Measuring Efficiency of Macro Systems: An Application to Millennium Development Goal Attainment

Tandon, Ajay Working Paper Measuring Efficiency of Macro Systems: An Application to Millennium Development Goal Attainment ERD Working Paper Series, No. 66 Provided in Cooperation with: Asian Development Bank (ADB), Manila Suggested Citation: Tandon, Ajay (2005) : Measuring Efficiency of Macro Systems: An Application to Millennium Development Goal Attainment, ERD Working Paper Series, No. 66, Asian Development Bank (ADB), Manila, https://hdl.handle.net/11540/1894 This Version is available at: https://hdl.handle.net/10419/109268 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. http://creativecommons.org/licenses/by/3.0/igo ERD Working Paper No. 66 Measuring Efficiency of Macro Systems: An Application to Millennium Development Goal Attainment AJAY TANDON March 2005 Ajay Tandon is an Economist in the Development Indicators and Policy Research Division of the Economics and Research Department, Asian Development Bank. The author thanks Eric Suan for research assistance. Asian Development Bank P.O. Box 789 0980 Manila Philippines ©2005 by Asian Development Bank March 2005 ISSN 1655-5252 The views expressed in this paper are those of the author(s) and do not necessarily reflect the views or policies of the Asian Development Bank. FOREWORD The ERD Working Paper Series is a forum for ongoing and recently completed research and policy studies undertaken in the Asian Development Bank or on its behalf. The Series is a quick-disseminating, informal publication meant to stimulate discussion and elicit feedback. Papers published under this Series could subsequently be revised for publication as articles in professional journals or chapters in books. CONTENTS Abstract vii I. Theoretical Background 2 A. Outputs 2 B. Inputs 3 C. Exogenous Determinants 3 II. Empirics of Efficiency Measurement 5 A. Deterministic Frontiers 5 B. Stochastic Frontiers 7 C. Measuring Efficiency: A Simple Framework 8 III. Efficiency of the Health System in Indonesia: A Subnational Application 10 IV. Conclusions 13 References 14 ABSTRACT At least part of the effort toward MDG attainment in the social sector could come from improvements in efficiency of delivery mechanisms. Hence, it is important to know which countries—or which regions within countries—are able to attain higher MDG outcomes even after controlling for resource inputs. This information can be useful for policymakers and enable a second-stage analysis of why is it that some are doing better than others. This paper reviews the methodology for measuring efficiency in macro systems using the health and education sectors as examples. A simpler characterization of efficiency that is less dependent on econometric specifications is introduced. As an example, this method of measuring efficiency is applied to assess health system outcomes at the district (kabupatam) level in Indonesia. The UN Millennium Declaration, which was adopted by 189 countries in September 2000, has focused attention on the attainment of eight Millennium Development Goals (MDGs) by 2015. The goals, which are reflective of a fairly broad conceptualization of development, include targets for poverty reduction, gender equality, environment sustainability, educational attainment, as well as health improvements (UNDP 2003). This focus on MDGs has resulted in renewed attention toward measurement and monitoring issues, as well as on projections of indicators to 2015 to assess which countries are “on track.” In addition, there have been attempts to identify resource, institutional, and other constraints to MDG attainment (World Bank 2004). There is a general consensus in the development community that at least part of the effort toward MDG attainment (and this is especially true for the social sector) could come from improved efficiency of existing delivery mechanisms (Jayasuria and Wodon 2003). Whereas it is true that macroeconomic growth would facilitate improvements in human development, the positive spillover effects from economic growth to the social sector are not as big as they might be for income poverty reduction (World Bank 2004). Furthermore, there is empirical evidence that suggests that high levels of economic development are not necessarily a prerequisite for high levels of human development. One reason is that, given the labor-intensive nature of service provision, the supply of health and education costs relatively less in poorer countries (Dreze and Sen 1989). Hence, the same levels of health and education outcomes can be achieved at far lower resource outlays in low-income countries. Two oft-cited example are