log-likelihood function becomes In L( a, P IA~rsi, A~ollow) = I Yesh • in[ <t>(! -¾ A~rst )] h=l + No Yes . In[<t>(g_ -! A follow) - <t>(g_ -! A first)~ h crcrh crcrh1 (2-22) where A~rst denotes the first bid, A~ollow denotes the (lower) follow-up bid and No Yesh and NoNoh indicate the sequence of responses to the first and the follow-up bids. The Log-Likelihood function for the payment card interval data can be specified in a similar way since the selection of a specific bid interval [ A~ow, A~P ]on the payment card implies that the respondent accepts the bid amount of the lower bound of the interval A~ow and (approximately) rejects the upper bound A~P. The log-likelihood function therefore becomes lnL(a,PIA~w,A~P) = Iln[<t>(!-¾A~w)- <t>(!-¾A~P)]. (2-23) h=l The maximization of the respective Log-Likelihood functions yields the parameters a and p from which the mean and median WTP can be directly computed according to 2-20. Since the welfare estimate is computed as the ratio between two parameter estimates each of which has its own standard error of estimation the computation of the 95%-confidence interval as a measure for the variance of the WTP estimate is not as straightforward as for the open-ended WTP described above. For CVM interval data a number of simulation approaches for the approximate computation of confidence intervals are available in the literature ( cf. Cooper 1994 ). The present study will employ the approach of Park et al. ( 1991 ). In their bootstrap approach a large number, e. g. 1000, of values for WTP are simulated by randomly drawing values of the parameters a and P on the basis of their estimated variance-covariance matrix. From these simulated WTP values the 95%-confidence interval can easily be obtained by discarding the lower and upper 2,5% of these values, respectively. 38 utility criterion which requires people to think about the probability of occurrence and the severity of an event simultaneously. As Machina (1987) observed people tend to separate odds and consequences of an event and focus on the element that seems more "attractive" to them. Some focus on the low probability of occurrence and thus ignore the harmful event altogether which would lead to an underprovision of protection against harmful events. Others focus on the consequences of its occurrence and fail to take into account that it is rather unlikely to occur so that they exhibit overly cautious behavior termed "plan for the worst, hope for the best" by Sunstein (2002). A cost-benefit analysis where people exhibit predominantly this latter behavior would lead to biased benefit estimates and thus to an overprovision of protection against harmful events. Another anomaly widely known as preference reversal occurs frequently when evaluating lotteries (cf. Lichtenstein and Slovic 1973, Sugden 1999). Seidl (200 I: 621 f) defines preference reversals as "an empirical regularity such that there exists a robust experimental design of lotteries for which substantial fractions of subjects state prices [ ... ] which are opposite to the preferences expressed for or the choices made out of the respective lotteries". In other words, preference reversals represent a violation of the principle of procedure invariance according to which valid methods for preference elicitation should yield the same preference ordering. Preference reversals matter in CVM studies of risk and uncertainty because respondents in a CVM interview might state a monetary value for some risk reduction policy when asked their WTP, however, one cannot be sure that the same result would have been obtained if the respondent had been asked to choose between two uncertain alternatives based on his preferences. As Hanley and Shogren (2005: 24) note such cost-benefit analyses reveal little useful information since the valuation depends strongly upon the context in which the policy is framed. The authors propose a mechanism based on Cherry et al. (2003) for CVM studies inducing respondents to avoid preference reversing behavior in CVM settings, however this mechanism appears rather impractical and time consuming in practice. The problems associated with valuation of risky and uncertain outcomes using the CVM and the solutions proposed in the literature so far reveal that unresolved methodological issues remain. Respondents have trouble behaving according to the normative rational decision criterion of expected utility so that simple CVM studies not taking these problems into account will necessarily lead to non-optimal outcomes, in most cases to an overvaluation of risk reduction. 45 2.2.2 Rationality problems due to preference uncertainty In addition to uncertainty over future outcomes or environmental states it was shown in the literature that respondents often face some uncertainty w. r. t. their own preferences between environmental and market goods, especially so when they are asked to think about their personal trade-offs between these goods. Such preference uncertainty might be the source of a number of the procedural biases discussed above since uncertainty over their preferences would make respondents susceptible to answer WTP questions in a systematically distorted way. It is reasonable to expect that in a situation where respondents are uncertain of whether they prefer one situation over another or not their answers could easily be influenced by specific elements of the CVM questionnaire and survey design giving rise to irrational WTP statements thus leading to socially desirable responses and starting point bias etc. The question formats and the methods for analyzing CVM responses described above do not take the existence of preference uncertainty into account. Therefore, this section will briefly analyze existing approaches for dealing with preference uncertainty in CVM studies. It is hypothesized that one main source of such preference uncertainty is the respondent's unfamiliarity with the environmental good to be valued, i. e. his lack of experience in using it or, in case of an environmental degradation, his lack of experience in being deprived of it and its environmental services. Another important source of preference uncertainty is certainly missing familiarity with the valuation task, i. e. to think in monetary terms about environmental goods (cf. Samnaliev et al. 2006: 508). Although people might acknowledge that in reality there are numerous situations where environmental goods are actually traded off against market goods, these decisions usually occur in the domain of public decision making where the general population is not involved since such decisions are delegated to a higher administrative level. Being all of a sudden put into the situation to personally attribute a monetary value to some environmental improvement is certainly not an everyday and common task. However, preference uncertainty seems not to be restricted to non-market goods. As Ariely et al. (2003) demonstrate even the valuations of commonly used market goods exhibit a considerable degree of arbitrariness. In their experiments test persons were asked whether they would accept to purchase some common market good, e. g. a cordless trackball, a cordless computer keyboard, bottles of average and rare wines etc, at a price in dollar terms equaling the last two digits of their social security numbers. Subsequently they had to state their maximum WTP for the product. The answers were consequential since the test persons were required to purchase the good if a random device chose that the item would be sold at the stated price. It was 46 demonstrated that although the test persons were made aware of the randomness of this bid amount their valuations were anchored on it so that a significantly positive relation between the amount derived from the social security numbers and the personal valuations of the goods was found. However, within the product categories the test persons exhibited consistent valuations in that cordless trackballs were consistently valued lower than cordless keyboards and average wines lower than rare wines. The authors of this study describe the observed behavior as "coherent arbitrariness" since on the one hand valuations seem coherent due to the expected relations of value within the product categories but on the other hand are significantly influenced by the arbitrary anchor. It is hypothesized, therefore, that consumers in general do not have specific WTP values for products, they rather have some range of values what the item would be worth to them (cf. Ariely et al. 2003: 77). If the price falls below this range they will certainly purchase the item, if it exceeds the range they will decline the purchase. However, it is uncertain how they will decide if the price falls within the range which opens the opportunity for the observed arbitrariness of valuations. If such uncertainty ranges exist for common market goods that are familiar to people it is only plausible to assume the same in the case of the valuation of environmental goods. Respondents in CVM surveys certainly have a clear idea which bid they would definitely accept in a dichotomous choice format and which bid is clearly beyond being acceptable. Whenever the proposed bid falls between these two values that respondents would clearly accept or, respectively, reject, uncertainty of their true valuation exists. A number of methodological CVM studies have approached the issue of dealing with respondents' uncertainties of their preferences in order to obtain more valid welfare estimates. The approaches of dealing with respondent uncertainty can be classified into two categories: ( 1) uncertainty questions in combination with open-ended and dichotomous choice question formats and (2) multiple category (polychotomous choice) valuation questions allowing respondents to express uncertainty. In the first approach respondents are usually in a first step asked their WTP for some environmental project in the standard way. Subsequently, they are asked to rate on a given scale, e. g. between 0% and 100%, how certain they are that they would actually pay the stated amount (cf. Li and Mattsson 1995, Champ et al. 1997, Loomis and Ekstrand 1998, Berrens et al. 2002). Other studies use discrete categories like "definitely sure" and "probably sure" in order to avoid specific probabilistic statements ( cf. Blumenschein et al. 19,98, Johannesson et al. 1998). The validity of the first approach resulting in a post-decisional certainty measure must be seen very critical. It is highly doubtful that respondents will be able and motivated to reassess their just previously made WTP statement correctly in the light of their preference uncertainty. Such an 47 approach bears the risk that respondents feel like fools when they have to admit that their statement is actually quite doubtful. Therefore, the second approach of assessing the level of preference uncertainty using a polychotomous choice question format is more promising. In this format respondents are given the possibility to express uncertainty directly when stating their WTP, either in a DC or in a PC format. The simplest form of polychotomous choice which was already recommended by the NOAA-panel in 1993 is to include a "not sure"-option in a DC question format. Carson et al. ( 1996b) recommend to treat "not sure"-responses conservatively as "no" responses since it must be expected that if those respondents were forced to choose strictly between "yes" and "no" they would reject the bid. In an alternative, however more complex, polychotomous choice approach respondents can choose from a wide range of feeling uncertain about their "true" WTP while not being forced to contradict themselves. Multiple-bounded discrete choice (MBDC) represents a mixture between the payment card question format and the dichotomous choice format (cf. Ready et al. 1995, Welsh and Poe 1998, Alberini et al. 2003). Like in the PC format respondents are presented a list of bids, however, instead of indicating the highest acceptable amount for the proposed program respondents in the MBDC format are given a polychotomous choice option of rating for each interval on the list how likely they are to vote for the program if they had to pay the specified amount. Thus, for each bid respondents should indicate one of the given categories of likelihood "definitely yes", "probably yes", "not sure", "probably no" and "definitely no". For bid levels below their uncertainty range it is expected that respondents will indicate "definitely yes" whereas for bid levels above that range "definitely no" will be chosen. The uncertainty categories in this format give the respondent the possibility to express uncertainty about the respective bid levels in the three broad verbal categories "probably yes", "not sure" and "probably no", thus in this format respondents consider their certainty about bid levels not in retrospect but simultaneously. In contrast to the post-decisional certainty measures, therefore, expressed uncertainty in the MBDC format directly refers to preference uncertainty and not to the likelihood of having told the truth in the preceding WTP question. The response data collected in a MBDC format allow to formulate different models for the estimation of WTP based on the desired level of certainty. For example, if absolute certainty of the "yes"-response is desired a "definitely yes"- model can be estimated where the highest amount on the list of bids for which "definitely yes" was indicated is taken as the lower bound of the respondent's WTP interval and the next higher bid level is taken as upper bound. Alternatively, one could generate a "probably yes"-model or a "not sure"-model. A comparison of the "definitely yes"-, the "probably yes"- and the "not sure"- model with WTP responses obtained from regular open-ended (OE), PC and 48 single-bounded DC formats reveals three interesting results: the "definitely yes"- model yields WTP estimates well below those obtained from the regular OE, PC and DC formats, the "probably yes"-model yields estimates close to the OE and PC formats, whereas the DC estimates are nearly identical with the "not sure"- model (cf. Welsh and Poe 1998: 179). These results shed light on the reasons for the differences between the elicitation question formats: in the OE and PC formats respondents behave more cautiously and state as their maximum WTP only those values they feel quite confident with. In contrast, the DC format induces respondents to answer "yes" to the proposed bid although they feel considerably uncertain about whether they are actually willing to pay this amount. Thus, these findings are in line with the observed starting point bias in the DC format. The rationality of WTP statements made under preference uncertainty is certainly an issue that deserves scrutiny, especially if respondents have no possibility to express this feeling while giving their WTP responses. This issue will, therefore, be taken up again in chapter 4 where a theoretical approach employing fuzzy preferences will be discussed that may prove useful to incorporate the phenomenon of preference uncertainty into environmental valuation methods. 2.3 Summary This chapter gave an overview of the main aspects of the state of the art of environmental valuation with a focus on the Contingent Valuation Method. As a direct method of preference elicitation the CVM has the advantage to allow the assessment of both use and non-use values which play an important role in the context of environmental goods. In 2.2 the Hicksian Compensating Variation was derived as an appropriate individual welfare measure for environmental improvement projects. The Compensating Variation in this case can, as an approximation, be interpreted as the willingness to pay for a proposed improvement of an environmental good and is as such accessible to valuation using the CVM. In order to lay the foundations for further research of the CVM in this study the main approaches of questionnaire design and econometric estimation as well as the main theoretical and procedural concerns addressed in the past and current literature were presented. It was shown, however, that the simulated market settings employed by the direct valuation methods in order to measure also non-use values of environmental changes come at the cost of concerns that respondents often do not behave fully rationally. Such irrational behavior in CVM interviews may, therefore, result in biased benefit estimates. Therefore, the second section of this chapter discussed in detail what can go wrong in CVM interviews when respondents do not behave fully rationally and 49 approaches found in the literature to mitigate biases resulting from irrational response behavior were presented. Finally, the issue of preference uncertainty was addressed and its effects in CVM surveys were highlighted. Preference uncertainty was identified to be one of the prerequisites for the occurrences of procedural biases since the lack of firm preferences between market and environmental goods may make respondents susceptible to being unduly influenced by specific characteristics of the survey instrument employed. It is the purpose of this study to build on this previous work in the literature and find new ways of describing unexplained response behavior and make recommendations for an improvement of the CVM design in order to better account for the behavior of real world decision makers. 50 3 Rationality in economics 3.1 Outline of the chapter The assumption of rational economic agents has always played a prominent and very important role in economic theory. Rational action and decision making is seen as the underlying postulate of economic behavior. In fact, it is argued that the rationality postulate is essential for economic models to have a meaning, i. e. to have explanatory value with respect to economic behavior. As Silberberg (1990: 300) puts it, "Anything in the world can be explained on the basis that the participants are stupid [... ].", but no systematic conclusions or refutable hypotheses could be drawn from such an assumption. The challenge and at the same time the value of building economic models is to explain people's observed economic behavior based on the assumption that they make rational decisions, i.e. that they are not stupid. At the same time, over the course of time the rationality assumption has proven to be one of the most controversial and criticized of all the assumptions stated in economic models. This stems from the fact that on the one hand side the definitions or axioms of rationality used in many economic models are often unrealistic in that real economic agents could not be expected to fully act on the basis of these axioms and on the other hand it has been shown that in certain and reproducible circumstances people consistently violate these rationality axioms in their observed economic behavior. This chapter presents the emergence and further development of rationality concepts in economics. To this end, in section 3.2.1 the history of the rationality postulate starting from Adam Smith via Alfred Marshall is briefly reviewed. The three axioms of rationality which form the basis of the concept of instrumental rationality in neoclassical economics are introduced. Subsequently, the main points of criticism of the central rationality axiom, transitivity, will be highlighted. Specifically, arguments are presented as to why it is not reasonable to expect that economic agents always optimize. Section 3.2.2 will explore extensions of the concept of instrumental rationality leading to the overarching concept of bounded rationality. In section 3.3 the emergence of the bounded rationality concept as well as prominent instances of boundedly rational behavior will be presented. Since bounded rationality draws heavily on psychological insights on human information processing and decision making the main concepts of cognitive psychology shall be addressed in the light of decision making in environmental valuation. Finally, specific models of dualprocesses of reasoning reflecting boundedly rational decision making in environmental valuation will be outlined. These models form the conceptual 51 basis for the development of an empirical survey instrument for the analysis of bounded rationality in chapter 4. 