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Aquesta tesi estudia les interaccions entre les dinàmiques del mercat laboral i l'estructura de les famílies, i com aquestes interaccions afecten les polítiques públiques. Als EUA, s'observen patrons molt diferents pel que fa a participació laboral, ocupació i desocupació entre les persones casades i solteres. Fins i tot un cop es controla per la distinta composició dels dos grups, encara apareixen comportaments molt diferents entre casats i solters en termes del mercat de treball. L'explicació proposada en aquesta tesi és simple: la gent es comporta de manera diferent quan forma part d'una família comparat amb quan està sola. A partir d'aquesta premissa, la tesi explora dues qüestions fonamentals. La primera és analitzar quina part de les diferencies que observem a les dades és deguda a l'efecte de la família. La segona tracta d'entendre com canvien les implicacions d'una política bàsica del mercat laboral, com és l'assegurança d'atur, quan introduïm la família en l'anàlisi. En el primer capítol, escrit amb en Sekyu Choi, documentem una diferència remarcable i estable entre la taxa d'atur de la gent casada i la soltera, als EUA. A través d'una descomposició estàndard de les transicions laborals, trobem quins són els canals que expliquen millor les diferències tant en termes de gènere com a d'estructura familiar. Després, construïm un model simple del mercat laboral, on els agents presenten diferències en termes de xocs d'ingressos, béns, gènere i estat civil. A través del model, demostrem que la família genera dos efectes de signe oposat sobre la taxa d'atur. Per una banda, actua completant els mercats i, per tant, reduint els incentius per treballar, el que genera una menor ocupació i, ceteris paribus, major taxa d'atur. Per altra banda, augmenta la inclinació dels agents a sortir de l'atur a través de no participar en el mercat laboral, cosa que redueix la taxa d'atur. En el segon capítol, escrit amb en Nezih Guner i na Yuliya Kulikova, estudiem les transicions conjuntes de les parelles en el mercat laboral. La literatura empírica existent s'ha centrat en analitzar els moviments entre ocupació i atur, ignorant la participació. Una altre característiques de la literatura existent és que analitza individus, en canvi, nosaltres focalitzem en nostre anàlisi en parelles. Els homes i les dones casades son diferents pel que fa a les seves dinàmiques en el mercat laboral. Les transicions entre atur i inactivitat tenen un paper més important per a les dones que per als homes. Per tant, tenir en compte el marge de participació és clau per entendre les dinàmiques laborals de les parelles. Els nostres resultats mostren que el component de coordinació per explicar els moviments de les parelles a través dels estats laborals és fonamental. En el tercer capítol, estudio un programa d'assegurança d'atur, semblant al que està en marxa als EUA, en un entorn on la principal font d'heterogeneïtat entre els agents és el tipus de llar on viuen: alguns viuen sols mentre els altres viuen amb la seva parella formant una família. La principal conclusió, es que l'assegurança d'atur beneficia als solters però no als casats. Aquest resultat no depèn de les diferents característiques entre solters i casats. Fins i tot si els solters formessin una família amb els seus clons, no es beneficiarien de l'assegurança. En canvi, si els casats visquessin sols, si que la valorarien. Per tant, la principal raó per la qual els casats no es beneficien de l'assegurança és que la família, amb els seus dos treballadors, és un mecanisme suficient de suport.
This thesis comprises three chapters that delve into various labor market dynamics and the policy implications in the context of the COVID-19 pandemic and its aftermath. In the first chapter (joint with Andre Kurmann and Etienne Lale), we investigate the dynamics of small businesses and employment using real-time data from the private sector throughout the COVID-19 crisis. The pandemic has led to an explosion of research using private-sector data to measure small business activity. Yet important questions remain about sample representativeness and how to identify business openings and closings. We propose new methods to address these issues by exploiting information on business activity from Google, Facebook, and Safegraph. We apply our methods to Homebase data and show that the resulting estimates closely fit official statistics. We then use the data to study whether small businesses have been hit harder by the pandemic and the extent to which the Paycheck Protection Program helped mitigate these effects. The second chapter (joint with Andreas Hornstein, Marios Karabarbounis, Andre Kurmann, Etienne Lale) focus on the effects of pandemic unemployment insurance (UI) benefits. UI acts as both a disincentive for labor supply and as a stimulus for labor demand. In equilibrium, the two effects combine, which may explain why several studies have found only small negative effects of the generous UI expansions during the pandemic on job finding rates and employment. In this paper we propose a new research design to estimate independently the disincentive effects of pandemic unemployment benefits. Using high-frequency worker-firm matched data from Homebase, we document that employment of low-wage businesses recovered more slowly from the initial pandemic shock than neighboring high-wage businesses, and that this recovery gap is significantly related to the relative generosity of UI benefits. By comparing neighboring businesses that are largely sharing the benefits of the local UI stimulus, our research design identifies more closely the disincentive effects of pandemic UI benefits. We use an equilibrium model of labor search with heterogeneity in firms and workers to translate the reduced-form estimate of the recovery gap into an unemployment duration elasticity and an aggregate employment loss. Our model, which captures well the recovery gap between low- and high-wage businesses, implies relatively low duration elasticities. Yet, the sheer size and multitude of the pandemic programs implies that the disincentive effects arising from the pandemic UI benefits are substantial and amount to 5 percent of normal employment. The third chapter studies work-from-home (WFH) work mode's implications on labor market. The COVID-19 pandemic has triggered a widespread adoption of WFH practices and accelerated the advancement of remote work technologies. Surprisingly, even after the pandemic has subsided, a substantial shift towards WFH remains evident among workers. However, the accessibility to WFH is not uniform across all types of workers. Notably, high-tech industries, characterized by a predominantly high-skilled workforce, exhibit a higher prevalence of WFH. This raises concerns about the effects of WFH on workers employed in industries where remote work is unfeasible. In this paper, I develop a spatial equilibrium model that incorporates WFH to examine the implications on workers' mobility, local market outcomes, and overall welfare. I find 3 key insights: (1) there is a productivity threshold for WFH adoption, (2) there is a one-way dependence of low-skilled workers on high-skilled workers' mobility, and (3) if workers are fully mobile, both types of workers benefit from the introduction of WFH.