those of Sri Lanka and the state of Kerala in India. The implications are that resource constraints can, at least in part, be offset by good governance, effective institutions, political will, or other such factors. In order to identify efficiencies, the first step is to identify which countries as well as which regions within countries have been relatively successful in MDG attainment after controlling for resource inputs. A second step would be to then examine why is it that some countries are doing better than others in their resource-level group in achieving MDG outcomes. If a given country is found to be relatively efficient but has yet to attain a given MDG then this would imply that additional resource outlays are most likely going to be required for achieving further progress. If, on the other hand, a country is relatively inefficient then this suggests that both increases in efficiency at current resource levels as well as increases in resource outlays are potential pathways to MDG outcome increases. In addition, identification of inefficiencies is a first step toward understanding factors that contribute to inefficiencies: some of these may be policy-related, but others may be factors that are beyond the immediate control of governments (e.g., external shocks, civil strife, etc.). The problem of estimating MDG efficiency is similar to the classic problem of estimating technical efficiency in industrial and agricultural economics, whereby efficiency in converting inputs into outputs is inferred from how far the output of a given production unit is from the maximum output (the “frontier”). This paper summarizes the methodology as applied to MDG attainment for two macro systems, namely the health and education sectors. The paper is based in part on Tandon et al. (2003). The paper outlines a simpler way to characterize efficiency that is more transparent and 2MARCH 2005 MEASURING EFFICIENCY OF MACRO SYSTEMS: AN APPLICATION TO MILLENNIUM DEVELOPMENT GOAL ATTAINMENT AJAY TANDON less dependent on specific econometric assumptions. The paper concludes with a discussion of this approach in helping identify policy-dependent factors that can have an effect on improving the efficiency of MDG outcomes. These issues are especially relevant for human development in Asian DMCs as most projections show that, even though progress on income-related MDGs has been encouraging, the prognosis for achieving social-sector and other nonincome MDGs by 2015 is not positive for the region as a whole (ADB 2004). I. THEORETICAL BACKGROUND In the production function literature, technical efficiency is defined as output relative to the maximum output for given input levels (Kumbhakar and Lovell 2000). Usually, one way to assess efficiency is to estimate a frontier production function (the maximum observed output for all available input levels).1 Once the frontier has been identified, then distance from the frontier is a measure of efficiency [b/(a+b) in Figure 1]. Figure 1 shows one example with two countries having the same output. However, because country A is able to achieve the output at a lower level of inputs than country B, it is deemed to be more efficient. The first step in applying this framework to MDG attainment is to conceptualize the pertinent sectors as production units. In this paper, we consider applying the efficiency framework to health and education-related MDG attainment and this implies conceptualizing—at least metaphorically—the health sector and education sector as productionoriented macro systems. The next steps are to specify inputs, outputs, and other factors that can have an influence on the production process. A. Outputs As the concern is to assess the efficiency of MDG attainment, the relevant MDG indicators can be assumed to represent outputs of the respective sectors.2 So, for instance, for the education sector we take net primary enrollment ratio as an indicator for the following MDG education target: Ensuring that, by 2015, children everywhere, boys and girls alike, will be able to complete a full course of primary schooling. Similarly, we take under-five morality rate as an indicator for the following MDG health target: Reducing by two-thirds, between 1990 and 2015, the under-five mortality rate. 1This approach is the macro approach. A micro approach to measuring efficiency would identify the set of available interventions that yield the maximum possible outcomes. 2In several instances, there are multiple indicators of any given MDG target. This multiplicity can be taken into account by constructing an output index. For expository purposes, for now we focus only on one of the indicators each for the health and education MDG targets. 