Fatih Guvenen joined the Federal Reserve Bank of Minneapolis as a visiting scholar in 2008. He is currently a consultant in the Research Department and is a professor of economics at the University of Minnesota.
Fatih received his M.Sc. and Ph.D. in economics from Carnegie Mellon University. He also holds a B.Sc. in electrical and electronics engineering from Bilkent University (Turkey). He is a research associate at the National Bureau of Economic Research (EF&G Program) and served as an advisor to the Central Bank of Turkey from 2013 to 2015.
Fatih’s current research focuses on topics at the intersection of macroeconomics and inequality, including the causes and consequences of wage and earnings inequality, how rising wage dispersion among workers is linked to rising dispersion among their employers, and how individual-level wage and earnings risk varies over the life cycle and over the business cycle.
Fatih is an associate editor for the Review of Economic Dynamics and the Journal of Monetary Economics. Fatih’s work has appeared in a number of prominent economics journals, including the American Economic Review, Econometrica, the Review of Economic Studies, the Journal of Political Economy, and the Journal of Monetary Economics. He has a forthcoming book with Princeton University Press, entitled Quantitative Economics with Heterogeneity: An A-to-Z Guidebook.
How does wealth taxation differ from capital income taxation? When the return on investment is equal across individuals, a well-known result is that the two tax systems are equivalent. Motivated by recent empirical evidence documenting persistent heterogeneity in rates of return across individuals, we revisit this question. With such heterogeneity, the two tax systems have opposite implications for both efficiency and inequality. Under capital income taxation, entrepreneurs who are more productive, and therefore generate more income, pay higher taxes. Under wealth taxation, entrepreneurs who have similar wealth levels pay similar taxes regardless of their productivity, which expands the tax base, shifts the tax burden toward unproductive entrepreneurs, and raises the savings rate of productive ones. This reallocation increases aggregate productivity and output. In the simulated model parameterized to match the US data, replacing the capital income tax with a wealth tax in a revenue-neutral fashion delivers a significantly higher average lifetime utility to a newborn (about 7.5% in consumption-equivalent terms). Turning to optimal taxation, the optimal wealth tax (OWT) in a stationary equilibrium is positive and yields even larger welfare gains. In contrast, the optimal capital income tax (OCIT) is negative—a subsidy—and large, and it delivers lower welfare gains than the wealth tax. Furthermore, the subsidy policy increases consumption inequality, whereas the wealth tax reduces it slightly. We also consider an extension that models the transition path and find that individuals who are alive at the time of the policy change, on average, would incur large welfare losses if the new policy is OCIT but would experience large welfare gains if the new policy is an OWT. We conclude that wealth taxation has the potential to raise productivity while simultaneously reducing consumption inequality.
Official statistics display a significant slowdown in U.S. aggregate productivity growth that begins in 2004. We show how offshore profit shifting by U.S. multinational enterprises affects GDP and, thus, productivity measurement. Under international statistical guidelines, profit shifting causes part of U.S. production generated by multinationals to be excluded from official measures of U.S. production. Profit shifting has increased significantly since the mid-1990s, resulting in lower measures of U.S. aggregate productivity growth. We construct an alternative measure of value added that adjusts for profit shifting. The adjustments raise aggregate productivity growth rates by 0.09 percent annually for 1994-2004, 0.24 percent annually for 2004-2008, and lowers annual aggregate productivity growth rates by 0.09 percent after 2008. Our adjustments mitigate, but do not eliminate, the measured productivity slowdown. The adjustments are especially large in R&D-intensive industries, which most likely produce intangible assets that facilitate profit shifting. The adjustments boost value added in these industries by as much as 8 percent in the mid-2000s.