3.2 Rationality concepts in economics - an overview 3.2.1 What is rationality? Although Adam Smith does not use the term "rationality" explicitly in his work "The Wealth of Nations" first published in 1776, his reflections on human behavior in economic contexts serve as a good starting point for a discussion of what "rationality" means in economics and how the interpretation and operationalization of this term has changed over time. In his famous sentence "It is not from the benevolence of the butcher, the brewer, or the baker, that we expect our dinner, but from their regard to their own interest" ( cf. Smith 1993: I.ii, p. 22) he postulates that people enter into mutually beneficial bargains out of their selfishness. Thus, Smith establishes the individual's focus on his selfinterest as the fundamental driver of any economic behavior, and any action that an individual undertakes should be in pursuit of this self-interest. In this respect, the major task of human beings as economic agents is "to judge where selfinterest lies" ( cf. Simon 1997: 6). Without referring to the term "rational" directly Smith clearly provides a description of the appropriate criterion of economic behavior. His view of rationality stems from everyday common sense, with respect to their behavior he simply assumes that people have reasons for what they do, i.e. in Silberberg's words: that they are not stupid. Smith's common sense view of rationality was soon going to be further specified and adapted to the requirements of the developing economic theory (cf. Simon 1987). Alfred Marshall who developed the marginalist approach to economics uses in his book "Principles of Economics" (cf. Marshall 1890: 6) the formulation "[ ... ] free choice by each individual of that line of conduct which after careful deliberation seems to him the best suited for attaining his ends, [ ... ]" in order to specify how an economic choice should be made. Thus, Marshall proposes that an economic agent who is to make the choice out of a number of alternative economic actions uses active reasoning given the available information about these alternative actions in order to find out which of the given actions represents the best way to satisfy the individual agent's goals and needs. This formulation, therefore, sets the scene for two fundamental assertions of neoclassical economics: ( 1) reasoning about the utility that is generated by each available alternative and, (2) choosing among the given alternatives so as to maximize the utility that can be achieved from the given alternative economic actions. It must be noted, that Marshall extends Smith's notion of self-interest as 52 the main driver of economic action. He explicitly states that the ends that an economic agent wishes to attain by some economic action might be either selfish or unselfish. With this remark, Marshall already acknowledges that otherregarding behavior, i. e. altruism, can be as much an element from which people derive individual utility as behavior that one might call selfish or egoistic. It can be speculated that Adam Smith used the term "self-interest" in quite the same sense as Marshall without explicitly making the difference between strict selfishness on the one hand and unselfishness on the other. The view of rationality that was established by Marshall and that is currently the view of rationality in the standard neoclassical economic models is usually termed fall, perfect, global or instrumental rationality. The terms perfect and global should indicate that under this rationality concept economic agents are assumed to have full knowledge or information about all possible economic actions and their resulting outcomes and are able to fully compute the ( expected) consequences of these actions and outcomes on their utilities in order to be able to make the decisions that maximize their utilities. The term instrumental refers to the view that "rational action is defined with respect to a given set of objectives: it is the action which best satisfies those objectives" (cf. Hargreaves Heap 1989: 40), i. e. the action leading to the outcome that best satisfies those objectives is considered the instrument suitable for achieving these. For every achievable outcome there is at least one instrument, one line of action, which yields this outcome. In neoclassical microeconomic theory full rationality is described by a set of desirable properties of individuals' preference orderings, the three rationality axioms. A preference ordering that is reflexive, complete and transitive is generally perceived as a rational preference ordering since these properties guarantee that an individual will always make consistent choices out of a set of available consumption bundles ( cf. Mas-Colell 1995: 6). Among these axioms, transitivity is by the far the most important one. Given completeness, transitivity imposes logical consistency restrictions on the preferences of an individual. If transitivity holds, the existence of preference cycles is ruled out, i. e. it is assured that for instance if coffee is stated to be at least as good as tea and tea at least as good as coke, then coke cannot be preferred to coffee. It is obvious that one would require an individual to exhibit transitivity in his preferences in order to classify him as rational in this example, the preference of coke over coffee in the above example would simply be logically inconsistent with the previous two preference assertions with respect to coffee, tea and coke. It has been criticized that the concept of instrumental rationality with its three main axioms of rational preference orderings does not adequately capture the rationality inherent in economic decisions of real-world economic agents. It is concerned only with the optimal instrument but not with the possibilities that economic agents actually have to find this instrument in real-world decision 53 environments. There is an abundant literature on the criticism of the neoclassical rationality concept and its operationalization, utility maximization. The most frequently criticized axiom of rational preference orderings in neoclassical economics is transitivity. In general, two lines of criticism are discussed: (I) transitivity and the assumption of stability of preferences over time and (2) unidimensional versus multidimensional consumption bundles. As to issue (I), there is no reason why preferences should not be allowed to change over time, either systematically or unsystematically, and, therefore, exhibit intransitivities among the alternatives available. An example of some systematic, or context dependent, preference change leading to intransitivities is given by Rosenberg (1992, cited in Lagueux, 2004 ): is it irrational for an individual to prefer regular coffee over milk at breakfast, milk over decaffeinated coffee at lunch, and the latter over regular coffee at dinner? In order to save the stability of preferences of this individual one would have to redefine the commodities like e. g. "milk for breakfast" and "regular coffee for lunch" where "breakfast" and "lunch" represent the different contexts in which the individual beverages need to be evaluated. But even with such a definition stability of preferences and transitivity are not assured. If, on one day, the individual plans a late night out he might well prefer regular coffee to decaf coffee for dinner and thus violate transitivity over time. One could, thus, specify the beverage even further as e. g. "regular coffee for dinner if a late night out is planned". This example could be extended into infinity which would only reveal that preferences can certainly not be assumed to be stable so that the fulfillment of transitivity as a condition for rational choice can reasonably only be expected at any one particular point in time. While under these circumstances it is still possible to represent a commodity choice at that point in time as conforming to the common rationality concept and thus as utility maximizing, the failure of preferences to exhibit transitivity over time makes a generalization of this utility maximizing choice to other similar decision situations impossible. As to issue (2) it is expected and has generally been found that transitivity is fulfilled in situations of choices among unidimensional or two-dimensional commodities or commodity bundles consisting of only two single commodity quantities. In a set of unidimensional commodities the single commodities differ only in the level of that single attribute that characterizes them, e. g. the face value of a coin. In the situation of choosing from two-dimensional commodity bundles the individual only needs to make trade-offs among the quantities of the underlying commodities, i. e. more of one commodity against less of the other. These situations are usually sufficiently simple for transitivity to prevail. As has been argued and shown already by May ( 1954) choices from multidimensional commodities or commodity bundles exhibit a substantial potential for intransitivities. May's design of a multidimensional decision problem was the following: three marriage partners were distinguished; each of them was ranked 54 generally conceived as operating in one single mode. Since the hybrid concepts of institutional and evolutionary rationality draw on both single-mode concepts they can be classified as dual-mode concepts of rationality. The field of descriptive rationality concepts derived from a more procedural perception of rationality shall be subsumed here under the term "bounded rationality". In the literature, no clear cut definition of what bounded rationality comprises and what it does not, has emerged. In any case, the central characteristic of bounded rationality is its requirement to be in line with the central findings of cognitive psychology regarding information processing in human brains, problem solving and decision making. As already mentioned in the section on procedural rationality as conceptualized by Herbert Simon, the use of decision heuristics in order to find a way out of the notorious infinite regress problem of rational choice is the main feature of the descriptive rationality concepts. Evolutionary rationality explains the emergence of such decision rules while institutional rationality provides an intuition as to when it is rational to employ conscious, cognitively effortful reasoning and when procedural, rule-following behavior seems to be more appropriate. Due to the importance of the overarching concept of bounded rationality for this study, the following section shall briefly review its development and evidence in the literature before addressing more specifically the kinds of decision heuristics employed by boundedly rational decision makers. 3.3 Bounded rationality 3.3.1 The emergence of bounded rationality in the literature Even before the term "bounded rationality" appeared for the first time in the social science literature with Herbert Simon's book "Models of Man" (cf. Simon 1957), the concept developed in social science works under different terms. In a recent historiographic survey Klaes and Sent (2005) analyze the occurrence of related terms over the course of time. They identify a base field of expressions and technical terms setting the stage and preceding the occurrence of bounded rationality. The term limited intelligence appeared for the first time in the literature in 1840 in a Report to the Council of the Statistical Society and can be considered the starting point of the conceptual development of bounded rationality. Limited intelligence is later joined by a number of terms within the base field of bounded rationality, namely finite intelligence, incomplete rationality, limited rationality and approximate rationality. The numbers of occurrences of these terms of the base field in the literature up to now, along with those of subsequent concepts, are illustrated in table 3-1. 61 While limited intelligence was at that time far from being used as a technical term and rather carried along prejudicial and offending connotations with respect to other peoples or social classes, the term finite intelligence became a technical term largely confined to the philosophical literature as of the year 1880. It was mainly used to distinguish man's intelligence, thoughts and ideas from divine, perfect intelligence, thus closely associated with religious ideas. In the 1920s this term becomes mainly used to describe the limitations of human cognition with respect to the perception of the natural world. Table 3-1: The development of the Bounded Rationality field from 1840 - 1995, from Klaes and Sent (2005: 30) Base field Limited intelligence Finite intelligence Incomplete rationality Limited rationality Approximate rationality Bounded rationality Procedural rationality Finite rationality Constrained rationality first occurrence 1840 1880 1922 1945 1948 1957 1963 1972 1978 Total 73 40 7 105 9 626 124 17 7 In 1922 the word "rationality" starts to be associated with discussions of finite intelligence in Oakeley's article "On the Meaning of Value" (cf. Oakley 1922, cited in Klaes and Sent 2005: 34) which is contrary to its title not an economic work but a philosophical treatise of how humans with their finite intelligence and limited knowledge of the world could possibly "comprehend ideals of value". In this sense, incomplete rationality is seen as a central property of, in this respect, limitedly endowed human beings. Whereas incomplete rationality was just very shortly and rarely used in the literature (see table 3-1 ), the expression limited rationality first used by Almond (1945, cited in Klaes and Sent 2005: 36) turned out to be a much more potent technical term for a further diffusion of the controversies on rationality. When Herbert Simon entered the discussion of rationality concepts in economics, he picked up limited rationality as the common term in the social science literature at that time in his groundbreaking article "A Behavioral Model of Rational Choice" in 1955 (cf. Simon 1955). 62 According to Klaes and Sent (2005) Simon seemed to experiment for some time with variations of rationality terms, in the process coining the term approximate rationality, until he finally created the technical expression bounded rationality which came to dominate the entire conceptual field in the subsequent decades. Simon intended "to use this expression as a label for the things that economists needed to pay attention to -and were not" (Simon 1999: 23, cited in Klaes and Sent 2005: 37). From hindsight, bounded rationality emerged as the dominating technical term for mainly two reasons: first, Simon elevated it to the rank of a principle, the "principle of bounded rationality" which seemed to motivate discussions and further research as to a deeper understanding of such a principle, and, second, the term "bounded" seemed to appeal to mathematically oriented economists who were used to thinking of optimization problems in terms of boundary conditions to some objective function. Thus, the limitations of the human mind were coined as a mere extension to the already existing boundary conditions of a mathematical optimization problem which made this concept easier to assimilate in economics. In the introduction to part IV of "Models of Man" ( cf. Simon 1957: 196ft), where the term bounded rationality was supposedly used for the first time in the literature, Simon sets out the principle as follows: "The alternative approach employed in these papers is based on what I shall call the principle of bounded rationality: The capacity of the human mind for formulating and solving complex problems is very small compared with the size of the problems whose solution is required for objectively rational behavior in the real world -or even for a reasonable approximation to such objective rationality". Later, Simon (1987: 266) states that the concept is used to "designate rational choice that takes into account the cognitive limitations of the decision maker -limitations of both knowledge and computational capacity." Thus, the concept was intended as a criticism of neoclassical economics which used to model decision making generally in an environment of either perfect information or optimal risk taking under the assumption of unlimited computational abilities. With his models based on the "principle of bounded rationality" Simon starts to provide a formal framework for modeling decision making under circumstances that are seen to be more appropriate in real-world situations and thus challenges the standard neoclassical models. He explicitly takes into account and includes into his models those conditions of the human mind and of his social, external environment that prevent human actors from making decisions in such a way that would even approximate the predictions of neoclassical economics. Instead of aiming only on the outcome of a decision problem, as this would be the focus under the concept of substantive or global rationality, bounded rationality stresses the importance of the process of decision making, of how people actually arrive at their decisions given their knowledge, computational capabilities and external constraints. In order to be 63 able to arrive at suitable decisions at all, human actors seem to have developed simplifying strategies, based on tradition and experience, that have proved to be successful in the past. These rules of thumb, or heuristics, enable a decision maker to arrive at least at a satisfactory decision within the given constraints. For this search for merely satisfactory outcomes for which, after attained in the decision making process, any search for better outcomes is terminated, Simon has coined the term "satisficing". Under the satisficing heuristic a decision maker defines an aspiration level, i. e. a minimal level of well-being to be attained by some decision, and searches and evaluates the available alternatives, the budget set, until an alternative satisfying that minimal aspiration level is found. At that point, the search and evaluation of further alternatives is terminated and the decision maker settles with the (first) satisfactory outcome found along the search. In this simple procedure, the main concern of the principle of bounded rationality and its main point of criticism of neoclassical economics becomes apparent: the necessity to define at which point a search or a decision making process is finally terminated. The satisficing heuristic, therefore, represents a real-world operationalization of the common condition for search-stopping that the marginal benefit of further search should equal its marginal cost. 3.3.2 Evidence of bounded rationality in economics and the social sciences Accepting the existence of bounded rationality in real-world decision making does not mean to assume that all decisions exhibit strong distorting effects that would entirely reject the results predicted by the standard theory of instrumental or substantive rationality. There are many situations in which the outcomes of economic decision problems are in conformity with the standard theory, i.e. where economic agents achieve optimal or nearly optimal outcomes. However, the literature provides a wide variety of examples in which the assumptions of the standard theory seem to fail systematically and where alternative approaches for explaining the observed behavior, like for example bounded rationality, need to be taken into consideration. This section will review some of the evidence of boundedly rational behavior found in the literature and will try to uncover some unifying pattern from these examples. One line of evidence of boundedly rational behavior is based on direct experiments with single individuals in order to test whether they adhere to the assumption of substantive rationality in that experimental setting. The basic idea in many of such experiments is to confront individuals with a specific decision problem to which an objectively correct solution exists, such as dealing with probabilities and statistical evidence. These experiments demonstrate that individuals are susceptible to a number of systematic biases: e. g. they often 64 seem to misunderstand statistical independence of given data, they mistake random data for patterned data and vice versa, they make errors in updating probabilities on the basis of new information ( a violation of Bayes' rule), make false inferences about causalities and exaggerate the ex ante probability of a random event which has already occurred,just to name a few (see Conlisk 1996 for a detailed review of these effects). Other experiments do not make use of such a reference point of objectively correct answers but they test whether the observed behavior exhibited by test individuals in an experimental setting conforms to the expectation predicted by the standard rationality assumption. In these experiments it is often found, for example, that people place higher values on "status quo" options than would be expected, that they fail to discount the future consistently and that they fail to adjust repeated choices in the light of changing constraints ( cf. Conlisk 1996 ). It is, thus, hypothesized that people systematically commit cognitive errors and use simplifying rules, or heuristics, when solving a given task. The above mentioned results emerged from a body of literature mainly initiated by decision theory psychologists around Daniel Kahneman, Amos Tversky and Paul Slovic who started an extensive research program known as "Heuristics and Biases" (cf. Kahneman et al. 1982, Gilovich et al. 2002). Under the overarching theme of simplifying mechanisms of information processing leading to systematic biases of judgment and decision behavior, three basic heuristics were identified to be accountable for these effects: (1) availability, (2) representativeness, and (3) anchoring and adjustment. The availability heuristic refers to judgment errors caused by the ease of memory retrieval, e. g. the estimation of how frequently a specific event occurs would be biased by how recently such an event has occurred because recent events are more easily available in the mind than less recent ones. The representativeness heuristic refers to judgment which is influenced by what one considers typical. A rather famous and widely controversially discussed example is the "Linda problem" which shall be cited here because of its prominence in the literature. In this example, test persons are given a brief description of a 31 year-old woman who is single, outspoken and very bright. As a student she majored in philosophy and was deeply concerned with issues of discrimination and social justice. Also, she participated in anti-nuclear demonstrations. After this description the test persons are asked to rank a number of statements about her according to their probability to be true. Surprisingly, a majority oftest persons rank the statement "Linda is a bank teller and is active in the feminist movement" (T&F) more likely than the more general statement "Linda is a bank teller" (T). This judgment is a clear violation of the conjunction rule according to which the more specific category T &F cannot be more likely than the more general category T since the former is just a subset of the latter. Therefore, such biased judgment was termed "conjunction 65 fallacy". It is argued that this behavior is brought about by the higher representativeness of the specific statement T &F in terms of the description of the personality, i. e. the description resembles that of a typical feminist (without even mentioning this trait explicitly) so that the more specific statement of Linda being a feminist bank teller is invoked more strongly than the one of being "just" a bank teller, for which the personality description is not at all typical. The conjunction fallacy could be replicated in a wide variety of experiments under different environments. An often cited consequence of the representative heuristic is the phenomenon of preference reversals which have already been discussed in relation to reasoning errors in the CVM under risk and uncertainty in section 2.2.1. Preference reversals represent a violation of the fundamental principle of procedure invariance and are, thus, of great concern for any empirical application of economic decision making. For illustration, a simple example of preference reversals shall be given here using the following two gambles A and B: Gamble A: 90% probability to win $8 Gamble B: 20% probability to win $30 In preference reversal experiments test persons are asked to state a minimum price at which they would sell each of these gambles (assuming they had acquired the right to play the gambles themselves) and to subsequently choose which gamble they would like to play. In this experiment, most people choose to play gamble A over gamble B, but at the same time a high proportion of people ( 40% -50%) states a higher selling price for gamble B. This result is a clear violation of procedural invariance according to which it should not matter which method, pricing versus choice, is used for eliciting the preferences over these gambles. Preference reversals are usually explained by the compatibility effect and the prominence effect which can both be interpreted as being based on representativeness. The compatibility effect states that when monetary values are an available attribute of a gamble they have more influence on an evaluative