Florent Bresson

On the Estimation of Growth and Inequality Elasticities of Poverty with Grouped Data

After decades of intensive research dedicated to efficient and flexible parametric statistical distributions, the lognormal distribution still enjoys, despite its empirical weaknesses, widespread popularity in the applied literature related to poverty and inequality analysis. In the present study, we emphasize the drawbacks of this choice for the calculation of the elasticities of poverty. For this purpose, we estimate the growth and inequality elasticities of poverty using 1,132 income distributions, and 15 rival assumptions on the shape of the income distributions. Our results confirm that the lognormal distribution is not appropriate in most cases for the analysis of poverty: the magnitude of the elasticities is generally overestimated and the estimation of the relative impact of growth and redistribution on poverty alleviation is biased in favor of the growth objective.

Intertemporal poverty comparisons

The paper deals with poverty orderings when multidimensional attributes exhibit some degree of comparability. The paper focuses on an important special case of this, that is, comparisons of poverty that make use of incomes at different time periods. The ordering criteria extend the power of earlier multidimensional dominance tests by making (reasonable) assumptions on the relative marginal contributions of each time dimension to poverty. Inter alia, this involves drawing on natural symmetry and asymmetry assumptions as well as on the mean/variability framework commonly used in the risk literature. The resulting procedures make it possible to check for the robustness of poverty comparisons to choices of intertemporal aggregation procedures and to areas of intertemporal poverty frontiers. The results are illustrated using a rich sample of 23 European countries over 2006–2009.

Intertemporal Poverty Comparisons

The paper deals with poverty orderings when the value of multidimensional attributes can be compared on a same scale, such as with income of different types or from different members of the same household. The dominance criteria extend the power of earlier multidimensional dominance tests (see Duclos et al. 2006) by making (reasonable) assumptions on the relative marginal contributions of each dimensional attribute to poverty. The paper focuses on an important special case of this, that is comparisons of poverty over time. In contrast to earlier work on intertemporal poverty comparisons, this paper proposes procedures to check for whether poverty comparisons can be made robust to wide classes of aggregation procedures and to broad areas of intertemporal poverty frontiers.

When More Does Not Necessarily Mean Better: Health‐Related Illfare Comparisons with Non‐Monotone Well‐Being Relationships

Most welfare studies are based on the assumption that wellbeing is monotonically related to the variables used for the analysis. While this assumption can be regarded as reasonable for many dimensions of wellbeing like income, education, or empowerment, there are some cases where it is definitively not relevant, in particular with respect to health. For instance, health status is often proxied using the Body Mass Index (BMI). Low BMI values can capture undernutrition or the incidence of severe illness, yet a high BMI is neither desirable as it indicates obesity. Usual illfare indices derived from poverty measurement are then not appropriate. This paper proposes illfare indices that are consistent with some situations of non-monotonic wellbeing relationships and examines the partial orderings of different distributions derived from various classes of illfare indices. An illustration is provided for health-related illfare as proxied by the BMI and weight-for-age indicators using DHS data for Bangladesh during the period 1997-2007. It is shown inter alia that the gains from the decline of undernutrition for Bangladeshi mothers are undermined by the rapid increase of obesity.

Axiomatic and Robust Multidimensional Poverty Measurements in Five Southern Mediterranean Countries

The main goal of this chapter is to undertake a multidimensional poverty analysis in relation to five southern Mediterranean countries, namely Egypt, Lebanon, Morocco, Tunisia and Turkey. We rely on a broader concept of poverty by considering the deprivations in womens educational attainments, the possession of durable goods and the consequences of housing conditions, each of which we operationalise by making use of recent developments in multidimensional poverty measurement. This analysis is based on an axiomatic approach to poverty and on the use of stochastic dominance tools to achieve robust results that do not hinge on the choice of poverty line and weighting scheme. Our findings provide comparisons over time for each country and between countries that cannot be obtained when each dimension of poverty is analysed separately, as the approaches take into account the correlations which may exist between different kinds of poverty. Furthermore, in contrast to rankings drawn from cardinal poverty measures (for example, from the Multidimensional Poverty Index), multidimensional tests make it possible to nuance the performance levels reached by certain countries.