Advances in Inequality Measurement and Usefulness of Statistical Inference

Assessment of inequality measurement is the focus for this survey. All measures of inequality must be evaluated based on a set of desirable properties. More importantly, the usefulness of statistical inference for measures of inequality needs examination.     

Income distribution and redistribution through taxation: An international comparison

Income tax progressivity is studied with Generalized Entropy measures of inequality. Luxembourg Income Study data sets for nine countries are used for international comparison and analysis. progressivity indices are generated by using the Generalized Entropy family as well as Atkinson measures. We further our understanding by examining pre-tax and post-tax measures of inequality based respectively on gross and disposable household incomes. The decomposition property is shown to be desirable for enhancing our knowledge of income inequality and the redistributive effect of income taxes. Thus decomposition based on family size and number of earners is conducted. We learn that countries vary in their emphasis regarding redistributive effects of income taxes.     

Statistical analysis of inequality with decompositions: the Canadian experience

This study carries out a decomposition of Theil-entropy measures into a between-group component, based on factors such as education, age, gender, and marital status, and a component representing inequality within each group. We apply a bootstrapping technique to measures of inequality to enable statistical inference. Trends in household income inequality in Canada are investigated using data from 1991 to 1997 drawn from Survey of Consumer Finance. We find an evident trend toward increasing inequality of household incomes between the years 1991–1997, during which the economy was recovering from a steep recession. Although most of the increase in measured inequality is attributed to the `within-group' component, we find the change in `between-group' inequality to be significant for education, age, and marital status. First version received: May 2001/Final version received: September 2001     

Bounding Lifetime Income Using A Cross Section Of Data

Measures of income inequality based on current income are well known to overstate lifetime income inequality for two reasons: intracohort mobility and the shape of the age-earnings profile. Utilizing the concept of age equivalence scales along with varying assumptions concerning the extent of intracohort mobility, the method presented bounds lifetime income inequality using only cross-sectional data from the CPS, 1967–86. As a result, we are able to analyze changes in lifetime inequality over this period.     

Advances in Inequality Measurement and Usefulness of Statistical Inference

Assessment of inequality measurement is the focus for this survey. All measures of inequality must be evaluated based on a set of desirable properties. More importantly, the usefulness of statistical inference for measures of inequality needs examination.

The globalization of poverty according to Malthus

Malthus began publishing in economics two centuries ago. His thoughts on income distribution and poverty are profound. Recently, more original findings on these issues have appeared, but can be viewed as rediscovering Malthus. His thought remains germane to the present debate on poverty and his foresight deserves respect.     

Decomposable measures of income tax progressivity

A class of decomposable income tax progressivity indices is defined by using a family of generalized entropy measures. For demonstration, changes in income tax progressivity in the United States are studied over time.     

Generalized entropy measures of long-run inequality and stability among male headed households

This paper provides measures of short and long-run inequalities as well as income stability among households with male heads using the panel study of income dynamics for the period 1969–1981. It is found that short-run inequalities have been increasing over the time period examined. Moreover, some fluctuations around this increasing trend are of a transitory nature and appear to be smooth over time. Long-run measures are less subject to fluctuations and provide a better measure of inequality. They show a decrease in inequality in the early periods but increases after the mid-1970's. Several aggregator functions are used to compute permanent income variables for the long-run measures of inequality and stability. The measures are decomposed to reflect differences in age, education, and race. They are decomposed also into groups which are free of such group characteristics. Education has the most important influence on inequality. Stability profiles indicate, furthermore, most of the reduction in inequality in the early periods has been within particular groups. Reductions across groups are minimal.Helpful comments from Esfandiar Maasoumi, Joseph Craycraft, Kenneth Koford and two referees are acknowledged. The usual caveat as to remaining errors applies.     

Data‐ and metrics‐driven approach to human resource practices: Using customers,employees, and financial metrics

Should scientific measures be used to evaluate the effectiveness of HRM practices? Can HRM demonstrate that its proposals cause a predicted outcome? If the allocation of capital within an organization is based upon projected financial returns, should HRM be required to demonstrate the expected returns of its proposals? Would the use of scientific and financial measures give HRM practices greater internal support and continuity? The authors demonstrate how metrics were used to evaluate two new HRM projects at one of the world's largest retailers. © 2000 John Wiley & Sons, Inc.