9ERD WORKING PAPER SERIES NO. 66 TABLE 2 EDUCATION AND HEALTH SECTOR OUTCOMES: HIGH VERSUS LOW EFFICIENCY COUNTRIES (ASIAN DMCS HIGHLIGHTED) INPUT EDUCATION SECTOR OUTCOMES HEALTH SECTOR OUTCOMES QUINTILE HIGH EFFICIENCY LOW EFFICIENCY HIGH EFFICIENCY LOW EFFICIENCY 1Bangladesh (BAN) Eritrea (ERI) Tajikistan (TAJ) Niger (NGR) Equatorial Guinea Burkina Faso (BUF) Azerbaijan (AZE) Afghanistan (AFG) (EQG) Niger (NGR) Comoros (COM) Sierra Leone (SIE) Cambodia (CAM) 2Korea (KOR) Ghana (GHA) Sri Lanka (SRI) Central African Jamaica (JAM) Tanzania (TNZ) Georgia (GEO) Republic (CAR) Dominican Republic Djibouti (DJI) Moldova (MOL) Liberia (LIB) (DOR) Angola (ANG) 3 Peru (PER) Namibia (NAM) Cuba (CUB) Zimbabwe (ZIM) Fiji (FIJ) Swaziland (SWA) Jamaica (JAM) Cambodia (CAM) Mexico (MEX) Kenya (KEN) Libya (LBY) Swaziland (SWA) 4 Argentina (ARG) Oman (OMA) Malaysia (MAL) Maldives (MLD) Ecuador (ECU) Serbia & Montenegro Belarus (BLR) Namibia (NAM) Tonga (TON) (YUG) Dominica (DOM) Botswana (BOT) Ukraine (UKR) 5 Barbados (BAR) Armenia (ARM) Singapore (SIN) Tuvalu (TUV) Seychelles (SEY) Azerbaijan (AZE) Czech Republic (CZR) South Africa (SOA) Malta (MLT) Saudi Arabia (SAU) Malta (MLT) Brazil (BRA) Health Outcomes by Input Quintiles Education Outcomes by Input Quintiles 1000 mlnn under-five mortality rate 1,000 Net primary enrollment ratio 900 800 700 100 80 60 40 20 1234512345 F IGURE 6 E DUCATION AND H EALTH S ECTORS : O UTCOMES BY I NPUT Q UINTILES F IGURE 6 E DUCATION AND H EALTH S ECTORS : O UTCOMES BY I NPUT Q UINTILES Input quintiles Input quintiles SECTION III EMPIRICS OF EFFICIENCY MEASUREMENT 10 MARCH 2005 MEASURING EFFICIENCY OF MACRO SYSTEMS: AN APPLICATION TO MILLENNIUM DEVELOPMENT GOAL ATTAINMENT AJAY TANDON III. EFFICIENCY OF THE HEALTH SYSTEM IN INDONESIA: A SUBNATIONAL APPLICATION Arguably, the greatest utility of doing a sectoral efficiency analysis is within countries and not across countries, the latter often being dismissed by some as being of relevance only for international organizations and donor countries (Haines and Cassels 2004). For policymakers, the most useful information content of a macro system efficiency analysis could come from being able to identify regions or districts within countries that are outperforming others despite resource constraints. Information on efficient subnational regions can be useful for many reasons. First, as a stock-taking exercise, it can help shed light on the extent to which variations in education or health outcomes exist within countries. Second, as mentioned earlier, once such regions or districts are identified, such an analysis can help highlight what factors might be responsible for differences in outcome attainment, and to what extent these are related to resource deficiencies. An oft-cited example is the state of India in Kerala that has stellar education and health outcomes despite having a fairly low income per capita. Good governance, political will, and lower levels of income inequality are often cited as reasons explaining Kerala’s efficiency with regard to outcome attainment in the social sector. 12-2 -1 03 Control of corruption index 12-2 -1 03 Control of corruption index 0 .2 .4 .6 .8 1 0 .2 .4 .6 Efficiency vs. Corruption Education Sector Efficiency vs. Corruption Health Sector Probability of being efficient Probability of being efficient 1 .8 F IGURE 7 E DUCATION AND H EALTH S ECTORS : E FFICIENCY VERSUS C ORRUPTION F IGURE 7 E DUCATION AND H EALTH S ECTORS : E FFICIENCY VERSUS C ORRUPTION 11ERD WORKING PAPER SERIES NO. 66 This section reports on the results obtained from an exercise done for measuring health system efficiency at the district (kabupatam) level in Indonesia.6 The potential relevance of such an analysis for policymakers is especially apparent given the recent implementation of decentralization in Indonesia. Instead of using a proxy for resource inputs, the Indonesia subnational application used a more general conceptualization of factors influencing outcomes: these factors were taken to be an index of districtlevel constraints to attainment of district-level health system outcomes. The approach follows a framework developed by Hanson et al. (2003). In the empirical application of their approach, they categorize constraints in terms of the level at which they operate and the degree to which the effect of the constraint can be overcome by additional resources (Ranson et al. 2003). Hanson et al. consider constraints at three broad levels: (i) community/household; (ii) health service delivery; and (iii) overall environment. Under community/household constraints they look at factors such as female education (which influences demand for health). For health service delivery, they consider indicators such as vaccination coverage (DPT3), number of nurses per 100,000 population, and health infrastructure (proportion of population living within one hour of health facility). For overall environment, they consider a corruption control index, a government effectiveness index, and GDP per capita. They create an overall index: an unweighted average of all three levels of constraint indicators measuring the degree to which it is likely to be difficult for countries to scale up access to health interventions. Although useful, their framework—by mixing both input indicators (such as nurses per capita) with outcome indicators (such as immunization coverage) and with exogenous determinants (such as governance)—potentially dilutes the recovery of critical information content regarding the efficiency of health systems. In the application to the district level in Indonesia, we follow a modification of the Hanson et al. (2003) approach. We create an outcome index (composed of a weighted average of complete immunization coverage, skilled birth attendance, iodized salt content, catastrophic expenditure, and life expectancy); and an input index (a weighted average of estimated permanent income, female education, nurses per 100,000, out-of-pocket health expenditure, and access to health facilities).7 The output index consists of health system outcomes including an index measuring the extent to which the population is protected from impoverishment (catastrophic expenditure). The framework adapts the one used by the World Health Organization in its country-level efficiency analysis (WHO 2000). Figure 8 plots the outcome index versus the input index for 300+ kabupatams in Indonesia for which data were available, along with a DEA frontier (some of the districts on or near the frontier are labeled). Figure 9 plots the same data using the simpler approach elaborated in the previous section. As the figures suggest, there are wide variations in district-level health system performance. Resource and environmental constraints are only part of the explanation: other factors such as districtlevel governance and epidemiological background may need to be studied for further determinants of efficiency analysis. This analysis is part of ongoing research. 6The results of this are forthcoming in a report being prepared by the World Health Organization and the Indonesian National Institute of Health Research and Development. 7The weights were derived using confirmatory factor analysis assuming one outcome factor and one input factor. However, the analysis is not sensitive to choice of weights and factors: similar results were obtained using an unweighted index. SECTION III EFFICIENCY OF THE HEALTH SYSTEM IN INDONESIA: A SUBNATIONAL APPLICATION 12 MARCH 2005 MEASURING EFFICIENCY OF MACRO SYSTEMS: AN APPLICATION TO MILLENNIUM DEVELOPMENT GOAL ATTAINMENT AJAY TANDON -4 -2 Output index 6 4 2 0 -4 -2 Input index Indonesia District-level Efficiency Analysis 4 2 0 Jayawi Jaya (Papua) Manokwari (Papua) Soppeng (Sulawesi Selatan) Kulon Progo (DI Yogyakarata) Blitar (Jawa Timur) Madiun (Jawa Timur) F IGURE 8 I NDONESIAN D ISTRICT - LEVEL H EALTH S YSTEM E FFICIENCY A NALYSIS --I F IGURE 8 I NDONESIAN D ISTRICT - LEVEL H EALTH S YSTEM E FFICIENCY A NALYSIS --I -4 -2 2 0 Distribution of output index 4 Deciles of Input Index 123456789 10 F IGURE 9 I NDONESIAN D ISTRICT - LEVEL H EALTH S YSTEM E FFICIENCY A NALYSIS --II F IGURE 9 I NDONESIAN D ISTRICT - LEVEL H EALTH S YSTEM E FFICIENCY A NALYSIS --II 13ERD WORKING PAPER SERIES NO. 66 IV. CONCLUSIONS Almost all countries in the world have signed on their commitment to attainment of MDG outcomes. At least part of the effort toward attaining MDGs in the social sector has to come from additional resource outlays to these sectors. However, improvements in efficiency at existing resource levels— or those combined with additional resource outlays—provide one more mechanism by which progress can be made. Frontier production analysis provides one simple framework within which to examine these efficiency-related issues at the macro system level such as at the level of the health sector or the education sector. This paper gives an overview of the application of frontier methods to attain two MDG indicators: net primary enrollment for education and under-five mortality rates for health. We compare the attainment of these MDG outcomes relative to the resource inputs currently available to these sectors. For illustrative purposes, we consider the teacher-pupil ratio as an indicator of the resource inputs to the education sector, and