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This dissertation consists of three essays that address important questions within the fields of labor economics and public economics. I use advanced empirical methods and a combination of restricted access and public-use data to study the role of inequality in labor markets and wealth.In Chapter 1, I study whether the effects of unemployment insurance (UI) extensions are different for workers exposed to higher levels of local labor market concentration, a potential source of employer market power. UI extensions can improve the bargaining power of job seekers relative to employers by improving workers' outside options. I exploit measurement error in state unemployment rates that led to quasi-random assignment of UI durations in the U.S. during the Great Recession. Using matched employer-employee data from the Longitudinal Employer-Household Dynamics program, I find that UI extensions lengthen nonemployment durations by one week and cause economically meaningful but not statistically significant increases in earnings. The UI-earnings effect is significantly lower at higher levels of concentration, while there is no difference in the UI-duration effect. The lower UI-earnings effect is driven by differences at the extremes of the distribution of concentration. Workers exposed to higher concentration also are slightly more likely to change workplaces, local labor markets, and industries following an extension, but they are not induced to match into less-concentrated markets. My results imply that the benefits of more generous UI, in terms of match quality, are attenuated at higher levels of concentration, and so UI policy that accounts for local concentration is potentially warranted.In Chapter 2, joint with Anne M. Burton, we revisit how Ban the Box (BTB) policies affect the employment of minority men. BTB policies are intended to help ex-offenders find employment by delaying when employers can ask about criminal records. Existing evidence finds BTB causes discrimination against young, non-college-educated minority men. We show that effects for this group are not robust to a simple change in specification and the coding of BTB laws. Using a distinct treatment definition, we find no evidence of statistical discrimination: employment effects are near zero, precisely estimated, and not statistically significant.In Chapter 3, joint with N. Meltem Daysal and Michael F. Lovenheim, we study the effect of changes in parental wealth in childhood on the intergenerational transmission of wealth. Rising wealth inequality has spurred an increased interest in understanding how and why wealth is correlated across generations. Prior research has found an intergenerational correlation between 0.2 and 0.4 and has emphasized the role of family characteristics in driving this correlation. We contribute to this literature by examining the intergenerational transmission of wealth changes, which allows us to isolate the causal effect of wealth shocks from pre-determined parental preferences and household characteristics. Using Danish Register Data, we examine the effect of home price changes that occur between ages 0-5, 6-11, and 12-17 on overall wealth, housing wealth, and nonhousing wealth of adult children at ages 29-33. For the youngest age group, we find that 16.5% and 22.2% of each Krone of home price change is transmitted to overall wealth and housing wealth in adulthood, respectively. The corresponding transmission rates for the 6-11 age group are 30.8% and 18.5%, with a transmission to non-housing wealth of 12.3%. There is no transmission of home price changes that occur during the teenage years for any wealth outcome. Examining mechanisms, we find that home price increases in the first two age groups lead to modest increases in home ownership, educational attainment, and income. There also is an increase in partner wealth for the younger two groups. Income and education can explain less than a third of the intergenerational transmission we document. We argue that our results largely reflect changes to parental/household behaviors and preferences that are passed down to children and cause them to accumulate more housing wealth in young adulthood.
