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International audience; OECD countries have experienced a large increase in top wage inequality. Atkinson (2008) attributes this phenomena to the superstar theory leading to a Pareto tail in the wage distribution with a low Pareto coefficient. Do we observe a similar phenomena for academic wages? We examine wage formation in a public US university using for each academic rank a hybrid mixture formed by a lognormal distribution for regular wages and a Pareto distribution for top wages, using a Bayesian approach. The presence of superstars wages would imply a higher dispersion in the Pareto tail than in the lognormal body. We concluded that academic wages are formed in a different way than other top wages. There is an effort to propose competitive wages to some young Assistant Professors. But when climbing up the wage ladder, we found a phenomenon of wage compression which is just the contrary of a superstar phenomenon.

International audience; The growth incidence curve of Ravallion and Chen (2003) is based on the quantile function. Its distribution-free estimator behaves erratically with usual sample sizes leading to problems in the tails. The authors propose a series of parametric models in a Bayesian framework. A first solution consists in modeling the underlying income distribution using simple densities for which the quantile function has a closed analytical form. This solution is extended by considering a mixture model for the underlying income distribution. However, in this case, the quantile function is semi-explicit and has to be evaluated numerically. The last solution consists in adjusting directly a functional form for the Lorenz curve and deriving its first-order derivative to find the corresponding quantile function. The authors compare these models by Monte Carlo simulations and using UK data from the Family Expenditure Survey. The authors devote a particular attention to the analysis of subgroups.

This survey paper reviews the recent Bayesian literature on poverty measurement. After introducing Bayesian statistics, we show how Bayesian model criticism could help to revise the international poverty line. Using mixtures of lognormals to model income, we derive the posterior distribution for the FGT, Watts and Sen poverty indices, then for TIP curves (with an illustration on child poverty in Germany) and finally for Growth Incidence Curves. The relation of restricted stochastic dominance with TIP and GIC dominance is detailed with an example on UK data. Using panel data, we show how to decompose poverty into total, chronic and transient poverty, comparing child and adult poverty in East Germany when redistribution is introduced. When a panel is not available, a Gibbs sampler is used to build a pseudo panel. We illustrate poverty dynamics by examining the consequences of the Wall on poverty entry and poverty persistence in occupied West Bank.

International audience; Two main nonpharmaceutical policy strategies have been used in Europe in response to the COVID-19 epidemic: one aimed at natural herd immunity and the other at avoiding saturation of hospital capacity by crushing the curve. The two strategies lead to different results in terms of the number of lives saved on the one hand and production loss on the other hand. Using a susceptible–infected–recovered–dead model, we investigate and compare these two strategies. As the results are sensitive to the initial reproduction number, we estimate the latter for 10 European countries for each wave from January 2020 till March 2021 using a double sigmoid statistical model and the Oxford COVID-19 Government Response Tracker data set. Our results show that Denmark, which opted for crushing the curve, managed to minimize both economic and human losses. Natural herd immunity, sought by Sweden and the Netherlands does not appear to have been a particularly effective strategy, especially for Sweden, both in economic terms and in terms of lives saved. The results are more mixed for other countries, but with no evident trade-off between deaths and production losses.

International audience; This study investigates the differences between zombie firms and non-zombie firms in corporate social responsibility activities such as reporting, disclosure and fulfillment. Using Chinese listing company data collected from 2009 to 2016, we apply a three stage model with a double Heckman correction to deal with potential self-selection/endogeneity bias and to measure the differences consistently. We found that zombie firms are less willing to release standalone corporate social responsibility reports than non-zombie firms. Among companies that release standalone corporate social responsibility reports, the corporate social responsibility disclosure of zombie firms is at least not worse than non-zombie firms, but the corporate social responsibility fulfillment is significantly lower. We conclude from this gap between disclosure and fulfillment to the hypocritical behavior of zombie firms, due to the absence of control in corporate social responsibility. We suggest that government should enhance supervision over zombie firms’ corporate social responsibility activities and subsidies towards them in order to lower their economic damage. Supplementary analyses provide some clues concerning the heterogeneity of inconsistence in term of external support characteristics, ownership and censorship which require further studies.

