Efficiency and environmental regulation : a 'complex situation'

Documents de Treball Departament d'Economia de l'Empresa EFFICIENCY AND ENVIRONMENTAL REGULATION: A ‘COMPLEX SITUATION’ Andrés J. Picazo-Tadeo Diego Prior Document de Treball núm. 05/2 © Andrés J. Picazo-Tadeo; Diego Prior Coordinador / Coordinator Documents de treball: Carles Gispert http://selene.uab.es/dep-economia-empresa/recerca/Documents.htm e-mail: [email protected] Telèfon / Phone: +34 93 5814296 Fax: +34 93 5812555 Edita / Publisher: Departament d'Economia de l'Empresa http://selene.uab.es/dep-economia-empresa/ Universitat Autònoma de Barcelona Facultat de Ciències Econòmiques i Empresarials Edifici B 08193 Bellaterra (Cerdanyola del Vallès), Spain Tel. 93 5811209 Fax 93 5812555 Abril / April, 2005 La sèrie Documents de treball d'economia de l'empresa presenta els avanços i resultats d'investigacions en curs que han estat presentades i discutides en aquest departament; això no obstant, les opinions són responsabilitat dels autors. El document no pot ser reproduït total ni parcialment sense el consentiment de l'autor/a o autors/res. Dirigir els comentaris i suggerències directament a l'autor/a o autors/res, a la direcció que apareix a la pàgina següent. A Working Paper in the Documents de treball d'economia de l'empresa series is intended as a mean whereby a faculty researcher's thoughts and findings may be communicated to interested readers for their comments. Nevertheless, the ideas put forwards are responsibility of the author. Accordingly a Working Paper should not be quoted nor the data referred to without the written consent of the author. Please, direct your comments and suggestions to the author, which address shows up in the next page. EFFICIENCY AND ENVIRONMENTAL REGULATION: A ‘COMPLEX SITUATION’ Andrés J. Picazo-Tadeo Diego Prior Document de Treball núm. 05/2 1 Efficiency and environmental regulation: a ‘complex situation’ Andrés J. Picazo-Tadeo (a) Diego Prior (b) (a) Universitat de València. Dpto. Economía Aplicada II. Avda. dels Tarongers, s/n. 46022. Valencia, SPAIN. Email: [email protected] (b) Universitat Autònoma de Barcelona. Dpto. Economia de l’Empresa. 08193 Bellaterra, Barcelona, SPAIN. Email: [email protected] February 22, 2005 ABSTRACT.- Production of desirable outputs is often accompanied by undesirable byproducts that have damaging effects on the environment, and whose disposal is frequently regulated by public authorities. In this paper, we compute directional technology distance functions under particular assumptions concerning disposability of bads in order to test for the existence of what we call ‘complex situations’, where the biggest producer is not the greatest polluter. Furthermore, we show that how in such situations, environmental regulation could achieve an effective reduction in the aggregate level of bad outputs without reducing the production of good outputs. Finally, we illustrate our methodology with an empirical application to a sample of Spanish tile ceramic producers. Key words: environmental regulation; efficiency; disposability of bads. JEL Classification: C61; D21; L68. 1. Introduction The analysis of firms’ environmental performance and the assessment of the costs of abating undesirable by-products that frequently come jointly with production of desirable goods, are receiving growing attention by both academics and policy decision-makers. Furthermore, environmental issues are also becoming a major matter of concern for firms’ managers. From the eighties onward, a growing literature has arisen devoted to incorporating environmental issues into traditional production theory, which has, to date, produced a wealth of contributions (see Tyteca, 1996 and Allen, 1999 for a review). On the one hand, some studies have focused on adjusting conventional productivity indexes to allow for undesirables into the output vector. Pitman (1983) pioneered this line of research by using econometric techniques to calculate shadow prices for undesirable outputs, which were used to compute an index of productivity change that