Session 14: The Micro and Macro of Labor Markets

A growing number of studies suggest that minimum wages have limited disemployment effects while at the same time increasing output prices. This finding contradicts the "law of demand", which states that output demand, and therefore employment, should fall whenever prices increase. We propose a simple framework to explain this fact and to highlight some aspects of ethical consumption more generally. Consumers derive extra utility when engaging in transactions that can be associated with positive moral attributes. In the context of the minimum wage, consumers derive higher marginal utility when they know that the good they are consuming is produced by a worker earning a higher wage. Combined with firms' inability to credibly commit to higher wages, a mandated minimum wage policy can lead to higher output and positive employment effects simultaneously. We implement an online survey experiment in the U.S. to test for the proposed mechanism. We use our findings to reassess the welfare implications of the policy.

Using field and laboratory experiments, we demonstrate that the complexity of incentive schemes and worker bounded rationality can interact to affect effort provision, by shrouding particular attributes of the incentives. In our setting, complexity leads workers to over-provide effort relative to a fully rational benchmark, and improves efficiency. We identify contract features, and facets of worker cognitive ability, that matter for shrouding. We find that even relatively small degrees of shrouding can cause large shifts in behavior. Our results illustrate important implications of complexity for designing and regulating workplace incentive contracts.

The matching efficiency of the U.S. labor market has dropped significantly post-Covid-19, leading to an outward shift of the Beveridge Curve. Additionally, there has been a notable reduction in the average weekly hours worked by non-agricultural workers in the aftermath of the pandemic. I introduce a novel channel that explains the joint movement of matching efficiency and working hours in the labor market - the disutility experienced by workers in their jobs. I develop a random search model with two-dimensional ex-post heterogeneity and two-sided private information. When a worker and a firm form a match, firms possess private information regarding the worker’s productivity, while workers hold private information about their own disutility experienced during work. Furthermore, firms offer a range of employment contracts composed of wages and working hours to the employees, posing a challenging mechanism design problem. I assess the theoretical implications of changes in the distribution of disutility for shifts in the Beveridge curve. Subsequently, I calibrate the model to match the hours worked and matching efficiency observed in the U.S. labor market both before and after the Covid-19 pandemic. I find a noteworthy rightward shift in the distribution of disutility post-Covid-19, resulting in a substantial increase in the average disutility of work by 60.4%.

A large literature documents that immigrants and native-born workers are segregated from each other in the labour market and that immigrants initially enter low wage firms. At the same time, many studies find that immigration has muted effects on the wages of native-born workers. We argue, both theoretically and empirically, that these two phenomena are related. Using a wage posting model with differentiated firms, we show that segregation dampens the wage effects of migration. Furthermore, migration shocks can induce a reallocation of native-born workers across firms. Our empirical analysis tests the predictions of the model using comprehensive matched employer-employee data from Germany over the period 2005-19.

The number of location-flexible jobs has markedly increased in the United States in recent years. In tandem with this trend, dozens of municipalities have introduced Remote Worker Relocation Programs by subsidizing remote workers to move in. Using the policy variation, this paper provides new evidence on how the influx of remote workers who come with high skills and jobs affects the local residents in destination cities. Leveraging data from Tulsa Remote (the largest and the earliest program) and an event study design, I find heterogeneous effects by industry, with employment increasing by 7.95% in the local service sector but falling by 12.6% in the wholesale trade sector after one year of the program. To study the welfare consequences of Remote Worker Relocation Programs, I build and estimate a structural equilibrium model that incorporates workers' selection into the industry. The program improves the average welfare of local residents, primarily due to their higher wages and more varieties of local goods, offsetting higher prices of local goods and rents. The program raises local inequality by 1.44%, with high-skilled local service workers benefit the most, while low-skilled tradable workers experience a slight welfare loss. Lastly, the Remote Worker Relocation Program subsidized by taxes collected from local residents is welfare enhancing, but only up to a certain threshold.

This paper studies a historically large payroll tax cut that affected a subset of Brazilian firms. Difference-in-differences estimates based on plausibly exogenous legal variation, indicate that the payroll tax reduction causes an increase in employment, wages, and profits, while capital decreases. Responses are substantially more pronounced among small firms, which are estimated to possess less market power. In terms of mechanisms, two-thirds of the employment effect arises from plant size expansion rather than input substitution. Consumers pay 75% of payroll taxes, while firm owners and workers pay 25%. Estimates of a monopsonistically competitive model of factor demand quantifies that a targeted alternative tax policy focusing on small firms could amplify efficiency gains by 36% while enhancing workers’ welfare gains by 95%. These results show that market power not only mitigates the distortionary costs of taxation, but also redistributes the tax burden from workers to firm owners and consumers.

Canonical theories of frictional labor markets conceptualize separations as job destruction and vacancies as job creation. Yet, workers exiting the labor force hence vacating their positions, dubbed the vacating channel, is an empirically important source of both employment outflows and vacancy inflows. It is absent in standard models that treat vacancies as recruiting efforts, while I document facts on vacancy dynamics that point to an alternative view of vacancies as part of the job life cycle. I develop a model that incorporates the vacating channel and quantitatively replicates properties of labor market flows. It brings novel insights into the business cycle theory of unemployment: Procyclical employment-to-nonparticipation quits contribute to vacancy fluctuations due to the vacating channel, accounting for about one-third of unemployment fluctuations. Understanding the source of vacancies also has important policy implications: While creating a new job as an investment activity is responsive to the interest rate, reposting a vacated position is not. This sheds new light on the possibility of a “soft landing”—raising interest rates without causing high unemployment—during the “Great Resignation,” a period of elevated vacating.