We propose a new methodology to revise the international poverty line (IPL) after Ravallion et al. (2009) using the same database, but augmented with new variables to take into account social inclusion in the definition of poverty along the lines of Atkinson and Bourguignon (2001). We provide an estimation of the world income distribution and of the corresponding number of poor people in the developing world. Our revised IPL is based on an augmented two-regime model estimated using a Bayesian approach, which allows us to take into account uncertainty when defining the reference group of countries where the IPL applies. The influence of weighting by population is discussed, as well as the IPL revision proposed in Deaton (2010). We also discuss the impact of using the new 2011 PPP and the recent IPL revision made by the World Bank.

International audience; In 2002, the Israeli government decided to build a wall inside the occupied West Bank. The wall had a marked effect on the access to land and water resources as well as to the Israeli labour market. It is difficult to include the effect of the wall in an econometric model explaining poverty dynamics as the wall was built in the richer region of the West Bank. So a diff-in-diff strategy is needed. Using a Bayesian approach, we treat our two-period repeated cross-section data set as an incomplete data problem, explaining the income-to-needs ratio as a function of time invariant exogenous variables. This allows us to provide inference results on poverty dynamics. We then build a conditional regression model including a wall variable and state dependence to see how the wall modified the initial results on poverty dynamics. We find that the wall has increased the probability of poverty persistence by 58 percentage points and the probability of poverty entry by 18 percentage points.

Summary We find that the empirical results reported in Chang (Journal of Applied Econometrics 2011; 26(5): 854–871) are contingent on the specification of the model. The use of Heckman's initial conditions combined with observed and not latent lagged dependent variables leads to a counter-intuitive estimation of the true state dependence. The use of Wooldridge's initial conditions together with the observed lagged dependent variable and a proper modelling of censoring provides a much more natural estimate of the true state dependence parameters together with a clearer interpretation of the decision to participate in the labour market in the two-tiered model. Copyright © 2015 John Wiley & Sons, Ltd.

AD; International audience; The log-normal distribution is convenient for modelling the income distribution, and it offers an analytical expression for most inequality indices that depends only on the shape parameter of the associated Lorenz curve. A decomposable inequality index can be implemented in the framework of a finite mixture of log-normal distributions so that overall inequality can be decomposed into within-subgroup and between-subgroup components. Using a Bayesian approach and a Gibbs sampler, a Rao-Blackwellization can improve inference results on decomposable income inequality indices. The very nature of the economic question can provide prior information so as to distinguish between the income groups and construct an asymmetric prior density which can reduce label switching. Data from the \UK\ Family Expenditure Survey (FES) (1979 to 1996) are used in an extended empirical application.

We propose a new approach for modeling nonlinear multivariate interest rate processes based on time-varying copulas and reducible stochastic differential equations (SDEs). In the modeling of the marginal processes, we consider a class of nonlinear SDEs that are reducible to Ornstein--Uhlenbeck (OU) process or Cox, Ingersoll, and Ross (1985) (CIR) process. The reducibility is achieved via a nonlinear transformation function. The main advantage of this approach is that these SDEs can account for nonlinear features, observed in short-term interest rate series, while at the same time leading to exact discretization and closed-form likelihood functions. Although a rich set of specifications may be entertained, our exposition focuses on a couple of nonlinear constant elasticity volatility (CEV) processes, denoted as OU-CEV and CIR-CEV, respectively. These two processes encompass a number of existing models that have closed-form likelihood functions. The transition density, the conditional distribution function, and the steady-state density function are derived in closed form as well as the conditional and unconditional moments for both processes. In order to obtain a more flexible functional form over time, we allow the transformation function to be time varying. Results from our study of U.S. and UK short-term interest rates suggest that the new models outperform existing parametric models with closed-form likelihood functions. We also find the time-varying effects in the transformation functions statistically significant. To examine the joint behavior of interest rate series, we propose flexible nonlinear multivariate models by joining univariate nonlinear processes via appropriate copulas. We study the conditional dependence structure of the two rates using Patton (2006a) time-varying symmetrized Joe--Clayton copula. We find evidence of asymmetric dependence between the two rates, and that the level of dependence is positively related to the level of the two rates. (JEL: C13, C32, G12) Copyright The Author 2010. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oxfordjournals.org, Oxford University Press.