response which is also in monetary units like a price. Thus, since $30 is much higher than $8 gamble B receives a higher price. On the other hand, when asked to choose a gamble to play a probability of winning of 90% features much more prominent than one of 20% so that people tend to make their choice, in this case correctly, based on the higher probability. The literature dealing with preference reversals is much too extensive to be reviewed here ( cf. Irwin et al. 1993, List 2002, Safra et al. 1990, Seidl 2001 ). The anchoring and adjustment heuristic refers to judgment which is influenced by what comes first, i. e. where "people make estimates by starting from an initial value that is adjusted to yield the final answer [and where] 66 adjustments are typically insufficient" (cf. Tversky and Kahneman 1974: 1128). Such anchors, although randomly chosen and presented to test persons, were shown to influence judgments consistently in a wide variety of task environments. Thus, whenever anchors are chosen or provided in a biased way the outcome of a judgment based on anchoring and adjustment will be biased as well. The starting point bias in the dichotomous choice elicitation format is a good example for the use of the anchoring and adjustment heuristic in the context of the CVM. A number of results inconsistent with the traditional rationality assumptions, especially in judgments based on the correct application of the expected utility criterion, could be explained by these three underlying heuristics and as such form the conceptual basis for frequently observed judgment errors in CVM surveys. It was found that certain cognitive errors could be avoided with increasing experience on the side of the individual decision maker and by making certain changes in the experimental design. From these findings, it was investigated under which circumstances the found systematic biases could be made to disappear ( de biasing). It turned out that while setting clear economic incentives and punishing cognitive errors successfully eliminated some of the biases, others consistently kept occurring so that the possibilities for debiasing remained limited ( cf. Grether 1992, Slonim 1994 ). A second line of evidence of boundedly rational behavior is rooted in testing rationality assumptions using real economic data, either from actual transactions or from economic surveys. Thaler (1992) provides a comprehensive overview of anomalies in everyday economic life collected from a series of articles in The Journal of Economic Perspectives. In the field of consumer behavior it commonly occurs that households deviate substantially from the assumptions of standard life cycle theory of intertemporal choice. Smoothing of consumption on the basis of perceived life-time income is usually far from efficient in this sense so "that the young and the old consume too little, that consumption is unduly sensitive to short run income fluctuations, that consumption is not sensitive enough to expected future changes in income, and that consumption is improperly sensitive to the composition of wealth and income" ( cf. Conlisk 1996: 672). A rich source of anomalies are the financial markets, e. g. the stock market and foreign exchange markets where investors exhibit anomalous behavior with respect to asset pricing. The development of asset prices generally deviates from the predictions of the efficient markets hypothesis according to which arbitrage should make price predictability impossible. However, a number of studies demonstrate anomalies like end-of-week, end-of-year, seasonal and holiday effects ( cf. Thaler 1992: 139ft), excess fluctuation in prices relative to fluctuation in fundamental data and dramatic bubbles that cannot be explained by changes in fundamentals, just to name a few. Cutler et al. (1991) provide an extensive overview of such anomalies. 67 An anomaly already discussed in the context of environmental valuation (see chapter 2) seems to be present in other economic situations as well: that people attribute a higher value to a good if they are asked to sell it than if they were to acquire it, i. e. the disparity between willingness-to-pay and willingness-toaccept. This anomaly is at odds with standard utility theory and implies that an individual's indifference curve exhibits a kink at the status quo location. Such indifference curves whose location changes every time a different status quo is observed cannot conform to the basic assumptions of utility theory like e. g. transitivity. In their prospect theory Kahneman and Tversky ( 1979) have termed this kind of behavior "loss aversion" and "endowment effect". Since the development of the theory, prospect theory has been extended in a number of ways, e.g. allowing for uncertainty of status quo and reference points (see Schmidt et al. forthcoming for a discussion of refinements of prospect theory). A further example of frequently occurring anomalies is the phenomenon of overbidding, termed "winner's curse" by Thaler ( 1992). During auctions, experimental or real, it is a common phenomenon that the winning bid either exceeds the value of the offered stake or turns out to generate a disappointingly low surplus falling short of the opportunity costs of the investment. Numerous studies ( e. g. Capen et al. 1971, Hendricks et al. 1987, cited in Thaler 1992) have been conducted on returns of oil drilling lease auctions documenting the losses and low returns for the winners. According to Thaler (1992: 62) "the key ingredient is the existence of a cognitive illusion, a mental task that induces a substantial majority of subjects to make a systematic error. [ ... ] Whenever such an illusion can be demonstrated, the possibility that market outcomes will diverge from the predictions of economic theory is present." In summary, the above mentioned behavioral anomalies demonstrate the fact that the standard assumption of substantive rationality is too idealistic to accommodate and explain many facets of behavior observed in the real world. As was shown in chapter 2 deviations from instrumentally rational behavior was also widely observed in the field of environmental valuation methods. This section demonstrated that the reasons for such anomalous behavior, whether in every day economic decisions, laboratory experiments or CVM surveys, are based largely on the same behavioral principles. Thus far, however, bounded rationality and its behavioral consequences were treated in a rather descriptive way. In order to understand and analyze boundedly rational behavior its underlying mechanisms need to be explored further. Since the main characteristics of bounded rationality as described above were found in people's limited cognitive and information processing capabilities explanations for boundedly rational reasoning should be found in the field of psychology, especially modem cognitive psychology. The following section of this chapter will, therefore, explore these foundations of boundedly rational information 68 processing, specifically in relation to environmental valuation methods, by looking over the disciplinary fence into the neighboring field of psychology. 3.3.3 The psychological foundations of bounded rationality in environmental valuation 3.3.3.1 Why deal with psychology? Looking at human decision making behavior in general, evidence of decision not conforming to the assumption of full rationality is rather strong in real-world situations. As shown above, in many judgment and decision making environments people deviate systematically from the predictions made by standard theories based on the fully rational homo oeconomicus. One explanation for this behavior is certainly that deliberation comes at a cost to the economic agent so that these costs need to be included into models of optimal decision making. This approach, however, is limited by the infinite regress problem of optimal search mentioned in section 3.2.2 where Simon proposed the use of the satisficing heuristic to determine the point of equality of marginal benefits of further search and marginal cost in an intuitive way. Given these observations and given the fact that decisions are actually taken in the real world despite the impossibility of determining optimal stopping as defined above there must be other explanations of how people actually arrive at decisions, some even in very short time without possibly being able to check for the fulfillment of the mentioned marginal condition. Relating the insights of the preceding sections of this chapter to the theme of this study, environmental valuation using direct valuation methods like the CVM, some important connections can be drawn between the rationality problems mentioned in chapter 2 and the concept of bounded rationality described above. It was revealed that CVM respondents are susceptible to produce systematically biased responses to the WTP elicitation question when particular characteristics of a questionnaire or an interview situation prevail. In case respondents were fully rational in the instrumental sense their responses to the WTP elicitation question would simply be guided by their evaluation of their preference ordering w. r. t. to market and environmental goods. Their response would, thus, be invariant to procedural characteristics of the survey as long as the environmental good to be valued remains the same. Obviously, this is not the case as demonstrated by a multitude of valuation studies systematically exploring biased response behavior. Instead, respondents' WTP statements seem to be guided to some extent by characteristics of the survey that should have nothing to do with their "real" valuation of the environmental good. The initial bid in a dichotomous choice 69 elicitation question or the presence of an interviewer during the interview appear to trigger certain behavioral programs within the respondent with which he reacts to these elements of the decision environment. It might be suspected that such behavior stems from certain rules the respondent has learned to apply in particular decision situations. For example, as is often suspected, an initial bid signals the respondent a reasonable amount that everyone would have to pay for the provision of an environmental good, like e. g. a fair share of the cost of provision. The behavioral rule activated in this situation might be to accept such a fair share although the respondent is not entirely certain of the actual benefits accruing to him in case the environmental good is provided. For the respondent such a behavior must not be considered irrational, although it might be from a strictly instrumental point of view. Employing such a behavioral rule functions as a simplifying heuristic that allows him to evaluate an unknown situation that would otherwise require much cognitive effort with much less time and effort, instead. The respondent considers the use of such a heuristic as rational since it might have helped him in previous situations to make adequate decisions. Therefore, such observed behavior must be evaluated in the light of bounded rationality as discussed above. In order to search for the underlying reasons for boundedly rational reasoning and human decision making behavior it seems promising to look into the neighboring field of psychology as a discipline that lies at the core of mental processes in human brains, the foundations of all behavior. The necessity to transgress the disciplinary boundaries of economics and search for explanations of boundedly rational behavior in psychology was prominently stated by Simon in two citations: "If the principle [ of bounded rationality] is correct, then the goal of classical economic theory -to predict the behavior of rational man without making an empirical investigation of his psychological properties - is unattainable" ( cf. Simon 1957: 199) and: "Theories of bounded rationality are more ambitious [than simply expected utility], in trying to capture the actual process of decision as well as the substance of the final decision itself. A veridical theory of this kind can only be erected on the basis of empirical knowledge of the capabilities and limitations of the human mind; that is to say, on the basis of psychological research" (cf. Simon 1987: 267). In the light of this necessity, after a long period of seemingly insurmountable gaps in their respective world views the scientific fields of economics and psychology have in recent times come increasingly closer in the way they perceive human decision making (cf. Handgraaf and van Raaij 2005). Behavioral economics (from the side of economists) and economic psychology (from the side of psychologists) are now well-established fields of interdisciplinary cooperation. Broadly speaking, psychology aims at understanding mental processes of human beings and at explaining human behavior using this understanding. Exploring the link between the outside world with its many stimuli and the inner 70 the meaning of input information can be seen as the representation of the content of that verbal input within the cognitive system, i.e. in the memory. The fact that verbal information is represented as abstract propositions highlights the importance of the translation process ofthe verbal description ofa CVM scenario into the propositions stored for further processing. The recipient of verbal information, either text to be read by the interviewee himself or being read out loudly by the interviewer, needs to be able to filter out the important parts of the information in order to establish a propositional network that carries the essential facts about the presented scenario and payment scheme. This emphasizes the well-known recommendation that CVM researchers devote much time and effort especially on the design of verbal scenario information. Further, the fact that visuospatial and verbal information is represented in different ways is underscored by the finding that different regions of the brain have been shown to be active depending on the processing of visuospatial or verbal information. Furthermore, Shephard (1967) and Standing (1973) have both shown that visual memory is superior to the memory of verbal information stemming from the assumption that analog representations are more easily retrievable than abstract propositional representations. This explains the wellknown fact that it is easier to memorize verbal information if it is associated with a visual imagination of that information. Quite naturally, the combination of verbal and visual information in the presentation of a CVM scenario helps the interviewee to absorb and memorizes higher amounts and more complex information. Theories of memory: the role of elaboration Due to its importance for the storage of scenario information for further processing in the course of evaluating such a CVM scenario some remarks about the human memory system should be dropped at this point. Formerly, the human memory system was perceived as a sequence of storage units, namely the sensory memory as mentioned above from which the relevant information is transferred to the short-term memory through the filter of attention. Subsequently, contents of the short-term memory could be transferred by the active process of memorization into the long-term or permanent memory (cf. Broadbent 1958, Waugh and Norman 1965). It was hypothesized that the shortterm memory had a limited capacity of about 6 - 8 elements, the so-called memory span, which can easily be determined by the number of elements, e. g. numbers, letters, words etc., that one can reproduce immediately after being presented. If one does not achieve the transfer of an element of the short-term memory into long-term memory by active memorization (e.g. constant repetition or rehearsal) that element would be overwritten by new, i.e. more recent information entering the short-term memory via attention. This theory 77 which was in line with a lot of experimental data at the time was challenged by Craik and Lockhart (1972) who argued that the amount of information stored in long-term memory did not as much depend on the time spent on (mechanical) memorization, e. g. the number of repetitions, but on the depth with which this particular information is processed in the cognitive system. Their theory of processing levels states that memorization only increases the likelihood of storage in the memory if that information is memorized in a deep and meaningful way, i.e. passive memorization like pure repetitions will not lead to permanent storage. Craik and Lockhart's theory and a number of experiments verifying this distinction ( cf. Glen berg et al. 1977) led to the abandonment of the assumption of a separate short-term memory, it simply turned out to be superfluous for the explanation of memory processes. In place of short-term memory Baddeley (1986) proposed the concept of a phonological and articulatory loop for verbal stimuli in order to account for the existence of the memory span of 6 to 8 elements mentioned above. The articulatory loop represents the so-called working memory as the amount of information that can be kept in memory by constant repetition (loop) and it corresponds roughly to the amount of syllables that can be read (and repeated) within 1.5 to 2 seconds (cf. Baddeley et al. 1975). Whereas the articulatory loop represents the working memory for verbal stimuli, visual stimuli are kept available in the so-called visuospatial sketchpad. The task of the sketchpad is to keep constant track of changes of the spatial arrangements of objects surrounding us, i. e. determining one's own location in relation to the outside world. These two systems of working memory represent support systems for the central executive which coordinates attention and the systems of working memory and which utilizes their information for higher cognitive processes, for example the evaluation of a CVM scenario in the light of one's preferences. The distinction of these support systems to the concept of a short-term memory is that they work independently from each other and exhibit no interference. Thus, the phonological and articulatory loops and the visuospatial sketchpad are simply support systems to keep information available and accessible for further processing by the central executive. As mentioned above primary sensory information is quickly translated into semantic information where especially the meaning of verbal information is represented in some kind of propositional structure while the superfluous details, like the exact wording in sentences, are erased, i. e. lost. It appears that this translation is crucial for a transfer of information to the long-term memory. Such translations occur the better the more meaning is given to the primary information, i.e. the more a person elaborates on it (cf. Medin et al. 2005: 155). Elaborative processing consists of an enrichment of the content to be stored by additional information that creates associations and thus embeds this content into a broader context. In line with the theory of processing level a higher degree 78 of elaboration on sensory information increases the likelihood that this information is translated into meaningful propositional structures that are then more easily transferred to the long-term memory. The fact that information can usually be remembered better if it is considered to be personally of importance can also be explained by a higher degree of processing, by higher elaboration that creates a meaningful propositional structure and forms associations with other aspects of personal importance. In section 3.3.4 theories of information processing, especially the theories of dual-processes will be described in more detail since they form the underlying psychological theory of the research approach pursued in this study. While the long term memory does not play an important role in the context of environmental valuation due to the short duration of CVM interviews storage of scenario information in the working memory is certainly a crucial aspect. In this respect the distinction between short term memory and working memory is mostly academic, however, the importance of elaboration is highlighted by the theory of processing levels. The more an interviewee elaborates on the provided scenario information and gives a personal meaning to it the better this information will be available in the working memory for further evaluation. An interviewee will elaborate more on the given information if it relates to his personal context so that the information carries meaning for his personal circumstances. In order to help interviewees to elaborate it is common practice in CVM interviews that the essential aspects of the scenario information are repeated before proceeding to the WTP question. For example, the respondent is asked to what extent he considers certain aspects of the presented scenario as important. Such an intermezzo forces the interviewee to reconsider the presented information and put it into a personal context, thus increasing its availability for further information processing, for example a monetary evaluation of the benefits generated by the CVM scenario. This short introduction should serve to highlight some basic and relevant aspects of current knowledge of cognitive psychological processes of human beings in order to provide some necessary background for the more specific models of information processing and reasoning. It was shown how central aspects of cognitive psychology relate to crucial issues of the design of environmental valuation surveys. The field of cognitive psychology is developing rapidly and important and stunning insights into the functioning of the human mind are published at a high rate. These new insights are mainly due to the modem technologies of fMRI (see above) that allow almost a direct observation of the working of the brain. For a most recent textbook covering the entire state-of-the-art in cognitive psychology consult Medin et al. (2005). In the following section the basic concepts of cognitive psychology just presented will be employed in a set of theories and models of human information processing and reasoning forming the basis of the empirical research approach of this study. 