accounts for environmental effects. Färe et al. (1993) calculated firm-specific shadow prices of undesirables from the computed parameters of an output 2 distance function. Afterward, this methodological approach has been applied in numerous papers, Coggins and Swinton (1996), Swinton (1998) and Reig-Martínez et al. (2001), among others. On the other hand, a second strand of the literature has addressed the issue of extending the traditional efficiency analysis framework (Farrell, 1957) to explicitly account for the presence of undesirable outputs. Färe et al. (1989) suggested the computation of hyperbolic productive efficiency measures under both strongly and weakly disposable technologies, to measure the impact on firms’ performance of lack of free disposability of wastes, e.g. due to environmental-friendly regulations. Other interesting papers that analyse environmental and economic performance are Ball et al. (1994), Brännlund et al. (1995), Färe et al. (1996), Tyteca (1997), Hernández-Sancho et al. (2000) and Zofio and Prieto (2001). In recent years, it has emerged a renewed interest in measuring environmental performance together with pollution abatement costs arising from public regulations aimed at achieving determined standards of environmental quality. A number of papers, including that by Chung et al. (1997) and Ball et al. (2001), have proposed the use of directional distance functions (Färe and Grosskopf, 2000; see also Färe and Grosskopf, 2004) as an useful tool in modelling production theory in presence of undesirables and, particularly, in assessing environmental performance. Some other studies have used directional distance functions to explicitly calculate the costs of abating contamination. Färe et al. (2003) interpret pollution abatement costs as the foregone production of good outputs that results from the reallocation of productive inputs to pollution reduction activities, i.e. resources that otherwise could be addressed to good output production. Furthermore, Picazo-Tadeo et al. (2005) utilise directional technology distance functions to calculate productive-oriented efficiency measures under both strongly and weakly disposable technologies, which are used to compute firm-specific reduced production of goods resulting from regulations that prevent free disposal of residuals. This paper differs from Färe et al. (2003) by scaling both goods and inputs, instead of scaling only good outputs. In this paper, we propose to consider in more detail the use of directional distance functions in assessing firms environmental performance and the opportunity cost of pollution abatement. Particularly, we show that computing directional distance functions under certain assumptions concerning disposability of undesirables, allows to identify what we call complex situations, where the biggest producer is not the greatest polluter. In such situations, 3 firms can increase their production of goods reducing bads, and regulating authorities could achieve an effective environmental regulation without affecting firms’ desirable production. The remainder of the paper is organised as follows. Section two deals with methodological issues. Section three describes the data and discuses the empirical application. Finally, section four concludes. 2. Methodology Introducing some notation, let us consider that production technology is defined by the set of feasible input, () ,..., ,...,=∈ I 1iI+ xxxxR , and output, ( ) ,..., ,...,=∈ J 1jJ+ yyy y R, vectors: () { } , can produce S=x y x y (1) Traditional production theory assumes that the properties of the production technology are the following (Shephard, 1970; see also Grosskopf, 1986): a) Inactivity. a.1) Possibility of inaction: () , ∈ S00 (2) It is technological possible not to produce. a.2) No free lunch: (,) ;∉>S0 yy 0 (3) Positive quantities of inputs are required to produce positive amounts of outputs. b) Strong disposability of inputs (SDI). () ( ) ,, ,, + ∀∈ ∈ ⇒ ∈ ≥ Iif S SxR xy x'y x'x (4) It is feasible to produce the same amount of output using a bigger quantity of any input, i.e., the inputs excess can be disposed at no cost. c) Strong disposability of outputs (SDO). () ( ) ,, , , + ∀∈ ∈ ⇒ ∈ ≤ Jif S Sy R xy xy' y' y (5) Any feasible output can be freely disposed. d) Convexity. 