In the first chapter, I propose a tractable model of the labor share that emphasizes the interaction between labor market imperfections and productivity dispersion. I bring the model to the data using an administrative dataset covering the universe of firms in Canada. As in the data, most firms have a high labor share, yet the aggregate labor share is low due to the disproportionate effect of a small fraction of large, extremely productive “superstar firms”. I find that a rise in the dispersion of productivity across firms leads to a decline of the aggregate labor share in favor of firm profit. The mechanism is that productivity dispersion effectively shields high-productivity firms from wage competition. Reduced-form evidence from cross-country and cross-industry data supports both the prediction and the mechanism. Through the lens of the model, rising productivity dispersion has caused the U.S. labor share to decline starting around 1990. In the second chapter, we propose a new, systematic approach for analyzing and solving heterogeneous-agent models with fat-tailed wealth distributions. Our approach exploits the asymptotic linearity of policy functions and the analytical characterization of the Pareto exponent to make the solution algorithm more transparent, efficient, and accurate with zero additional computational cost. As an application, we solve a heterogeneous-agent model that features persistent earnings and investment risk, borrowing constraint, portfolio decision, and endogenous Pareto-tailed wealth distribution. We find that a wealth tax is a “lose-lose” policy: the introduction of a 1% wealth tax (with extra tax revenue used as consumption rebate) decreases wage by 6.5%, welfare (in consumption equivalent) by 7.7%, and total tax revenue by 0.72%. In the third chapter, I propose a model of earnings dynamics and inequality within the firm. The model combines a production hierarchy with a “rank order tournament” promotion scheme. I motivate the theory by documenting three sets of facts using proprietary personnel data. First, most of inequality within the firm is between hierarchy levels rather than within. Second, there is on average very little upward mobility within the firm. Third, there is important heterogeneity in earnings trajectories. The model provides a positive theory of these facts and sheds light on the determinants of inequality within the firm.
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Racial inequality and wealth are inextricably linked. Wealth gaps are an important dimension of racial inequality. In addition, wealth itself plays a causal role in other dimensions of inequality, including unequal labor market and education outcomes. In the first essay, I estimate the effect of access to extended family wealth on college enrollment and I find a positive relationship. This is important for higher education policies that aim to reduce inequality but fail to account for race and wealth. In the second essay, I estimate the effect of Medicaid on individual assets. Whereas economic theory in the literature predicts a negative effect, I develop a framework that shows how public insurance can increase savings and I present empirical evidence against a negative effect. Finally, the third essay develops an analytical framework called Latinx stratification economics by reviewing the main economic theories applied to Latinxs and demonstrating how stratification economics and Latinx studies may be used to critique the dominant theories.
Whilst there is widespread agreement about the goals of economic policy, consensus about how best to achieve them can be harder to achieve. No issues are more contentious than employment and income distribution. In recent years full employment and a just distribution of incomes have been downgraded as policy objectives, as greater priority has been given to price stability and balance of payments objectives. This emphasis has been supported by a mainstream economic theory which has an unswerving belief in the ability of market forces to achieve a satisfactory regulation of employment and income distribution Other economists have remained more sceptical, and none more so than Kurt Rothschild. This new volume collects together his twenty two most important essays in the area, many of which are appearing in English for the first time. Throughout pure theory is linked to relevant practical investigations.
This dissertation studies the impact of technological progress on various aspects of the U.S. labor markets such as the recent decline in the labor's share of income, job and wage polarization, rising income and wealth inequalities and skill accumulation. Chapter 1, "Capital-Task Complementarity and the Decline of the U.S. Labor Share of Income," studies how changes in occupational composition of the labor force contributes to the recent decline of the US labor share of income. Following the job polarization literature and classifying labor by tasks performed, I estimate unitary elasticity between equipment capital and labor performing non-routine tasks. This implies that income loss of labor em- ployed in routine task occupations is the main driver of the decline of the aggregate labor share. For a given path of technological change, decline of the labor share is larger when: (i) the substitutability between equipment capital and routine tasks is stronger, and (ii) equip- ment capital has a larger weight in production. Furthermore, a dynamic general equilibrium model shows that the impact of permanent technology shocks on the labor share gets smaller as the fraction of routine task labor declines. Consistent with this, the model predicts that the labor share should stabilize at around 55% in the long-run even if technological progress continues at its