This thesis consists of three chapters on labor market dynamics. In the first chapter, I show empirically that the unequal incidence of recessions is a core channel through which aggregate shocks are amplified. I show that the aggregate marginal propensity to consume (MPC) is larger when income shocks disproportionately hit high-MPC individuals, and I define the Matching Multiplier as the increase in the output multiplier originating from the matching of workers to jobs with different income elasticities - a greater matching multiplier translates into more powerful amplification in a range of business cycle models. Using administrative data from the United States, I document that the earnings of individuals with a higher marginal propensity to consume are more exposed to recessions. I show that this covariance between worker MPCs and the elasticity of their earnings to GDP is large enough to increase shock amplification by 40 percent over a benchmark in which all workers are equally exposed. Using local labor market variation, I validate this amplification mechanism by showing that areas with higher matching multipliers experience larger employment fluctuations over the business cycle. Lastly, I derive a generalization of the matching multiplier in an incomplete markets model and show numerically that this mechanism is quantitatively similar within this structural framework. In the second chapter, joint with David Autor, David Dorn, Lawrence Katz, and John Van Reenen, we explore the well-documented fall of labor's share of GDP in the United States and many other countries. Existing empirical assessments typically rely on industry or macro data, obscuring heterogeneity among firms. In this paper, we analyze micro panel data from the U.S. Economic Census since 1982 and document empirical patterns to assess a new interpretation of the fall in the labor share based on the rise of "superstar firms." If globalization or technological changes advantage the most productive firms in each industry, product market concentration will rise as industries become increasingly dominated by superstar firms. Since these firms have high markups and a low labor share of firm value-added and sales, this depresses the aggregate labor share. We empirically assess seven predictions of this hypothesis: (i) industry sales will increasingly concentrate in a small number of firms; (ii) industries where concentration rises most will have the largest declines in the labor share; (iii) the fall in the labor share will be driven largely by reallocation rather than a fall in the unweighted mean labor share across all firms; (iv) the between-firm reallocation component of the fall in the labor share will be greatest in the sectors with the largest increases in market concentration; (v) the industries that are becoming more concentrated will exhibit faster growth of productivity and innovation; (vi) the aggregate markup will rise more than the unweighted firm markup; and (vii) these patterns should be observed not only in U.S. firms, but also internationally. We find support for all of these predictions. In the third chapter, I explore how the distribution of tasks across industries affects labor market responses to shocks. I present a model in which task-level wages connect industries employing the same tasks, meaning that the distribution of tasks across industries insures some workers against shocks and alters their labor market experiences. Workers trained in more dispersed tasks (e.g. accountants) face less unemployment risk from industry-specific shocks than workers who do tasks that are concentrated in few industries (e.g. petroleum engineers). Using industry and regional data, I show empirical evidence that supports the model's predictions - industries that employ more specialized labor contract less in response to demand shocks than industries with less specialized labor. JEL Classifications: E21, J23, D33
This dissertation explores the business cycle dynamics of the aggregate labor market. In two essays I advance the theoretical modelling of these markets and examine whether the new theory does quantitatively better at accounting for empirical evidence than existing models. Both essays examine models where market incompleteness faced by workers implies that long term wage contracts play a role in providing consumption smoothing to workers. The terms of these state contingent contracts depend on: (1) the preferences of the contracting parties, (2) whether parties can commit to contracts. The essays embed such optimal dynamic contracting problems into a Mortensen-Pissarides style model of labor market flows with aggregate shocks, contributing to the theoretical modelling of wage determination in this model framework. I find that market incompleteness has quantitatively only limited ability to explain the volatility puzzle facing existing models: unemployment varies strongly over the business cycle, while labor productivity varies much less. Whether the models are consistent with wage data hinges both on the preferences of contracting parties: entrepreneurs versus workers, as well as constraints on contracting.