We use a massive, matched employer-employee database for the United States to analyze the contribution of firms to the rise in earnings inequality from 1978 to 2013. We ﬁnd that one-third of the rise in the variance of (log) earnings occurred within firms, whereas two-thirds of the rise occurred between firms. However, this rising between-firm variance is not accounted for by the firms themselves: the firm-related rise in the variance can be decomposed into two roughly equally important forces—a rise in the sorting of high-wage workers to high-wage firms and a rise in the segregation of similar workers between firms. In contrast, we do not ﬁnd a rise in the variance of firm-speciﬁc pay once we control for worker composition. Instead, we see a substantial rise in dispersion of person-speciﬁc pay, accounting for 68% of rising inequality, potentially due to rising returns to skill. The rise in between-firm variance, mostly due to worker sorting and segregation, accounted for a particularly large share of the total increase in inequality in smaller and medium firms (explaining 84% for firms with fewer than 10,000 employees). In contrast, in the very largest firms with 10,000+ employees, 42% of the increase in the variance of earnings took place within firms, driven by both declines in earnings for employees below the median and a substantial rise in earnings for the 10% best-paid employees. However, because of their small number, the contribution of the very top 50 or so earners at large firms to the overall increase in within-firm earnings inequality is small.
We revisit recent empirical evidence about the rise in top income inequality in the United States, drawing attention to key issues that we believe are critical for an informed discussion about changing inequality since 1980: the definition of income (labor versus total), the unit of analysis (individual versus tax unit), the importance of partnership and S-corporation income, income shifting between the corporate and personal sectors in response to tax incentives, the definition of the top of the distribution, and trends in the middle and bottom of the distribution. Our goal is to inform researchers, policymakers, and journalists who are interested in top income inequality.
Income inequality is a topic of much research and heated debate—concern well warranted given the substantial and continuing rise in inequality over the past four decades. But income risk—intimately related and arguably of equal concern to workers, families and firms—has received far less attention. This essay seeks to redress that imbalance. It provides a close look at income risk, discussing findings from recent research that uses innovative technique and draws upon a wealth of new data.
The magnitude of and heterogeneity in systematic earnings risk has important implications for various theories in macro, labor, and ﬁnancial economics. Using administrative data, we document how the aggregate risk exposure of individual earnings to GDP and stock returns varies across gender, age, the worker’s earnings level, and industry. Aggregate risk exposure is U-shaped with respect to the earnings level. In the middle of the earnings distribution, aggregate risk exposure is higher for males, younger workers, and those in construction and durable manufacturing. At the top of the earnings distribution, aggregate risk exposure is higher for older workers and those in ﬁnance. Workers in larger employers are less exposed to aggregate risk, but they are more exposed to a common factor in employer-level earnings, especially at the top of the earnings distribution. Within an employer, higher-paid workers have higher exposure to employer-level risk than lower-paid workers.
What determines the earnings of a worker relative to his peers in the same occupation? What makes a worker fail in one occupation but succeed in another? More broadly, what are the factors that determine the productivity of a worker-occupation match? In this paper, we propose an empirical measure of skill mismatch for a worker-occupation match, which sheds light on these questions. This measure is based on the discrepancy between the portfolio of skills required by an occupation and the portfolio of abilities possessed by a worker for learning those skills. This measure arises naturally in a dynamic model of occupational choice and human capital accumulation with multidimensional skills and Bayesian learning about one’s ability to learn these skills. In this model, mismatch is central to the career outcomes of workers: it reduces the returns to occupational tenure, and it predicts occupational switching behavior. We construct our empirical analog by combining data from the National Longitudinal Survey of Youth 1979 (NLSY79), the Armed Services Vocational Aptitude Battery (ASVAB) on workers, and the O*NET on occupations. Our empirical results show that the effects of mismatch on wages are large and persistent: mismatch in occupations held early in life has a strong negative effect on wages in future occupations. Skill mismatch also significantly increases the probability of an occupational switch and predicts its direction in the skill space. These results provide fresh evidence on the importance of skill mismatch for the job search process.
We study the evolution of individual labor earnings over the life cycle using a large panel data set of earnings histories drawn from U.S. administrative records. Using fully nonparametric methods, our analysis reaches two broad conclusions. First, earnings shocks display substantial deviations from lognormality–the standard assumption in the incomplete markets literature. In particular, earnings shocks display strong negative skewness and extremely high kurtosis–as high as 30 compared with 3 for a Gaussian distribution. The high kurtosis implies that in a given year, most individuals experience very small earnings shocks, and a small but non-negligible number experience very large shocks. Second, these statistical properties vary significantly both over the life cycle and with the earnings level of individuals. We also estimate impulse response functions of earnings shocks and find important asymmetries: positive shocks to high-income individuals are quite transitory, whereas negative shocks are very persistent; the opposite is true for low-income individuals. Finally, we use these rich sets of moments to estimate econometric processes with increasing generality to capture these salient features of earnings dynamics.
