Income, Aging, Health and Wellbeing Around the World: Evidence from the Gallup World Poll

During 2006, the Gallup Organization conducted a World Poll that used an identical questionnaire for national samples of adults from 132 countries. I analyze the data on life satisfaction (happiness) and on health satisfaction and look at their relationships with national income, age, and life-expectancy. Average happiness is strongly related to per capita national income; each doubling of income is associated with a near one point increase in life satisfaction on a scale from 0 to 10. Unlike most previous findings, the effect holds across the range of international incomes; if anything, it is slightly stronger among rich countries. Conditional on national income, recent economic growth makes people unhappier, improvements in life-expectancy make them happier, but life-expectancy itself has little effect. Age has an internationally inconsistent relationship with happiness. National income moderates the effects of aging on self-reported health, and the decline in health satisfaction and rise in disability with age are much stronger in poor countries than in rich countries. In line with earlier findings, people in much of Eastern Europe and in the countries of the former Soviet Union are particularly unhappy and particularly dissatisfied with their health, and older people in those countries are much less satisfied with their lives and with their health than are younger people. HIV prevalence in Africa has little effect on Africans' life or health satisfaction; the fraction of Kenyans who are satisfied with their personal health is the same as the fraction of Britons and higher than the fraction of Americans. The US ranks 81st out of 115 countries in the fraction of people who have confidence in their healthcare system, and has a lower score than countries such as India, Iran, Malawi, or Sierra Leone. While the strong relationship between life-satisfaction and income gives some credence to the measures, as do the low levels of life and health satisfaction in Eastern Europe and the countries of the former Soviet Union, the lack of correlations between life and health satisfaction and health measures shows that happiness (or self-reported health) measures cannot be regarded as useful summary indicators of human welfare in international comparisons.

Saving and Liquidity Constraints

This paper is concerned with the theory of saving when consumers are not permitted to borrow, and with the ability of such a theory to account for some of the stylized facts of saving behavior. When consumers are relatively impatient, and when labor income is independently and identically distributed over time, assets act like a buffer stock, protecting consumption against bad draws of income. The precautionary demand for saving interacts with the borrowing constraints to provide a motive for holding assets. If the income process is positively autocorrelated, but stationary, assets are still used to buffer consumption, but do so less effectively, and at a greater cost in terms of foregone consumption. In the limit, when labor income is a random walk, it is optimal for impatient liquidity constrained consumers simply to consume their incomes. As a consequence, a liquidity constrained representative agent cannot generate aggregate U.S. saving behavior if that agent receives aggregate labor income. Either there is no saving, when income is a random walk, or saving is contracyclical over the business cycle, when income changes are positively autocorrelated. However, in reality, microeconomic income processes do not resemble their average, and it is possible to construct a model of microeconomic saving under liquidity constraints which, at the aggregate level, reproduces many of the stylized facts in the actual data. While it is clear that many households are not liquidity constrained, and do not behave as described here, the models presented in the paper seem to account for important aspects of reality that are not explained by traditional life-cycle models.

Health, Inequality, and Economic Development

I explore the connection between income inequality and health in both poor and rich countries. I discuss a range of mechanisms, including nonlinear income effects, credit restrictions, nutritional traps, public goods provision, and relative deprivation. I review the evidence on the effects of income inequality on the rate of decline of mortality over time, on geographical pattens of mortality, and on individual-level mortality. Much of the literature needs to be treated skeptically, if only because of the low quality of much of the data on income inequality. Although there are many puzzles that remain, I conclude that there is no direct link from income inequality to ill-health; individuals are no more likely to die if they live in more unequal places. The raw correlations that are sometimes found are likely the result of factors other than income inequality, some of which are intimately linked to broader notions of inequality and unfairness. That income inequality itself is not a health risk does not deny the importance for health of other inequalities, nor of the social environment. Whether income redistribution can improve population health does not depend on a direct effect of income inequality and remains an open question.

Data for monitoring the poverty MDG

human development, millennium development goals, mdgs

Inequalities in Income and Inequalities in Health

What is inequality in health? Are economists' standard tools for measuring income inequality relevant or useful for measuring it? Does income protect health and does income inequality endanger it? I discuss two different concepts of health inequality and relate each of them to the literature on the inequality in income. I propose a model in which each individual's health is related to his or her status within a reference group as measured by income relative to the group mean. Income inequality, whether within groups or between them, has no effect on average health. Even so, the slope of the relationship between health and income, the gradient,' depends on the ratio of between- to within-group inequality. The model is extended to allow income inequality to play a direct role in determining health status. Empirical evidence on cross-country income inequality and life-expectancy within the OECD, and on time series for the U.S., Britain, and Japan, provides little support for the idea that inequality is a health hazard at the national level. Birth cohorts in the US between 1981 and 1993 show no relationship between mortality and income inequality. However, there is a well-defined health gradient in these data, and its slope increases with cohort income inequality.

Mortality, Income, and Income Inequality Over Time in Britain and the United States

We investigate age-specific mortality in Britain and the United States since 1950. Neither trends in income nor in income inequality provide plausible explanations. Britain and the US had different patterns of income growth but similar patterns of mortality decline. Patterns of income inequality were similar in both countries, but adult and elderly mortality rates declined most rapidly during the period when inequality increased. Changes in the rate of mortality decline in the US led changes in Britain by about four years, most notably for infant and older adult mortality where there have been significant technical improvements in treatment. British mortality is lower, but the schedules cross at around age 65. This pattern was established before Medicare, and most likely comes from rationing by age in Britain. Merged income, income inequality, and mortality data on an age/year (or cohort/year) basis show no evidence that income has any effect on mortality in Britain. Education is protective, but less so than in the US. Understanding the effect of income on mortality presents many puzzles, between countries, and between analyses at different levels of aggregation. Our results suggest an important role for medical technology in determining the rate of mortality decline since 1950.

