Bootstrap Testing for restricted stochastic dominance of a pre-specified order between two distributions is of interest in many areas of economics. This paper develops a new method for improving the performance of such tests that employ a moment selection procedure: tilting the empirical distribution in the moment selection procedure. We propose that the amount of tilting be chosen to maximize the empirical likelihood subject to the restrictions of the null hypothesis, which are a continuum of unconditional moment inequality conditions. We characterize sets of population distributions on which a modified test is (i) asymptotically equivalent to its non-modified version to first-order, and (ii) superior to its non-modified version according to local power when the sample size is large enough. We report simulation results that show the modified versions of leading tests are noticeably less conservative than their non-modified counterparts and have improved power. Finally, an empirical example is discussed to illustrate the proposed method.

The health concentration curve is the standard graphical tool to depict socioeconomic health inequality in the literature on health inequality. This paper shows that testing for the absence of socioeconomic health inequality is equivalent to testing if the conditional expectation of health on income is a constant function that is equal to average health status. In consequence, any test for parametric specification of a regression function can be used to test for the absence of socioeconomic health inequality (subject to regularity conditions). Furthermore, this paper illustrates how to test for this equality using a test for parametric regression functional form and applies it to health-related behaviors from the National Health Survey 2014.

Stochastic dominance comparisons of distributions based on ordinal data arise in many areas of economics. This paper develops a testing procedure for such comparisons under survey sampling from large finite populations with nonresponse using the worst-case bounds of the distributions. The advantage of using these bounds in distributional comparisons is that conclusions are robust to the nature of the nonresponse-generating mechanism. While these bounds on the distributions are often too wide in practice, we show that they can be informative for distributional comparisons in an empirical analysis. This paper examines the dynamics of trust in Lebanese public institutions using the 2013 World Values Survey as well as the 2016 and 2018 waves of the Arab Barometer, and finds convincing evidence of a decrease in confidence in most public institutions between 2013 and 2016.

This paper uses the 2013 World Value Survey, as well as the 2016 and 2018 waves of the Arab Barometer, to analyze the dynamics of trust in public institutions in Lebanon. It finds strong evidence that confidence in most public institutions has decreased between 2013 and 2016. The evidence of this decrease is robust to the numerical scale assigned to the different ordinal categories of trust and to assumptions on the missing values generating process. This finding highlights the importance for policymakers in developing countries to survey the perceptions and political attitude of their constituents in order to improve the performance of public institutions.

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