I discuss mechanisms linking health and inequality and review evidence for effects of income inequality on aggregate and individual mortality, over time and over space. I conclude that there is no direct link. Correlations come from factors other than income inequality itself, some of which are linked to broader notions of inequality and inequity that are most likely important for health. Whether income redistribution can improve population health does not depend on the existence of a direct link between income inequality and health and remains an open question.

The extent to which growth reduces global poverty has been disputed for 30 years. Although there is better data than ever before, controversies are not resolved. A major problem is that consumption measured from household surveys, which is used to measure poverty, grows less rapidly than consumption measured in national accounts, in the world as a whole, and in large countries, particularly India, China, and the US. In consequence, measured poverty has fallen less rapidly than appears warranted by measured growth in poor countries. One plausible cause is that richer households are less likely to participate in surveys. But growth in the national accounts is also upwardly biased, and consumption in the national accounts contains large and rapidly growing items that are not consumed by the poor and not included in surveys. So it is possible for consumption of the poor to grow less rapidly than national consumption, without any increase in measured inequality. Current statistical procedures in poor countries understate the rate of global poverty reduction, and overstate growth in the world.

The extent to which growth reduces global poverty has been disputed for 30 years. Although there are better data than ever before, controversies are not resolved. A major problem is that consumption measured from household surveys, which is used to measure poverty, grows less rapidly than consumption measured in national accounts, in the world as a whole and in large countries, particularly India, China, and the United States. In consequence, measured poverty has fallen less rapidly than appears warranted by measured growth in poor countries. One plausible cause is that richer households are less likely to participate in surveys. But growth in the national accounts is also upward biased, and consumption in the national accounts contains large and rapidly growing items that are not consumed by the poor and not included in surveys. So it is possible for consumption of the poor to grow less rapidly than national consumption, without any increase in measured inequality. Current statistical procedures in poor countries understate the rate of global poverty reduction, and overstate growth in the world.

This paper explores the relationship between adult heights and the distribution of income across populations of individuals. There is a long literature that examines the relationship between mean adult heights and living standards. If adult height is set by the balance between food intake and charges to disease in early childhood, it is informative about economic and epidemiological conditions in childhood. Because taller populations are better-off, more productive, and live longer, the relationship between childhood conditions and adult height has become an important focus in the study of the relationship between health and wealth. Here I follow one of the tributaries of this main stream. A relationship between income and height at the individual level has implications for the effects of income inequality on the distribution of heights. These relationships parallel, but are somewhat more concrete than, the various relationships between income inequality and health that have been debated in the economic and epidemiological literatures, Richard G. Wilkinson (1996), Angus Deaton (2003).

For thirty years it has been accepted that consumption is smooth because permanent income is smoother than measured income. This paper considers the evidence for the contrary position, that permanent income is in fact less smooth than measured income, so that the smoothness of consumption cannot be straightforwardly explained by permanent income theory. The paper argues that in postwar U.S. quarterly data, consumption is smooth because it responds with a lag to changes in income.

Recent years have seen widespread use of small-area maps based on census data enriched by relationships estimated from household surveys that predict variables, such as income, not covered by the census. The purpose is to obtain putatively precise estimates of poverty and inequality for small areas for which no or few observations are available in the survey. We argue that to usefully match survey and census data in this way requires a degree of spatial homogeneity for which the method provides no basis and which is unlikely to be satisfied in practice. We document the potential empirical relevance of such concerns using data from the 2000 census of Mexico.

A concept of demographic separability is proposed that formalizes the notion that there are groups of goods (adult goods) that have little or no relationship to specific classes of household demographics (the numbers or ages of children).That there exist adult goods demographically separable from children is a necessary but not sufficient condition for the validity of Rothbarth's method for measuring child costs. We propose two different methods for testing demographic separability and present results from a 1981 survey of Spain. The econometric evidence is in fair agreement with the theoretical presuppositions.

In this paper we analyze the relationship between turnover-driven growth and subjective well-being. Our model of innovation-led growth and unemployment predicts that: (i) the effect of creative destruction on expected individual welfare should be unambiguously positive if we control for unemployment, less so if we do not; (ii) job creation has a positive and job destruction has a negative impact on well-being; (iii) job destruction has a less negative impact in areas with more generous unemployment insurance policies; and (iv) job creation has a more positive effect on individuals that are more forward-looking. The empirical analysis using cross-sectional MSA (metropolitan statistical area)-level and individual-level data provide empirical support to these predictions.