We analyze changes in the gender structure at the top of the earnings distribution in the United States over the last 30 years using a 10% sample of individual earnings histories from the Social Security Administration. Despite making large inroads, females still constitute a small proportion of the top percentiles: the glass ceiling, albeit a thinner one, remains. We measure the contribution of changes in labor force participation, changes in the persistence of top earnings, and changes in industry and age composition to the change in the gender composition of top earners. A large proportion of the increased share of females among top earners is accounted for by the mending of, what we refer to as, the paper floor – the phenomenon whereby female top earners were much more likely than male top earners to drop out of the top percentiles. We also provide new evidence at the top of the earnings distribution for both genders: the rising share of top earnings accruing to workers in the Finance and Insurance industry, the relative transitory status of top earners, the emergence of top earnings gender gaps over the life cycle, and gender differences among lifetime top earners.
This paper uses the information contained in the joint dynamics of individuals’ labor earnings and consumption-choice decisions to quantify both the amount of income risk that individuals face and the extent to which they have access to informal insurance against this risk. We accomplish this task by using indirect inference to estimate a structural consumption-savings model, in which individuals both learn about the nature of their income process and partly insure shocks via informal mechanisms. In this framework, we estimate (i) the degree of partial insurance, (ii) the extent of systematic differences in income growth rates, (iii) the precision with which individuals know their own income growth rates when they begin their working lives, (iv) the persistence of typical labor income shocks, (v) the tightness of borrowing constraints, and (vi) the amount of measurement error in the data. In implementing indirect inference, we find that an auxiliary model that approximates the true structural equations of the model (which are not estimable) works very well, with negligible small sample bias. The main substantive findings are that income shocks are not very persistent, systematic differences in income growth rates are large, individuals have substantial amounts of information about their income growth rates, and about one-half of income shocks are effectively smoothed via partial insurance. Putting these findings together, we argue that the amount of uninsurable lifetime income risk that individuals perceive is substantially smaller than what is typically assumed in calibrated macroeconomic models with incomplete markets.
In this paper, we study the role of education as insurance against a bad marriage. Historically, due to disparities in earning power and education across genders, married women often found themselves in an economically vulnerable position, and had to suffer one of two fates in a bad marriage: either they get divorced (assuming it is available) and struggle as low-income single mothers, or they remain trapped in the marriage. In both cases, education can provide a route to emancipation for women. To investigate this idea, we build and estimate an equilibrium search model with education, marriage/divorce/remarriage, and household labor supply decisions. A key feature of the model is that women bear a larger share of the divorce burden, mainly because they are more closely tied to their children relative to men. Our focus on education is motivated by the fact that divorce laws typically allow spouses to keep the future returns from their human capital upon divorce (unlike their physical assets), making education a good insurance against divorce risk. However, as women further their education, the earnings gap between spouses shrinks, leading to more unstable marriages and, in turn, further increasing demand for education. The framework generates powerful amplification mechanisms, which lead to a large rise in divorce rates and a decline in marriage rates (similar to those observed in the US data) from relatively modest exogenous driving forces. Further, in the model, women overtake men in college attainment during the 1990s, a feature of the data that has proved challenging to explain. Our counterfactual experiments indicate that the divorce law reform of the 1970s played an important role in all of these trends, explaining more than one-quarter of college attainment rate of women post-1970s and one-half of the rise in labor supply for married women.