NUTRITION IN INDIA: FACTS AND INTERPRETATIONS

The Indian economy has recently grown at historically unprecedented rates and is now one of the fastest-growing economies in the world. Real GDP per head grew at 3.95 percent a year from 1980 to 2005, and at 5.4 percent a year from 2000 to 2005. Measured at international prices, real per capita income in India, which was two-thirds of Kenya’s in 1950, and about the same as Nigeria’s, is now two and a half times as large as per capita income in both countries. Real per capita consumption has also grown rapidly, at 2.2 percent a year in the 1980s, at 2.5 percent a year in the 1990s, and at 3.9 percent a year from 2000 to 2005. Although the household survey data show much slower rates of per capita consumption growth than do these national accounts estimates, even these slower growth rates are associated with a substantial decrease in poverty since the early 1980s, Deaton and Drèze (2002), Himanshu (2007). Yet, per capita calorie intake is declining, as is the intake of many other nutrients; indeed fats are the only major nutrient group whose per capita consumption is unambiguously increasing. Today, more than three quarters of the population live in households whose per capita calorie consumption is less than 2,100 in urban areas and 2,400 in rural areas – numbers that are often cited as “minimum requirements” in India. A related concern is that anthropometric indicators of nutrition in India, for both adults and children, are among the worst in the world. Furthermore, the improvement of these measures of nutrition appears to be slow relative to what might be expected in the light of international experience and of India’s recent high rates of economic growth. Indeed, according to the National Family Health Survey, the proportion of underweight children remained virtually unchanged between 1998-99 and 2005-06 (from 47 to 46 percent for the age group of 0-3 years). 2 Undernutrition levels in India remain higher even than for most countries of sub-Saharan Africa, even though those countries are currently much poorer than India, have grown much more slowly, and have much higher levels of infant and child mortality. In this paper, we do not attempt to provide a complete and fully documented story of poverty, nutrition and growth in India. In fact, we doubt that such an account is currently possible. Instead, our aim is to present the most important facts, to point to a number of unresolved puzzles, and to present an outline of a coherent story that is consistent with the facts. As far as the decline in per capita calorie consumption is concerned, our leading hypothesis, on which much work remains to be done, is that while real incomes and real wages have increased (leading to some nutritional improvement), there has been an offsetting reduction in calorie requirements, due to declining levels of physical activity and possibly also to various improvements in the health environment. The net effect has been a slow reduction in per capita calorie consumption. Whatever the explanation, there is historical evidence of related episodes in other countries, for example in Britain from 1775 to 1850, where in spite of rising real wages, there was no apparent increase in the real consumption of food, Clark et al (1995). Per capita calorie consumption also appears to have declined in contemporary China in the 1980s and 1990s (a period of rapid improvement in nutrition indicators such as height and weight), see Du, Lu, Zhai and Popkin (2002). One of our main points is that, just as there is no tight link between incomes and calorie consumption, there is no tight link between the numbers of calories consumed and nutritional or health status. Although the number of calories is important, so are other factors, such as a balanced diet containing a reasonable proportion of fruits, vegetables, and fats, not just calories from cereals, as are factors that affect the need for and retention of calories, such as activity 3 levels, clean water, sanitation, good hygiene practices, and vaccinations. Because of changes in these other factors, the fact that people are increasingly choosing away from a diet that is heavy in cereals does not imply that nutritional status will automatically get worse. Nor should a reduction in calories associated with lower activity levels be taken to mean that Indians are currently adequately nourished; nothing could be further from the truth. We start by documenting the decline in per capita calorie consumption (Section 2.1), as well as the state of malnutrition (Section 2.2). We then look at possible reasons for the reduction in calories (Section 3.1), and try to tease out how it fits into the general picture of economic growth and malnutrition in India (Section 3.2). Section 4 concludes. We emphasize at the outset that our analysis covers the period up to 2006, so that we do not discuss what has happened to calorie consumption or to nutritional status in the subsequent two years, during which there has been a marked increase in the price of food, both in India and around the world.

Consumption, health, gender, and poverty

Standard methods of measuring poverty assume that an individual is poor if he or she lives in a family whose income or consumption lies below an appropriate poverty line. Such methods provide only limited insight into male and female poverty separately. Nevertheless, there are reasons why household resources are linked to the gender composition of the household: women's earnings are often lower than men's; families in some countries control their fertility through differential stopping rules; and women live longer than men. It is also possible to link family expenditure patterns to the gender composition of the household, something the authors illustrate using data from India and South Africa. Such a procedure provides useful information on who gets what, but cannot tell us how total resources are allocated between males and females. More can be gleaned from data on consumption by individual household members,and for many goods, collecting such information is good survey practice in any case. Even so, it will be some time before such information can be used routinely to produce estimates of poverty by gender. A more promising approach is likely to come within a broader definition of poverty that includes health (and possibly education) as well as income. The authors discuss recent work on collecting self-reported measures of nonfatal health and argue that such measures are already useful for assessing the relative health status of males and females. The evidence is consistent with non-elderly women generally having poorer health than non-elderly men. The authors emphasize the importance of simultaneously measuring poverty in multiple dimensions. The different components of well-being are correlated, and it is misleading to look at any one in isolation from the others.Housing&Human Habitats,Public Health Promotion,Population&Development,Health Monitoring&Evaluation,Environmental Economics&Policies,Health Monitoring&Evaluation,Environmental Economics&Policies,Population&Development,Housing&Human Habitats,Poverty Lines

Measuring Poverty in a Growing World (Or Measuring Growth in a Poor 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