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This paper examines the assertion that returns to schooling increase as an economy transitions to a market environment. This claim has been difficult to assess as existing empirical evidence covers only a few countries over short time periods. A number of studies find that returns to education increased from the "pre-transition" period to the "early transition" period. It is not clear what has happened to the skills premium through the late 1990s, or the period thereafter. The authors use data that are comparable across countries and over time to estimate returns to schooling in eight transition economies (Bulgaria, Czech Republic, Hungary, Latvia, Poland, Russia, Slovak Republic, and Slovenia) from the early transition period up to 2002. In the case of Hungary, they capture the transition process more fully, beginning in the late 1980s. Compared to the existing literature, they implement a more systematic analysis and perform more comprehensive robustness checks on the estimated returns, although at best they offer only an incomplete solution to the problem of endogeneity. The authors find that the evidence of a rising trend in returns to schooling over the transition period is generally weak, except in Hungary and Russia where there have been sustained and substantial increases in returns to schooling. On average, the estimated returns in the sample are comparable to advanced economy averages. There are, however, significant differences in returns across countries and these differentials have remained roughly constant over the past 15 years. They speculate on the likely institutional and structural factors underpinning these results, including incomplete transition and significant heterogeneity and offsetting developments in returns to schooling within countries.

Bank Policy --- Checks --- Debt Markets --- Education --- Education for All --- Education Reform and Management --- Effective Schools and Teachers --- Finance and Financial Sector Development --- Government expenditures --- Human capital --- Labor market --- Macroeconomic controls --- Market economy --- Market environment --- Primary Education --- Returns --- Transition economies

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March 2000 - How to make firm-level surveys more consistent, yielding data more relevant to policy analysis. The World Bank has increasingly focused on firm-level surveys to build the data foundation needed for accurate policy analysis in developing and transition economies. Recanatini, Wallsten, and Xu take stock of some recent Bank surveys and discuss how to improve their results. Lessons on data issues and hypothesis testing: Use panel data, if possible; Have enough information about productivity to estimate a production function; Avoid the paradigm of list the severity of the obstacle/problem on a scale of 1 to 5. Instead, ask for data on specific dimensions of the problem that will shed light on alternative hypotheses and policy recommendations; Pick particular disaggregated industries and sample those industries in each survey; Identify the most important policy interventions of interest and consider how you will empirically identify specific changes by picking instruments useful for doing so. Lessons on questionnaire design: Incorporate only one idea or dimension in each question. Do not ask, in one question, about the quality, integrity, and efficiency of services, for example; Consider the costs and benefits of numeric scales compared with adjectival scales. Scales in which each point is labeled may be more precise than numeric scales in which only the endpoints are labeled. But responses are very sensitive to the exact adjective chosen and it may be impossible to translate adjectives precisely across languages, making it impossible to compare responses across countries; Recognize that the share of respondents expressing opinions will be biased upward if the survey does not include a middle (indifferent or don't know) category and downward if it does include the middle category; When asking degree-of-concern and how-great-an-obstacle questions, consider first asking a filter question (such as Do you believe this regulation is an obstacle or not?). If the answer is yes, then ask how severe the obstacle is; Be aware of the effects of context. The act of asking questions can affect the answers given on subsequent, related questions; Think carefully about how to ask sensitive questions. Consider using a self-administered module for sensitive questions. Alternatively, a randomized response mechanism may be a useful, truth-revealing mechanism. This paper - a product of Regulation and Competition Policy, Development Research Group - is part of a larger effort in the group to develop consistent cross-country firm level surveys. The authors may be contacted at frecanatini@worldbank.org, wallsten@leland.stanford.edu, or lxu1@worldbank.org.

Accounting --- Bankruptcy --- Banks and Banking Reform --- Capital Stock --- Corporate Governance --- Debt Markets --- Developing Countries --- E-Business --- Economic Theory and Research --- Emerging Markets --- Entry Barriers --- Finance and Financial Sector Development --- Financial Literacy --- Firm Performance --- Future --- Goods --- Human Capital --- ICT Policy and Strategies --- Information and Communication Technologies --- Investment --- Labor Policies --- Macroeconomics and Economic Growth --- Market --- Market Environment --- Market Structure --- Micro Data --- Microfinance --- Political Economy --- Private Sector Development --- Share --- Social Protections and Labor --- Stock --- Transaction --- Transition Countries --- Transition Economies