4 () ( ) ()( )( ) [] ,,,,,,, ,1 , ,0,1 αα α ++ ∀∈ ∀∈ ∈ ⇒+− ∈∈ IJ if S S xx' R yy' R xy x'y' xy x'y' (6) The linear combinations of feasible production plans are also feasible. Furthermore, let us assume that production of desirable outputs comes jointly with undesirable by-products, and that the output vector can be partitioned into a sub-vector of desirable or good outputs, () ,..., ,..., g gggG 1gG+ yyy=∈ y R, and a sub-vector of undesirable or bad outputs, () ,..., ,..., bbbbB 1bB+ yyy=∈ y R, so that ( ) ,=∈ g bJ + yyy R. In order to introduce joint production of good and bad outputs into the characterisation of the technology, two additional axioms are usually assumed, null-joint production (Shephard and Färe, 1974) and weak disposability of outputs, both desirable and undesirable (Färe and Primont, 1995). Formally, these axioms are formulated as: e) Null-jointness. ,,00 gG bBb g ++ ∀∈ ∀∈ =⇒ =yR yRy y (7) If some good outputs are produced, then some bads will also be produced. f) Weak disposability of outputs (WDO). () ( ) ,,,, ,,,1 αα α ++ ∀∈ ∀∈ ∈⇒ ∈ ≤ gG bB gb gb SSyR yR xyy xy y (8) Proportional reduction of good and bad outputs is feasible, but the isolated disposal of bad outputs may not be. The axiom of WDO constitutes a reasonable way of recognising that reducing undesirables may not be a free activity, as traditional production theory assumes. Conversely, when firms face environmental-friendly regulations, disposing undesirable outputs involves a cost that could be measured in terms of opportunity as a shrinkage of the maximum attainable production of goods from a given endowment of resources (Färe et al., 1989). In other words, inputs that otherwise could have a productive use, i.e. production of desirable outputs, have to be diverted to reduce or eliminate undesirable outputs in compliance with the environmental regulations. Our next theoretical building block is the directional distance function (DDF). This function generalises both input and output Shephard’s distance functions, providing a complete 5 representation of the production technology (Färe et al., 2000 summarise the theory and main applications of these functions). In presence of undesirable outputs, the DDF is defined as: () ( ) , , ; , , Sup , , gb g b gb g b xx yy y y Dggg gggS ββ β β ⎡ ⎤ −−= − + −∈ ⎢ ⎥ ⎣ ⎦ xy y x y y r (9) () ,,=− − gb xyy gg gg being the direction vector. Directional distance functions model joint production of desirable and undesirable outputs, allowing for increasing goods while simultaneously reducing bads, along a path previously determined through a particular direction vector. Accordingly, the DDF of expression (9) inflates the vector of good outputs in the g y g direction and contracts the vectors of inputs and bad outputs in the −x g and −b y g directions, respectively, while staying within the set of technologically feasible productive plans S. Furthermore, it can be proved that1: () ( ) ,,; , , 0 ,,−−≥⇔ ∈ r gb gb gb xyy Dggg Sxy y xy y (10) The computed DDF for a particular decision making unit measures its level of technical efficiency2. If the DDF equals to zero, the productive unit under evaluation is efficient in the Farrell-Debreu notion3. In other words, no other peer has been found that yields greater vector of good outputs with little consumption of inputs and smaller level of bad outputs. Under the set of assumptions made concerning the technology, and imposing variable returns to scale4, for a productive unit O, the DDF of expression (9) can be computed solving the following linear programming problem (see Färe et al., 2003): 1 Other relevant properties of DDF are summarised in Chambers et al. (1998). 2 Computed scores of technical efficiency must be considered here as measures of productive-oriented efficiency, rather than output- or input-oriented efficiencies, given that the directional distance function expands goods simultaneously reducing inputs. 