As GDP is a measure of market capacity and not economic well-being, this report has been commissioned to more accurately understand the social progress indicators of any given state. Gross domestic product (GDP) is the most widely used measure of economic activity. There are international standards for its calculation, and much thought has gone into its statistical and conceptual bases. But GDP mainly measures market production, though it has often been treated as if it were a measure of economic well-being. Conflating the two can lead to misleading indications about how well-off people are and entail the wrong policy decisions. One reason why money measures of economic performance and living standards have come to play such an important role in our societies is that the monetary valuation of goods and services makes it easy to add up quantities of a very different nature. When we know the prices of apple juice and DVD players, we can add up their values and make statements about production and consumption in a single figure. But market prices are more than an accounting device. Economic theory tells us that when markets are functioning properly, the ratio of one market price to another is reflective of the relative appreciation of the two products by those who purchase them. Moreover, GDP captures all final goods in the economy, whether they are consumed by households, firms or government. Valuing them with their prices would thus seem to be a good way of capturing, in a single number, how well-off society is at a particular moment. Furthermore, keeping prices unchanged while observing how quantities of goods and services that enter GDP move over time would seem like a reasonable way of making a statement about how society’s living standards are evolving in real terms. As it turns out, things are more complicated. First, prices may not exist for some goods and services (if for instance government provides free health insurance or if households are engaged in child care), raising the question of how these services should be valued. Second, even where there are market prices, they may deviate from society’s underlying valuation. In particular, when the consumption or production of particular products affects society as a whole, the price that individuals pay for those products will differ from their value to society at large. Environmental damage caused by production or consumption activities that is not reflected in market prices is a well-known example.

https://andrewoswald.com/docs/stiglitz20report_commission20final20200920sept.pdf

Report by the commission on the measurement of economic performance and social progress

We develop a theory of rational addiction in which rationality means a consistent plan to maximize utility over time. Strong addiction to a good requires a big effect of past consumption of the good on current consumption. Such powerful complementarities cause some steady states to be unstable. They are an important part of our analysis because even small deviations from the consumption at an unstable steady state can lead to large cumulative rises over time in addictive consumption or to rapid falls in consumption to abstention. Our theory also implies that "cold turkey" is used to end strong addictions, that addicts often go on binges, that addicts respond more to permanent than to temporary changes in prices of addictive goods, and that anxiety and tensions can precipitate an addiction.

https://sites.duke.edu/econ206_01_s2011/files/2015/04/14_TeamGrossman_RationalAddiction.pdf

A Theory of Rational Addiction

The inverse relationships between socioeconomic status (SES) and unhealthy behaviors such as tobacco use, physical inactivity, and poor nutrition have been well demonstrated empirically but encompass diverse underlying causal mechanisms. These mechanisms have special theoretical importance because disparities in health behaviors, unlike disparities in many other components of health, involve something more than the ability to use income to purchase good health. Based on a review of broad literatures in sociology, economics, and public health, we classify explanations of higher smoking, lower exercise, poorer diet, and excess weight among low-SES persons into nine broad groups that specify related but conceptually distinct mechanisms. The lack of clear support for any one explanation suggests that the literature on SES disparities in health and health behaviors can do more to design studies that better test for the importance of the varied mechanisms.

/pdf/socioeconomic-disparities-in-health-behaviors-55fg79n1kq.pdf

Socioeconomic Disparities in Health Behaviors

Mortality rates have fallen dramatically over time, starting in a few countries in the 18th century, and continuing to fall today. In just the past century, life expectancy has increased by over 30 years. At the same time, mortality rates remain much higher in poor countries, with a difference in life expectancy between rich and poor countries of also about 30 years. This difference persists despite the remarkable progress in health improvement in the last half century, at least until the HIV/AIDS pandemic. In both the time-series and the cross-section data, there is a strong correlation between income per capita and mortality rates, a correlation that also exists within countries, where richer, better-educated people live longer. We review the determinants of these patterns: over history, over countries, and across groups within countries. While there is no consensus about the causal mechanisms, we tentatively identify the application of scientific advance and technical progress (some of which is induced by income and facilitated by education) as the ultimate determinant of health. Such an explanation allows a consistent interpretation of the historical, cross-country, and within-country evidence. We downplay direct causal mechanisms running from income to health.

/pdf/the-determinants-of-mortality-3bnfivuqfy.pdf

The Determinants of Mortality

This chapter contains a detailed treatment of the human capital model of the demand for health which was originally developed in 1972. Theoretical predictions are discussed, and theoretical extensions of the model are reviewed. Empirical research that tests the predictions of the model or studies causality between years of formal schooling completed and good health is surveyed. The model views health as a durable capital stock that yields an output of healthy time. Individuals inherit an initial amount of this stock that depreciates with age and can be increased by investment. The household production function model of consumer behavior is employed to account for the gap between health as an output and medical care as one of many inputs into its production. In this framework the “shadow price” of health depends on many variables besides the price of medical care. It is shown that the shadow price rises with age if the rate of depreciation on the stock of health rises over the life cycle and falls with education (years of formal schooling completed) if more educated people are more efficient producers of health. An important result is that, under certain conditions, an increase in the shadow price may simultaneously reduce the quantity of health demanded and increase the quantities of health inputs demanded.

The Human Capital Model

Numerous studies by economists during the past decade have revealed a large, statistically significant correlation between health and years of schooling after controlling for differences in income and other variables. Cigarette smoking is a likely intervening variable because of the strong effect of smoking on morbidity and mortality, and because there is a strong negative correlation between smoking and years of schooling -- at least at high school levels and above. This paper tests the hypothesis that schooling causes differences in smoking behavior. We use retrospective smoking histories of 1,183 white, non-Hispanic men and women who had completed 12 to 18 years of schooling. The data were collected in 1979 by the Stanford University Heart Disease Prevention Program from randomly selected households in four small California cities. The most striking result is that the negative relation between schooling and smoking observed at age 24 is accounted for by differences in smoking behavior present at age 17, when all subjects were still in approximately the same grade. We conclude that additional years of schooling cannot be the cause of differential smoking behavior; one or more "third variables" must cause changes in both smoking and schooling. Analysis of smoking by cohort reveals that the schooling-smoking correlation developed only after the health consequences of smoking became widely known; it has remained strong even in the most recent cohorts. This implies that the mechanism behind the schooling-smoking correlation may also give rise to the schooling-health correlation.

https://papers.ssrn.com/sol3/Delivery.cfm?abstractid=351321

Schooling and Health: The Cigarette Connection

https://www.nber.org/system/files/working_papers/w0768/w0768.pdf

Phillip Farrell

Papers

Schooling and Health: The Cigarette Connection

Schooling and health: The cigarette connection☆

Schooling and Health: The Cigarette Connection