Business Cycles, Migration and Health

This paper uses data from the PSID to investigate how selective migration affects the relationship between business cycles and health. We show that, among the healthy, migration is used to insure against macroeconomic fluctuations. However, among the unhealthy, there is no relationship between migration and business cycles. In other words, illness erases a person’s ability to use migration to hedge against business cycle fluctuations. This suggests that recessions should induce an out-migration of disproportionately healthy people from economically depressed areas. This implies that - ceterus paribus - mortality and morbidity rates should be counter-cyclical.

Heterogeneity, State Dependence and Health

We investigate the evolution of health over the life-cycle. We allow for two sources of persistence: unobserved heterogeneity and state dependence. Estimation indicates that there is a large degree of heterogeneity. For half the population, there are modest degrees of state dependence. For the other half of the population, the degree of state dependence is near unity. However, this may be the result of a high frequency of people in our data who never exit healthy states, potentially resulting in a failure to pin down the state dependence parameter for this segment of the population. We conclude that individual characteristics that trace back to early adulthood and before can have far reaching effects on health.health, dynamic panel data models, gradient

Health Inequality over the Life-Cycle

We consider the covariance structure of health. Agents report their health status on the basis of a latent health stock that is determined by permanent and transitory shocks, and time invariant fixed effects. At age 25, permanent shocks account for 5% to 10% of the variation in health. At age 60, this percentage rise to between 60% and 80%. We document a gradient in which permanent shocks matter less for college-educated people and for women.health, dynamic panel data models, variance decomposition

Bounding Expected Per Capita Household Consumption in the Presence of Demographic Change

This paper deals with the measurement of per capita household consumption expenditures when the household's underlying demographic structure changes during the survey period. To do this, we provide a formal definition of precisely what it means to mis-measure the household's demographic structure. We then use assumptions on demographic processes within the household during the survey period to construct bounds on expected per capita consumption expenditures. We estimate these bounds using two surveys from El Salvador, a country in which household demographic structures are very fluid. Our results reveal that these bounds can be wide suggesting that the measurement error in the household's demographic structure is non-trivial. We conclude by showing that mis-measured household size can have important implications when identifying economies of scale within the household.Migration, Measurement Error, Semi-Parametric Bounds, Economies of Scale

Identifying State Dependence in Non-Stationary Processes

We consider the identification of state dependence in a non-stationary process of binary outcomes within the context of the dynamic logit model with time-variant transition probabilities and an arbitrary distribution for the unobserved heterogeneity. We derive a simple identification result that allows us to calculate a test for state dependence in this model. We also consider alternative tests for state dependence that will have desirable properties only in stationary processes and derive their asymptotic properties when the true underlying process is non-stationary. Finally, we provide Monte Carlo evidence that shows a range of non-stationarity in which the effects of mis-specifying the binary process as stationary are not too large.Dynamic Panel Data Models, State Dependence, Non-Stationary Processes

Income Risk and Health

We investigate the impact of exogenous income shocks on health using twenty years of data from the Panel Study of Income Dynamic. To unravel the impact of income on health from unobserved heterogeneity and reverse causality, we employ techniques from the literature on the estimation of dynamic panel data models. Contrary to much of the previous literature on the gradient, we find that, on average, adverse income shocks lead to a deterioration of health. These effects are most pronounced for working-aged men and are dominated by transitions into the very bottom of the earnings distribution. We also provide suggestive evidence of an association between negative income shocks and higher mortality for working-aged men.Gradient, Recessions, Health, Dynamic Panel Data Models

Mismeasured Household Size and Its Implications for the Identification of Economies of Scale

We consider the possibility that demographic variables are measured with errors which arise because household surveys measure demographic structures at a point-in-time, whereas household composition evolves throughout the survey period. We construct and estimate sharp bounds on household size and find that the degree of these measurement errors is non-trivial. However, while these errors have the potential to resolve the Deaton-Paxson paradox, they fail to do so.migration, measurement error, semi-parametric bounds, economies of scale

Income Volatility and Health

We investigate the impact of exogenous income fluctuations on health using twenty years of data from the Panel Study of Income Dynamics. To unravel the impact of income on health from unobserved heterogeneity and reverse causality, we employ techniques from the literature on the estimation of dynamic panel data models. Contrary to much of the previous literature on health and socio-economic status, we find that, on average, adverse income shocks lead to a deterioration of health. These effects are most pronounced for working-aged men and are dominated by transitions into the very bottom of the earnings distribution. We also provide suggestive evidence of an association between negative income shocks and higher mortality for working-aged men.Gradient, Health, Dynamic Panel Data Models, Recessions

Heterogeneity, State Dependence and Health

In this paper, we use longitudinal data on Self-Reported Health Status from the Panel Study of Income Dynamics to estimate a model of the evolution of health over the life-cycle. The model allows for two sources of persistence in health: unobserved heterogeneity, which models an individual’s (unobserved) ability to cope with health shocks, and state dependence, which models the extent to which the ability to cope with health shocks depends on health status. We allow for flexibility in both sources of persistence. Estimation indicates that heterogeneity is an important determinant of health suggesting that a person’s health today has important antecedents earlier on in life. We also find evidence of state dependence. However, its magnitude depends crucially on the individual’s age and unobserved heterogeneity. The relative contributions of heterogeneity and state dependence that we uncover have different implications for how health policy should be conducted.health, dynamic panel data models, gradient

Health Inequality over the Life-Cycle

We investigate the evolution of health inequality over the life-course. Health is modeled as a latent variable that is determined by three factors: endowments, and permanent and transitory shocks. We employ Simulated Minimum Distance and the Panel Study of Income Dynamics to estimate the model. We estimate that permanent shocks account for under 10% of the total variation in health for the colleged educated, but between 35% and 70% of total health variability for people without college degrees. Consistent with this, we find that health inequality moves substantially more slowly over the life-course for the college educated.health, dynamic panel data models, variance decomposition