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Dominance techniques are used to analyze and rank inequality, welfare, and poverty across regions in Thailand in the 1990s. Inference-based dominance methods are applied to consumption expenditure microdata from the Household Socio-Economic Surveys (SES) of 1992, 1994, 1996, 1998 and 2000. Attention is focused on the period immediately before and after the economic contraction of 1996–1997. Lorenz dominance is employed to assess inequality, while first-order Engel food share dominance is applied to rank welfare across time and among regions. Poverty is evaluated by comparing truncated food-share quantile functions. The evidence reveals that the economic crisis in 1997 seems to affect inequality in Bangkok (the richest region) more than the Northeast (the poorest region), and most dramatic changes occur in the North and South. Welfare in Bangkok is unambiguously higher than in other regions before and after economic contraction. In fact, the great economic contraction changes the rankings of economic well-being and poverty only in the North, South, and Northeast.

In a period of political change in the European Union, when the European Constitution is in the centre of the debate, the social convergence among European Union countries is a crucial issue. However, the measurement of welfare, inequality and poverty and the comparisons among countries are issues of great controversy. One of the main reasons for this is that implicit or explicit value judgements have to be made, and it is not easy to determine which of these value judgements are the most appropriate ones. In this paper we apply inference-based stochastic dominance methods to study welfare, inequality and poverty in European Union countries in 2000, applying purchasing power parities from the OECD. There are two main advantages of the methods and data used in this work: on the one hand, the stochastic method uses explicit and widely, though not universally, accepted assumptions, and if this small number of assumptions is accepted, the welfare and poverty ranking that the method provides is unambiguous. On the other hand, the use of the European Community Household Panel permits the comparisons in welfare, inequality and poverty among different countries using harmonised data. In addition, the use of inference tests permits a more precise ranking.

Hypothesis tests for dominance in income distributions has received considerable attention in recent literature. See, for example, Barrett and Donald (2003a, b), Davidson and Duclos (2000) and references therein. Such tests are useful for assessing progress towards eliminating poverty and for evaluating the effectiveness of various policy initiatives directed towards welfare improvement. To date the focus in the literature has been on sampling theory tests. Such tests can be set up in various ways, with dominance as the null or alternative hypothesis, and with dominance in either direction (X dominates Y or Y dominates X). The result of a test is expressed as rejection of, or failure to reject, a null hypothesis. In this paper, we develop and apply Bayesian methods of inference to problems of Lorenz and stochastic dominance. The result from a comparison of two income distributions is reported in terms of the posterior probabilities for each of the three possible outcomes: (a) X dominates Y, (b) Y dominates X, and (c) neither X nor Y is dominant. Reporting results about uncertain outcomes in terms of probabilities has the advantage of being more informative than a simple reject/do-not-reject outcome. Whether a probability is sufficiently high or low for a policy maker to take a particular action is then a decision for that policy maker.

The methodology is applied to data for Canada from the Family Expenditure Survey for the years 1978 and 1986. We assess the likelihood of dominance from one time period to the next. Two alternative assumptions are made about the income distributions – Dagum and Singh-Maddala – and in each case the posterior probability of dominance is given by the proportion of times a relevant parameter inequality is satisfied by the posterior observations generated by Markov chain Monte Carlo.

Dominance complementarity, which is the tendency for people to respond oppositely to others along the control dimension of interpersonal behavior, is a means by which people create and perpetuate informal forms of interpersonal hierarchy within social relationships (Tiedens, Unzueta, & Young, 2007b). In the present chapter, I explore the likely effects of such complementarity on group creativity. I propose specifically that expressions of dominance, even those borne not out of formal hierarchy but rather out of such factors as expertise and enthusiasm for the task, are likely to elicit submissive responses from fellow group members when the group is trying to generate creative ideas. As group members behaving submissively are likely to contribute fewer ideas to group discussion, I argue that group members who behave dominantly may, through their influence on other group members, reduce both the number and diversity of ideas generated within the group. I, therefore, propose that dominance complementarity may impair groups' abilities to generate creative ideas.

