Earnings Dynamics and Its Intergenerational Transmission: Evidence from Norway, Quantitative Ecoomics, forthcoming.(with E. Halvorsen and S. Salgado )
Part of the Global Income Dynamics Project (by F. Guvenen, L. Pistaferri and G. Violante), which aims to produce a harmonized cross-country database containing detailed and relevant statistics on individual- and household-level wages, earnings, and related labor market measures. The STATA code used to produce the harmonized statistics in all countries is prepared by S. Salgado and myself.
Abstract: Using administrative data from Norway, we first present stylized facts on labor earnings dynamics between 1993 and 2017 and its heterogeneity across narrow population groups. We then investigate the parents' role in children's income dynamics—the intergenerational transmission of income dynamics. We find that children of high-income, high-wealth fathers enjoy steeper income growth over the life cycle and face more volatile but more positively skewed income changes, suggesting that they are more likely to pursue high-return, high-risk careers. Children of poorer fathers also face more volatile incomes, but theirs grow more gradually and are more left skewed. Furthermore, the income dynamics of fathers and children are strongly correlated. In particular, children of fathers with steeper life-cycle income growth, more volatile incomes, or higher downside risk also have income streams of similar properties. We also confirm that fathers' significant role in workers' income dynamics is not simply spurious because of omitted variables, such as workers' own permanent income. These findings shed new light on the determinants of intergenerational mobility.
What Do Data on Millions of U.S. Workers Say About Lifecycle Labor Income Risk?, Econometrica, 2021(with F. Guvenen, F. Karahan, and J. Song)
2019 Draft Downloadable data moments in 2019 draft Parameter estimates for the income processes Older Version (2016) (based on wage/salary + self employment income over 1994-2013): Data Appendix: Moments For Men Moments For WomenOlder Version (2015) (based on wage/salary income over 1978-2013): Data Appendix
Media Coverage: A nontechnical summary blog post on VoxEU Washington Post Slate The Telegraph Bloomberg/Business Bloomberg II CNBC
We study individual male earnings dynamics over the life cycle using panel data on millions of U.S. workers. Using nonparametric methods, we first show that the distribution of earnings changes exhibits substantial deviations from lognormality, such as negative skewness and very high kurtosis. Further, the extent of these non-normalities varies significantly with age and earnings level, peaking around age 50 and between the 70th and 90th percentiles of the earnings distribution. Second, we estimate nonparametric impulse response functions and find important asymmetries: Positive changes for high-income individuals are quite transitory, whereas negative ones are very persistent; the opposite is true for low-income individuals. Third, we turn to long-run outcomes and find substantial heterogeneity in the cumulative growth rates of earnings and the total number of years individuals spend nonemployed between ages 25 and 55. Finally, by targeting these rich sets of moments, we estimate stochastic processes for earnings that range from the simple to the complex. Our preferred specification features normal mixture innovations to both persistent and transitory components and includes state-dependent long-term nonemployment shocks with a realization probability that varies with age and earnings.
This paper studies business cycle variation in individual earnings risk using administrative SSA dataset. We document two sets of results. First, contrary to past research, we find that the variance of idiosyncratic earnings shocks is not countercyclical. Instead, it is the left-skewness of shocks that is strongly countercyclical: during recessions, the upper end of the shock distribution collapses—large upward earnings movements become less likely—whereas the bottom end expands–-large drops in earnings become more likely. Thus, while the dispersion of shocks does not increase, shocks become more left skewed and, hence, risky during recessions. Second, we find that the fortunes during recessions are predictable by observable characteristics before the recession. For example, prime-age workers that enter a recession with high earnings suffer substantially less compared with those who enter with low earnings. Finally, the cyclical nature of earnings risk is dramatically different for the top 1% compared with all other individuals—even those in the top 2% to 5%.
Taxation of Human Capital and Wage Inequality: A Cross-Country Analysis, Review of Economic Studies, 2014(with F. Guvenen and B. Kuruscu)
Wage inequality has been significantly higher in the U.S. than in continental European countries (CEU) since the 1970s. Moreover, this inequality gap has further widened during this period as the U.S. has experienced a large increase in wage inequality, whereas the CEU has seen only modest changes. This article studies the role of labour income tax policies for understanding these facts, focusing on male workers. We construct a life cycle model in which individuals decide each period whether to go to school, work, or stay non-employed. Individuals can accumulate human capital either in school or while working. Wage inequality arises from differences across individuals in their ability to learn new skills as well as from idiosyncratic shocks. Progressive taxation compresses the (after-tax) wage structure, thereby distorting the incentives to accumulate human capital, in turn reducing the cross-sectional dispersion of (before-tax) wages. Consistent with the model, we empirically document that countries with more progressive labour income tax schedules have (i) significantly lower before-tax wage inequality at different points in time and (ii) experienced a smaller rise in wage inequality since the early 1980s. We then study the calibrated model and find that these policies can account for half of the difference between the U.S. and the CEU in overall wage inequality and 84% of the difference in inequality at the upper end (log 90–50 differential). In a two-country comparison between the U.S. and Germany, the combination of skill-biased technical change and changing progressivity of tax schedules explains all the difference between the evolution of inequality in these two countries since the early 1980s.
