Jean-Yves Duclos

Polarization: Concepts, Measurement, Estimation

The purpose of this paper is two-fold. First, we develop the measurement theory of polarization for the case in which asset distributions can be described using density functions. Second, we provide sample estimators of population polarization indices that can be used to compare polarization across time or entities. Distribution-free statistical inference results are also derived in order to ensure that the orderings of polarization across entities are not simply due to sampling noise. An illustration of the use of these tools using data from 21 countries shows that polarization and inequality orderings can often differ in practice.

Statistical inference for the measurement of the incidence of taxes and transfers

We establish the asymptotic sampling distribution of general functions of quantile-based estimators computed from samples that are not necessarily independent. The results provide the statistical framework within which to assess the progressivity of taxes and benefits, their horizontal inequity, and the change in the inequality of income which they cause. By the same token, these findings characterise the sampling distribution of a number of popular indices of progressivity, horizontal inequity, and redistribution. They can also be used to assess welfare and inequality changes using panel data, and to assess poverty when it depends on estimated population quantiles. We illustrate these results using micro data on the incidence of taxes and benefits in Canada.

Testing for Restricted Stochastic Dominance

Asymptotic and bootstrap tests are studied for testing whether there is a relation of stochastic dominance between two distributions. These tests have a null hypothesis of nondominance, with the advantage that, if this null is rejected, then all that is left is dominance. This also leads us to define and focus on restricted stochastic dominance, the only empirically useful form of dominance relation that we can seek to infer in many settings. One testing procedure that we consider is based on an empirical likelihood ratio. The computations necessary for obtaining a test statistic also provide estimates of the distributions under study that satisfy the null hypothesis, on the frontier between dominance and nondominance. These estimates can be used to perform bootstrap tests that can turn out to provide much improved reliability of inference compared with the asymptotic tests so far proposed in the literature.

Modelling the take-up of state support

Abstract We discuss the modelling of the take-up of state support by going beyond the standard analysis and recognising that both the researcher and the welfare agency make errors is assessing entitlement. We apply the discussion to an examination of the take-up of Supplementary Benefits in Britain. By explicitly modelling the costs to taking up state support, we can illustrate how these costs can dampen the welfare impact of state support and mitigate or aggravate welfare agency errors in assessing entitlement.

What is “Pro-Poor”?

Assessing whether distributional changes are “pro-poor” has become increasingly widespread in academic and policy circles. Starting from relatively general ethical axioms, this paper proposes simple graphical methods to test whether distributional changes are indeed pro-poor. Pro-poor standards are first defined. An important issue is whether these standards should be absolute or relative. Another issue is whether pro-poor judgements should put relatively more emphasis on the impact of growth upon the poorer of the poor. Having formalized the treatment of these issues, the paper describes various ways for checking whether broad classes of ethical judgements will declare a distributional change to be pro-poor.

Robust Multidimensional Poverty Comparisons with Discrete Indicators of Well-Being

This paper provides a method to make robust multidimensional poverty comparisons when one or more of the dimensions of well-being or deprivation is discrete. Sampling distributions for the statistics used in these poverty comparisons are provided. Several examples show that the methods are both practical and interesting in the sense that they can provide richer information than do univariate poverty comparisons.

Sequential Stochastic Dominance and the Robustness of Poverty Orderings

When comparing poverty across distributions, an analyst must select a poverty line to identify the poor, an equivalence scale to compare individuals from households of different compositions and sizes, and a poverty index to aggregate individual deprivation into an index of total poverty. A different choice of poverty line, poverty index or equivalent scale can of course reverse an initial poverty ordering. This paper develops sequential stochastic dominance conditions that throw light on the robustness of poverty comparisons to these important measurement issues.

Testing for Pro-Poorness of Growth, with an Application to Mexico

This paper proposes techniques to test for whether growth has been pro-poor. We first review different definitions of pro-poorness and argue for the use of methods that can generate results that are robust over classes of pro-poor measures and ranges of poverty lines. We then provide statistical procedures that rely on the use of sample data to infer whether growth has been pro-poor in a population. We apply these procedures to Mexican household surveys for the years of 1992, 1998 and 2004. We find strong statistical evidence that Mexican growth has been absolutely anti-poor between 1992 and 1998, absolutely pro-poor between 1998 and 2004 and between 1992 and 2004, and relatively pro-poor between 1992 and 2004 and between 1998 and 2004. The relative assessment of the period between 1992 and 1998 is statistically too weak to lead to a robust evaluation of that period.

Poverty-Decreasing Indirect Tax Reforms: Evidence from Tunisia

This paper proposes a methodology to identify revenue-neutral directions for poverty-alleviating tax reforms. The search for such poverty-reducing tax reforms is done “robustly” over broad classes of poverty measures and poverty lines. The methodology, which is illustrated using data from Tunisia, is of significant policy interest given the widespread use of commodity subsidization and taxation in developing and developed countries alike. The results suggest that Tunisian poverty could be decreased robustly by following reform directions that are often at odds with frequently-heard views. They also highlight the importance of stating clearly under which set of ethical criteria the desirability of potential indirect tax reforms is assessed. Copyright Springer Science + Business Media, LLC 2007

Household Incidence of Pollution Control Policies: A Robust Welfare Analysis Using General Equilibrium Effects

This study assesses the incidence of pollution control policies on households. In contrast to previous studies, we employ an integrated framework combining a multisector general equilibrium model with a stochastic dominance analysis using household-leved data. We consider three policy instruments in a domestic emission trading system: (i) an output-based allocation of permits (OBA); (ii) the use of the proceeds of permit sales to reduce payroll taxes (RPT); (iii) and the use of these proceeds to reduce consumption taxes instead (UCS). The general equilibrium results suggest that the return to capital is more negatively affected than the wage rate in all simulations, since polluting industries are capital intensive. Abstracting from pollution externalities, the dominance analysis allows us to conclude that all three policies have a normatively robust negative (positive) impact on welfare (poverty). Formal dominance tests indicate that RPT first-order welfare dominates OBA over all values of household incomes. UCS also first-order poverty dominates RPT for any choice of poverty line below