79 3.3.4 Psychological models of reasoning: dual-process approaches 3.3.4.1 The concept of dual-process approaches After this discussion regarding the important connections between cognitive psychological aspects and response behavior in CVM surveys a specific class of theories concerning the process of reasoning and problem solving need to be addressed in detail. These theories form the conceptual basis of the empirical research of this study since they allow the formulation of survey instruments for an analysis of CVM response behavior in the light of bounded rationality of respondents. However, unlike the fundamentals of cognitive psychology described above the question of which basic processes actually guide our thinking, reasoning, inferring and problem solving is far from being settled. Experimental findings of reasoning have produced a number of theories each of which can claim some plausibility for explaining the observed data. Traditionally, the competition stretches from "models of mental phenomena to be built out of networks of associative devices that pass activation around in parallel and distributed form" (see e.g. McClelland et al. 1986 for models of parallel distributed processing) to the other extreme of "models built out of formal languages in which symbols are composed into sentences that are processed sequentially", in close analogy to the functioning of computers (cf. Sloman 2002: 379). However, there is a vast amount of evidence to strongly suggest that neither of these two extreme views holds the sole truth. Human thinking rather seems to be composed of building blocks from both of the above mentioned extremes each of which is sometimes more and sometimes less involved in a specific reasoning task. This perspective is summarized in the field of cognitive research on the two systems of reasoning, i.e. on the so-called "dual-process" approaches. Until now, dual-process theories of reasoning do not form a coherent view w. r. t. the exact nature of reasoning, rather a multitude of specific approaches and conceptual models has arisen since the beginning of the 1980s each focusing on a more or less specific problem constellation. However, these models all have in common that they aim at explaining the puzzling facts, i. e. that people are "capable of being foolish one moment and wise the next, capable of behaving intransigently and then credulously in tum, capable of believing the right thing with their whole hearts while saying precisely the wrong thing with their whole mouths" (cf. Gilbert 1999: 4). The common perception of these models is the view that "two qualitatively different modes of information processing operate in making judgments and decisions in solving problems. In essence, the common distinction in dual-process models is between a fast, associative information-processing mode based on low-effort heuristics, and a slow, rulebased information-processing mode based on high-effort systematic reasoning" 80 ( cf. Chaiken and Trope 1999: ix). Not surprisingly, this distinction mirrors the dual-mode rationality concepts of institutional and evolutionary rationality mentioned in section 3.2.2 The multitude of models for these two different modes of information processing has also generated a multitude of names. Overall, one of these processes has been referred to as intuitive, natural, automatic, heuristic, preconscious, schematic, prototypical, narrative, implicit, imagistic-nonverbal or experiential while the other fundamental process is often termed rational, thinking-conceptual-logical, extensional, conscious, deliberative-ejfortful-intentional, systematic, explicit or verbal ( cf. Epstein et al. 1996 and citations there). In general, the dual-process models of reasoning are motivated by the principle of least effort ( cf. Allport 1954) which describes people's tendency to achieve desirable outcomes by employing as little cognitive effort as possible due to their feelings that their own cognitive resources like e. g. attention, memory or logical thinking are naturally constrained. In an environment where constant and complex stimuli need to be evaluated and to which an individual possibly needs to react it is necessary to economize on those scarce cognitive resources. It has been described above that such scarcity is implied by the bottlenecks and capacity constraints in information processing, i. e. the competition among simultaneous cognitive tasks for processing capacity. It is thus argued that the default mode of information processing relies on simplification and learned automatic processes like e.g. the use of heuristics that have been acquired over time by dealing successfully with similar situations in the past. These simplifications "avoid effortful expenditures of cognitive energy" (cf. Moskowitz et al. 1999: 28) whenever possible in order to achieve satisfactory outcomes. But how is this satisfaction level determined, what happens if it cannot be attained in the default mode of information processing? The underlying view in all dual-process models is that people seek sufficient rather than accurate knowledge of states, acceptable rather than optimal outcomes. As long as available information is seen as sufficient for a specific situation, e. g. explaining the motives of behavior of someone or deciding whether to undertake an action or not, and as long as the expected outcome of such an action is perceived acceptable, the default mode of processing will do. However, such economizing information processors become motivated to process information more deeply and systematically whenever a feeling of insufficiency arises, i. e. if their feeling of confidence in the automated heuristics and low-effort reasoning processes gets too low. In such situations, people will be motivated to take "a closer look", they will shift to more effortful, more systematic processes in order to overcome and alleviate this feeling of insufficiency. It has been argued that on the one hand such a shift generally occurs when the information at hand is perceived as being so inconsistent with prior structures that an 81 individual's confidence in his judgment is seriously shaken. On the other hand, people might willfully choose to look closer in situations where they desire accuracy of information and judgment ( cf. Tetlock 1985). Thus, people are seen to be "flexible processors", i.e. they are capable of more elaborate processing when they desire greater certainty. Each of the specific dual-process models that will be described in the next section has developed their own criteria for the shift of use of information processes, or their mix, so this issue will be discussed in detail there. Before presenting selected specific dual-process models, a classification of the nature of these models shall be attempted. The basic distinction between the dual-process approaches concerns the way and the degree to which these two fundamental systems (for simplicity they shall be called intuitive vs. rational in the following) interact. Under the first view, only one of these two processing modes is involved in a given task, the second view holds that every outcome is ultimately produced by both modes. Following Gilbert ( 1999), the first view comprises two possible designs of interaction: ( 1) the selective design where the specific task at hand or outside stimuli activate one of the two processing modes selectively while the other remains dormant and (2) the competitive design where both processing modes are initially activated but the one with the stronger activation outcompetes the other at a specific state of processing which has no further part in the fulfillment of the task. An example of the latter could be seen in analogy to the simultaneous activation of the two meanings of the word "bank" where the specific context quickly decides which of the meanings is more appropriate, the river-bank or the financial institution. Under the second view two alternative designs of processing mode interaction are conceivable: (3) the consolidative design where any outcome is always a mix of both processing modes to a varying degree and ( 4) the corrective design where one of the two processing modes, preferably the intuitive mode, gets activated first but its outcome is subsequently subjected to a possibly corrective intervention by the other, the rational mode. Table 3-2 illustrates the distinction of these four possible designs of dual-processing modes. To date the second view seems to be more prominent, therefore the majority of dual-process models that will be presented and discussed subsequently follows this view. However, the borderline between consolidative and corrective designs is often blurred in these specific models, in fact, as will be illustrated below, the described classification applies best to specific judgmental situations and not to entire dual-process modeling approaches. 82 Table 3-2: Features of the four elementary dual-process designs (adapted from Gilbert 1999: 7) Are both processes Do both processes control activated? output? Selective design No No Competitive design Yes No Consolidative Yes Yes design Corrective design Sometimes Sometimes In conclusion, the dual-process models of reasoning allow to address the often voiced reservation to perceive CVM respondents as fully rational decision makers more specifically. According to these models reasoning and information processing in CVM interviews can now be perceived to follow two different branches: the first branch conforms more to the concept of instrumental rationality where conscious evaluation of the available information using effortful sequential cognitive processes takes place, the second branch conforms more to the concept of procedural rationality where the "economy of cognition" leads respondents to employ simplifying heuristics in order to arrive at satisfactory outcomes. In the dual-process models the two branches are presumed to interact or rather to work in parallel to an extent depending on the specific circumstances of the cognitive task to be fulfilled. The analysis of the extent to which these two fundamentally different reasoning processes are employed during the perception and evaluation of a CVM scenario by a respondent, i. e. the degree of boundedly rational information processing, requires to look more specifically at selected dual-process models found in the literature. From these models the empirical survey instrument for the analysis of boundedly rational behavior in CVM surveys will be developed in chapter 4. 3.3.4.2 Specific model approaches of dual-processes in the context of environmental valuation From the multitude of conceptual models of dual information processing found in the literature, three selected models shall be described here in more detail. In conjunction, these three models allow to address a great variety of aspects of response behavior in CVM interviews and thus form a suitable framework for the analysis of bounded rational information processing in environmental valuation. Specifically, two of the three models have developed well-tested psychometric instruments which allow to classify individuals regarding the 83 rationality concepts described above. These instruments shall be taken as the basis for the development of an empirical instrument to describe and analyze boundedly rational information processing in CVM. Both the elaboration likelihood model (ELM) developed by Petty (1977, cited in Petty and Wegener 1999) as well as the heuristic-systematic model (HSM) by Chaiken (1980) deal explicitly with the question what determines the degree to which individuals employ deliberative, rational reasoning versus more intuitive, heuristic information processing. Specifically, the ELM distinguishes two processes, the "routes" to persuasion referring to changes of attitudes based on the intensity of elaborative processing of information, i. e. the degree of elaboration (see above). On the one hand the "central-route" attitude changes are those that are brought about by "relatively extensive and effortful informationprocessing activity" (cf. Petty and Wegener 1999: 42). Such "central-route" processing is associated with a deep scrutiny and analysis of the issues and information presented in order to uncover their "central merits". The term "elaboration" is used to suggest that people add something of their own to the specific information provided. On the other hand, attitude changes brought about by the "peripheral-route" are based on processes requiring less cognitive effort, such as processes that differ from the "central-route" process quantitatively, i. e. for example examining the same available information less carefully, or even qualitatively by using mental short-cuts like heuristics or schemas etc. Regarding the degree of employing the central versus peripheral routes the critical concept of the ELM is the so-called "elaboration continuum". It signifies the range of degrees of elaboration by an individual faced with a judgment task. The points along the elaboration continuum at which a given individual operates in a given judgment or problem are determined by the strength of motivation and cognitive capability to elaborate on that situation, i. e. to scrutinize and evaluate information, to put new information in the context of existing information and/or to assess the likely outcomes of decisions taken. The ELM supposes that the degree of elaboration is directly related to the cognitive effort expended in a given task. The notion of an "elaboration continuum" implies that people elaborate to varying degrees, i. e. although people want to hold correct attitudes and make correct judgments, the amount and nature of elaboration in which they are willing and able to engage vary both with individual and situational factors. Thus, personal motivation and mental ability are assumed to be the main drivers of cognitive effort, the more motivated and able people are the more likely they are to effortfully scrutinize all information available and relevant for the task at hand. However, "economy of cognition" decides to what extent the individual follows the peripheral and central routes of reasoning. In some situations where it does not "pay" to exert considerable mental effort it is advisable to behave as a "cognitive miser" ( cf. Taylor 1981 ), i. e. as someone 84 who tries his best to avoid cognitive effort. At other times, however, it is more appropriate for them to expend their cognitive resources more generously. Compared to the ELM, the heuristic-systematic model (HSM) operationalizes the least-effort principle more specifically by transforming it into a sufficiency principle. It is assumed that people "attempt to strike a balance between minimizing cognitive effort on the one hand and satisfying their current motivational concerns on the other" (cf. Chen and Chaiken 1999: 74). To this end, the authors distinguish between an individual's actual confidence that he has in relation to a judgmental task and the desired confidence, i. e. that level of confidence that the individual would personally like to have when performing some judgmental task. This desired level of confidence is called sufficiency threshold. The authors claim that individuals will exert cognitive effort up to the point where actual and desired confidence coincide at which point then a decision is taken or an attitude is formed or expressed etc. In case low-effort heuristic processing alone does not achieve the closure of this gap between actual and desired confidence or where such processing is not possible due to the absence of any information that might serve as a cue for the activation of a heuristic, people are likely to adopt systematic processing in order to close this gap. Furthermore, the HSM claims that it is in principle possible to predict whether a person is likely to employ either heuristic or systematic processing alone or to what extent and in which way those modes co-occur and interact given different patterns of cognitive, situational and motivational factors. On the one hand heuristic and systematic processing may be used in an additive way whenever both heuristic-cue information as well as other judgment-relevant information, so-called individuating information that describes a certain context in a more detailed and specific way, point into the same direction, i. e. are not contradictory. Such additivity is likely to occur for example in situations where consumers are asked to evaluate some product and where its brand name serves as a positive heuristic cue which is also in accordance with other individuating information about that product. In such a situation the brand name as a heuristic cue establishes an already quite high level of actual confidence on top of which some further systematic processing based on the individuating information closes the gap to the desired confidence. In cases where the "brand name" heuristic is not applicable, e. g. when the brand name is not given or that particular brand is not known to the person (non-availability of the heuristic) the level of actual confidence is quite low at the beginning so that systematic processing on the basis of the individuating information has to occur to a higher degree in order to attain the sufficiency threshold. On the other hand, heuristic cues like e. g. the brand name can also lead to a biased processing of individuating information. In this case, systematic processing does not only occur to a lower degree than in the example above but 85 individuating information is even seen in a more favorable light. Thus, in those cases when individuating information is ambiguous to some extent or even contradictory and would, therefore, require more complex reasoning about the task at hand, the presence of heuristic cues, e. g. positive ones like the brand name or negative ones like the doubtful quality of the source of information, can lead to systematic processing of the individuating information either in a more favorable or in a more unfavorable light. In both cases the outcome of the evaluation will be biased. Such effects were indeed found in experimental studies ( cf. Chaiken and Maheswaran 1994, Chen et al. 1996). Similar effects occur when people are given information on the opinions of others, e. g. of representatives of their own peer group, on certain task-relevant issues, so that the "consensus" heuristic was shown to have a large biasing effect on systematic processing of individuating information. All aspects of the ELM and HSM mentioned above are relevant in the context of CVM surveys. The level of motivation of a respondent to evaluate an environmental change scenario may depend highly on the specific good to be valued. In case the environmental change has a high personal relevance for the respondent he may be more highly motivated to scrutinize the given information and, thus, engage in the central route of information processing. On the other hand, an environmental change scenario showing a low degree of personal relevance may, therefore, trigger the peripheral route and lead to superficial information processing with a higher susceptibility to heuristic cues present in the scenario or payment scheme. The HSM addresses even more specifically the role of such heuristic cues. It highlights the role a positive heuristic cue, e. g. the participation of a well-known and respected non-governmental organization in the implementation of the environmental project, may play in the way a respondent processes and evaluates further project relevant, i. e. individuating, information. The presence of that organization may create a notion of trust where the respondent evaluates the given information in a more favorable light than he would otherwise do if that organization were not mentioned. Moreover, Chen and Chaiken (1999)'s findings on the consensus heuristic highlight the danger of including information about what other people think of project related issues into the questionnaire since people tend to follow the consensus in case they consider themselves as part of that group. Another important feature of the HSM in relation to CVM response behavior is the "multiple-motive framework" which serves as a classification for people's motivations to engage in heuristic or systematic processing. Three basic types of motivation are distinguished: (1) accuracy motivation which claims that people are motivated to hold accurate attitudes and beliefs, (2) defense motivation which "refers to the desire to hold attitudes and beliefs that are congruent with one's perceived material interests or existing self-definitional attitudes and beliefs" ( cf. Chen and Chaiken 1999: 77), and (3) impression motivation 86 4 Bounded rationality in environmental valuation 4.1 Review and outline of the chapter The preceding chapters dealt with rationality as one of the central topics in economic decision making and put special emphasis on the role of rationality in environmental valuation. As was laid out in detail in chapter 2 a rational decision in the context of an environmental valuation interview using the Contingent Valuation Method requires that a respondent be able to evaluate whether he or she is better off after some proposed project with environmental consequences has been carried out than before. In addition, the response, i. e. the stated WTP or WT A, must be consistent with this personal evaluation of expected change in well-being resulting from the proposed project. It was shown, however, that in the practice of environmental valuation respondents seem to have difficulties conforming to these requirements of rational decision making. Often, the available time during such an interview is rather short so that the respondent may have trouble evaluating a complex environmental change scenario thoroughly enough to take all the personal consequences resulting from the project into account. Due to the novelty of the situation for a respondent in an environmental valuation interview the respondent may not even be certain what his preferences relating to the proposed environmental change are. Moreover, the design of the questionnaire, like e.g. the WTP elicitation question or the specific payment vehicle used, exerts a significant influence on the respondent's reasoning and decision making which results in numerous procedural biases well documented by an abundant literature. In order to put these findings into the general context of decision making in economics chapter 3 explored violations of rationality in a broader perspective. The biases detected in environmental valuation interviews are largely consistent with findings from the field of behavioral economics where the concept of bounded rationality is used as a more realistic perspective on human reasoning. Psychological decision mechanisms like the availability, representativeness and anchoring and adjustment heuristics made famous by Daniel Kahneman and Amos Tversky were shown to be responsible for a wide variety of common reasoning failures. A closer look at central findings of cognitive psychology then revealed that human beings have developed and learned mental strategies to cope with the complexity of reasoning and decision making situations in the real world enabling them to make "reasonable" decisions, however often not based on exact judgment, with their limited cognitive capabilities. Such decisions seem to make use of a two-tiered mechanism of information processing where an analytical system requiring rather