A minimum disparity estimator minimizes a @f-divergence between the marginal density of a parametric model and its non-parametric estimate. This principle is applied to the estimation of stochastic differential equation models, choosing the Hellinger distance as particular @f-divergence. Under an hypothesis of stationarity, the parametric marginal density is provided by solving the Kolmogorov forward equation. A particular emphasis is put on the non-parametric estimation of the sample marginal density which has to take into account sample dependence and kurtosis. A new window size determination is provided. The classical estimator is presented alternatively as a distance minimizer and as a pseudo-likelihood maximizer. The latter presentation opens the way to Bayesian inference. The method is applied to continuous time models of the interest rate. In particular, various models are tested using alternatively tests and their results are discussed.

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Cet article a pour objet l’investigation des modèles empiriques de taux d’intérêt de court terme sur données américaines. Il utilise une combinaison de méthodes classiques non paramétriques et de méthodes bayésiennes paramétriques. La forme des fonctions de dérive et de volatilité du modèle discrétisé est tout d’abord examinée au moyen d’une analyse non paramétrique préliminaire. Le texte développe ensuite une méthode bayésienne de choix de modèles qui est basée sur la capacité d’un modèle à minimiser la distance de Hellinger entre la densité prédictive a posteriori du modèle discrétisé et la densité de l’échantillon observé. Une discrétisation du modèle en temps continu est estimée en utilisant différentes variantes paramétriques allant du modèle à variance constante jusqu’à différents types de modèles de switching suggérés par l’analyse non paramétrique préliminaire., This paper investigates empirical models of the US short term interest rate. It make use of a combination of classical non-parametric methods and of parametric bayesian methods. In a first step, it investigates the shape of drift and volatility functions using non parametric tools. The paper then develops a bayesian approach to model selection based on the minimisation of the Hellinger distance between the posterior predictive density of a discretised model and a non-parametric estimation of the data density. A discretisation of various parametric formulations are then estimated, ranging between constant elasticity of variance to switching regimes.

The econometrics of inequality measurement is adapted in order to investigate the publishing habits of the economists of seven European countries: Belgium, France, Germany, Italy, Netherlands, Spain and UK. California is added for comparison. Data come from the CD-ROM of the Journal of Economic Literature. A Bayesian model selection procedure helps to select a Weibull distribution as an admissible reduction of the generalised Beta-II. Analytical upper partial moment curves and modified generalised Lorenz curves are derived for the Weibull model and serve to detect a group of three dominant european countries: The Netherlands, the UK and Belgium.

This paper shows how one can compute option prices from a Bayesian inference viewpoint, using a GARCH model for the dynamics of the volatility of the underlying asset. The proposed evaluation of an option is the predictive expectation of its payoff function. The predictive distribution of this function provides a natural metric, provided it is neutralised with respect to risk, for gauging the predictive option price or other option evaluations. The proposed method is compared to the Black and Scholes evaluation, in which a marginal mean volatility is plugged, but which does not provide a natural metric. The methods are illustrated using symmetric, asymmetric and smooth transition GARCH models with data on a stock index in Brussels. D 2002 Elsevier Science B.V. All rights reserved.

Summary This paper explains how the Gibbs sampler can be used to perform Bayesian inference on GARCH models. Although the Gibbs sampler is usually based on the analytical knowledge of the full conditional posterior densities, such knowledge is not available in regression models with GARCH errors. We show that the Gibbs sampler can be combined with a unidimensional deterministic integration rule applied to each coordinate of the posterior density. The full conditional densities are evaluated and inverted numerically to obtain random draws of the joint posterior. The method is shown to be feasible and competitive compared with importance sampling and the Metropolis‐Hastings algorithm. It is applied to estimate an asymmetric Student‐GARCH model for the return on a stock exchange index, and to compute predictive option prices on the index. We prove, moreover, that a flat prior on the degrees of freedom parameter leads to an improper posterior density.