3 Here, we follow the well-known Farrell-Debreu notion of efficiency. There exist, however, another more exigent concept of efficiency: the Pareto-Koopmans efficiency (see Färe et al., 1994 for details). 4 Other properties concerning the nature of the scale properties of the technology could also be assumed (see Banker et al., 1984). 12 In order to apply our algorithm to this dataset and testing for the possible existence of complex situations, we have computed the DDF of expressions (11), (12) and (16) assuming, as proposed, a direction that expands desirable output while maintaining inputs and bad outputs6, i.e., the direction vector is that of expression (13). Under this direction vector, the expression for the DDF becomes: ()() , , ;0,1,0 Sup , , gb g b DS ββ ⎡⎤ = +∈ ⎣⎦ xy y x y y r (17) This distance measures the extent to which a firm could increase its production of good output, while maintaining inputs and bads. In other words, given their endowment of inputs, it could be possible for inefficient tile firms to move to cleaner environmental-friendly productive plans that would enable them to produce more ceramic pavements while holding the same amount of watery mud and used oil. Since the amount of ceramic pavements increases with constant amount of bads, the ratio of each bad output per unit of good output will decrease. Comparing the DDF computed under the assumptions of SDB and SDIB, i.e., the solutions to programs (11) and (12), shows, on the one hand, that 29 firms (out of 35) present a behaviour corresponding to the basic situation depicted in Figure 1 (see Table 2). For these firms, the maximal increase in their production of ceramic pavements, requires an increase in the production of watery mud and used oil. When no regulation is assumed and wastes can be freely disposed, the aggregate desirable output produced by these firms could be augmented by 25 per cent, figure that amounts to 64,915 thousands of euros, with an average of 2,238 thousands per firm. Besides, eleven firms behave efficiently in this unregulated scenario, i.e., their computed DDF equals to zero. In opposition, when it is assumed a regulated scenario and disposing wastes becomes a costly activity, the maximum attainable aggregate expansion of goods goes down to 16,982 thousands of euros (586 euros per firm), showing that environmental regulations have an opportunity cost measurable in terms of a lower feasible expansion of desirable outputs. In this case, the reduced production of ceramic pavements due to inefficiency represents 6.5 per cent of the total good output produced by these firms. In the regulated scenario, twenty two tile firms show an efficient behaviour. [Table 2 about here] 6 Notice that this direction changes the left hand side of restrictions (i), (ii) and (iii) in expressions (11), (12) and (16) to o x, () g o β +y and b o y, respectively. 13 For these ceramic firms behaving according what we have termed the basic situation, the impact of environmental regulation can be conventionally computed as stated by expression (14), i.e., as the difference between the potential increases of ceramic pavements under both the unregulated and regulated scenarios. Figures on regulatory impacts are reported on the third column of Table 2. When it is assumed that environmental rules prevent free disposal of bads, in aggregate terms these ‘well behaved’ producers would have to renounce to a potential increase of desirable output of 47,933 thousands of euros (1,653 per firm). This figure amounts to 18.5 per cent of their observed aggregated production of ceramic pavements. On the other hand, comparison of DDF computed under the SDB and SDIB axioms also reveals that the behaviour of the six remaining firms (decision making units 1, 7, 11, 13, 24 and 27) corresponds to what we have denominated the complex situation depicted in Figure 2 (see the last column of Table 2). In particular, firm number 13 displays a behaviour analogous to productive unit C, while firms 1, 7, 11, 24 and 27 are productive