we take health expenditure per capita as a proxy for resources available to the health sector. Although the proxies may be crude, they are used more for expository purposes. We show how the health and education sectors can be viewed as production units and apply different ways of estimating the frontier to the data. We show how the choice of method can yield very different estimates of efficiency. In addition, the complexity of the econometric methods used may not be transparent and the assumptions required too heroic for the data at hand. A simpler approach is to simply derive efficiencies by looking at the distribution of the outcome within different bins of the input index. This method is transparent and easy to explain to nonspecialists (including policymakers) and does not require detailed assumptions regarding the distribution of efficiency. It also easily allows us to assess exogenous (environmental) factors that influence efficiency such as governance and control of corruption, yielding insights into what policy-related or other factors may be constraining MDG attainment in the social sectors. We demonstrate the application of the simpler method to assess kabupatam efficiency in attaining health system outcomes in Indonesia. Further research needs to be done in order to assess why is it that some regions are doing better than others. However, knowledge of knowing who are the best performers is critical to understanding policy options that may allow for improvements in outcomes without—or in addition to—additional resource outlays. SECTION IV CONCLUSIONS 14 MARCH 2005 MEASURING EFFICIENCY OF MACRO SYSTEMS: AN APPLICATION TO MILLENNIUM DEVELOPMENT GOAL ATTAINMENT AJAY TANDON REFERENCES ADB, 2004. Review of the Asian Development Bank’s Poverty Reduction Strategy. Asian Development Bank, Manila, Philippines. 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Pernia, October 2001 No. 2 India’s Economic Reforms What Has Been Accomplished? What Remains to Be Done? —Arvind Panagariya, November 2001 No. 3 Unequal Benefits of Growth in Viet Nam —Indu Bhushan, Erik Bloom, and Nguyen Minh Thang, January 2002 No. 4 Is Volatility Built into Today’s World Economy? —J. Malcolm Dowling and J.P. Verbiest, February 2002 No. 5 What Else Besides Growth Matters to Poverty Reduction? Philippines —Arsenio M. Balisacan and Ernesto M. Pernia, February 2002 No. 6 Achieving the Twin Objectives of Efficiency and Equity: Contracting Health Services in Cambodia —Indu Bhushan, Sheryl Keller, and Brad Schwartz, March 2002 No. 7 Causes of the 1997 Asian Financial Crisis: What Can an Early Warning System Model Tell Us? —Juzhong Zhuang and Malcolm Dowling, June 2002 No. 8 The Role of Preferential Trading Arrangements in Asia —Christopher Edmonds and Jean-Pierre Verbiest, July 2002 No. 9 The Doha Round: A Development Perspective —Jean-Pierre Verbiest, Jeffrey Liang, and Lea Sumulong, July 2002 No. 10 Is Economic Openness Good for Regional Development and Poverty Reduction? The Philippines —E. M. Pernia and Pilipinas Quising, October 2002 ERD TECHNICAL NOTE SERIES (TNS) (Published in-house; Available through ADB Office of External Relations; Free of Charge) No. 1 Contingency Calculations for Environmental Impacts with Unknown Monetary Values —David Dole, February 2002 No. 2 Integrating Risk into ADB’s Economic Analysis of Projects —Nigel Rayner, Anneli Lagman-Martin, and Keith Ward, June 2002 No. 3 Measuring Willingness to Pay for Electricity —Peter Choynowski, July 2002 No. 4 Economic Issues in the Design and Analysis of a Wastewater Treatment Project —David Dole, July 2002 No. 5 An Analysis and Case Study of the Role of Environmental Economics at the Asian Development Bank —David Dole and Piya Abeygunawardena, September 2002 No. 6 Economic Analysis of Health Projects: A Case Study in Cambodia —Erik Bloom and Peter Choynowski, May 2003 No. 11 Implications of a US Dollar Depreciation for Asian Developing Countries —Emma Fan, July 2002 No. 12 Dangers of Deflation —D. Brooks and Pilipinas Quising, December 2002 No. 13 Infrastructure and Poverty Reduction— What is the Connection? —Ifzal Ali and Ernesto Pernia, January 2003 No. 14 Infrastructure and Poverty Reduction— Making Markets Work for the Poor —Xianbin Yao, May 2003 No. 15 SARS: Economic Impacts and Implications —Emma Xiaoqin Fan, May 2003 No. 16 Emerging Tax Issues: Implications of Globalization and Technology —Kanokpan Lao Araya, May 2003 No. 17 Pro-Poor Growth: What is It and Why is It Important? —Ernesto M. Pernia, May 2003 No. 18 Public–Private Partnership for Competitiveness —Jesus Felipe, June 2003 No. 19 Reviving Asian Economic Growth Requires Further Reforms —Ifzal