This paper studies the nature of business cycle variation in individual earnings risk using a confidential dataset from the U.S. Social Security Administration, which contains (uncapped) earnings histories for millions of individuals. The base sample is a nationally representative panel containing 10 percent of all U.S. males from 1978 to 2010. We use these data to decompose individual earnings growth during recessions into “between-group” and “within-group” components. We begin with the behavior of within-group shocks. Contrary to past research, we do not find the variance of idiosyncratic earnings shocks to be countercyclical. Instead, it is the left-skewness of shocks that is strongly countercyclical. That is, 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, to study between-group differences, we group individuals based on several observable characteristics at the time a recession hits. One of these characteristics—the average earnings of an individual at the beginning of a business cycle episode—proves to be an especially good predictor of fortunes during a recession: prime-age workers that enter a recession with high average earnings suffer substantially less compared with those who enter with low average earnings (which is not the case during expansions). Finally, we find that the cyclical nature of earnings risk is dramatically different for the top 1 percent compared with all other individuals—even relative to those in the top 2 to 5 percent.
This paper uses the information contained in the joint dynamics of households’ labor earnings and consumption-choice decisions to quantify the nature and amount of income risk that households face. We accomplish this task by estimating a structural consumption-savings model using data from the Panel Study of Income Dynamics and the Consumer Expenditure Survey. Specifically, we estimate the persistence of labor income shocks, the extent of systematic differences in income growth rates, the fraction of these systematic differences that households know when they begin their working lives, and the amount of measurement error in the data. Although data on labor earnings alone can shed light on some of these dimensions, to assess what households know about their income processes requires using the information contained in their economic choices (here, consumption-savings decisions). To estimate the consumption-savings model, we use indirect inference, a simulation method that puts virtually no restrictions on the structural model and allows the estimation of income processes from economic decisions with general specifications of utility, frequently binding borrowing constraints, and missing observations. The main substantive findings are that income shocks are not very persistent, systematic differences in income growth rates are large, and individuals have substantial amounts of information about their future income prospects. Consequently, the amount of uninsurable lifetime income risk that households perceive is substantially smaller than what is typically assumed in calibrated macroeconomic models with incomplete markets.
Wage inequality has been significantly higher in the United States than in continental European countries (CEU) since the 1970s. Moreover, this inequality gap has further widened during this period as the US has experienced a large increase in wage inequality, whereas the CEU has seen only modest changes. This paper studies the role of labor income tax policies for understanding these facts. We begin by documenting two new empirical facts that link these inequality differences to tax policies. First, we show that countries with more progressive labor income tax schedules have significantly lower before-tax wage inequality at different points in time. Second, progressivity is also negatively correlated with the rise in wage inequality during this period. We then construct a life cycle model in which individuals decide each period whether to go to school, work, or be unemployed. Individuals can accumulate skills 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. We find that these policies can account for half of the difference between the US and the CEU in overall wage inequality and 76% of the difference in inequality at the upper end (log 90-50 differential). When this economy experiences skill-biased technological change, progressivity also dampens the rise in wage dispersion over time. The model explains 41% of the difference in the total rise in inequality and 58% of the difference at the upper end.
I study asset prices in a two-agent macroeconomic model with two key features: limited stock market participation and heterogeneity in the elasticity of intertemporal substitution in consumption (EIS). The model is consistent with some prominent features of asset prices, such as a high equity premium; relatively smooth interest rates; procyclical stock prices; and countercyclical variation in the equity premium, its volatility, and in the Sharpe ratio. In this model, the risk-free asset market plays a central role by allowing non-stockholders (with low EIS) to smooth the fluctuations in their labor income. This process concentrates non-stockholders’ labor income risk among a small group of stockholders, who then demand a high premium for bearing the aggregate equity risk. Furthermore, this mechanism is consistent with the very small share of aggregate wealth held by non-stockholders in the US data, which has proved problematic for previous models with limited participation. I show that this large wealth inequality is also important for the model’s ability to generate a countercyclical equity premium. When it comes to business cycle performance the model’s progress has been more limited: consumption is still too volatile compared to the data, whereas investment is still too smooth. These are important areas for potential improvement in this framework.