current pace. The model also documents that the fall in relative equipment capital prices alone can explain 72% of the decline of the labor share for the 1967-2013 period. Finally, repeating the analysis by disaggregating labor into educational groups reveals that the theory based on capital-task interactions improves on the capital-skill complementarity theory in explaining the decline of the labor share. Chapter 2, "Impact of Information Technology on the Labor Share: Evidence from the U.S. Sectoral Data," contributes to the debate over the relationship between capital deep- ening and the aggregate labor share from a sectoral perspective. The study focuses on a specific group of equipment capital: information and communication technology (ICT) capital and exploits various sectoral heterogeneities to characterize the conditions under which the surge in ICT capital cause the labor share to fall. First, I document significant capital- task complementarity at each sector. Second, decline in ICT capital prices turns out to have a positive impact on the labor share. However, gains of labor devoted to non-routine task occupations are offset by the losses of labor employed in routine task occupations when a sector has: (i) initially high load of employment in routine task occupations, and (ii) weak absolute complementarity between ICT capital and labor working in occupations associated with non-routine tasks. Since sectors satisfying these two conditions have compromised the majority of the economy, the aggregate labor share has exhibited a downward trend so far, leading to the illusion that information technology has been driving the labor share downwards. However, there are two promising facts concerning the future: in one hand, the share of these sectors in value added is persistently falling and on the other hand, the share of routine task employment continues to fall at every sector. Thus, once the structural shifts and within sectoral adjustments are completed, the decline in the labor share should revert back. Chapter 3, "Job Polarization, Skill Accumulation and Wealth Inequality," is one of the first attempts in literature to incorporate the job polarization idea into an otherwise standard incomplete markets model with heterogeneous agents in two dimensions: skills and idiosyn- cratic productivity shocks. This set up allows us to contribute to the existing literature in two ways: (i) linking job polarization with rising wealth concentration, and (ii) modeling the continuous rise in skill supply in response to technological progress and job polarization accompanying it over time. When calibrated and solved for the years 1981 and 2011, the model shows that the decline in relative computer (ICT) capital prices alone accounts for a significant portion of the increases in employment share and relative wages of high skill occupations, as well as the increase in the supply of labor with a college or above-college degree. Consistent with the routinization hypothesis, the model also shows that advances in computer technology can account for most of the decline of the employment share and rela- tive wage of middle class over the three decades between 1981 and 2011. Furthermore, the model successfully captures the erosion of middle-class wealth, whereas wealth concentration rises substantially at the right tail and slightly at the left tail of the wealth distribution.
This thesis consists of three chapters on aspects of labor market inequality. In chapter 1, I estimate the dynamic effects of federal affirmative action regulation, exploiting variation in the timing of regulation and deregulation across work establishments. I find that affirmative action sharply increases the black share of employees, with the share continuing to increase over time: five years after an establishment is first regulated, its black share of employees increased by an average of 0.8 percentage points. Strikingly, the black share continues to grow even after an establishment is deregulated. Building on the canonical Phelps (1972) model of statistical discrimination, I argue that this persistence is in part driven by affirmative action inducing employers to increase the precision with which they screen potential employees. I then provide supporting evidence. In chapter 2, I study the spatial mismatch hypothesis, which proposes that job suburbanization isolates blacks from work opportunities and depresses black employment. Using synthetic panel methods and variation across metropolitan areas from 1970 to 2000, I find that for every 10% decline in the fraction of metropolitan area jobs located in the central city, black employment (earnings) declined by 1.4-2.1% (1.1-2.3%) relative to white employment (earnings). This relationship is driven primarily by job suburbanization that occurred during the 1970's. To address the potential endogeneity of suburbanization, I exploit exogenous variation in highway construction and find that highways cause job suburbanization and declines in black relative employment in a manner consistent with spatial mismatch. In chapter 3, joint work with Isaiah Andrews, we analyze the effect of heterogeneity on the widely used analyses of Baily (1978) and Chetty (2006) for optimal social insurance. The basic Baily-Chetty formula is robust to heterogeneity along many dimensions but requires that risk aversion be homogeneous. We extend the Baily-Chetty framework to allow for arbitrary heterogeneity across agents, particularly in risk preferences. We find that heterogeneity in risk aversion affects welfare analysis through the covariance of risk aversion and consumption drops, which measures the extent to which larger risks are borne by more risk tolerant workers. Calibrations suggest that this covariance effect may be large.