Ali, June 2003 No. 20 The Millennium Development Goals and Poverty: Are We Counting the World’s Poor Right? —M. G. Quibria, July 2003 No. 21 Trade and Poverty: What are the Connections? —Douglas H. Brooks, July 2003 No. 22 Adapting Education to the Global Economy —Olivier Dupriez, September 2003 No. 23 Avian Flu: An Economic Assessment for Selected Developing Countries in Asia —Jean-Pierre Verbiest and Charissa Castillo, March 2004 18 No. 25 Purchasing Power Parities and the International Comparison Program in a Globalized World —Bishnu Pant, March 2004 No. 26 A Note on Dual/Multiple Exchange Rates —Emma Xiaoqin Fan, May 2004 No. 27 Inclusive Growth for Sustainable Poverty Reduction in Developing Asia: The Enabling Role of Infrastructure Development —Ifzal Ali and Xianbin Yao, May 2004 No. 28 Higher Oil Prices: Asian Perspectives and Implications for 2004-2005 —Cyn-Young Park, June 2004 No. 29 Accelerating Agriculture and Rural Development for Inclusive Growth: Policy Implications for Developing Asia —Richard Bolt, July 2004 No. 30 Living with Higher Interest Rates: Is Asia Ready? —Cyn-Young Park, August 2004 No. 31 Reserve Accumulation, Sterilization, and Policy Dilemma —Akiko Terada-Hagiwara, October 2004 32 The Primacy of Reforms in the Emergence of People’s Republic of China and India —Ifzal Ali and Emma Xiaoqin Fan, November 2004 33 Population Health and Foreign Direct Investment: Does Poor Health Signal Poor Government Effectiveness? —Ajay Tandon, January 2005 34 Financing Infrastructure Development: Asian Developing Countries Need to Tap Bond Markets More Rigorously —Yun-Hwan Kim, February 2005 1. Improving Domestic Resource Mobilization Through Financial Development: Overview September 1985 2. Improving Domestic Resource Mobilization Through Financial Development: Bangladesh July 1986 3. Improving Domestic Resource Mobilization Through Financial Development: Sri Lanka April 1987 4. Improving Domestic Resource Mobilization Through Financial Development: India December 1987 5. Financing Public Sector Development Expenditure in Selected Countries: Overview January 1988 6. Study of Selected Industries: A Brief Report April 1988 7. Financing Public Sector Development Expenditure in Selected Countries: Bangladesh June 1988 8. Financing Public Sector Development Expenditure in Selected Countries: India June 1988 9. Financing Public Sector Development Expenditure in Selected Countries: Indonesia June 1988 10. Financing Public Sector Development Expenditure in Selected Countries: Nepal June 1988 11. Financing Public Sector Development Expenditure in Selected Countries: Pakistan June 1988 12. Financing Public Sector Development Expenditure in Selected Countries: Philippines June 1988 13. Financing Public Sector Development Expenditure in Selected Countries: Thailand June 1988 14. Towards Regional Cooperation in South Asia: ADB/EWC Symposium on Regional Cooperation in South Asia February 1988 15. Evaluating Rice Market Intervention Policies: Some Asian Examples April 1988 16. Improving Domestic Resource Mobilization Through Financial Development: Nepal November 1988 17. Foreign Trade Barriers and Export Growth September 1988 18. The Role of Small and Medium-Scale Industries in the Industrial Development of the Philippines April 1989 19. The Role of Small and Medium-Scale Manufacturing Industries in Industrial Development: The Experience of Selected Asian Countries January 1990 20. National Accounts of Vanuatu, 1983-1987 January 1990 21. National Accounts of Western Samoa, 1984-1986 February 1990 22. Human Resource Policy and Economic Development: Selected Country Studies July 1990 23. Export Finance: Some Asian Examples September 1990 24. National Accounts of the Cook Islands, 1982-1986 September 1990 25. Framework for the Economic and Financial Appraisal of Urban Development Sector Projects January 1994 26. Framework and Criteria for the Appraisal and Socioeconomic Justification of Education Projects January 1994 27. Investing in Asia 1997 (Co-published with OECD) 28. The Future of Asia in the World Economy 1998 (Copublished with OECD) 29. Financial Liberalisation in Asia: Analysis and Prospects 1999 (Co-published with OECD) 30. Sustainable Recovery in Asia: Mobilizing Resources for Development 2000 (Co-published with OECD) 31. Technology and Poverty Reduction in Asia and the Pacific 2001 (Co-published with OECD) 32. Asia and Europe 2002 (Co-published with OECD) 33. Economic Analysis: Retrospective 2003 34. Economic Analysis: Retrospective: 2003 Update 2004 35. Development Indicators Reference Manual: Concepts and Definitions 2004 SPECIAL STUDIES, COMPLIMENTARY (Available through ADB Office of External Relations)