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Poverty measures set a poverty line or threshold and then evaluate resources against that threshold. The official poverty measure is flawed on both counts: it uses thresholds that are outdated and are not adjusted appropriately for the needs of different types of individuals and households; and it uses an incomplete measure of resources which fails to take into account the full range of income and expenses that individuals and households have. Because of these (and other) failings, statistics using the official poverty measure do not provide an accurate picture of poverty or the role of government policies in combating poverty. To address these well-known limitations, the Census Bureau recently implemented a supplemental poverty measure (SPM) which applies an improved set of thresholds and a more comprehensive measure of resources. In this report we apply an alternative poverty measure which differs from the SPM in only one respect. Instead of having a threshold that is re-calculated over time, we use today's threshold and carry it back historically by adjusting it for inflation using the CPI-U-RS. Because this alternative measure is anchored with today's SPM threshold, we refer to as an anchored supplemental poverty measure or anchored SPM for short. In addition to the reasons discussed above, another advantage of an anchored SPM (or any absolute poverty measure, for that matter) is that poverty trends resulting from such a measure can be explained by changes in income and net transfer payments (cash or in kind). Trends in poverty based on a relative measure (e.g. SPM poverty), on the other hand, could be due to over time changes in thresholds. Thus, an anchored SPM arguably provides a cleaner measure of how changes in income and net transfer payments have affected poverty historically

We use the methodology developed in a previous study to individualise all incomes reported in the European Union Statistics on Income and Living Conditions (2006). Based on individual incomes we compute financial-dependency rates which are compared with the household-level at-risk-of-poverty rates defined by the European Commission. The determinants of financial dependency are studied by means of descriptive statistics and by the estimation of bivariate probit regressions for men and women. We cover nine European countries. Finally, four new indicators are proposed to complement the Laeken indicators.

ABSTRACTThe paper develops simple statistical test procedures for generalized decomposable poverty measures. It is shown that the estimates of the decomposable poverty indices, including the overall and various subgroup poverty indices, have (asymptotic) jointly normal distributions. The full variance‐covariance structure is derived and can be estimated consistently without prior specification of the population density underlying the sample data. The (overall/decomposed) poverty indices can thus be used as tools for statistical inference instead of simply as descriptive statistics. We illustrate the test procedure by examining the contributions of whites and non‐whites to total US poverty in 1975 and 1985.