In this paper, we construct a parsimonious overlapping-generations model of human capital accumulation and study its quantitative implications for the evolution of the U.S. wage distribution from 1970 to 2000. A key feature of the model is that individuals differ in their ability to accumulate human capital, which is the main source of wage inequality in this model. We examine the response of this model to skill-biased technical change (SBTC), which is modeled as an increase in the trend growth rate of the price of human capital starting in the early 1970s. The model displays behavior that is consistent with several important trends observed in the US data, including the rise in overall wage inequality; the fall and subsequent rise in the college premium, as well as the fact that this behavior was most pronounced for younger workers; the rise in within-group inequality; the stagnation in median wage growth; and the small rise in consumption inequality despite the large rise in wage inequality. We consider different scenarios regarding how individuals’ expectations evolve during SBTC. Specifically, we study the case where individuals immediately realize the advent of SBTC (perfect foresight), and the case where they initially underestimate the future growth of the price of human capital (pessimistic priors), but learn the truth in a Bayesian fashion over time. Lack of perfect foresight appears to have little effect on the main results of the paper. Overall, the model shows promise for explaining a diverse set of wage distribution trends observed since the 1970s in a unifying human capital framework.
Search theory routinely assumes that decisions about the acceptance/rejection of job offers (and, hence, about labor market movements between jobs or across employment states) are made by individuals acting in isolation. In reality, the vast majority of workers are somewhat tied to their partners—in couples and families—and decisions are made jointly. This paper studies, from a theoretical viewpoint, the joint job-search and location problem of a household formed by a couple (e.g., husband and wife) who perfectly pools income. The objective of the exercise, very much in the spirit of standard search theory, is to characterize the reservation wage behavior of the couple and compare it to the single-agent search model in order to understand the ramifica-tions of partnerships for individual labor market outcomes and wage dynamics. We focus on two main cases. First, when couples are risk averse and pool income, joint search yields new oppor-tunities—similar to on-the-job search—relative to the single-agent search. Second, when the two spouses in a couple face job offers from multiple locations and a cost of living apart, joint search features new frictions and can lead to significantly worse outcomes than single-agent search.
The current literature offers two views on the nature of the labor income process. According to the first view, which we call the “restricted income profiles” (RIP) model, individuals are subject to large and very persistent shocks while facing similar life-cycle income profiles (MaCurdy, 1982). According to the alternative view, which we call the “heterogeneous income profiles” (HIP) model, individuals are subject to income shocks with modest persistence while facing individual-specific income profiles (Lillard and Weiss, 1979). In this paper we study the restrictions imposed by the RIP and HIP models on consumption data—in the context of a life-cycle model—to distinguish between these two hypotheses. In the life-cycle model with a HIP process, which has not been studied in the previous literature, we assume that individuals enter the labor market with a prior belief about their individual-specific profile and learn over time in a Bayesian fashion. We find that learning is slow, and thus initial uncertainty affects decisions throughout the life cycle. The resulting HIP model is consistent with several features of consumption data including (i) the substantial rise in within-cohort consumption inequality, (ii) the non-concave shape of the age-inequality profile, and (iii) the fact that consumption profiles are steeper for higher educated individuals. The RIP model we consider is also consistent with (i), but not with (ii) and (iii). These results bring new evidence from consumption data on the nature of labor income risk.
In this paper we present an analytically tractable general equilibrium overlapping-generations model of human capital accumulation, and study its implications for the evolution of the U.S. wage distribution from 1970 to 2000. The key feature of the model, and the only source of heterogeneity, is that individuals differ in their ability to accumulate human capital. Therefore, wage inequality results only from differences in human capital accumulation. We examine the response of this model to skill-biased technical change (SBTC) theoretically. We show that in response to SBTC, the model generates behavior consistent with the U.S. data including (i) a rise in overall wage inequality in both the short run and long run, (ii) an initial fall in the education premium followed by a strong recovery, leading to a higher premium in the long run, (iii) the fact that most of this fall and rise takes place among younger workers, (iv) stagnation in median wage growth (and a slowdown in aggregate labor productivity), and (v) a rise in consumption inequality that is much smaller than the rise in wage inequality. These results suggest that the heterogeneity in the ability to accumulate human capital is an important feature for understanding the effects of SBTC, and interpreting the transformation that the U.S. economy has gone through since the 1970s.