large amounts of cognitive resources and a more effortless intuitive system based on experience and learned decision rules, 93 i. e. heuristics, interact in a kind of "economy of cognition". It was also shown in chapter 3 that such psychological models of reasoning, the so-called dualprocess models, may well be related to information processing and decision making in the context of environmental valuation interviews and, thus, have the potential to better explain and analyze procedural biases in CVM response behavior. This chapter will now build on this literature review and the connection that has been established between psychological models of reasoning and response behavior in CVM surveys in order to gain a more realistic perspective of the way respondents process complex information in CVM interviews where both time and the available information are limited in principle. As described above, two aspects are of particular importance in this respect: (I) how respondents deal with preference uncertainty, and (2) whether and to what extent respondents make use of an "economy of cognition" and, consequently, base their decisions in CVM interviews on simplifying heuristics instead of thorough analytical reasoning. In section 4.2 these two aspects will first be considered from a theoretical point of view. Regarding preference uncertainty, section 4.2. l will present and discuss a modification of the traditional neoclassical model of preference orderings. The concept of fuzzy preferences will be used to describe the uncertainty over preferences with respect to environmental goods. It will be shown, however, that the practicability of this approach is rather limited since it is technically not possible to derive proper value functions for environmental goods like e. g. the Hicksian Compensating Variation which would be necessary for a quantitative representation of environmental values. Section 4.2.2 will then address the issue of information processing in CVM interviews from the perspective of bounded rationality and the dual-process models of reasoning described in chapter 3. From those models a specific set of expectations concerning boundedly rational CVM response behavior will be formulated which serves as the basis for the development of empirical instruments for classifying and detecting such behavior. In section 4.3 these instruments will then be used in an empirical CVM study regarding the social benefits of an improvement of tap water quality in northern Thailand. The purpose of this empirical application is to test the usefulness of the developed instruments for the analysis of boundedly rational information processing behavior and for the development of recommendations for an improvement of CVM survey designs. The empirical study underlying this test was conducted as part of a subproject within an international collaborative research project in northern Thailand. Thus, section 4.3.1 will first describe the background and the design of the empirical research project conducted and will present the details of the implementation of the scales of bounded rationality within this project. Section 4.3.2 will present and discuss the empirical results of 94 the project in general and, in greater detail, of the bounded rationality scales employed. Subsequently, the implications of the empirical results of the chosen research approach for the design of contingent valuation studies will be discussed. 4.2 Theoretical considerations 4.2.1 Dealing with preference uncertainty: a fuzzy approach In section 2.2.2 of chapter 2 it was argued that it is plausible to assume that some respondents in CVM surveys are uncertain about their preferences toward environmental goods when having to state their WTP. Due to unfamiliarity with the good and the task to express rather abstract values people commonly hold for the environment in monetary terms it appears more reasonable to consider the existence of an uncertainty range within which respondents are not entirely sure whether they are truly willing to pay a particular monetary amount or not. Below that range respondents are certain that they would pay the proposed amount, above that range they are certain that they would reject to pay it. As was shown in the preceding chapter the methodological approaches to account for such a situation of preference uncertainty are manifold and deal with this quite uncommon situation in ways that appear rather ad hoc, i. e. they are not founded on an underlying coherent theory of preference uncertainty. The purpose of this section is to consider an existing theory of preference uncertainty more thoroughly and to apply it to the context of environmental valuation in order to (possibly) rationalize the approaches described in 2.2.2 on the basis of a theory of preference uncertainty. To this end, a theory of preferences based on fuzzy set theory shall be unearthed from the rather unnoticed and inaccessible niche it has been occupying in the literature, mostly in highly specialized journals, so far. The advantage of fuzzy set theory for a description of preference uncertainty is its inherent concept of vagueness or ambivalence. Unlike in the two-valued logic where a statement is either true or false fuzzy set theory, or fuzzy logic as it is often called, allows intermediate states where a statement is neither fully true nor entirely false, just as one would assume a respondent in CVM to be neither fully sure about whether he would actually pay a proposed amount nor entirely certain that he would definitely not pay it, at least for amounts falling into his range of uncertainty. Therefore, fuzzy set theory and the existing theory of fuzzy preferences provide a suitable starting point for considering preference uncertainty in the context of environmental valuation. 95 4.2.1.1 Fuzzy logic and fuzzy preferences Fuzzy set theory dates back to Lofti Zadeh (1965) who developed the concept of fuzzy sets building on the concept of multi-valued logic introduced by the Polish mathematician Jan Lukasiewicz in the 1920s. Multi-valued logic was successful in solving problems in quantum physics that could not be adequately addressed by the commonly used crisp sets of standard two-valued Boolean logic. In a crisp set A some x e X either is an element of some set A or it is not an element of that set, i. e. there exists certainty as to whether x belongs to A or not. Crisp sets are common in the real world: e. g. from a number of objects, let's say cars, bicycles and boats, it can usually be determined without doubt which ones are classified as land transportation vehicles and which are water transportation vehicles. In the case of a fuzzy set A, however, a given element x e X may not fully belong to the fuzzy set but only to some degree while it may belong to some degree to some other fuzzy set B , i. e. following Ott (2001: 14) a fuzzy set A can be defined as A= {{x,µA(x))I x e X} where µA(x): x~[0,l]. (4-1) The function µA (x) denotes the degree between 0 and 1 to which the element x belongs to the fuzzy set A. µA (x) is often called "characteristic function" or "membership function" ofx to A (cf. Zimmermann 1996). Let's consider as an example the set "high income", a possible category in economics. When this set is to be crisp we need to define a lower threshold income above which income is classified as "high income". It is obvious that such a threshold is purely arbitrary since if the figure 100,000 Euros per year is defined as threshold for high incomes it would be hard to justify why an income of 99,000 Euros should not be classified as "high income", as well. Here, "high income" could instead be defined as a fuzzy set where all incomes at or above 100,000 Euros assume a value of the membership function of 1, i.e. µA (x ~ 100,000) = 1, whereas values between, let's say, 50,000 and 99,999 Euros assume membership values to the fuzzy set A between 0 and 1, i.e. 0 < µA (50,000 $; x $; 99,999) < 1 and incomes below 50,000 Euros assume a membership of 0, i. e. strictly do not belong to the category "high income". Figure 4-1 graphically illustrates such an exemplary fuzzy set "high income". 96 Figure 4-1: The fuzzy set "high income" (adapted from Ott 2001: 15) 50,000 100,000 Income (Euro/year) Obviously, fuzzy sets are often used for linguistic categories that are vague by definition, i. e. categories without a clear natural boundary of what belongs to them and what does not. Another example is the classification of thermal states like "cool", "warm" or "hot". There is no clear boundary between these states since they represent subjective feelings so that a specific temperature might still belong to a certain degree to the state "cool" and to some degree to "warm" already. In these cases it has proven very useful to be able to specify the degree to which some element is a member of that linguistic category. However, fuzzy sets and fuzzy logic have also become favorite concepts in the field of technology whenever complex technical processes are controlled by automated computer programs (cf. Klir and Yuan 1995 for examples). The mathematics of fuzzy sets, however, has become quite complicated and is a field of fast development where many fundamental theorems have not yet been proven. This section will, therefore, make use of only simple fuzzy mathematics in order to illustrate the basic features of fuzzy preferences. An important concept of fuzzy logic necessary for a simple representation of fuzzy preferences are fuzzy relations ( cf. Ovchinnikov 1981, Ovchinnikov and Roubens 1992). In the crisp, i.e. non-fuzzy case a relation between two elements x, y e X is clearly determined, i. e. either x is greater than y or it is not, there is no ambivalence. In the case of fuzzy relations this is different: here, x may be greater than y only to some degree, let's say a degree of certainty. To some degree of certainty it may also be that y is greater than x, it is thus ambivalent. Formally, this can be expressed by a fuzzy relation r which is a mapping from the two-dimensional space X2 to the closed interval between 0 and 1, i.e. r: X2 ~ [ 0, 1 ]. In the case of fuzzy preferences, for example, such a vague comparison may occur in case the evaluation of goods is 97 ambivalent, i. e. in case an individual is uncertain regarding his preference of x over y. Fuzzy preferences can thus be defined as fuzzy preference relations ( cf. Salles 1998: 322ff). Let x, y E X be two commodity bundles from the non-negative commodity space X, then r (x, y) E [0, 1] denotes the degree to which an individual considers x to be "at least as good" as y, i.e. x ;i:; y, whereas r (y, x) E [0, 1] denotes the degree to which y is considered "at least as good" as x, i.e. y ;i:; x. Obviously, the crisp preference relation ;i:; is the limit of the fuzzy preference relation r where the relation would only take values of O or 1 ( cf. De Wilde 2003). While it appears odd at first sight to assume that the weak preference relation ;i:; between two commodity bundles can only be determined to a degree between O and 1, the common interpretation of such a degree is how certain an individual is that bundle x will generate at least as much utility as bundle y, thus the fuzzy preference relation r (x, y) E [0, 1] represents a measure of preference uncertainty of the bundles x and y. This uncertainty of assessing whether x is at least as good as y may stem from unfamiliarity with the commodity bundles, i. e. some commodities have not been consumed before and the individual is still uncertain about the utility they generate, or it may stem from difficulties in comparing the utilities some of the commodities in bundle x generate with the utility other commodities in bundle y generate, thus a difficulty with the trade-off of some commodities against others. A fuzzy relation that satisfies the properties of reflexivity, strong completeness and transitivity as defined below can be considered a fuzzy binary preference relation ( cf. Barret et al. 1990: 198, Ott 2001: 97): Reflexivity: r ( x, x ) = 1 't/ x E X Strong completeness: r(x,y) + r(y,x) ~ 1 't/ x,yeX Transitivity: r( x, z) ~ min [ r( x, y ), r( y, z)] 't/ x, y, z e X The definition of reflexivity is straightforward and implies that there is no uncertainty that the same bundles are actually the same bundles. The property of strong completeness is already a quite strong one. It can be interpreted as a plausibility assumption of the individual's reasoning about the relation between the two bundles: the degree of doubt that x ;i:; y must be explainable at least by the degree of confidence that, in tum, y could be at least as good as x (i. e. y ;i:; x). The transitivity definition used here is the most commonly used definition of transitivity in the theory of fuzzy preferences and follows Barrett et al. ( 1990: 198). However, there are a number of alternative definitions that differ to some degree from the definition above ( cf. Salles 1998, Dasgupta and Deb 1996). The meaning of transitivity is that the degree of preference of x over z 98 cannot be smaller than the weakest degree of preference of x over y or of y over z. If this condition were violated the individual would be "too uncertain" regarding his preference of x over z, i. e. the preference uncertainty between x and z could not be explained by the uncertainty between x and y and y and z alone and would thus be "irrational". 4.2.1.2 Is it possible to assess fuzzy preferences regarding the environment? The theoretical concept to express uncertainty over preferences between commodity bundles in terms of fuzzy binary preference relations as defined above seems quite attractive at first sight. As opposed to other approaches of preference uncertainty (cf. Li and Mattsson 1995, Wang 1997) that define uncertainty in an ad-hoc fashion fuzzy relations allow to express uncertainty in a fuzzy preference ordering that fulfills the usual properties of ( quasi-)orders reflexivity, completeness and transitivity in their fuzzy definitions. However, and this is bad news for environmental valuation, no suitable concept of fuzzy utility functions has been derived so far from fuzzy preference orderings as defined above. The Hicksian welfare measures presented in chapter 2 forming the basis for expressing welfare changes resulting from changes in environmental quality are, however, not based on the (direct) utility function but on the expenditure function. But, again, it is also not possible to derive a fuzzy version of the expenditure function since this would require a suitable definition of a fuzzy utility level or an upper contour set for the expenditure minimization ( cf. Ahlheim and Rose 1989: 264). For the expenditure minimization problem the restriction, i. e. the upper contour set, must be a convex set, a requirement which is as such not fulfilled in the fuzzy case due to the uncertainty over preferences. Thus, a derivation of welfare measures in analogy to those usually employed when preferences are crisp, i. e. certain, remains elusive. It appears, therefore, that a formal treatment of preference uncertainty in the context of environmental valuation is not possible and that the various ad-hoc approaches described in chapter 2 to take such uncertainty of respondents into account remain the only practicable way. However, due to the lack of a clear reference point how such uncertainty should be treated none of the proposed approaches can be recommended as being a good representation of preference uncertainty. Moreover, the direct assessment of how certain respondents are that they would actually pay a proposed or stated amount of money must be seen very critical. It must be suspected that respondents do not want to reveal their uncertainty of whether to pay or not, especially not in the presence of an interviewer and when the good under consideration is a public good, i. e. a "good cause". In such a situation, respondents are likely to understate their uncertainty, especially when assessed after the WTP question. 99 An ideal way of assessing preference uncertainty, therefore, would be to avoid any personal statements regarding the level of uncertainty but, instead, to repeatedly assess the same respondent's WTP for the proposed project. In case the response varies over time one could use this information to compute a measure of uncertainty. However, such an approach is certainly not practicable since respondents would be annoyed if their WTP for the same project were assessed every few weeks or so. Instead, it appears more sensible to concentrate on indirect approaches for detecting uncertainty, i. e. some proxy variable that is strongly correlated with uncertainty but at the same time not as problematic to assess directly as the personal uncertainty statement used in many CVM surveys. As mentioned in section 2.2.2 the existence of preference uncertainty might be an important factor for explaining the occurrence of common procedural biases in CVM like the starting point bias, the social desirability effect and the embedding effect. Uncertain respondents being forced to give a precise WTP statement in the DC or the PC question format, for instance, are likely to make use of reference points, frames or circumstances of the interview in order to narrow down the sensible figures from their range of uncertainty. Therefore, the measurement of a respondent's uncertainty level might be useful in two ways: (1) to explain the occurrence of procedural biases, and (2) to serve as a test for the reliability of WTP statements in CVM surveys. In the following section such a proxy variable for the assessment of respondents' levels of uncertainty will be developed and included into an integrated empirical instrument to detect and classify boundedly rational information processing and decision making in CVM. 4.2.2 Considering bounded rationality in environmental valuation Building on the research on bounded rationality in the field of cognitive psychology the central objective of this study is to analyze the role different kinds of information processing play in environmental valuation surveys. In chapter 3 it was discussed that responses in a CVM interview could depend heavily on the way information is received, stored and processed in the human brain and that the specific situation of such interviews puts more or less serious pressure on respondents' limited cognitive capacities. It can be argued that these limitations play an important role for the occurrence of the procedural biases described in detail in chapter 2. The research approach taken here, therefore, aims at applying the theoretical framework of bounded rationality as described by cognitive psychological models of reasoning and information processing to the context of CVM surveys in order to scrutinize the rationality assumption of respondents in environmental valuation interviews. It is expected that the adoption of this perspective leads to new insights regarding so far unexplained 100 non-rational response behavior, i. e. the observed procedural biases, in CVM surveys. Finally, these insights shall lead to recommendations for an improvement of the design ofCVM surveys. First, a normative view of how respondents should behave and perform in such interviews so that valid and reliable results are achieved will be laid out. This normative view will then serve as a reference for the assessment of the influence of boundedly rational behavior and of the impact on the validity and reliability of CVM results. Subsequently, the specific research questions following from the analysis of expected problems resulting from bounded rationality in CVM surveys will be developed. These research questions, then, will lead to the construction of an empirical survey instrument that is suited for detecting boundedly rational behavior and analyze specific kinds of information processing in empirical CVM studies. This survey instrument will be derived from the rational experiential inventory (REI) which is based on cognitiveexperiential self theory (CEST) presented and discussed in detail in the preceding chapter. In order to fit the needs and specifics of contingent valuation studies, the existing REI will be adapted so that a new empirical tool for the assessment of the degree of individual differences in the type of information processing and decision making in environmental valuation studies based on CEST will be available. 4.2.2.1 What constitutes rationality in environmental valuation? The normative view Chapter 3 presented an ambivalent view of bounded rationality: on the one hand the cognitive limitations and the ensuing simplifying heuristics and mental short cuts were seen as sources of biases and systematic errors in human judgment and decision making. Many empirical experiments where people's behavior in decision tasks was tested against objective criteria of decision quality exhibited those effects consistently and a number of experimental setups that facilitate the occurrence of such biased behavior were identified. This is the main view of the heuristics and biases research program around Daniel Kahneman and Amos Tversky. On the other hand, as argued in line with the descriptive rationality concepts presented in section 3 .2.2, the employment of simplified decision rules represents an evolutionary adaptation to the complexity of real-world decision environments. In order to be able to deal with the multitude of everyday decisions, individuals make use of mechanisms that have turned out to be successful in the past. As a result, it is sometimes argued that such simplifying heu_ristics are not a source of bias in comparison to normative decision strategies but instead necessary means to achieve, on average, the best outcomes possible in such real-world environments (cf. Payne et al. 1993, Todd and Gigerenzer 2003 for details regarding ecological rationality in the real world). Thus, 101 "economy of cognition" is not necessarily a source of bias, as argued by Kahneman and Tversky, but an ecologically rational behavior adapted to the structure of decision environments outside of the laboratory. As a result, there are two conflicting views w. r. t. the role of bounded rationality in human judgment and decision making and both rest on a firm experimental basis. The question that invariably arises is which of the perspectives on bounded rationality applies to the context of environmental valuation studies employing empirical assessment methods like for example the CVM. Under the first perspective any boundedly rational behavior would introduce systematic errors and biases into the empirical data which would result in invalid and unreliable benefit estimates. Under the second perspective, any use of boundedly rational decision making strategies would have to be considered as ecologically rational, i. e. the resulting estimates would have to be regarded as valid and reliable since they are a product of respondents' "economy of cognition" and, thus, well adapted to the constraints of the particular decision environment. From a normative perspective, however, the concept of ecological rationality based on the "economy of cognition" should clearly be discarded as a reference for the rationality of decisions in environmental valuation interviews. Since the aim of environmental valuation is the elicitation of people's true preferences w. r. t. an environmental, i. e. a public, good any type of information processing circumventing thorough and differentiated reasoning about the elements of a CVM scenario cannot be considered to be an appropriate way for individuals to evaluate and express their preferences. Thus, it is clearly not in the interest of environmental valuation surveys to allow respondents to strategically employ mental shortcuts and heuristic reasoning in order to deal with the complexity of a CVM scenario since such behavior would prevent them from expressing their true preferences for the proposed environmental good. Instead, a CVM survey should be crafted in a way that respondents are able to fully reflect on the proposed scenario and express their preferences on the basis of thorough reasoning. 