Brian J. Cushing's research while affiliated with West Virginia University and other places

Publications (4)

Article
This paper develops asymptotically distribution-free inference for testing inequality indices with dependent samples. It considers the interpolated Gini coefficient and the generalized entropy class, which includes several commonly used inequality indices. We first establish inference tests for changes in inequality indices with completely dependen...
Article
Poverty in the United States varies greatly by location. The difference in poverty intensity among locations, however, has only been evaluated by the official poverty measure - the headcount ratio - which has several drawbacks. The official poverty statistics also suffer from use of a single, arbitrary poverty line. This paper uses a recently-devel...
Article
We explore how poverty differs between urban and rural areas and among U.S. regions, using metropolitan versus nonmetropolitan to proxy urban versus rural. Our study focuses on social and demographic characteristics, rather than economic characteristics. We are concerned with which personal characteristics appear to increase the risk of poverty, re...

Citations

... This section uses Luxembourg Income Study data to examine whether this is true. It presents estimates of poverty intensity, the poverty rate and the poverty gap for the four countries for which long term time series are available [Canada (1971, 1975, 1981, 1987, 1991, 1994), Sweden (1975, 1981, 1987, 1992), United Kingdom (1974 Kingdom ( , 1979 Kingdom ( , 1986 Kingdom ( 1991 Kingdom ( and 1995), and United States (1974 States ( , 1979 States ( , 1986 States ( , 1991 States ( , 1994 States ( and 1997 supplemented occasionally with data from Germany (1981 Germany ( , 1983 Germany ( , 1989 Germany ( and 1994). In order to focus on the appropriate index of poverty, this paper submits to the constraints of the data and assumes that all individuals within households share equally in household resources, and have no claim on the resources of other households 9 . ...
... Empirical findings suggest a positive correlation between means and variances of the earnings distribution in age and schooling of subgroups (Sahota, 1978). Whites are generally economically better off than their non-White counterparts after controlling for other demographic characteristics (Brandon, 1995;DeNavas-Walt et al., 2005;Harknett, 2001;Sandefur and Pahari, 1989;Smock, 1993;Cushing and Zheng, 1999). The effect of education on earnings is higher for Whites than for African Americans (Weiss, 1970), partly due to differential treatment in education and the labor market (Lichter, 1989). ...
... Spatial dependence is within the two samples used in stochastic dominance tests, not between elements of the samples. Cross-sectional dependence has received some attention in the individual income inequality literature (Zheng & Cushing, 2001), but those results have yet to be formally extended to either stochastic dominance testing or the spatial cross-sectional case. ...
... The spatial-price adjusted estimate of nonmetro poverty is lower than the adjusted metro estimate for all FGT 21 The analysis in this paper focuses on metro and nonmetro areas, both because this mirrors the design of the FMR index and also because the disbursement of Federal funds are in many cases linked to this geographic definition. Cushing and Zheng (2000) and Jolliffe (2003b) examine the geographic distribution of several poverty measures using central city, suburb and nonmetro as the geographic units and find that relative poverty rates tend to be the highest in central cities and lowest in suburbs. Adjusting these measures with the FMR index does not result in a re-ranking of this ordering -FMR adjusted poverty is highest in central cities and lowest in suburbs. ...