units similar to point D. The traditional approach to the measurement of the impact of environmental regulations on firms performance, i.e., the simple comparison of DDF computed under both SDB and WDB, would lead to assess that, given their respective inputs vectors, no chance exists for the five firms type D to attain increases of their production of ceramic pavements, neither under the unregulated scenario nor under the regulated one. On the contrary, by behaving efficiently, the only firm type C in our sample (decision making unit number 13) could increase its production of ceramic pavements by 1,821 thousands of euros, under both the unregulated and regulated scenarios. Accordingly, environmental regulation is not binding for productive units type C and D, and their regulatory impact index equals to zero. Nevertheless, computation of the DDF for tile firms showing a complex behaviour under the axiom of SDIB, i.e., considering bads as strong disposable detrimental inputs, displays a picture somewhat different. In the light of this new technological consideration, these six productive units could attain an aggregate increase in their production of ceramic pavements of 13,026 thousands of euros, without additional consumption of inputs, with an average per firm of 2,171 thousands of euros. Doubtless, this is an information of great interest for the managers of these firms. Nonetheless, regulating authorities should also be aware that these tile firms are producing a level of bad output over to they would require, even in the case they maximize their production of ceramic pavements. In this situation, an effective reduction in the 14 aggregate level of watery mud and used oil could be achieved by environmental-friendly regulations, without limiting the production of the good output. 4. Concluding remarks Environmental performance is a major matter of concern for both firms’ managers and academics in the field of environmental economics. Besides, the growing recognition of the environment as a public good in the industrialised countries has stimulated wide-ranging legislation aimed at achieving predetermined standards of environmental quality. This setting calls for new methods to evaluate the environmental performance of firms and the impact of environmental-friendly regulations on their productive activity. In this paper we propose the use of directional distance functions to test for the existence of firms behaving accordingly to what we call complex situations, corresponding to productive units showing a quite unsuccessful economic and environmental performance. We show that when the biggest polluter is not the greater producer, by enforcing adequate environmental regulations, public authorities could achieve an effective reduction on the production of bads, without affecting the level of goods. Furthermore, we illustrate our methodological proposal with an empirical application to a sample of cross-section data of Spanish tile producers. Acknowledgements We are indebted to Francesc Hernández-Sancho for data availability. Andrés J. Picazo- Tadeo gratefully acknowledges the financial aid received from the Spanish Ministry of Science and Technology (project AGL2003-07446-C03-03). Diego Prior received financial aid from the Spanish Ministry of Science and Technology (project SEC2003-04770). The usual disclaimer applies. References Allen, K., 1999, DEA in the ecological context: an overview. In: Westermann, G. (Ed.), Data Envelopment Analysis in the service sector. Gabler Edition Wissenschaft, Germany, 203- 235. 