WAGE DISCRIMINATION ACROSS ETHNIC GROUPS: EVIDENCE FROM ISRAEL

We investigate wage differentials between ethnic groups in Israel, proposing a new methodology and an illustration based on the latest Israeli census. By using separate wage equations for the various occupations, our methodology allows us to decompose the wage differential into three components: one reflecting human capital differences; one reflecting wage discrimination; and a third indicating occupational segregation. We find that 70 percent of the wage gap is due to segregation, 26 percent to wage discrimination and only 4 percent to human capital differences. Evidence is also found for the existence of duality in the Israeli labor market.     

Amplification of Sensitivity Analysis in Matched Observational Studies

A sensitivity analysis displays the increase in uncertainty that attends an inference when a key assumption is relaxed. In matched observational studies of treatment effects, a key assumption in some analyses is that subjects matched for observed covariates are comparable, and this assumption is relaxed by positing a relevant covariate that was not observed and not controlled by matching. What properties would such an unobserved covariate need to have to materially alter the inference about treatment effects? For ease of calculation and reporting, it is convenient that the sensitivity analysis be of low dimension, perhaps indexed by a scalar sensitivity parameter, but for interpretation in specific contexts, a higher dimensional analysis may be of greater relevance. An amplification of a sensitivity analysis is defined as a map from each point in a low dimensional sensitivity analysis to a set of points, perhaps a 'curve,' in a higher dimensional sensitivity analysis such that the possible inferences are the same for all points in the set. Possessing an amplification, an investigator may calculate and report the low dimensional analysis, yet have available the interpretations of the higher dimensional analysis.     

Using the Shapley Decomposition to Disentangle the Impact of Circumstances and Efforts on Health Inequality

Following previous work on inequality in health opportunity, this paper attempts to determine the contribution of circumstances, efforts and lifestyle, and demographic variables to the overall inequality in health in Luxembourg. Health is measured via the answers given to a question on self-assessed health and is considered as an ordinal variable. The educational level of each parent, the financial situation of the family during childhood, the area of birth of the individual, and of his/her parents, and the year of immigration are considered as circumstances. Effort and lifestyle variables are proxied by information on the educational level of the individual, whether he/she smoked and whether he/she had a physical activity on a regular basis. Sex and age are considered as demographic variables. To solve the issue of correlation between circumstances and effort and lifestyle the estimation is implemented in two stages. In the first stage, each effort and lifestyle variable is regressed in a separate equation against the vector of circumstances and demographic variables and, in a second stage, the individual health status is regressed against the vector of circumstances and demographic variables along with the estimated residuals of the effort equations described previously. The respective impacts of the three categories of explanatory variables (circumstances, effort and lifestyle and demographic variables) on health inequality are derived via a Shapley decomposition of the likelihood ratio of the health ordered logit regression. It appears that differences in circumstances and effort and lifestyle explain each around a quarter of this likelihood ratio.     

Gini’s concentration index and the measurement of the distance between relative price vectors

A new measure is developed for the distance between relative price vectors. It is shown to be related to Gini’s Index of Concentration and is applied to cross-country data for the year 1975.     

The diversity of household assets holdings in the United States in 2007 and 2009: measurement and determinants

Review of Economics of the Household - We apply diversity indices, such as the Gini-Simpson index and entropy related indices, to the study of the distribution of individual asset holdings in the...     

When near means related: evidence from three web survey experiments on inter-item correlations in grid questions

In this article, we present the results of three question design experiments on inter-item correlations, which tested a grid design against a single-item design. The first and second experiments examined the inter-item correlations of a set with five and seven items, respectively, and the third experiment examined the impact of the question design on inter-item correlations of follow-up questions. We found that the inter-item correlations in grid designs were higher for both the set of five and seven items than for questions in a single-item design. Additionally, the inter-item correlations of the set of follow-up questions were higher if the preceding set of questions was presented in a grid. According to the findings of the present research, respondents seem to apply the interpretative near means related heuristic when answering grid questions, and also when answering follow-up questions preceeded by grid questions.