The widespread prevalence of rising economic inequality across western democracies has led to immense academic and policy interest, as well as the rapid development of the tools required to study it. Researchers are now equipped with rich data and advanced computational methods which are well-suited to analyzing the processes underlying the extensive differences exhibited across individuals and groups within and between societies. To an extent, diverse outcomes reflect an intrinsic natural variation in individual tastes and preferences. However, in many cases we rather consider inequalities, particularly economic inequalities, to reflect injustice, misallocation and constrained opportunities. When considering labor market earnings, a substantial proportion of the variation across individuals can be explained by a single predictor: a worker's gender. In the first chapter of this dissertation I study a policy explicitly designed to reduce this association, in which employers are required to publicly report gender pay gap statistics. Proponents argue that increasing the information available to workers and consumers places pressure on firms to close pay gaps, but opponents argue that such policies are poorly targeted and ineffective. I contribute to the debate by analyzing the UK's recent reporting policy, in which employers are mandated to publicly report simple measures of their gender pay gap each year. Exploiting a discontinuous size threshold in the policy's coverage, I apply a difference-in-difference strategy to linked employer-employee payroll data. I find that the introduction of reporting requirements led to a 1.6 percentage-point narrowing of the gender pay gap at affected employers. This large-magnitude effect is primarily due to a decline in male wages within affected employers and is not caused by a change in the composition of the workforce. To explain this effect, I propose that a worker preference against high pay gap employers induces the closing of pay gaps upon information revelation. Newly-gathered survey evidence shows that female workers in particular exhibit a significant preference for low pay gap employers. In a hypothetical choice experiment, over half of women accept a 2.5\% lower salary to avoid a high pay gap employer. I also demonstrate substantial heterogeneity in the interpretation of pay gap statistics across workers and show that this affects their valuation of jobs at employers with different pay gaps. Does the importance of your family background on how far you get in adulthood also depend on where you grow up? For England and Wales, a paucity of data has made this a difficult question to reliably answer. My second chapter, co-authored with Brian Bell and Stephen Machin, presents a new analysis of intergenerational mobility across three cohorts in England and Wales using linked decennial census microdata. These data permit the study of different mobility outcomes in occupation, home ownership and education, at the spatial level through time. As well as showing national results consistent with previous studies, we find strong sub-regional patterns in mobility, with four main results emerging. First, area-level differences in upward occupational mobility are highly persistent over time. Second, consistent with evidence from other countries, absolute and relative mobility are positively correlated for all measures and particularly strongly for home ownership. Third, there is a robust relationship between upward educational and upward occupational mobility. Last, there is a small negative relationship between upward home ownership mobility and upward occupational mobility, revealing that social mobility comparisons based on different outcomes can have different trends. Social scientists have long been interested in the relationship between parental factors and later child income. Finding the best characterization of this relationship for the question at hand is however fraught with choices. In my third chapter, co-authored with Erling Risa, we use machine learning methods to assess the `completeness' of one popular modelling approach. Here, completeness refers to how well the model summarizes the total predictive relationship between multiple parental factors and a single child outcome. Machine learning methods enable us to depart from functional form assumptions, allowing flexible interactions between a large set of possible parental factors. Using our most flexible complete model as a benchmark, we assess the popular `rank-rank' model relating parent and child incomes. Applying our approach to high-quality Norwegian administrative data, we demonstrate that the rank-rank model explains 68\% of the total explainable variation in child income rank, based on a broad set of potential parental factors entering a neural network. Parental wealth and parental education explain the majority of the remaining explainable variation. At the regional level, we estimate homogeneous completeness across areas. Rankings of areas based on rank-rank slope estimates align with those based on the predictive fit of the broader flexible model.