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This article represents an attempt to bring together and survey the diverse techniques devised by individual scholars and institutions for the purpose of measuring comparative economic development. Any merits it therefore possesses must rest in its clarifications rather than in its inspirations. However, so many techniques exist, founded upon so many theoretical bases, that a concise overview would appear to be justified.

We examine the predictive validity of survey-measured left-right political ideology by testing whether this measure is able to explain observed choices regarding equality versus efficiency. We study this in a real-effort distribution experiment, in which decision-makers allocate money equally or efficiently. We distinguish between decision-makers that receive 'manna-from-heaven' and decision-makers that have earned the money to be distributed in a real effort task. We find that, conditional on entitlement concerns, self-reported right-wing ideology significantly predicts preferences for efficiency. Reported left-wing ideology does not have predictive value in explaining preferences for equality.

Empirical analysis of rural credit market failure has been of key scientific and political interest in recent years. The aim of this paper is to give an overview of various methods for measuring credit rationing of farms employed in the literature. Furthermore, based on a common analytical framework entailing a formal model of a credit rationed farm household, the methods are subjected to a comparative evaluation of their specific strengths or shortcomings. Six approaches are distinguished: measurement of loan transaction costs, analysis of qualitative information collected in interviews, analysis of quantitative information collected in interviews by using the credit limit concept, analysis of spill-over effects with regard to secondary credit sources, econometric household modelling, and the econometric analysis of dynamic investment decisions. The first approach defines credit rationing as the impossibility to take a loan due to prohibitively high, measurable transaction costs on loan markets, which is a price rationing mechanism. All other approaches at least implicitly define credit rationing as a persistent private excess demand in terms of a quantity restriction. The six approaches are more or less closely linked to the neo-classical efficiency concept. An explicit comparison with a first-best solution is impossible in the first three approaches, since they essentially rely on a subjective assessment of borrowers' access to credit, based on qualitative or quantitative indicators. The fifth and sixth approach allow a rigorous interpretation in the framework of neo-classical equilibrium theory. The fourth approach takes an intermediate position, since spill-over on segmented loan markets reveals a willingness to pay with regard to the supposedly less expensive but rationed primary source. Approaches are fairly data demanding in general, usually requiring specific data on loan transactions. Even so, most approaches are applicable to cross-sectional household data. Only dynamic modelling of investment decisions necessitates the availability of panel data, therefore restricting the applicability in low-income and transition countries. With the exception of the first, all methods surveyed might plausibly be used to empirically detect credit rationing. ; Die empirische Analyse von Marktversagen auf ländlichen Kreditmärkten ist in den vergangenen Jahren von hohem wissenschaftlichen und politischen Interesse gewesen. Ziel dieses Beitrags ist es, einen Überblick über verschiedene in der Literatur angewandte Methoden zur Messung von Kreditrationierung zu geben. Auf der Grundlage eines gemeinsamen analytischen Bezugsrahmens werden die Methoden darüber hinaus einer vergleichenden Bewertung im Hinblick auf ihre Stärken und Schwächen unterzogen. Es werden sechs Vorgehensweisen unterschieden: die Messung von Kredittransaktionskosten, die Analyse von in Interviews gewonnenen qualitativen Informationen, die Analyse von in Interviews erhobenen quantitativen Information unter Rückgriff auf das Konzept des credit limits, die Analyse von Überschusseffekten im Hinblick auf sekundäre Kreditquellen, ökonometrische Haushaltsmodellierung sowie die ökonometrische Analyse von dynamischen Investitionsentscheidungen. Die erste Vorgehensweise versteht unter Kreditrationierung die Unmöglichkeit, einen Kredit zu erhalten aufgrund von prohibitiv hohen, messbaren Transaktionskosten auf Kreditmärkten. Es handelt sich hierbei um einen Mechanismus der Preisrationierung. Alle anderen Vorgehensweisen definieren Kreditrationierung zumindest implizit als andauernde Überschussnachfrage, folglich eine Mengenbeschränkung. Die sechs Vorgehensweisen sind mehr oder weniger eng mit dem neoklassischen Effizienzkonzept verbunden. Ein expliziter Vergleich mit einer first-best Lösung ist in den ersten drei Vorgehensweisen jedoch unmöglich, da sie auf einer subjektiven Einschätzung des Kreditzugangs beruhen. Die fünfte und sechste Methode erlauben hingegen eine strikte Interpretation im Rahmen der neoklassischen Gleichgewichtstheorie. Die vierte Vorgehensweise nimmt eine Zwischenstellung ein, da Überschusseffekte auf segmentierten Kreditmärkten eine Zahlungsbereitschaft im Hinblick auf die primäre, rationierte Kreditquelle implizieren. Die Methoden erfordern die Verfügbarkeit von geeigneten Datensätzen über Kredittransaktionen. Die meisten Ansätze können allerdings auf Querschnittsdaten angewendet werden. Lediglich die dynamische Modellierung von Investitionsentscheidungen erfordert Paneldaten und beschränkt daher die Einsatzmöglichkeit in Entwicklungs- und Transformationsländern. Mit Ausnahme des ersten können alle Ansätze auf plausible Weise für die empirische Untersuchung von Kreditrationierung eingesetzt werden.

Empirical analysis of rural credit market failure has been of key scientific and political interest in recent years. The aim of this paper is to give an overview of various methods for measuring credit rationing of farms employed in the literature. Furthermore, based on a common analytical framework entailing a formal model of a credit rationed farm household, the methods are subjected to a comparativeevaluation of their specific strengths or shortcomings. Six approaches are distinguished: measurement of loan transaction costs, analysis of qualitative information collected in interviews, analysis of quantitative information collected in interviews by using the credit limit concept, analysis of spill-over effects with regard to secondary credit sources, econometric household modelling, and the econometric analysis of dynamic investment decisions. The first approach defines credit rationing as the impossibility to take a loan due to prohibitively high, measurable transaction costs on loan markets, which is a price rationing mechanism. All other approaches at least implicitly define credit rationing as a persistent private excess demand in terms of a quantity restriction. The six approaches are more or less closely linked to the neo-classical efficiency concept. An explicit comparison with a first-best solution is impossible in the first three approaches, since they essentially rely on a subjective assessment of borrowers' access to credit, based on qualitative or quantitative indicators. The fifth and sixth approach allow a rigorous interpretation in the framework of neo-classical equilibrium theory. The fourth approach takes an intermediate position, since spill-over on segmented loan markets reveals a willingness to pay with regard to the supposedly less expensive but rationed primary source. Approaches are fairly data demanding in general, usually requiring specific data on loan transactions. Even so, most approaches are applicable to cross-sectional household data. Only dynamic modelling of investment decisions necessitates the availability of panel data, therefore restricting the applicability in low-income and transition countries. With the exception of the first, all methods surveyed might plausibly be used to empirically detect credit rationing.

Suggests that unclear terms are likely to produce biased estimates. The results indicate that evaluation of survey questions to identify key terms that are not consistently understood and defining unclear terms are ways to reduce systematic error in survey measurement. (Abstract amended)