This paper deals with poverty decompositions into subgroups defined with respect to intervals of income and the robustness of comparisons of the absolute contribution of such groups to poverty. For instance, world poverty estimates by the World Bank often distinguish between the extreme poor whose incomes are lower than $1.25 a day (in PPP terms) and the other poor with incomes between $1.25 and $2.5 a day. Existing dominance conditions can tell whether overall poverty and extreme poverty have declined in a robust manner when comparing countries at two points of time, but they cannot say anything for the contribution of the non-extreme poor to overall poverty. In the present paper we propose stochastic generalized dominance criteria to perform robust poverty ordering when the focus is placed on some interval of the poverty domain. Using generated data based on grouped data from World Bank’s PovcalNet tool, the paper finally investigates whether the robust decline of extreme poverty around the world during the last decades was also accompanied by a decline of the contribution of non-extreme poverty.

Anchoring vignettes have become a popular method to adjust self-assessed data for systematic differences in reporting behaviour to aid comparability, for example, of cross-country analyses. The method relies on the two fundamental assumptions of response consistency and vignette equivalence. Evidence on the validity of these assumptions is equivocal. This chapter considers the utility of the vignette approach by considering how successful the method is in moving self-assessed reports of health mobility towards objective counterparts. We draw on data from the Survey of Health, Ageing and Retirement in Europe (SHARE) and undertake pairwise country comparisons of cumulative distributions of self-reports, their objective counterparts and vignette adjusted reports. Comparison of distributions is based on tests for stochastic dominance. Multiple cross-country comparisons are undertaken to assess the consistency of results across contexts and settings. Both non-parametric and parametric approaches to vignette adjustment are considered. In general, we find the anchoring vignette methodology poorly reconciles self-reported data with objective counterparts.

We use the Duclos, Makdissi and Wodon (2005) decomposition of programme dominance into targeting dominance and allocation dominance curves to identify poverty-reducing programme reforms. In particular we recognise the importance of considering more than one dimension when identifying poverty-reducing policy reforms. For this purpose, we use sequential stochastic dominance methods to analyse the poverty impact of policy programme reforms, particularly the case of income transfers and commodity taxation.

This chapter proposes tests for stochastic dominance in mobility based on the empirical likelihood ratio. Two views of mobility are considered, either based on measures of absolute mobility or based on transition matrices. First-order and second-order dominance conditions in mobility are first derived, followed by the derivation of statistical inferences techniques to test a null hypothesis of nondominance against an alternative of mobility dominance. An empirical analysis, based on the US Panel Study of Income Dynamics (PSID), is performed by comparing four income mobility periods ranging from 1970 to 1990.

This paper develops criteria for an alternative concept of inequality dominance and shows how they relate to criteria for comparing relative poverty. The results warn inter alia against the use of some popular indices of inequality. They do, however, provide an ethical basis for the use of other popular indices of (restricted) inequality as potential relative poverty indices. The results also suggest an interesting extension of the Schutz coefficient as well as a use of Lorenz curves for the analysis of relative poverty and restricted inequality. A graphical illustration shows how the new criteria of restricted inequality dominance extend the ranking power of previously proposed inequality dominance criteria.

We examine the cardinal gap between wage distributions of the incumbents and newly hired workers based on entropic distances which are well-defined welfare theoretic measures. Decomposition of several effects is achieved by identifying several counterfactual distributions of different groups. These go beyond the usual Oaxaca–Blinder decompositions at the (linear) conditional means. Much like quantiles, these entropic distances are well-defined inferential objects and functions whose statistical properties have recently been developed. Going beyond these strong rankings and distances, we consider weak uniform ranking of these wage outcomes based on statistical tests for stochastic dominance. The empirical analysis is focused on employees with at least 35 hours of work in the 1996–2012 monthly Current Population Survey (CPS). Among others, we find incumbent workers enjoy a better distribution of wages, but the attribution of the gap to wage inequality and human capital characteristics varies between quantiles. For instance, highly paid new workers are mainly due to human capital components, and in some years, even better wage structure.