4.2.2.2 Why is bounded rationality a problem in environmental valuation? Having established the reference of fully rational reasoning as the rationality concept of choice in environmental valuation it must be discussed in what ways respondents in CVM surveys can be expected to deviate from such information processing. In chapter 2 it was shown that respondents in CVM interviews are susceptible to a number of procedural biases of which the most prominent are the embedding effect, the warm glow of giving, the hypothetical bias, framing effects and the starting point and range biases. The occurrence of these biases reflects the fact that respondents often do not behave fully rational and give rise to the suspicion that important scenario information is processed in some limited 102 respondents both regarding general cogmt1ve dispositions and task-specific types of information processing intuitive respondents are expected to show a higher degree of susceptibility to biases. Regarding the starting point bias in the dichotomous choice question format analytical respondents should have developed a clearer picture about the valuation scenario and, thus, their response should not be influenced (as much) by the varying starting bids as the response of intuitive individuals (see also section 4.2.2.2). The same should hold for the range bias in the payment card format. As a general hypothesis, therefore, it shall be expected that analytical-rational respondents are less prone to procedural biases in CVM surveys than intuitive-heuristic respondents. This hypothesis will also be tested in the empirical study below. The fourth research question addresses the consequences of the investigation of boundedly rational CVM response behavior for CVM surveys. From the results of the empirical study below some generalizations shall be deducted that may tum out to be useful as a guideline for the improvement of future CVM survey designs. It is not the aim of this research to develop a mechanism to correct "erroneous" WTP statements, such an approach would require to know either "how wrong" the WTP statements of limited information processors are or, alternatively, to clearly identify untrustworthy responses and exclude them from the sample. Both approaches appear neither realistic nor desirable. In contrast, it shall be tried to improve the design of CVM surveys so that respondents with a tendency to employ strategies of limited information processing increase their use of analytical reasoning in the context of environmental valuation surveys. 4.3 Development of empirical instruments for analyzing bounded rationality in CVM On the basis of the above discussion an empirical instrument to be included as a standardized part of an empirical CVM survey shall be developed in this section in order to be able to investigate the research questions stated above. In a first step, these instruments shall be developed in a general form in order to be applicable and adaptable to any empirical environmental valuation study based on stated preferences. In a second step, the developed instruments will be applied in an empirical CVM study in section 4.4 and the research questions stated in 4.2.2.3 will be investigated. In the following section, a measure of individual differences in information processing and decision making which is derived from cognitive-experiential self-theory will be described. This measure will form the basis for the specific development of the empirical instruments. 109 4.3.1 A measure for individual differences in decision making: the rational experiential inventory (REI) As the basis for the detection of individual differences in information processing and decision making a self-report measure developed by Epstein et al. ( 1996) derived from their cognitive-experiential self-theory (CEST, see 3.3.4.2) will be used. In general, CEST proposes the existence of two fundamental and independent modes of reasoning, one based on intuition and personal experience and the other based on systematic and analytical cognitive processes. The interaction of these thinking styles produces the observable behavior in specific decision tasks, where it is assumed that while both styles are active, one usually dominates over the other to varying degrees. In addition, individuals are expected to differ in the degree to which these thinking styles are in general being employed, i. e. in their personal cognitive disposition. The rational experiential inventory (REI) was developed as a self-report measure to assess the degree to which individuals are confident with employing either thinking style in general. Further, it was designed by the authors to provide evidence for the assumption that the two thinking styles or information processing modes are actually independent from each other and interactive as postulated in CEST instead of being simply inversely related (like the NFC). In order to test the assumption of CEST that the two processing modes operate independently, the REI consists of two distinct sets of questions assumed to characterize either mode. The first set of questions refers to the degree to which an individual perceives to employ the analytic-rational thinking style. The elements of this set are taken from the Need-for-Cognition (NFC) scale developed by Cacioppo and Petty (1982) as a measure for the likelihood of elaboration in their ELM framework (see 3.3.4.2). The second set of questions is used for measuring respondents' tendency to employ the intuitiveheuristic thinking style. These questions were developed by Epstein et al. ( 1996) and termed Faith-in-Intuition (Fl). In conjunction, the NFC and the FI question sets form the rational experiential inventory (REI) as a total of 31 questions (items) where 19 items are selected from the original NFC scale and 12 items make up the FI scale. These questions are presented to test persons in a selfreport test who are asked to rate each given statement on a five-point Likert scale ranging from 1 = completely false to 5 = completely true. The items of the REI are listed in table 4-1 where (R) indicates that the particular item is formulated in reverse sense to the level of need for cognition, i. e. a high rating on that item would mean a low association with need for cognition. 110 Table 4-1: The Rational Experiential Inventory (adapted from Epstein et al. (1996: 394) Scale and item Need for Cognition (NFC) -analytical scale I would rather do something that requires little thought than something that is sure to challenge my thinking abilities. (R) I don't like to have the responsibility of handling a situation that requires a lot of thinking. (R) I would prefer complex to simple problems. I try to anticipate and avoid situations where there is a likely chance I will have to think in depth about something. (R) I find little satisfaction in deliberating hard and for long hours. (R) Thinking is not my idea of fun. (R) The notion of thinking abstractly is not appealing to me. (R) I prefer my life to be filled with puzzles that I must solve. Simply knowing the answer rather than understanding the reasons for the answer to a problem is fine with me. (R) I don't reason well under pressure. (R) The idea of relying on thought to make my way to the top does not appeal to me. (R) I prefer to talk about international problems rather than to gossip or talk about celebrities. Learning new ways to think doesn't excite me very much. (R) I would prefer a task that is intellectual, difficult, and important to one that is somewhat important but does not require much thought. I generally prefer to accept things as they are rather than to question them. (R) It is enough for me that something gets the job done, I don't care how or why it works. (R) I tend to set goals that can be accomplished only by expending considerable mental effort. I have difficulty thinking in new and unfamiliar situations. (R) I feel relief rather than satisfaction after completing a task that required a lot of mental effort. (R) 2 .74 -.08 .71 -.05 -.66 -.02 .65 -.06 .63 -.04 .59 .11 .58 -.02 -.57 .01 .57 .16 .55 -.10 .51 .12 -.49 -.13 .49 -.18 -.49 .04 .46 .00 .44 .20 -.42 -.18 .36 -.32 .36 .00 111 Table 4-1 continued Scale and item Faith in Intuition (FI) -intuitive scale My initial impressions of people are almost always right. I trust my initial feelings about people. When it comes to trusting people, I can usually rely on my gut feelings. I believe in trusting my hunches. I can usually feel when a person is right or wrong even if I can't explain how I know. I am a very intuitive person. I can typically sense right away when a person is lying. I am quick to form impressions about people. I believe I can judge character pretty well from a person's appearance. I often have clear visual images of things. I have a very good sense ofrhythm. I am good at visualizing things. 2 .02 .76 .21 .76 .18 .72 .18 .64 .10 .56 -.16 .53 -.12 .46 .20 .42 .22 .40 -.09 .35 -.07 .34 -.19 .34 In empirical tests the reliabilities of the NFC and the FI scales as measured by Cronbach's alpha4 (a) have been found to be very good (a= .87 for NFC and a = . 77 for FI).Epstein et al. (I 996) present an empirical study of the REI scale on a set of 184 test persons in order to test its validity. For a test of the independence of the two postulated thinking styles, the responses of this test sample are subjected to a factor analysis. This statistical method is widely used to detect systematic patterns in datasets with many variables by exploiting the correlation structure between those variables. It is often employed to reduce the dimension of a dataset, i. e. it determines so-called latent factors which represent underlying, but unobservable variables. Factors are formed by a number of observed variables that are substantially correlated with each other so that it can be assumed that they in conjunction have a common meaning, the interpretation of the factor. Each variable is related to each factor to a certain degree, the "factor loading", which can be interpreted as how strongly the meaning of the particular variable coincides with the "real" meaning of the factor to be interpreted. The meaning of the factor can thus only be inferred to be the common denominator of meanings of all the variables, i. e. 4 Cronbach's alpha is a statistical measure of reliability of factor scales and is based on the correlations between the various items of the factor. Values of .70 and higher are generally considered as sufficiently reliable, however, no convention of a threshold value for reliability exists (Janssen and Laatz 2003: 525). 112 items, that make up the particular factor. Table 4-1 shows that two factors could be generated or extracted from the dataset of the test sample. The numbers represent the factor loadings of the respective item where the bold figures indicate to which factor the particular item belongs, the one on which it loads highest. The factor loadings can assume values between -1 and 1 which can be interpreted as correlation coefficients of the items with the respective factor. Thus, in table 4-1 the items are ordered according to their strength of relation with the respective factor and not according to their sequence in the self-report questionnaire. Finally, it is possible to compute individual factor scores, i. e. a measure to what extent each individual is characterized by each of the extracted factors. As expected the factor analysis groups the question items according to the NFC set on the one hand and to the FI set on the other. Respondents with a high rating on one NFC item have shown, on average, a tendency to rate the other NFC items also high ( or low in case the item is formulated in reverse as indicated by (R)). The same applies for the FI items so that the correlation structure of the responses yields a clear distinction into two separate factors representing NFC and Fl, respectively. A useful property of factor analysis is that all factors that are extracted from the underlying dataset are statistically independent from each other. As a result, the score on the NFC factor is not systematically related to the score on the FI factor, i. e. a high NFC score does not imply a low FI score for any given individual. Therefore, Epstein et al. ( 1996) conjecture that there exist indeed two fundamental reasoning processes that, in general, operate independently from each other. At least it can be said that NFC and FI measure two different and independent processing modes. The very low and insignificant correlation between the NFC and the FI of r = - 0.07 underscores this independence. This implies that people should not be considered to be either intuitive-experiential or cognitive-rational thinkers as would have been the case if NFC and FI had been found to be inversely related. Rather, people must be conceived as exhibiting both a certain degree of need for cognition as measured by the NFC score and of faith in intuition as measured by the FI score. These scores can be both high, both low or any possible combination of the two scales (see figure 4-2). However, what does this independence really mean, how can it be interpreted? Can people be both analytical-rational and intuitive-experiential at the same time or, on the other end, not at all? From the formulations of the questions of the NFC and the FI scale in table 4-1 it becomes obvious that the REI does not intend to measure the actual employment of either thinking style objectively, i. e. to what extent individuals actually employ analytical or heuristic information processing. The object of measurement, rather, is the perception and the attitudes of individuals w. r. t. their own ease and success of using either mode in real life. The scores on NFC and FI mirror the experiences 113 that respondents have made in their lives with either mode. Thus, some people have made good experiences with analytical thinking, they enjoy problem solving and have, most probably, even solved problems successfully in this mode. At the same time, they have confidence in their intuitions and hunches when it comes to making judgments and taking decisions. Figure 4-2: Possible combinations of NFC versus FI scores NFC FI Individual A Individual B Individual C • NFC • Fl Individual D Such people like individual A in figure 4-2 would, thus, score high on both scales of general cognitive disposition. However, when actually taking decisions in a specific task context they would apply the tradeoff of information processing modes as indicated by the concept of economy of cognition laid out by the dual-process models in chapter 3. Here, the actual degree of employment of one mode versus the other depends critically on the structure of and the information provided in the specific task. The presence of heuristic cues would activate simplifying rules and analytical processing would be used to close the confidence gap (see chapter 3). However, the employment of cognitive resources would differ substantially from other kinds of people who score high on NFC and low on FI (individual B) or vice versa (individual C), or even score low on both scales (individual D). Those people have different levels of confidence in their information processing modes and perceive either one of the two modes as less reliable for decision making or they may even have little confidence in their cognitive abilities, analytical or intuitive, altogether due to continuous lack of success with their decisions. A reasonable interpretation of the NFC and FI scores would be, therefore, that they measure the cost of information processing in terms of cognitive resources employed in either processing mode where the higher the score on the scale the lower the cost associated with the respective mode. For example, when an individual scores high on FI but low on NFC like individual C in figure 4-2 it indicates that the cost of analytical information processing is perceived as 114 relatively high, i. e. relative to his own intuitive-experiential processing and relatively higher than someone else who scores higher on NFC and, therefore, has more ease with and confidence in such processing. In a specific task individual C would generally tend to rely to a higher extent on heuristic processing if made possible by the presence of heuristic cues where such heuristic processing would also generate a higher level of confidence than would be the case for other people scoring higher on NFC. High NFC indicates the ability to question the outcomes of heuristic processing and probably correct them in the light of other individuating information (see 3.3.4.2). The "relative cost" of such analytical processing as perceived by the individual would then determine the degree to which it is employed in specific tasks. When comparing the cognitive dispositions of individuals A and D for which analytical processing has the same cost relative to heuristic processing the difference of processing in specific tasks would result in different levels of confidence in their decisions. Individual A must be expected to be quite confident of his decision, i. e. quite sure that his decision was correct, since he feels that he can rely on his intuitions and likes to employ more effortful cognition to scrutinize his hunches and to carefully consider the available information. Individual D, on the contrary, the classical cognitive miser, has little trust in either processing mode and would, therefore, be expected to have little confidence that his decision will actually be correct. Thus, staying within the terminology of the HSM it is expected that individuals A and D differ in their desired levels of confidence in decision making. The REI is, therefore, considered to be a suitable starting point to develop measurement instruments for the assessment of individual differences in cognitive dispositions in CVM studies. In the following section, the REI as specified above will be adapted and extended in order to fit the research questions stated above. 4.3.2 Adaptation of the REI to the context of the CVM The main objective of a measurement instrument of bounded rationality is the analysis of individual differences in heuristic information processing in CVM surveys. Considering this objective, it is necessary to analyze respondents' information processing on two levels: first, in analogy to the REI a method to measure respondents' general dispositions to engage in intuitive-experiential and analytical-rational information processing needs to be available. Such a task independent scale provides an indication of respondents' thinking styles regardless of the task at hand. Second, an instrument for the measurement of heuristic versus systematic information processing specific to the actual task that respondents have to perform is needed, in this case the particular environmental 115 valuation study using the contingent valuation methodology. This task dependent scale of information processing creates the basis for an identification of the specific activation of heuristic responses due to the heuristic cue information provided in the specific CVM design as laid out in section 4.2.2.2. Thus, in conjunction the two individual scales of information processing generate a pattern of individual information processing and decision behavior that takes both the general dispositions to employ either thinking styles and the specific situation of a particular CVM task environment with its heuristic cues into account. As laid out in section 4.2.2.3 it is not unreasonable to expect that the two individual scales of information processing are correlated to a certain extent due to the fact that respondents with a high propensity for intuitive-experiential processing are likely to employ such a thinking style in the specific CVM interview as well. Thus, it could be argued that one single scale on respondents' information processing types would suffice for detecting boundedly rational behavior in CVM studies. However, it was argued by all of the dual-process models of reasoning and the models of boundedly rational decision making described extensively in chapter 3 that "economy of cognition" implies that individuals adapt their information processing to the specific decision environment. In environments providing a high number of non-contradictory heuristic cues such intuitive-experiential processing would be facilitated so that people would be expected to exhibit a higher degree of employment of heuristics independently of their general types. On the contrary, if only few or contradictory heuristic cues are given, actual confidence will be low and decision makers will have to make up for this by employing more cognitive resources for systematic, analytical-rational information processing and decision making. Hence, although they may be correlated to some degree, the two separate indicators for individual thinking styles and information processing, one general and one specific to the task at hand, are necessary for the investigation of bounded rationality in CVM interviews. In an ideal CVM design where only a minimum number of heuristic cues is present so that procedural biases are avoided the task dependent scale is expected to indicate very low levels of heuristic processing while the task independent scale of general individual thinking styles still exhibits the usual distinction within the general population. The task independent scale of information processing is adapted from the REI to fit the context of the interview situation of an environmental valuation study better than the original version. First of all, the original REI