15 Ball, V.E. Lovell, C.A.K., Nehring, R.F., Somwaru, A., 1994, Incorporating undesirable outputs into models of production: an application to US agriculture. Cahiers d’Economique et Sociologie Rurales 31, 59-73. Ball, V.E., Färe, R., Grosskopf, S., Nehring, R.F., 2001, Productivity of the US agricultural sector: the case of undesirable outputs. In: Hulten, Ch., Dean, E.R., Harper, M.J. (Eds.), New developments in productivity measurement. NBER. The University of Chicago Press. Banker, R.D., Charnes, A., Cooper, W.W., 1984, Some models for estimating technical and scale inefficiencies in Data Envelopment Analysis. Management Science 30, 1078-1092. Brännlund, R., Färe, R., Grosskopf, S., 1995, Environmental regulation and profitability: an application to Swedish pulp and paper mills. Environmental and Resource Economics 6, 23-36. Chambers, R.G., Chung, Y., Färe, R., 1998, Profit, directional distance functions and Nerlovian efficiency. Journal of Optimization Theory an Applications 98, 351-364. Chung, Y., Färe, R., Grosskopf, S., 1997, Productivity and undesirable outputs: a directional distance function approach. Journal of Environmental Management, 51, 229-240. Coggins, J.S., Swinton, J.R., 1996, The price of pollution: a dual approach to valuing SO2 allowances. Journal of Environmental Economics and Management 30, 58-72. Färe, R., Grosskopf, S., Lovell, C.A.K., 1994, Production Frontiers. Cambridge University Press, Cambridge. Färe, R., Grosskopf, S., 2000, Theory and application of directional distance functions. Journal of Productivity Analysis 13, 93-103. Färe, R., Grosskopf, S., 2004, New directions: efficiency and productivity. Kluwer Academic Publishers, Boston/London/Dordrecht. Färe, R., Grosskopf, S., Lovell, C.A.K., Pasurka, C., 1989, Multilateral productivity comparisons when some outputs are undesirable: a nonparametric approach. The Review of Economics and Statistics 71, 90-98. Färe, R., Grosskopf, S., Lovell, C.A.K., Yaisawarng, S., 1993, Derivation of shadow prices for undesirable outputs: a distance function approach. The Review of Economics and Statistics 75, 374-380. Färe, R., Grosskopf, S., Tyteca, D., 1996, An activity analysis model of the environment performance of firms: application to fossil-fuel-fired electric utilities. Ecological Economics 18, 161-175. Färe, R., Primont, D., 1995, Multi-output production and duality: theory and applications. Kluwer Academic Publishers. Färe, R., Grosskopf, S., Pasurka, C.A., 2003, Estimating pollution abatement costs: a comparison of ‘stated’ and ‘revealed’ approaches, Working Paper Oregon State University. http://oregonstate.edu/dept/econ/research/working_papers.php. 16 Farrell, M., 1957, The measurement of productive efficiency. Journal of the Royal Statistics Society. Series A 120, 253-282. Grosskopf, S., 1986, The role of the reference technology in measuring production efficiency. The Economic Journal 96, 499-513. Hernández-Sancho F., Picazo-Tadeo, A., Reig-Martínez, E., 2000, Efficiency and environmental regulation. Environmental and Resource Economics 15, 365-378. Picazo-Tadeo, A.J., Reig-Martínez, E., Hernández-Sancho, F., 2005, Directional distance functions and environmental regulation. Resource and Energy Economics, in press. Pittman, R.W., 1981, Issues in pollution control: interplant cost differences and economies of scale. Land Economics, 57, pp. 1-17. Pittman, R.W., 1983, Multilateral productivity comparisons with undesirable outputs. Economic Journal 93, 883-891. Prior, D., 2005, Efficiency and total quality management in health care organisations. A dynamic frontier approach. Annals of Operations Research, in press. Reig-Martínez, E., Picazo-Tadeo, A., Hernández-Sancho, F., 2001, Shadow prices and distance functions: an analysis for firms of the Spanish ceramic pavements industry. International Journal of Production Economics 69, 277-285. Reinhard, S, Lovell, C.A.K, Thijssen, G., 2002, Analysis of environmental efficiency variation. American Journal of Agricultural Economics 84, 1054-1065. Reinhard, S., Lovell, C.A.K., Thijssen, G., 1999, Econometric estimation of technical and environmental efficiency: an application to Dutch dairy farms. American Journal of Agricultural Economics, 81, 44-60. Shephard, R.W., 1970, Theory of cost and production functions. Princeton University Press, Princeton. Shephard, R.W., Färe, R., 1974, The law of diminishing returns. Zeitschrift für Nationalökonomie 34, 69-90. Swinton, J.R., 1998, At what cost do we reduce pollution? Shadow prices of SO2 emissions. Energy Journal 19, 63-83. Tyteca, D., 1996, On the measurement of the environmental performance of firms: a literature review and a productive efficiency perspective. Journal of Environmental Management 46, 281-308. Tyteca, D., 1997, Linear programming models for the measurement of environmental performance of firms: concepts and empirical results. Journal of Productivity Analysis 8, 175- 189. Zofio, J.L., Prieto, A., 2001, Environmental efficiency and regulatory standards: the case of CO2 emissions from the OECD industries. Resource and Energy Economics 23, 63-93. 