Empirical models of labor market competition usually assume that employers set wages non-cooperatively, despite frequent allegations of collusive wage-setting agreements. We propose an identification approach for labor market collusion that relies on production and cost data, and we use it to study how employer collusion affected wage markdowns of 227 Belgian coal firms between 1845 and 1913. We are able to detect collusion through the 1897 coal cartel, an observable shock to collusion, without ex-ante knowledge of its timing, and we find that it explains the fast growth in markdowns after 1900. We find that the cartel decreased both wages and employment by 6% to 17%.

Worker sorting into tasks and occupations based on their skills plays a potentially important role in aggregate labor productivity. This sorting may be inefficient if job-seekers have inaccurate beliefs about their skills and do not apply to jobs that match their skills. In South Africa, we assess young jobseekers' numeracy and communication skills and find jobseekers' self-perceived and measured comparative advantage persistently differ. In a field experiment, jobseekers given their skill assessment results have more accurate beliefs about their comparative advantage and redirect search toward jobs whose skill demand matches their comparative advantage in multiple search measures: an incentivized job choice task where workers choose between jobs with different skill requirements, usage data from an online job search platform, and self-reported search plans. In a larger field experiment, treatment has similar effects on self-reported measures of beliefs and search direction and substantially raises earnings and job quality, although not employment rates, after three months. These patterns are consistent with models of endogenously directed job search, where jobseekers' beliefs about their skills influence where they direct job applications and hence the wages they are offered.

How do anti-competitive practices such as non-compete and no-poaching agreements affect wages and employment? To assess this, we build a tractable framework of wage posting with on-the-job search that has large employers. We show formally how market structure affects wages, profits, and employment and that non-compete scan sharply hurt workers, effectively restoring the Diamond Paradox. The quantitative model captures existing empirical evidence on the impact of mergers on employment and wages. Banning non-competes can result in large wage increases, typically when the demand elasticity is low, training cost are high, markets are highly granular, and when non-competes are wide-spread. Increased worker turnover typically lead to a small associated total output loss of about.5%.

This paper investigates the increasing importance of domestic outsourcing in U.S. manufacturing. Under domestic outsourcing, the agency is the employer of record for temporary workers, though they perform their tasks at the client business’ premises. On a yearly basis, one in two manufacturing plants hires at least some of its workers through a temporary help agency. Furthermore, domestic outsourcing is becoming increasingly more important: the average share of revenue spent on such arrangements has gone up by 85 percent since 2006. We develop a methodology to transform reported expenses on temporary and leased workers into plant-level outsourced employment counts, using administrative data on the U.S. manufacturing sector. We find that domestic outsourcing is an important margin of adjustment that plants use to modify their workforce in response to productivity shocks. Plant-level outsourced employment adjusts more quickly and is twice as responsive as payroll employment. These micro implications have significant aggregate consequences. Without taking reallocations in outsourced employment into account, the measured pace at which jobs reallocate across workplaces is underestimated. On average, we omit the equivalent of 15 percent of payroll employment reallocations in each year. However, outsourced employment churns at a much higher rate compared to its payroll counterpart. Therefore, the omission of outsourced reallocations can rationalize 37 percent of the secular decline in the aggregate job reallocation rate. Lastly, the extent of mismeasurement varies with the business cycle; falling in downturns and increasing in upturns implying that the speed of economic recovery is underestimated.

We derive a non-parametric test for statistical discrimination that can be applied to cross-sectional wage data. Specifically, we show that the wage distributions for two groups (with identical observable characteristics) are consistent with a general reduced-form model of statistical discrimination if, and only if, neither wage distribution first-order stochastically dominates the other. Our model allows us to interpret a rejection of this condition as evidence of bias.

In this project, we use data from a large firm that provided information on all job applications as well as labor market outcomes within the firm over a 5 year period. Careful analysis of the data shows that African Americans and women engage in more overt job search activity within the organization than Caucasian males, attain shorter tenure on each job, and experience slower wage growth. We also see that African Americans are less likely to be interviewed for a position, although we do not see any differences with race for hiring probabilities conditional on being interviewed. To explain these empirical patterns, we develop and estimate a model of two sided search and matching, in which positions become vacant when the current occupant of the job leaves, the firm begins a search process by advertising the position, and workers employed both inside and outside the organization apply for the newly vacated position.The applicants are culled during a hiring process that lead both parties to become more informed about the potential job match with each applicant. After estimating the model, we will use counterfactuals to understand more about the differences in the search and matching process across racial  and gender groups, as well as how that affects wage outcomes. First, we know in the data that the durations that people stay in a job differs by race and gender. Our counterfactuals can analyze how large of a role these durations play in the hiring process. Second, we can study how outcomes would change if the hiring committee is forced to interview more or fewer candidates. This can help to understand how institutional restrictions will affect the likelihood that an individual is offered a position.

Dual-earner households face a colocation problem: They need to find two jobs in one location. We develop a spatial directed search model that captures the unique frictions that characterize the job search by dual-earner households. We derive general conditions under which this "colocation friction" is binding and quantify its consequences for the U.S. labor market. Estimated at the commuting zone level, the model implies that the colocation friction disproportionately affects women, reducing their short-term earnings gains from migration by 76%. The colocation friction further discourages migration, especially among "power couples," preempting relocation to more productive and higher-amenity locations in the long run. Taken together, we estimate that the colocation friction incurs a lifetime utility loss equivalent to a 1.4% decrease in lifetime earnings.