Relative deprivation,reference groups and the assessment of standard of living

This paper proposes two new indices of relative deprivation, derived from an extension of the concept of generalized Gini to the measurement of distributional change. Population- and income-weighted relative deprivation indices are then defined and, using panel data from the Consortium of Household Panels for European Socio-Economic Research (CHER), we check which of the various ways of defining individual deprivation best fits the answers given by individuals on the degree of their satisfaction with income. We find that the deprivation indices proposed are consistently and negatively correlated with income satisfaction as reported by respondents, that income weighted measures fit better than population weighted measures and that this fit improves with countries that experienced deep institutional changes such as the transitional economies of Eastern Europe.     

Measuring the Impact of Various Income Sources on the Link between Inequality and Development: Implications for the Kuznets Curve

To understand the link between inequality and development, a decomposition of the Gini index by income sources is used that emphasizes the role of three components measuring the impact of the shares of the sources, the degree to which they are unequally distributed, and their correlation with total income. Such a breakdown explains why the rising section of the Kuznets curve is mainly the consequence of the increasing share of wages while its declining section reflects the decreasing share of entrepreneurial income and the negative correlation between transfers and total income. The data sources were provided by the International Labour Office.     

MEASURING MULTIDIMENSIONAL POVERTY: AN EMPIRICAL COMPARISON OF VARIOUS APPROACHES

This paper makes a systematic comparison of four approaches to multidimensional poverty analysis based respectively on the theory of fuzzy sets, information theory, efficiency analysis and axiomatic derivations of poverty indices. The database was the 1995 Israeli Census that provided information on the ownership of various durable goods. There appears to be a fair degree of agreement between the various multidimensional poverty indices concerning the identification of the poor households. The four approaches have also shown that poverty decreases with the schooling level of the head of the household, first decreases and then increases with his/her age and with the size of the household. Poverty is higher when the head of the household is single and lower when he/she is married, lowest when the head of the household is Jewish and highest when he/she is Muslim. Poverty is also higher among households whose head immigrated in recent years, does not work or lives in Jerusalem. These observations were made on the basis of logit regressions. This impact on poverty of many of the variables is not very different from the one that is observed when poverty measurement is based only on the income or the total expenditures of the households.     

Weighting income ranks and levels: A Multiple-Parameter Generalization For Absolute and Relative Inequality Indices

This paper gives a general expression for a multiple parameter index of absolute or relative inequality and indicates that the indices suggested by Atkinson, Kolm and Gini are particular cases of the proposed generalized index.     

On an absolute measure of distributional change

This paper tries to combine Kolm's ideas on the measurement of inequality with the recent work of Cowell on the generalized entropy families of income distribution and change indices. A ‘leftist’ measure of income distributional change is proposed, which is invariant to equal absolute changes in all incomes and which has other interesting properties.     

MEASURING THE DIVERSITY OF HOUSEHOLD SPENDING PATTERNS

Households tend to diversify their spending across a wide range of goods and services as they become more affluent. Recently, there has been growing interest in understanding the precise manner in which this spending diversification process takes place. We review what facts are known about this process and the underlying behavioural tendencies that are thought to drive it. In addition, we clarify the relationship between different approaches to measuring the level of spending diversity. A number of indices are employed, including measures based on joint probabilities, distances and the concept of entropy. Using UK household spending data, we show the extent to which these measures deliver different results and shed light on the nature of behavioural heterogeneity.