We develop a reliable Bayesian inference for the RIF-regression model of Firpo, Fortin and Lemieux (Econometrica, 2009) in which we first estimate the log wage distribution by a mixture of normal densities. This approach is pursued so as to provide better estimates in the upper tail of the wage distribution as well as valid confidence intervals for the Oaxaca-Blinder decomposition. We apply our method to a Mincer equation for analysing the recent changes in the U.S. wage structure and in earnings inequality. Our analysis uses data from the CPS Outgoing Rotation Group (ORG) from 1992 to 2009. We find first that the largest part (around 77% on average) of the recent changes in the U.S. wage inequality is explained by the wage structure effect and second that the earnings inequality is rising more at the top end of the wage distribution, even in the most recent years. The decline in the unionisation rate has a small impact on total wage inequality while differences in returns to education and gender discrimination are the dominant factors accounting for these recent changes.

OS; International audience; We provide a Bayesian inference for a mixture of two Pareto distributions which is then used to approximate the upper tail of a wage distribution. The model is applied to the data from the CPS Outgoing Rotation Group to analyze the recent structure of top wages in U.S. from 1992 through 2009. We found enormous earnings inequality between the very highest wage earners (“the superstars”), and the other high wage earners. These findings are largely in accordance with the alternative explanations combining the model of super-stars and the model of tournaments in hierarchical organization structure. The approach can be used to analyze the recent pay gaps among top executives in large firms so as to exhibit the “superstar” effect.

This paper examines the determinants of equilibrium wage and unemployment rates in Belgium within the framework of a quantity rationing, right -to-manage model with decentralised wage-setting. Empirical results are obtained by first using the Johansen maximum-likelihood procedure for the analysis of cointegration among the variables of interest. The information from this stage is then used to estimate a three equation econometric model explaining the wage shares, the unemployment rate and the capital gap. The slowdown in world trade is depicted as the most important factor explaining the rise in unemployment in Belgium, with dampening effects due to wage control policies imposed in the eighties. Because we obtain only two cointegrating relations, for three endogenous variables, our results are compatible with the hypothesis of path dependency and multiple equilibria.

Differencing at order 1 removes the stochastic trend, and differencing at seasonal order s removes the seasonal peaks. We propose a joint unit root test at order 1 and at order s, and tabulation for this test.

Classical tests for unit roots have been criticized for their unusual asymptotic theory leading to disconnected confidence intervals and their lack of power in small samples. Such critiques were initiated by Sims (1988), who promoted a Bayesian approach to the question. Various papers then appeared, which took up this idea. The Bayesian approach is however not exempt from criticism, as shown by Phillips (1991), who emphasizes the role of the prior as a bias toward stationarity. In this paper, I emphasize the role of the model and of the initial conditions. I show that with a structural model and an adequate treatment of the first observation, a Bayesian unit root test based on the computation of Pr( p ⩾ 1 y ) can produce results which are more or less in accordance with classical results. The extended Nelson-Plosser data set serves as an illustration.

SummaryThis paper considers a special non-linear time series problem, that of testing for co-integration in a Bayesian framework when there is a break in the co-integrating relationship. It is shown that a partial linearization of the likelihood function solves many puzzling questions, in particular identification and common factor restrictions which are originally imbedded in the model. A generalization of the Jeffreys’ prior is derived for the dynamic parameter which monitors co-integration. The procedure is applied to a one time much debated question in France which concerns the wage regulation policy implemented at the beginning of the eighties.

The theory of human capital is one way to explain individual decisions to produce scientific research. However, this theory, even if it reckons the importance of time in science, is too short for explaining the existing diversity of scientific output. The present paper introduces the social capital of Bourdieu (1980), Coleman (1988) and Putnam (1995) as a necessary complement to explain the creation of scientific human capital. This paper connects these two concepts by means of a hierarchical econometric model which makes the distinction between the individual level (human capital) and the cluster level of departments (social capital). The paper shows how a collection of variables can be built from a bibliographic data base indicating both individual behaviour including mobility and collective characteristics of the department housing individual researchers. The two level hierarchical model is estimated on fourteen European countries using bibliometric data in the fields of economics.