contains too many items, i. e. the application of the full REI scale would be unreasonable in a typical CVM interview since it would take too much time in relation to the remaining questions and respondents would be reluctant to answer due to the obvious lack of connection between the issue of environmental valuation and 116 thinking styles. Therefore, the first task was to select from the REI a small number of representative items that could then be further adapted. Second, environmental valuation interviews are typically characterized by time pressure since such an interview almost always represents an unwanted interruption of other tasks the respondent is momentarily engaged in. Therefore, it is desirable to introduce the issue of information processing and decision making under time pressure into the task independent measure. This aspect is included in the original REI only to a limited extent. Table 4-2 presents a suitable question for the elicitation of such a task independent scale. In this question, respondents are told in a short introductory passage that the researcher is interested in the individual decision making process. Subsequently, the respondent is asked to what extent some statements regarding his personal attitude are true, i. e. the respondent is expected to give an individual rating of how much these statements apply to him. Here, a fivepoint Likert scale where e.g. "l" means "not true at all" and "5" means "fully true". Depending on the general intellectual background of the sample population it is also conceivable to use smaller or larger scales. In question 1, items A, B, D and E represent reformulations and summaries of question items from the NFC scale of the original REI (see above) where it was focused on those question items that had shown a high factor loading in table 4-1. It is expected that four items eliciting the same underlying thinking style in different alternative formulations should be sufficient for the purpose of this concise instrument. Items were reformulated for better understandability in many socioeconomic and educational contexts. However, it must be expected that E might not be applicable in all societies, as will be seen later in the empirical study performed in Thailand. Item C refers to an individual's role and behavior in a social context with the intention to elicit a respondent's tendency to be a leader or a follower and, connected to this, the ease of being persuaded in a social context. It is closely related to the original REI item "I generally prefer to accept things as they are rather than to question them" but it was intended to focus on the aspect of behavior in a group. Items F and I refer to the issue of information processing and decision making under time pressure and are related to the original REI item "I don't reason well under pressure". Items G and H are directly taken from the FI scale of the original REI since they were considered to be suitable and concise formulations. Also here, the items with the highest factor loadings were concentrated on. Item J is based on the FI-item "I can usually feel when a person is right or wrong even if I can't explain how I know" used in an interpersonal context. However, for the purpose of this study it was reformulated to fit intuition in a more general context, i.e. independent of judgments w. r. t. people. Altogether, this compilation of 10 items is expected to be a suitable 117 basis for computing a measurement scale of general task independent information processing types to be included in any CVM survey questionnaire. Table 4-2: Task independent scale -the question items Question I: I would like to know how you reached your decision. How true are the following statements regarding your personal attitude? A Thinking hard and for a long time about something bores me. B I enjoy doing something that challenges my thinking abilities like for example playing chess (or some other typical game that requires hard thinking). C In a group of friends I generally trust the arguments of others without always questioning where they come from. D A complex problem is a challenge to me rather than a nuisance. E Doing quizzes and cross-word puzzles are a pleasant form of entertainment for me. F Time is money, so I take decisions quickly. G I believe in trusting my hunches. H My initial impressions of people are almost always right. I I hate to make important decisions under time pressure. J Often, when I take decisions, I don't know why but I feel that I'm right. The second, i. e. task dependent measurement scale of information processing and decision making, is not based on any pre-existing scale. It was specifically developed for the task of measuring the level of response behavior based on heuristic cues contained in a CVM design and is oriented at the expected limited information processing strategies described in section 4.2.2.2. In an introductory sentence people are told to reconsider the way they had taken their decision whether or not (or alternatively how much) to contribute to the proposed environmental project. They are then asked to state whether the items given are true or false. The question items developed for the task dependent scale are listed in table 4-3. 118 aims in relation to the applicability of the CVM in the socio-economic and cultural context of Thailand and in relation to the possibility to develop a methodology to conduct valid and reliable CVM mail surveys. These methodological issues are treated in detail in Ahlheim et al. (2007); most of them shall not be presented and discussed here since they are not directly related to the specific topic of this study. Nevertheless, two of these methodological issues are of importance for this research. They shall be briefly touched on here since they form part of the empirical design of the CVM study described in detail below. The first of these methodological issues is the testing of the performance of two alternative WTP elicitation question formats in the Thai context, i. e. the dichotomous choice (DC) question format and the payment card (PC) format (for a detailed discussion of such question formats see chapter 2). The second methodological issue arises from the well-known social desirability effect and the results of a previous comparison between a CVM study conducted with personal interviews and as a mail survey where the mail survey yielded much lower WTP results (detailed results will be shown below). In search for an explanation for this result it was hypothesized that the observed difference is due to the social desirability effect in that respondents give an answer that they consider socially desirable, i. e. that the interviewer wants to hear. This phenomenon should disappear if respondents are given the opportunity to state their WTP secretly on a separate sheet of paper so that their response would not be known to the interviewer. This latter assumption will also be tested in the empirical study conducted here. In the following the empirical design of the CVM study will be specified in detail. 4.4.2.2 The empirical design The questionnaires employed in this CVM study consist of five parts (the complete questionnaire is provided in the appendix). The first part contains warming-up questions in order to reduce tensions that the respondent might feel due to the sudden interview situation and in order to obtain specific information on household water use. A number of questions are asked w. r. t. the purposes the MRWW water is used (washing, bathing, gardening, cooking, drinking etc.), how long the household has been connected to the MRWW system, whether particular problems like low pressure and interruptions of water service occur and how frequently they are experienced. Moreover, information is obtained on the household's primary source of drinking water and why that specific source was chosen. Subsequently respondents are questioned on their opinions concerning the water quality and the service of MR WW and whether they worry about catching specific water-borne diseases if they were to drink the MR WW water. 125 Box 4-1: Scenario description of the tap water improvement program Chiang Mai University, the University of Hohenheim and the Mae Rim Water Works MRWW are currently surveying water users' interests in the program "Drinkable Tap Water-Clean Stream". What is the idea of the program? The idea is that all MRWW customers should enjoy an uninterrupted supply of tap water which is also drinkable. How can this idea be achieved, what needs to be done? "Drinkable Tap Water-Clean Stream" consists of two main programs which are the improvement of the MRWW distribution system and an improvement of upstream water quality as the source of the MRWW water. Why are these improvements necessary? An improvement of the MRWW distribution system is necessary because of frequent pollution with biological pollutants in the area due to broken pipes in the distribution system. Biological pollutants might cause diarrhea or other diseases. The broken pipes are also responsible for frequent interruptions of water service which occur in some parts of Mae Rim. An improvement of upstream water quality is necessary to ensure that MRWW receives good water for treatment and distribution to the households. There are two main problems regarding the upstream water quality: the first is the red color of the water which occurs often in the rainy season and the second is the contamination with pesticides which might lead to severe health damages like for example cancer. The red color of the water is caused by soil erosion in the uplands of the Mae Sa valley. Pesticides in the water are an immediate consequence of their high use in the uplands of the Mae Sa valley. As you can see from this map, your tap water originates exclusively from the rivers of the Mae Sa valley. How is the program implemented? The program "Drinkable Tap Water-Clean Stream" should be implemented in the following way: First, the pipe system should be mended and maintained so that biological pollution and interruption of water supply would stop. Second, an effective soil conservation program should be implemented so that soil erosion would be stopped in the uplands. Third, pesticide use in the uplands should be reduced for example by employing a more adapted and targeted pest control system. Who will carry out the proposed measures? MRWW will carry out the improvements of the water distribution system. Chiang Mai University will carry out the measures that lead to an improvement of upstream water quality. This will be done in cooperation with the upstream communities and farmers. 126 Box 4 continued: Do only MRWW water users benefit from the program? If these proposed measures were carried out benefits for the whole population of Mae Rim would result. For example, this program would also reduce the contamination of fruits and vegetables with pesticides. Also, the accumulation of pesticides in the surrounding ecosystems would be stopped so that future harm to plant and animal life will be prevented and the health of future generations will not be threatened by these pesticides. Therefore, from the proposed measures the whole population of Mae Rim and future generations in this area would benefit. Who will guarantee that the program really works out? MRWW will test the tap water quality regularly at the households and will post the test results immediately in each affected community of Mae Rim. There will be a responsible person at MRWW that you can contact for any questions and problems you might have regarding the tap water supply. The second part of the questionnaire contains the scenario description. Along with this verbal description respondents are shown a set of photographs illustrating the mentioned issues in order to provide a better visualization and perception of the scenario information. The exact scenario description as presented to the respondents by the interviewer is given in box 4l. In order to be able to perceive the verbally described scenario elements respondents are subsequently asked to rate the eight scenario elements according to how important they are to them personally on a five-point Likert scale. For further reference, these eight scenario elements are: (I) no interruptions of water service, (2) no biological pollutants in the tap water, (3) no pesticides in the tap water, (4) no red color of the water, (5) less soil degradation in the uplands, (6) no accumulation of pesticides in the ecosystems, (7) less pesticides in fruits and vegetables, and (8) reduced health threats to future generations. The third part of the questionnaire contains the description of the hypothetical payment scheme and finally the willingness-to-pay elicitation question, which is the core element of the CVM. In this part respondents are told that carrying out the measures proposed in the scenario description would involve costs the financing of which needed to be secured before the proposed program can be started in order to achieve the envisaged water quality improvement. As a means of financing the program people are told that it is intended to increase the water fees that MR WW customers have to pay for a specified period of 5 years. The English translation of the wording presented to the respondents in Thai language reads as follows: "Since these measures are costly their financing has to be secured before such a program can be implemented. Therefore, it is intended to increase the water fee for the tap water supply for the next five years to get the program started." This formulation of the payment scheme 127 stresses the fact that this program has not been decided on, yet. The subsequent WTP elicitation question is worded so that respondents should realize that the implementation of the program would somehow be influenced by their willingness to contribute to its financing. As mentioned above, two different types of elicitation question formats were to be tested in this study, the dichotomous choice (DC) and the payment card (PC) format. For each format it was also intended to test whether procedural biases like the starting point bias or "yea"-saying in the DC format or the range and centering bias in the PC format occur since they would indicate boundedly rational behavior or limited information processing in response to heuristic cues included in the specific elicitation question design. For the DC version, therefore, a wide range of bids, i. e. starting bids well below and well above the expected range of the true WTP, should be used in the bid design in order to detect such distorting effects on response behavior. In pretests a first indication about the realistic range of bids was obtained which could be used for the bid design. For the PC version, at least two different ranges of specified bid intervals should be used so that the influence of the upper cut-off point on the bid chosen by the respondent can be determined. From these considerations a split-sample design following the scheme depicted in figure 4-4 was developed. Figure 4-4: Split sample design of the WTP elicitation question WTP elicitation question Dichotomous choice Payment card For the DC question the DeShazo format (see chapter 2) was selected due to findings in an earlier CVM study in the same problem context that responses to the double-bounded DC format were highly susceptible to anchoring effects. Table 4-4 compiles the bid design of the 5 questionnaire versions selected for the DC sample and the bounds of the two PC questionnaire versions where the cut-off bid signifies where the range of specified bid intervals ends and above 128 which an open interval is left. The detailed specification of bid intervals of the payment card is given in the appendix. After the description of the payment scheme (see above) respondents are asked the WTP elicitation question either in the DC version (anonymous or nonanonymous) or in the PC version (anonymous or non-anonymous). The nonanonymous question with the DC format for version 1 (see table 4-4) reads as follows: "If, as a consequence, your water bill increased by altogether 25 Baht per month for the next five years, would you support this program?" If the respondent answers "yes" the interview proceeds to the next question. If the respondent answers "no" a follow-up question using the lower follow-up bid (see table 4-4) is asked: "If instead the monthly water bill increased by only 12 Baht, would you then be willing to support this program?" After the response to the follow-up question the interview proceeds to the next question. Table 4-4: Bid design of the DC and the PC elicitation question formats (monetary values in Thai Baht /month) Dichotomous choice Payment card version first bid follow-up bid version starting bid 25 -----. 12 small 0 2 50 -----. 25 large 0 3 100-----. 50 4 200 -----. ioo 5 400 -----. 200 cut-off range >400 > 2000 In the anonymous version of the DC question the respondent is given a sheet containing the question with the first bid and is asked to check either the "yes" or the "no" box. Subsequently, the interviewer hands the respondent a second sheet with the follow-up question and is asked to check one of the boxes. Obviously, someone who has already checked "yes" on the first sheet would also check "yes" on the second. These sheets are then put into a "ballot box" indicating presumed anonymity of the response. The formulation of the PC elicitation question reads as follows: "We would now like to ask you how much money your household would be willing to contribute to the program. Please, select from the following list the highest increase in your monthly water bill you would be willing to tolerate for the next five years if the improvements described above were realized." Here the respondent receives either the small or the large version as described in table 4129 4. In the anonymous version the respondent receives a separate sheet of paper containing the question and the respective payment card on which he could check the payment interval that contains his personal WTP. After the WTP elicitation question the respondent is asked how difficult it was to find an answer to this question. Subsequently, the respondent is asked to rate on a fivepoint Likert scale how important given statements were for his answer to the WTP question, i.e. these statements indicate the reasons for the stated WTP. The statements were formulated so that all respondents regardless of their response to the WTP question could answer them. The understandability of these formulations were tested in an extensive pretesting process. In the fourth part of the questionnaire a number of questions concerning respondents' attitudes w. r. t. the environment, the role of government, the financing of public goods, the importance of money in their everyday lives and their donation behavior are asked. Further, respondents should rate their incomes and their households' economic situations in comparison to others and are asked how worried they are w. r. t. a number of personal and public aspects. This part of the questionnaire also contains the two questions forming the newly developed measurement scales of bounded rationality. Finally, in the fifth part the usual socio-economic and demographic questions are asked. This part also contains questions regarding households' indebtedness since it might be a determinant of stated WTP. 4.4.2.3 The measurement scales of bounded rationality in northern Thailand - research implementation in the survey design The scales of bounded rationality are implemented in the empirical design of this study in the form of two separate questions within the fourth part of the questionnaire. In order to maintain a suitable "choreography" of the interview the question containing the items for the task independent scale was positioned right after the respondents had given their response to the WTP elicitation question and had just rated the level of difficulty of responding to it. The general form of this question as presented in table 4-2 (see 4.3.2) was slightly adapted to fit the specific cultural context of Thai society. In this respect, item E " Doing quizzes and cross-word puzzles are a pleasant form of entertainment for me" was considered not to be applicable in Thailand since Thai people usually do not undertake such activities for entertainment that are well known in Western societies and e. g. even in Japan Gust consider the Sudoku quizzes for that matter). Therefore, this item was changed and reformulated even in reverse sense to fit Thai people's liking of watching entertainment programs on television. Thus, the following formulation was chosen: "Documentary programs on TV annoy me so that I often switch to a different channel". The other items were considered suitable in the context of Thailand. In the questionnaire, respondents are asked to 130 rate the degree to which these statements are true for them personally on a fivepoint Likert scale where "l" means "not true at all" and "5" means "fully true". The task dependent scale of bounded rationality was placed separately from the question containing the items of the task independent scale with a number of other questions in between so that the respondents would not consider these two questions to be related to each other. Therefore, the question containing the items described in table 4-3 (see 4.3.2) forms the conclusion of part four of the questionnaire just before the standard socio-economic and demographic questions begin. All items of this questions were considered to fit the Thai context so the question was included into the questionnaire just as presented in table 4-3. 