Household welfare, precautionary saving, and social insurance under multiple sources of risk

This paper assesses the quantitative importance of a number of sources of income risk for household welfare and precautionary saving. To that end I construct a lifecycle consumption model in which household income is subject to shocks associated with disability, health, unemployment, job changes, wages, work hours, and a residual component of household income. I use PSID data to estimate the key processes that drive and affect household income, and then use the consumption model to: (i) quantify the welfare value to consumers of providing full, actuarially fair insurance against each source of risk and (ii) measure the contribution of each type of shock to the accumulation of precautionary savings. I find that the value of fully insuring disability, health, and unemployment shocks is extremely small (well below 1/10 of 1 percent of lifetime consumption in the baseline model). The gains from insuring shocks to the wage and to the residual component of household income are significantly larger (above 1% and 2% of lifetime consumption, respectively). These two shocks account for more than 60% of precautionary wealth.Income ; Households ; Saving and investment

Fluctuations in individual labor income: a panel VAR analysis

This paper studies variation in individual labor income over time using a panel vector autoregression (PVAR) in income, the wage rate, hours of work, and hours of unemployment. The framework is used to investigate how much of the residual variation in labor income is due to residual variation in the wage rate, work hours, and unemployment hours. I also explore the dynamic effects of unanticipated changes in each of the variables in the system, investigate their interactions, and assess their contribution to short-run and long-run income movements. The model is estimated on a sample of male household heads from the Panel Study of Income Dynamics (PSID). I find that innovations in the wage rate and work hours (conditional on unemployment) are about equally important in the short run. Wage innovations are very persistent, while the effect of changes in hours is mostly transitory. As a result, the wage rate is much more important in the determination of income movements in the long run. Innovations in unemployment have a relatively small, but very persistent effect on income which operates through the wage rate.Income ; Wages

Modeling Earnings Dynamics

In this paper we use indirect inference to estimate a joint model of earnings, employment, job changes, wage rates, and work hours over a career. Our model incorporates duration dependence in several variables, multiple sources of unobserved heterogeneity, job-specific error components in both wages and hours, and measurement error. We use the model to address a number of important questions in labor economics, including the source of the experience profile of wages, the response of job changes to outside wage offers, and the effects of seniority on job changes. We provide estimates of the dynamic response of wage rates, hours, and earnings to various shocks and measure the relative contributions of the shocks to the variance of earnings in a given year and over a lifetime. We find that human capital accounts for most of the growth of earnings over a career although job seniority and job mobility also play a significant role. Unemployment shocks have a large impact on earnings in the short run as well a substantial long long-term effect that operates through the wage rate. Shocks associated with job changes and unemployment make a large contribution to the variance of career earnings and operate mostly through the job-specific error components in wages and hours

Rising inequality: transitory or permanent? New evidence from a U.S. panel of household income 1987-2006

We use a new and large panel dataset of household income to shed light on the permanent versus transitory nature of rising inequality in individual male labor earnings and in total household income, both before and after taxes, in the United States over the period 1987-2006. Due to the quality and the significant size of our dataset, we are able to conduct our analysis using rich and precisely estimated error-components models of income dynamics. Our main specification finds evidence for a quadratic heterogeneous income profiles component and a random walk component in permanent earnings, and for a moving-average component in autoregressive transitory earnings. We find that the increase in inequality over our sample period was entirely permanent for male earnings, and predominantly permanent for household income. We also show that the tax system, though reducing inequality, nonetheless did not materially affect its increasing trend. Furthermore, we compare our model-based findings against those of simpler, non-model based inequality decomposition methods. We show that the results for the trends in the evolution of the permanent and transitory variances are remarkably similar across methods, whereas the results for the shares of those variances in cross-sectional inequality differ widely. Further investigation into the sources of these differences suggests that simpler methods produce erroneous decompositions because they cannot flexibly capture the relative degree of persistence of the transitory component of income.Income distribution - United States - Mathematical models