In this introductory chapter, we give a subjective account of the content of Kolm’s book Macrojustice (2005) that gave rise to the idea of organising in 2006 a round table where this book was discussed by different authors coming from a large variety of horizons: philosophers, economists, econometricians. We leave Serge-Christophe Kolm the task of presenting his theory in the first part of this book. Macrojustice is concerned about social justice proposing a comprehensive redistributive scheme. Of course, any distributive proposal always raises questions at the ethical, theoretical and practical levels. These questions are at the core of the discussions that are presented in this book, which is designed as a forum for multidisciplinary exchange.

ACL-3; International audience; The theory of human capital is one way to explain individual decisions to produce scientific research. However, this theory, even if it reckons the importance of time in science, is too short for explaining the existing diversity of scientific output. The present paper introduces the social capital of Bourdieu (1980), Coleman (1988) and Putnam (1995) as a necessary complement to explain the creation of scientific human capital. This paper connects these two concepts by means of a hierarchical econometric model which makes the distinction between the individual level (human capital) and the cluster level of departments (social capital). The paper shows how a collection of variables can be built from a bibliographic data base indicating both individual behaviour including mobility and collective characteristics of the department housing individual researchers. The two level hierarchical model is estimated on fourteen European countries using bibliometric data in the fields of economics.

In this paper we model the income distribution using a Bayesian approach and a mixture of lognormal densities. The size of the mixture is determined by Chib (1995)'s method. Using the Federal Expenditure Survey data for the United Kingdom, we detect three groups corresponding to the three classes (poor, middle class and rich). The marked growth in UK income inequality during the late 1970s is increasingly attracting attention. The increasing gap between the poorest and the richest was accompanied by changes in the clustering of incomes in between. Using the decomposable Generalised Entropy (GE) inequality indices, we carry out a within-between group analysis of income inequality in the three identified groups in UK during 1979 to 1996 and show the evolution of the importance of each group. Whereas during the late 1970s the concentration of people around middle income levels began to break up and polarise towards high and low incomes as shown by Jenkins (1996), our Bayesian results show that the inequality within the low and middle income group do not change much and the importance of the high income is the most affected by the fight against inequality that followed the Thatcher period.

The Theory of Macrojustice, introduced by S.-C. Kolm, is a stimulating contribution to the debate on the macroeconomic income distribution. The solution called "Equal Labour Income Equalisation" (ELIE) is the result of a three stages construction: collective agreement on the scheme of labour income redistribution, collective agreement on the degree of equalisation to be chosen in that framework, individual freedom to exploit his-her personal productive capacities (the source of labour income and the sole basis for taxation). This collective book is organised as a discussion around four complementary themes: philosophical aspects of macrojustice, economic analysis of macrojustice, combinations of ELIE with other targeted transfers, econometric evaluations of ELIE.

The ELIE scheme of Kolm taxes labour capacities instead of labour income in order to circumvent the distortionary effect of taxation on labour supply. Still, Kolm does not study the impact of ELIE on human capital formation and investment. In this paper, we build an overlapping generations (OLG) model with heterogenous agents and endogenous growth driven by investment in human capital. We study the effect of ELIE on education investment and other aggregate economic variables. Calibrating the model to French data, we highlight a tradeoff between growth and redistribution. With a perfect credit market, ELIE is successful in reducing inequalities and poverty, but it is at the expense of lower investment in education and slower growth. In an economy with an imperfect credit market where individuals cannot borrow to educate, the tradeoff between growth and redistribution is not overturned but is less severe. However, it is possible to overturn completely that trade-off simply by changing the base of taxation for the young generation which is equivalent to subsidising education.

This paper analyses the problems linked to the implementation of the Equal Labour Income Equalisation (ELIE) scheme proposed by [Kolm, 2005]. It successively studies the influence of uncertainty in the information about individual incomes, the impact of equivalence scales and finally the consequences of capital accumulation. If uncertainty does not modify fundamentally the equity properties of ELIE, equivalence scales can have non trivial consequences depending on the relation between income and fertility. Finally, capital accumulation introduces strong inequalities in the income distribution which are not removed by taxation. The paper relies on simulations of the income distribution, calibrated on French data and on the use of taxation indices.