17 Table 1.- Sample description. Variable Measurement unit Mean Standard deviation Desirable output Ceramic pavements Euros (thousands) 8,814.1 11,470.0 Undesirable outputs Watery mud Tons 1,725.9 3,411.6 Used oil Kilograms 1,537.4 2,460.5 Inputs Clay, kaolin, felspar and limestones Tons 58,182.3 102,559.3 Labour Number of workers 87.0 101.5 Capital Kilowatts-hour (thousands) 3,408.4 4,006.8 18 Table 2.- Computed distance functions, regulatory impacts and type of firms. Bads as undesirable outputs Bads as strong disposable inputs Firm Unregulated scenario (SDB) Regulated scenario (WDB) R egulatory impact index SDIB Firm type 1 0 0 0 1,151 D 2 0 0 0 0 - 3 3,918 0 3,918 0 - 4 2,624 1,208 1,416 1,208 - 5 0 0 0 0 - 6 1,113 184 929 228 - 7 0 0 0 2,274 D 8 16,274 11,551 4,723 11,551 - 9 0 0 0 0 - 10 0 0 0 0 - 11 0 0 0 3,171 D 12 0 0 0 0 - 13 1,821 1,821 0 4,269 C 14 0 0 0 0 - 15 433 0 433 0 - 16 12,215 0 12,215 0 - 17 0 0 0 0 - 18 2,693 0 2,693 0 - 19 1,327 0 1,327 0 - 20 1,149 0 1,149 535 - 21 7,270 539 6,731 759 - 22 2,011 700 1,311 588 - 23 0 0 0 0 - 24 0 0 0 1,479 D 25 0 0 0 0 - 26 1,449 0 1,449 0 - 27 0 0 0 682 D 28 336 0 336 0 - 29 0 0 0 0 - 30 3,241 0 3,241 0 - 31 2,461 0 2,461 375 - 32 596 0 596 0 - 33 3,703 1,880 1,823 1,999 - 34 2,102 920 1,182 920 - 35 0 0 0 0 - 19 Figure 1.- Weak and strong disposability of bad outputs (I): the basic situation. D WDB A y g yb A B . A' A'' . . . D SDB A Figure 2.- Weak and strong disposability of bad outputs (II): the complex situation. . . . . C D'' D C'' C' . D SDIB D D SDIB C D SDB C D WDB C = D WDB A y g y b A B . A' A'' . . . D SDB A 20 Figure 3.- Weak and strong disposability of bad outputs (III): the long-run perspective. D WDB A y g y b A B . A' A'' . . . D SDB A . . . . C D'' D C'' C' .D SDIB D D SDIB C D SDB C D WDB C = E . Edicions / Issues: 95/1 Productividad del trabajo, eficiencia e hipótesis de convergencia en la industria textil-confección europea Jordi López Sintas 95/2 El tamaño de la empresa y la remuneración de los máximos directivos Pedro Ortín Ángel 95/3 Multiple-Sourcing and Specific Investments Miguel A. García-Cestona 96/1 La estructura interna de puestos y salarios en la jerarquía empresarial Pedro Ortín Ángel 96/2 Efficient Privatization Under Incomplete Contracts Miguel A. García-Cestona Vicente Salas-Fumás 96/3 Institutional Imprinting, Global Cultural Models, and Patterns of Organizational- Learning: Evidence from Firms in the Middle-Range Countries Mauro F. Guillén (The Wharton School, University of Pennsylvania) 96/4 The relationship between firm size and innovation activity: a double decision approach Ester Martínez-Ros (Universitat Autònoma de Barcelona) José M. Labeaga (UNED & Universitat Pompeu Fabra) 96/5 An Approach to Asset-Liability Risk Control Through Asset-Liability Securities Joan Montllor i Serrats María-Antonia Tarrazón Rodón 97/1 Protección de los administradores ante el mercado de capitales: evidencia empírica en España Rafael Crespí i Cladera 97/2 Determinants of Ownership Structure: A Panel Data Approach to the Spanish Case Rafael Crespí i Cladera 97/3 The Spanish Law of Suspension of Payments: An Economic Analysis From Empirical Evidence Esteban van Hemmen Almazor 98/1 Board Turnover and Firm Performance in Spanish Companies Carles Gispert i Pellicer 98/2 Libre competencia frente a regulación en la distribución de medicamentos: teoría y evidencia empírica para el caso español Eva Jansson 98/3 Firm’s Current Performance and Innovative Behavior Are the Main Determinants of Salaries in Small-Medium Enterprises Jordi López Sintas y Ester Martínez Ros