4.4.2.4 Practical implementation of the survey The sample for this survey was selected from the list of MR WW customers that receive their household tap water exclusively from the Mae Sa river. These households are located along 5 different water distribution lines which coincide quite well with particular neighborhoods of Mae Rim with a certain socioeconomic structure. For example, one distribution line delivers water into a residential area that consists of houses and apartments built for housing athletes of the Southeast Asian Games in the year 1995 which are now predominantly used by government officials. Another distribution line exclusively serves the residential area of a military camp and so on. Therefore, the different questionnaire versions of the described split sample design were allocated to these neighborhoods according to their relative frequencies in the population of MR WW customers so that the selected households constitute a representative sample of the population under consideration. The development of this survey and of the survey questionnaire followed a step-wise procedure that, apart from the usual expert interviews, in-depth interviews with households from the survey population and several waves of pretests where the questionnaire was tested on a limited selection of households and subsequently revised, also consisted of a participatory element of survey design. For this process, respondents of a previous CVM mail survey on the same project scenario were invited to join a series of group meetings with other respondents from the survey population in order to receive further information, discuss issues of the scenario of particular importance to them and comment on problematic issues of the questionnaire design. By means of these group discussions the researchers of this subproject intended to identify issues of conflict, resentments that respondents might have regarding certain aspects and questions, and taboos that respondents are reluctant to address. The mentioned aspects are considered to have the potential to distort the responses of CVM respondents and were attempted to be eliminated from the questionnaire. Details 131 concerning the technique and the results of this participatory procedure are given in Ahlheim et al. (2007). The survey was conducted from the end of July to the beginning of September 2005 by students of the Chiang Mai University who had been trained as interviewers for CVM surveys by the researchers of the project. Altogether, 55 interviewers were recruited, trained and employed. This large number of interviewers should result in a situation where effects caused by particular interviewers are negligible. Altogether, 823 households were interviewed from which 798 valid responses to the WTP elicitation questions were obtained. The distribution of interviewed households according to the split-sample design illustrated in figure 4-4 is given in table 4-5. Table 4-5: Distribution of responses in the split-sample design Question format Dichotomous choice Payment card Total Number of households interviewed (valid responses) 467 (454) 356 (344) 823 (798) 4.4.3 Empirical results of the project Response type anonymous non-anonymous anonymous non-anonymous Number of households interviewed 190 277 153 203 823 This section presents the empirical results of the research project. Before dealing with the results of the two scales of boundedly rational information processing and decision making, those general results obtained from this CVM study shall be highlighted that form the basis for the analysis of bounded rationality. First, the sample population shall be characterized by its socio-economic and demographic features in order to obtain an indication of the situation of the households under consideration. Second, the WTP results as assessed by the various procedures in the split-sample design shall be presented and discussed and the variables and factors that were found to systematically influence these WTP estimates shall be considered. Subsequently, the results of the scales of bounded rationality shall be analyzed in detail and their usefulness for explaining inconsistent response behavior shall be investigated. 132 4.4.3.1 Socio-economic and demographic characteristics of the respondent population Within the surveyed population of 823 household heads, male and female respondents were roughly equally represented with a percentage of 52% female and 48% male respondents. Exactly two thirds (66,4%) of the respondents had children or grandchildren. The values for the mean and standard deviation of household size, age and monthly household income are given in table 4-6. Table 4-6: Values of household size, age and income Variable Household size Age Monthly income Mean 3,07 40,4 18760 Baht (::::: 375 €) Standard deviation 1,45 13,6 14522 Baht (::::: 290 €) Household sizes ranged from 1 to 9 individuals per household, where 2-, 3and 4-person households were the most frequent with ca. 23 % each. 15% of the households were single households and roughly another 15% of households had 5 or more members. Age of respondents ranged from 13 to 92 where those respondents below 18 years of age were excluded from the sample since they were considered not to be the household head in charge of economic decisions. The distribution of rough income classes is given in figure 4-5 which also contains the relative frequencies of the categorical variables of the sample population. From b) in figure 4-5 it can be observed that while all classes of education are included in the survey, respondents holding a Bachelor degree are by far the most frequent. This evident overrepresentation of respondents with a Bachelor degree is obviously due to the very high frequency of officials in the sample, a peculiarity of the survey population chosen for this study. Since the survey sample is drawn from the list of MRWW customers for which no record of socio-economic and demographic variables exist the selected sample's representativeness can, unfortunately, not be verified by the usual comparison with the distribution of these variables within the general population. 133 Figure 4-5: Relative frequencies of categorical socio-economic and demographic variables a) Income classes c) Profession 50 40 30 20 JO 40 30 20 JO 60 50 40 30 20 JO b) Education d) Marital status 4.4.3.2 Estimates of willingness-to-pay for the tap water improvement program The ultimate aim of a CVM survey is the assessment of the willingness-to-pay (WTP) of the survey population. The estimates of WTP of this survey scenario are given in table 4-7 where the two elicitation question formats DC and PC were evaluated separately using a variety of different data evaluation methods. First of all, the data were analyzed separately according to anonymity or nonanonymity of the elicitation question and jointly (last column). Second, for the 134 Pavment Card Dichotomous Choice Question TDFl TDF2 TDF3 TDF4 TDFI TDF2 TDF3 coeff. coeff. coeff. coeff. coeff. coeff. coeff. (p-value) (p-value) (p-value) (p-value) (p-value) (p-value) (p-value) IOa Libraries .051 -.008 .01 I .010 .005 .025 -.119 (.360) (.882) (.844) (.853) (.915) (.604) (.012) IOb Discotheques .034 .026 -.030 .041 .000 .087 .028 (.540) (.642) (.589) (.465) (.994) (.066) (.552) IOc State Railway of -.016 -.111 .022 -.037 .010 .090 .027 Thailand (.767) (.045) (.698) (.506) (.835) (.058) (.573) IOd Swimming-pools, gyms, .064 -.062 .033 .017 .082 -.051 -.026 soorts fields (.250) (.265) (.547) (. 759) (.083) (.288) (.587) IOe Schools .036 -.014 .084 .034 .002 -.079 .119 (.5 I I) (.794) (.127) (.537) (.960) (.094) (.685) IOf Provincial Electricity .076 -.134 .045 .053 -.042 .039 .102 Authority (.168) (.015) (.412) (.337) (.373) (.408) (.032) IOg Theaters -.065 .055 .047 -.007 -.046 .087 -.017 (.237) (.323) (.399) (.894) (.331) (.067) (.720) IOh Provincial Water .049 -.045 .Q38 .103 -.013 .026 .096 Authority (.377) (.418) (.488) (.063) (.777) (.578) (.043) IOi Mass Transit Authority .090 -.145 -.016 .008 .001 -.039 .067 (. I 06) (.009) (.768) (.890) (.985) (.408) (.158) IOj Thailand Post .065 -.068 .031 .024 -.003 .001 .096 (.238) (.222) (.575) (.670) (.944) (.980) (.044) IOk Telephone of Thailand .118 -.082 .030 .073 -.047 .039 .121 (.032) (.140) (.583) (.190) (.326) (.418) (.010) lla I find it difficult to say .061 -.074 .054 -.033 .105 -.171 .014 "no" if a friend asks me (.270) (.179) (.331) (.554) (.027) (.000) (.761) a favor. lib It gives me a good .066 -.023 -.Q38 -.079 .108 -.055 -.110 feeling if! donate money (.235) (.679) (.487) (.151) (.022) (.243) (.020) for people I do not know !personally. lie The increase of my .027 -.019 -.033 -.172 .099 .044 -.003 "boon" associated with (.632) (.727) (.550) (.002) (.038) (.353) (.947) the donation is very important to me. lid I help other people -.056 .045 -.019 -.027 .012 .015 .120 because they will help (.315) (.412) (.737) (.620) (.794) (.755) (.01 I) me when I am in need. lie I donate money because -.007 -.058 -.057 -.106 .066 -.019 .090 "giving" is an (.896) (.297) (.307) (.056) (.162) (.692) (.057) established habit in our society. llf I promise to do .168 -.059 -.002 .080 .175 .053 .118 something although I do (.002) (.286) (.967) (.147) (.000) (.267) (.013) not want to do it. llg I give promises and then .053 .039 -.023 .115 .072 .172 .134 I do not keep them. (.339) (.484) (.679) (.037) (. 132) (.000) (.005) lib I am concerned what .073 .083 .086 .037 .064 -.063 -.003 other people think of me. (.186) (.135) (.120) (.499) (.178) (.185) (.946) 237 Pavmeot Card Dichotomous Choice Question TDFl TDF2 TDF3 TDF4 TDFl TDF2 TDF3 coeff. coeff. coeff. coeff. coeff. coeff. coeff. (p-value) (p-value) (p-value) (p-value) (p-value) (p-value) (p-value) 12a Taking care of .108 .025 .051 -.065 -.070 -.035 -.102 environmental protection (.051) (.646) (.360) (.243) (.138) (.462) (.031) is an important task of !government. 12b Law enforcement .086 -.066 -.019 -.065 .034 -.057 -.139 concerning (.120) (.233) (.732) (.239) (.474) (.229) (.003) environmental management is usually not effective. 12c Usually, government's .080 -.057 .040 -.095 -.019 -.083 -.066 action concerning (.148) (.306) (.471) (.085) (.687) (.082) (. 165) environmental protection is 'too late'. 12d Government should -.012 -.073 -.044 .010 -.046 -.004 -.097 collect more taxes to (.833) (.190) (.423) (.855) (.337) (.926) (.041) increase the budget for environmental management. 13 Classify: household .Oil .001 .007 .036 .003 -.024 -.062 richer or poorer than (.846) (.985) (.897) (.510) (.956) (.613) (.193) average 14 Classify: economic -.032 -.089 .46 .053 -.026 -.087 -.022 situation better or worse (.557) (. 106) (.403) (.340) (.579) (.066) (.636) than average 15 Classify: consider .018 -.027 .104 .002 .026 -.184 .094 income fair or unfair (.749) (.62 I) (.059) (.965) (.587) (.000) (.047) 16a I need money to be .146 .034 -.012 -.079 -.093 .013 .162 haoov. (.009) (.537) (.831) (.157) (.050) (.790) (.001) 16b I usually spend all my .121 -.016 .021 -.019 .053 .024 .174 income because buying (.029) (.778) (.713) (.734) (.262) (.615) (.000) things makes me haoov. 16c I like to buy things on .160 -.106 .083 .096 .141 .077 .169 installment. (.004) (.056) (.135) (.084) (.003) (.104) (.000) 16d I build up savings .099 -.052 .086 -.132 .012 -.134 .053 because I want to have (.074) (.350) (.121) (.017) (.807) (.005) (.263) security for the future. 16e I build up savings .098 .012 .069 -.179 .003 -.023 -.024 because I want to leave (.080) (.825) (.218) (.001) (.957) (.626) (.61 I) something for my children. 16f Even with more money .119 -.012 .002 .092 .185 .013 -.01 I for myself! would not be (.032) (.832) (.976) (.099) (.000) (.785) (.812) happier than now. 17a Worried about own .157 -.032 .063 .089 -.009 .122 .076 economic situation (.004) (.565) (.258) (.108) (.852) (.010) (.I 07) 17b Worried about health .200 -.078 -.022 .096 -.008 .069 .048 (.000) (.161) (.687) (.083) (.871) (.147) (.317) 238 Payment Card Dichotomous Choice Question TDFI TDF2 TDF3 TDF4 TDFI TDF2 TDF3 coeff. coeff. coeff. coeff. coeff. coeff. coeff. (p-value) (p-value) (p-value) (p-value) (p-value) (p-value) (p-value) 17c Worried about .014 -.165 .095 -.023 -.065 -.076 .016 progressive degradation (.808) (.003) (.086) (.677) (.170) (.I 10) (.734) of environment 17d Worried about peace in -.020 -. I I 8 -.007 .001 -.037 -.102 -.012 the world (.716) (.033) (.898) (.983) (.434) (.031) (.798) 17e Worried about the .021 -.131 .048 .050 -.01 I -.004 -.023 political situation in (.702) (.018) (.386) (.362) (.811) (.931) (.625) Thailand 17f Worried about the .104 -.052 .001 .081 -.036 .072 .056 security of income (.060) (.353) (.989) (.145) (.450) (.131) (.240) 17g Worried about the moral .084 -.094 .106 -.123 .008 -.148 -.044 values of young people (.130) (.089) (.055) (.027) (.870) (.002) (.349) 17h Worried about decrease .096 -.118 -.001 -.049 -.028 -.032 .034 in social justice in (.083) (.033) (.989) (.382) (.552) (.494) (.479) Thailand 17i Worried about corruption .201 -.197 .003 -.048 .067 -.031 .053 (.000) (.001) (.962) (.386) (.159) (.518) (.261) 17j Worried about foreigners .o70 -.147 .097 -.066 -.003 -.059 .062 (.203) (.008) (.079) (.236) (.944) (.216) (.I 91) 19-la Debts: bank or BAAC .062 .033 -.001 .o70 -.001 .092 -.034 (.265) (.554) (.979) (.206) (.979) (.052) (.480) 19-lb Debts: friends or family .017 .012 .091 .107 -.001 .047 -.045 (.756) (.835) (.102) (.054) (.989) (.321) (.348) 19-lc Debts: money lender .010 .123 -.008 .022 .026 .060 -.034 (.860) (.027) (.890) (.686) (.589) (.212) (.480) 19-ld Debts: village fund .144 .121 .016 .072 .080 .113 -.044 (.009) (.029) (.773) (.192) (.091) (.017) (.351) 19-le Debts: installment .000 -.004 .042 -.023 -.042 .Ill .016 IPavments (.999) (.937) (.451) (.675) (.377) (.020) (. 740) 19-3 Worried about debt level .009 .070 .008 .034 .125 .141 .081 (.890) (.274) (.169) (.598) (.019) (.008) (.131) 20-1 Sex -.018 -.023 .000 .034 -.013 .003 -.044 (.748) (.679) (.993) (.327) (.778) (.951) (.352) 20-4 Age -.027 .143 -.015 -.017 .060 -.029 -.057 (.625) (.009) (.787) (. 757) (.207) (.543) (.229) 20-5 Marital status .031 .083 -.037 -.016 -.018 -.oJO -.012 (.575) (.134) (.508) (.779) (. 705) (.534) (.799) 20-6 Children or -.017 .056 -.034 .006 .027 -.013 .007 grandchildren (.759) (.3 I 6) (.536) (.908) (.567) (.783) (.880) 20-7 Household size -.114 .001 -.079 -.109 -.012 .057 .098 (.039) (.981) (. 156) (.049) (.799) (.233) (.041) 20-9 Level of education -.036 -.126 .065 -.088 -.036 -.048 -.004 (.518) (.023) (.238) (.111) (.443) (.309) (.939) 20-12 Income -.080 -.078 -.021 -.065 -.089 -.125 .063 (. I 50) (.162) (.708) (.245) (.064) (.009) (. I 87) 239 HOHENHEIMER VOLKSWIRTSCHAFTLICHE SCHRIFTEN Band Walter Deffaa: Anonymisierte Befragungen mit zufallsverschliisselten Antworten. Die Randomized-Response-Technik (RRT). Methodische Grundlagen, Modelle und Anwendungen. 1982. Band 2 Thomas Michael Baum: Staatsverschuldung und Stabilisierungspolitik in der Demokratie. Zur neoinstitutionalistischen Kritik der keynesianischen Fiskalpolitik. 1982. Band 3 Klaus Schr6ter: Die wettbewerbspolitische Behandlung der leitungsgebundenen Energiewirtschaft. Dargestellt am Beispiel der Fernwiirmewirtschaft der Bundesrepublik Deutschland. 1986. Band 4 Hugo Mann: Theorie und Politik der Steuerreform in der Demokratie. 1987. Band 5 Max Christoph Wewel: lntervallarithmetische Dependenzanalyse in der Okonometrie. Ein konjekturaler Ansatz. 1987. Band 6 Heinrich Pascher: Die U.S.-amerikanische Deregulation Policy im Luftverkehrsund Bankenbereich. 1987. Band 7 Harald Lob: Die Entwicklung der franz6sischen Wettbewerbspolitik bis zur Verordnung Band 8 Band 9 Band 10 Band 11 Band 12 Band 13 Band 14 Band 15 Band 16 Band 17 Band 18 Band 19 Nr. 86-1243 vom 01. Dezember 1986. Eine exemplarische Untersuchung der Erfassung der Behinderungsstrategie auf der Grundlage des Konzepts eines wirksamen Wettbewerbs. 1988. Ulrich Kirschner: Die Erfassung der Nachfragemacht von Handelsunternehmen. Eine Analyse der 6konomischen Beurteilungskriterien und der wettbewerbsrechtlichen lnstrumente im Bereich der Verhaltenskontrolle.1988. Friedhelm Herb: Marktwirtschaftliche lnnovationspolitik. 1988. Claus Schnabel: Zur 6konomischen Analyse der Gewerkschaften in der Bundesrepublik Deutschland. Theoretische und empirische Untersuchungen von Mitgliederentwicklung, Verhalten und EinfluB auf wirtschaftliche Gr6Ben. 1989. Jan B. Rittaler: Industrial Concentration and the Chicago School of Antitrust Analysis. A Critical Evaluation on the Basis of Effective Competition. 1989. Thomas Martz: lnteressengruppen und Gruppeninteressen in der Demokratie. Zur Theorie des Rent-Seeking. 1990. Andreas Maurer: Statistische Verfahren zur Ermittlung von oligopolistischen Strukturen. 1990. Peter Mendler: Zur 6konomischen und politisch-institutionellen Analyse 6ffentlicher Kredithilfen. 1992. Heinrich J. Engelke: Die Interpretation der Rundfunkfreiheit des Grundgesetzes: Eine Analyse aus 6konomischer Sicht. 1992. Thomas Fischer: Staal, Recht und Verfassung im Denken von Walter Eucken. Zu den staatsund rechtstheoretischen Grundlagen einer wirtschaftsordnungspolitischen Konzeption. 1993. Stefan EIBer: lnnovationswettbewerb. Determinanten und Unternehmensverhalten. 1993. Reinhard Scharff: Regionalpolitik und regionale Entwicklungspotentiale. Eine kritische Analyse. 1993. Karin Beckmann: Probleme der Regionalpolitik im Zuge der Vollendung des Europiiischen Binnenmarktes. Eine okonomische Analyse. 1995. Band 20 Bernd Nolte: EngpaBfaktoren der Innovation und lnnovationsinfrastruktur. Eine theoretische und ernpirische Analyse fur liindliche Wirtschaftsriiurne in Baden-Wiirtternberg. 1996. Band 21 Klaus-Rainer Brintzinger: Die Nationalokonornie an den Universitiiten Freiburg, Heidelberg und Tiibingen 1918 -1945. Eine institutionenhistorische, vergleichende Studie der wirtschaftswissenschaftlichen Fakultiiten und Abteilungen siidwestdeutscher Universitiiten. 1996. Band 22 Band 23 Band 24 Band 25 Band 26 Band 27 Band 28 Band 29 Band 30 Band 31 Band 32 Band 33 Band 34 Band 35 Band 36 Band 37 Band 38 Band 39 Band 40 Steffen Binder: Die Idea der Konsurnentensouveriinitiit in der Wettbewerbstheorie. Teleokratische vs. nomokratische Auffassung. 1996. Alexander Burger: Deregulierungspotentiale in der Gesetzlichen Rentenversicherung. Reforrnnotwendigkeiten versus Reformmoglichkeiten. 1996. Burkhard Scherer: Regionale Entwicklungspolitik. Konzeption einer dezentralisierten und integrierten Regionalpolitik. 1997. Frauke Wolf: Lorenzkurvendisparitiit. Neuere Entwicklungen, Erweiterungen und Anwendungen. 1997. Hans Pitlik: Politische Okonomie des Foderalismus. Foderative Kompetenzverteilung im Lichte der konstitutionellen C>konomik. 1997. Stephan Seiter: Der Beitrag Nicholas Kaldors zur Neuen Wachstumstheorie. Eine vergleichende Studie vor dem Hintergrund der Debatte iiber den Verdoorn-Zusammenhang. 1997. Andre Schmidt: Ordnungspolitische Perspektiven der europaischen Integration im Spannungsfeld von Wettbewerbsund lndustriepolitik. 1998. Bernd Blessin: Innovationsund Umweltmanagement in kleinen und mittleren Unternehmen. Eine theoretische und empirische Analyse. 1998. Oliver Letzgus: Die Okonomie internationalen Umweltschutzes. 1999. Claudia Hafner: Systemwettbewerb versus Harmonisierung in Europa. Am Beispiel des Arbeitsmarktes. 1999. Jurgen Kulla: Okonomie der Musikindustrie. Eine Analyse der korperlichen und unkorperlichen Musikverwertung mil Hilfe von Tontriigern und Netzen. 1998. Michael Ganske: lntertemporale Aspekte von Staatsverschuldung und AuBenhandel. 1999. Margit Strobele: Die Deregulierungswirkungen der europiiischen Integration. Das Beispiel der Sondermarkte. 1999. Marion Benesch: Devisenmarktinterventionen in Theorie und Praxis. Eine umfassende Analyse ihrer Zielsetzungen, Wirkungsweisen und wirtschaftspolitischen Bedeutung. 1999. Torsten Gruber: Unterschiedliche geldpolitische Transmissionsrnechanismen und Stabilitatskulturen als mOgliche Ursachen geldpolitischer Spannungen in der Europiiischen Wiihrungsunion. 2000. Bertram Melzig-Thiel: Arbeit in der lnformationsgesellschaft. Chancen und Risiken neuer Informationsund Kommunlkationstechnologien fiir die Beschiiftigung. 2000. Annette Fritz: Die Entsorgungswirtschaft im Spannungsfeld zwischen Abfallpolitik und Kartellrecht. Eine industriecikonomische Branchenstudie. 2001. Harald Strotmann: Arbeitsplatzdynamik in der baden-wiirttembergischen lndustrie. Eine Analyse mit arntlichen Betriebspaneldaten. 2002. Dietrich Benner: QualitiitsungewiBheit bei Giitern mil Vertrauenseigenschaften. Entwicklung und Anwendung eines entscheidungstheoretisch fundierten Analyserahmens. 2002. Band 41 Jurgen M. Schechler: Sozialkapital und Netzwerkokonomik. 2002. Band 42 Kay-Uwe May: Haushaltskonsolidierung durch Ausgabekurzungen. Restriktionen und Strategien. 2002. Band 43 Peter Kuhnl: Der Wechselkurs als Zwischenziel der Geldpolitik im Aufholprozess. Die monetiirkeynesianische Entwicklungsstrategie der Berliner Schule vor dam Hintergrund der makrookonomischen Entwicklung ausgewiihlter Lander Mittelund Osteuropas. 2003. Band 44 Band 45 Band 46 Band 47 Band 48 Band 49 Band 50 Band 51 Band 52 Band 53 Band 54 Band 55 Band 56 Band 57 Band 58 Steffen Wirth: Nichtparametrische Analyse von Bildungsertragsraten. Neuere Entwicklungen und Anwendungen. 2003. Bernhard Holwegler: Innovation, Diffusion und Beschiiftigung. Die okonomische Theorie der Technologiediffusion und ihr Beitrag zur Erklarung technologischer Arbeitslosigkeit. 2003. Guntram A. M. Hepperle: Zukunftsorientierte lndustriepolitik. Moglichkeiten und Grenzen. 2004. Udo Vullhorst: Stabilisierungspolitik bei supranationaler Geldpolitik und nationaler Fiskalpolitik. Eine spieltheoretische Betrachung. 2004. Matthias Rosch: Die Bedeutung von lnvestivlohnen und Gewinnbeteiligungen fur Einkommensverteilung und Beschiiftigung. 2004. Michael Bubik: Erfolgskriterien !Or UntemehmenszusammenschlOsse. Eine theoretische und exemplarische Analyse. 2005. Jorg Wallin: Internationale Unternehmensbesteuerung. Allokation der Besteuerungsrechte unter veriinderten Rahmenbedingungen. 2005. Susanne Reichart: Zurn Konvergenzprozess der mittelund osteuropaischen EU-Beitrittsliinder. 2005. Daniel Hartmann: Geldpolitik und Beschiiftigung. Die geldpolitische Strategie der Federal Reserve: Vorbild oder Auslaufmodell? 2005. Marc Peter Radke: Explaining Financial Crises. A Cyclical Approach. 2005. Katja Holsch: Umverteilungseffekte in Europa. Eine Analyse !Or ausgewahlte Liinder. 2006. Ulrike Lehr: Contingent Valuation Dalen und Bayes'sche Verfahren. Ein Vorschlag zur Verbesserung von Umweltbewertung und Nutzentransfer. 2006. Jutta Maute: Hyperinflation, Currency Board, and Bust. The Case of Argentina. 2006. liegt noch nicht vorl Oliver Fror: Rationality Concepts in Environmental Valuation. 2007. www.peterlang.de C cu ~ n, .c u "' C cu "' "' § ... cu "'C Cl n, - ... j ... cu - n, C 0 "+i n, C ... cu +' C ... cu +' cu 0.. Michael B. Hinner lntercultural Application Guide for Work and Studies in the USA Frankfurt am Main, Berlin, Bern, Bruxelles, New York, Oxford, Wien, 2005 . 158 pp. ISBN 978-3-631-53121-1 · pb. € 17.50* This application guide explains how one applies for work and studies in the USA, and why typical German application documents and behavior could result in a rejection. While this guide is primarily directed at students, anyone seeking employment in the USA might find useful information and tips in this work. In addition to describing all phases of the entire application process, this guide also presents examples of all application documents -including letters of recommendation, acceptance, and rejection. Contents: The Application Process - The Preliminary Phase - The Application Phase - The Post-Application Phase · The Application Documents - The Resume and the Curriculum Vitae - Letters -Concluding Remarks Frankfurt am Main · Berlin · Bern · Bruxelles · New York · Oxford · Wien Distribution: Verlag Peter Lang AG Moosstr. 1, CH-2542 Pieterlen Telefax 0041 (0)32/3761727 *The €-price includes German tax rate Prices are subject to change without notice Homepage http://www.peterlang.de