Least squares cross-validation (CV) methods are often used for automated bandwidth selection. We show that they share a common structure which has an explicit asymptotic solution. Using the framework of density estimation, we consider unbiased, biased, and smoothed CV methods. We show that, with a Student t(nu) kernel which includes the Gaussian as a special case, the CV criterion becomes asymptotically equivalent to a simple polynomial. This leads to optimal-bandwidth solutions that dominate the usual CV methods, definitely in terms of simplicity and speed of calculation, but also often in terms of integrated squared error because of the robustness of our asymptotic solution. We present simulations to illustrate these features and to give practical guidance on the choice of nu.

Least squares cross-validation (CV) methods are often used for automated bandwidth selection. We show that they share a common structure which has an explicit asymptotic solution that we derive. Using the framework of density estimation, we consider unbiased, biased, and smoothed CV methods. We show that, with a Student t(ν) kernel which includes the Gaussian as a special case, the CV criterion becomes asymptotically equivalent to a simple polynomial. This leads to optimal-bandwidth solutions that dominate the usual CV methods, definitely in terms of simplicity and speed of calculation, but also often in terms of integrated squared error because of the robustness of our asymptotic solution, hence also alleviating the notorious sample variability of CV. We present simulations to illustrate these features and to give practical guidance on the choice of ν.

In this paper we examine the problem of testing for heterogeneity and heterosckedasticity in a Bayesian framework. We first show that a model with random coefficients is identical to a model with heteroskedastic residuals. We then consider two approaches for testing. The first one is concerned with the point of view of misspecification. The original model is homoskedastic. One is willing to detect any departure from homoskedasticity. We propose diagnostics based on the examination of the Bayesian residuals, after stressing the differences between classical and Bayesian residuals. In the second approach, the starting point is a precise form of the alternative hypothesis, and the model for inference is heteroskedastic. A test for homoskedasticity is then a test for a parameter restriction. This can be done by looking at highest posterior probability regions or by the use of the posterior odds ratio. As a joint product, we develop the posterior analysis of a heteroskedastic regression model for several classes of prior distributions.

When a linear econometric model is expressed in logarithms, the presence of identities entails a strong non-linearity for the simulation stage of the complete model. This aspect can be damageable for the simulation algorithms which are implemented on microcomputers. A traditional solution consists in linearizing the identity by a Taylor expansion around the mean of the variables. In this paper we propose an approximation based on an error correction mecanism which takes into account the statistical properties of the series. The quality of the approximation is shown on a three equation econometric model estimated on french quartely data covering the period 1963-1985.

This paper analyses the problems linked to the implementation of the Equal Labour Income Equalisation (ELIE) scheme proposed by Kolm (2005). It successively studies the influence of uncertainty in the knowledge of individual incomes, the impact of equivalence scales and finally the consequences of capital accumulation. If uncertainty does not modify fundamentally the equity properties of ELIE, equivalence scales can have non trivial consequences depending on the relation between income and fertility. Finally, capital accumulation introduces strong inequalities in taxation. The paper relies on simulations of the income distribution, calibrated on French data and on the use of taxation indices.

We provide a ranking of economics departments in Europe and we discuss the methods used to obtain it. The JEL CD-ROM serves as a database for a period covering 10 years. Journals are ranked using a combination of expert opinions and citation data to produce a scale from 1 to 10. The publication output and habits of fifteen European countries plus California are then compared. Individuals with a contribution greater than a predetermined minimum level are regrouped into departments which are ranked according to their total scores. A standard deviation is provided to underline the uncertainty of this ranking.

This paper proposes a new kind of asymmetric GARCH where the conditional variance obeys two différent regimes with a smooth transition function. In one formulation, the conditional variance reacts differently to negative and positive shocks while in a second formulation, small and big shocks have separate effects. The introduction of a threshold allows for a mixed effect. A Bayesian strategy, based on the comparison between posterior and predictive Bayesian residuals, is built for detecting the presence and the shape of non-linearities. The method is applied to the Brussels and Tokyo stock indexes. The attractiveness of an alternative parameterisation of the GARCH model is emphasised as a potential solution to some numerical problems.