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After a decade of research on the relationship between institutions and growth, scholars in this field seem to be divided. Economic institutions perform well in growth regressions and a body of literature argues that this supports the key importance of institutions for development. Other authors maintain that the type of constraints that the recent theoretical literature describes are the more stable political institutions, and these have been found to play no role in empirical growth analyses. In this paper we re-examine the role that institutions play in the growth process using cross-section and panel data for both developed and developing economies over the period 1970-2000. Our results indicate that the data is best described by an econometric model with two growth regimes. Political institutions are the key determinant of which growth regime an economy belongs to, while economic institutions have a direct impact on growth rates within each regime. These findings support the hierarchy of institutions hypothesis, whereby political institutions set the stage in which economic institutions and policies operate.

The standard theory of inequality measurement assumes that the equalisand is a cardinal quantity, with known cardinalization. However, one often needs to make inequality comparisons where either the cardinalization is unknown or the underlying data are categorical. We propose an alternative approach to inequality analysis that is rigorous, has a natural interpretation, and embeds both the ordinal data problem and the well‐known cardinal data problem. We show how the approach can be applied to the inequality of happiness and of health status.

Surveys are sometimes viewed with suspicion when used to provide economic values, since they are sensitive to framing effects. However, the extent to which those effects may vary between individuals has received little attention. Are some individuals less sensitive to framing effects than others? We use the theory of social representation to assign to each individual a new variable to serve as a proxy for the individual's sensitivity to framing effects. This allows to gather new and relevant information to limit the impact of framing effects. We examine two framing effects, starting-point bias and willingness-to-pay and willingness-to-accept divergence.

Sélection de modèles dans les questions d'évaluations successives Dans cet article, nous proposons un cadre unifié permettant de tester de nombreux modèles à choix discrets existants en évaluation contingente. Une application montre que le modèle développé dans Flachaire et Hollard [2007] est le plus performant. Nos résultats empiriques confirment le fait que les individus ont tendance à accepter les offres proposées lorsqu'ils sont incertains.

After a decade of research on the relationship between institutions and growth, scholars in this field seem to be divided. Economic institutions perform well in growth regressions and a body of literature argues that this supports the key importance of institutions for development. Other authors maintain that the type of constraints that the recent theoretical literature describes are the more stable political institutions, and these have been found to play no role in empirical growth analyses. In this paper we re-examine the role that institutions play in the growth process using cross-section and panel data for both developed and developing economies over the period 1970-2000. Our results indicate that the data is best described by an econometric model with two growth regimes. Political institutions are the key determinant of which growth regime an economy belongs to, while economic institutions have a direct impact on growth rates within each regime. These findings support the hierarchy of institutions hypothesis, whereby political institutions set the stage in which economic institutions and policies operate.

After a decade of research on the relationship between institutions and growth, scholars in this field seem to be divided. Economic institutions perform well in growth regressions and a body of literature argues that this supports the key importance of institutions for development. Other authors maintain that the type of constraints that the recent theoretical literature describes are the more stable political institutions, and these have been found to play no role in empirical growth analyses. In this paper we re-examine the role that institutions play in the growth process using cross-section and panel data for both developed and developing economies over the period 1970-2000. Our results indicate that the data is best described by an econometric model with two growth regimes. Political institutions are the key determinant of which growth regime an economy belongs to, while economic institutions have a direct impact on growth rates within each regime. These findings support the hierarchy of institutions hypothesis, whereby political institutions set the stage in which economic institutions and policies operate.

After a decade of research on the relationship between institutions and growth, scholars in this field seem to be divided. Economic institutions perform well in growth regressions and a body of literature argues that this supports the key importance of institutions for development. Other authors maintain that the type of constraints that the recent theoretical literature describes are the more stable political institutions, and these have been found to play no role in empirical growth analyses. In this paper we re-examine the role that institutions play in the growth process using cross-section and panel data for both developed and developing economies over the period 1970-2000. Our results indicate that the data is best described by an econometric model with two growth regimes. Political institutions are the key determinant of which growth regime an economy belongs to, while economic institutions have a direct impact on growth rates within each regime. These findings support the hierarchy of institutions hypothesis, whereby political institutions set the stage in which economic institutions and policies operate.

AbstractWe propose Fieller-type methods for inference on generalized entropy inequality indices in the context of the two-sample problem which covers testing the statistical significance of the difference in indices, and the construction of a confidence set for this difference. In addition to irregularities arising from thick distributional tails, standard inference procedures are prone to identification problems because of the ratio transformation that defines the considered indices. Simulation results show that our proposed method outperforms existing counterparts including simulation-based permutation methods and results are robust to different assumptions about the shape of the null distributions. Improvements are most notable for indices that put more weight on the right tail of the distribution and for sample sizes that match macroeconomic type inequality analysis. While irregularities arising from the right tail have long been documented, we find that left tail irregularities are equally important in explaining the failure of standard inference methods. We apply our proposed method to analyze income per-capita inequality across U.S. states and non-OECD countries. Empirical results illustrate how Fieller-based confidence sets can: (i) differ consequentially from available ones leading to conflicts in test decisions, and (ii) reveal prohibitive estimation uncertainty in the form of unbounded outcomes which serve as proper warning against flawed interpretations of statistical tests.