On the Persistence of Income Shocks over the Life Cycle: Evidence, Theory, and Implications, Review of Economic Dynamics, 2013(with F. Karahan)
How does the persistence of earnings change over the life cycle? Do workers at different ages face the same variance of idiosyncratic earnings shocks? This paper proposes a novel specification for residual earnings that allows for an age profile in the persistence and variance of labor income shocks. We show that the statistical model is identified, and we estimate it using Panel Study of Income Dynamics data. We find that shocks to earnings are only moderately persistent (around 0.75) for young workers. Persistence rises with age, up to unity, until midway through life. The variance of persistent shocks exhibits a U-shaped profile over the life cycle (with a minimum of 0.01 and a maximum of 0.05). These results suggest that the standard specification in the literature (with age-invariant persistence and variance) cannot capture the earnings dynamics of young workers. We also argue that a calibrated job turnover model can account for these nonflat profiles. The key idea is that workers sort into better jobs and settle down as they age; in turn, magnitudes of wage growth rates decline, thereby decreasing the variance of shocks. Furthermore, the decline in job mobility results in higher persistence. Finally, we investigate the implications of age profiles for consumption-savings behavior. The welfare cost of idiosyncratic risk implied by the age-dependent income process is up to 1.6 percent of lifetime consumption lower compared with its age-invariant counterpart. This difference is mostly due to a higher degree of consumption insurance for young workers, for whom persistence is moderate. These results suggest that age profiles of persistence and variances should be taken into account when calibrating life-cycle models.
Heterogeneous Scarring Effects of Full-Year Nonemployment, American Economic Review P&P, 2017(with F. Guvenen, F. Karahan and J. Song)
We use administrative data from the SSA to study not just the average scarring effects but investigate how the scarring effects vary with worker characteristics, such as age, skill level, and work history. Rather than focusing on involuntary job losses during mass layoffs, we consider more broadly the long lasting effects of spending at least one year nonemployment regardless of the reasons behind it. We find that the scarring effects of nonemployment vary greatly across workers with different recent earnings. In particular, low-recent-earnings workers as well as those in the top 5 percent suffer larger scarring effects of nonemployment. Furthermore, the large losses mostly result from the higher incidence of future nonemployment for the treatment group, rather than their lower earnings conditional on working. This effect is especially strong for low-income individuals.
Anatomy of Lifetime Earnings Inequality: Heterogeneity in Job Ladder Risk vs Human Capital, revision requested by the JPE-Macro(with F. Karahan, and J. Song)
We study the determinants of lifetime earnings (LE) inequality in the U.S. by focusing on job ladder dynamics and on-the-job learning as sources of wage growth. Using administrative data, we document that i) lower LE workers change jobs more often, which is mainly driven by nonemployment; ii) average annual earnings growth for job stayers is similar, around 2% in the bottom two-thirds of the LE distribution, whereas for job switchers it rises with LE; iii) top LE workers enjoy around 10% average earnings growth regardless of job switching. We estimate a job ladder model with on-the-job learning featuring a rich set of worker types and firm heterogeneity. We find that the vast differences across worker types in job ladder risk—job loss, job finding, and contact rates—account for 80% of wage growth differences among workers below median LE. Above the median, almost all lifetime wage growth differences are a result of Pareto-distributed learning ability. We conclude that different economic forces are driving the inequality in different parts of the LE distribution.
This paper examines whether nonlinear and non-Gaussian features of earnings dynamics are caused by hours or hourly wages. Our findings from the Norwegian administrative and survey data are as follows: (i) Nonlinear mean reversion in earnings is driven by the dynamics of hours worked rather than wages since wage dynamics are close to linear while negative changes to hours are transitory and positive changes are persistent. (ii) Large earnings changes are driven equally by hours and wages, whereas small changes are associated mainly with wage shocks. (iii) Both wages and hours contribute to negative skewness and high kurtosis for earnings changes, although hour-wage interactions are quantitatively more important. (iv) When considering household earnings and disposable household income, the deviations from normality are mitigated relative to individual labor earnings: changes in disposable household income are close to symmetric and less leptokurtic.
Preventive vs. Curative Medicine: A Macroeconomic Analysis of Health Care over the Life Cycle, revision requested by the Review of Economic Studies
This paper studies differences in health care usage and health outcomes between low- and high-income individuals. Using data from the Medical Expenditure Panel Survey (MEPS) I find that early in life the rich spend significantly more on health care, whereas from midway through life until very old age the medical spending of the poor dramatically exceeds that of the rich. In addition, low-income individuals are less likely to incur any medical expenditures in a given year, yet, when they do incur medical expenditures, the amounts are more likely to be extreme. To account for these facts, I develop and estimate a life-cycle model of two distinct types of health capital: preventive and physical. Physical health capital determines survival probabilities, whereas preventive health capital governs the endogenous distribution of shocks to physical health capital, thereby controlling the life expectancy. Moreover, I incorporate important features of the U.S. health care system such as private health insurance, Medicaid, and Medicare. In the model, optimal expected life span is longer for the rich, which can only be achieved by greater investment in preventive health capital. Therefore, as they age, their health shocks grow milder compared to those of the poor, and in turn they incur lower curative medical expenditures. Public insurance for the elderly amplifies this mechanism by hampering the incentives of the poor to invest in preventive health capital. I use the model to examine a counterfactual economy with universal health insurance in which 75% of preventive medical spending is reimbursed on top of existing coverage in the benchmark economy. My results suggest that policies encouraging the use of health care by the poor early in life produce significant welfare gains, even when fully accounting for the increase in taxes required to pay for them.
Work In Progress
We find that workers in smaller and shrinking firms experience lower earnings growth with more volatile and left skewed earnings changes as well as higher unemployment risk. When we control for unobservable worker and firm types jointly, we conclude that person effects explain majority of differences in earnings dynamics while firm effects explain relatively little. These findings have important implications for public policy such as unemployment insurance..
Code & Data
Part of the Global Income Dynamics Project, which aims to produce a harmonized cross-country database containing detailed and relevant statistics on individual- and householdlevel wages, earnings, and related labor market measures. The STATA code used to produce the harmonized statistics in all countries is prepared by S. Salgado and myself.