Essays in Macro-Labor
My doctoral research focuses on the role of labor market frictions in shaping macroeconomic outcomes. I am currently pursuing three main lines of research that constitute the three chapters of this dissertation. The first chapter focuses on involuntary part-time employment as an additional margin used by firms to adjust to business cycle fluctuations. The chapter documents empirical regularities of involuntary part-time employment in the U.S. and furnishes a tractable analytical framework for studying this phenomenon that has gained so much attention in the years that followed the Great Recession. In the second chapter, which is joint work with Sanjay Chugh, Ryan Chahrour and Alan Finkelstein-Shapiro, we study the labor market wedge in the context of a search and matching model to understand how static and dynamic inefficiencies change over the business cycle. Measuring the labor market wedge and understanding its sources of movement is of great importance from a macroeconomic point of view, as existing research shows it holds a prominent place in explaining fluctuations in aggregate output. Finally, in the third chapter I study empirically the determinants of the job finding probability, a key object in the context of frictional labor markets. More specifically, I analyze how decisions on time allocation by the unemployed affect their chances of finding a job, and identify the activities that make more likely for an unemployed individual to receive and accept a job offer. Chapter 1. In recent years researchers and policymakers have shown renewed interest in involuntary part-time employment as a crucial indicator of labor market health. The fact that individuals have part-time jobs even though they would be willing to work more hours is evidence that resources in the economy are not employed at full capacity. This group represents almost 40 percent of total underemployment. Despite its large size and importance to policy-makers, surprisingly little literature addresses the empirical regularities or economic role this margin plays in determining labor market outcomes. In "Underemployment and the Business Cycle" I address several questions regarding involuntary part-time employment. First, how does involuntary part-time employment differ from the standard extensive and intensive margins? Second, what factors influence the choice of firms to use involuntary part-time workers? Third, how might economic policy contribute to the existence of involuntary part-time employment in the economy? And, fourth, have there been any changes over time in the response of involuntary part-time employment to changes in aggregate economic conditions and, if so, what explains them? To describe the empirical regularities of involuntary part-time employment, I use detailed micro-level data from longitudinally-linked monthly files of the Current Population Survey. A novel finding that emerges from the analysis of this dataset is that wages of involuntary part-time workers display higher volatility and lower persistence than those of their full-time counterparts, thus indicating a higher degree of flexibility. In addition, I find that changes in involuntary part-time employment are mostly explained by reallocation of workers from full-time to part-time positions within the firm, which involves more than just a mere reduction in hours worked. I then aggregate the data and compute business cycle statistics. Surprisingly, I find that the behavior of involuntary part-time employment resembles the behavior of unemployment more than the one of full-time employment. In fact, the results indicate that involuntary part-time employment is very volatile and strongly countercyclical. To understand the evidence I find at the micro and macro levels, I build an augmented search and matching model of the labor market featuring full-time and part-time employment, and a production function that combines both types of workers. The decision of whether a worker is full-time or part-time is made entirely by the firm, depending on the realizations of both aggregate and idiosyncratic productivity processes. The model is able to deliver the countercyclicality of involuntary part-time employment found in the data. The key mechanism to obtain this result is the relatively higher flexibility of part-time contracts that makes it more profitable for the firm to reallocate workers from full-time to part-time arrangements during recessions. Based on the model that captures key empirical facts, I conduct policy analysis to evaluate the effect of an increase in the cost of health insurance on involuntary part-time employment. The policy experiment predicts that an increase in the cost of health insurance provided by the firm to its full-time workers, such that their share in average full-time wages goes up by 1 percentage point, leads to an increase of steady state involuntary part-time employment by 10 percent, which nowadays would be equivalent to half a million additional involuntary part-time workers. I find evidence that involuntary part-time employment has become more volatile and persistent in the last 25 years. I study the impact that innovation in workforce management practices, a process that started in the 1990s and that has increased the degree of substitutability between full-time and part-time workers, may have had in changing the response over time of involuntary part-time employment to business cycle fluctuations. Impulse response analysis from the model indicates that an increase in the degree of substitutability makes involuntary part-time employment more sensitive to aggregate productivity shocks. Chapter 2. In "The Labor Wedge: A Search and Matching Perspective" we define and quantify static and dynamic labor market wedges in a search and matching model with endogenous labor force participation. Existing literature has generally centered on Walrasian labor markets in characterizing the inefficiencies, or ``gaps'', between labor demand and labor supply. However, given the conventional view in the profession that the matching process plays an important role in the labor market, the neoclassically-measured labor wedge suffers from a misspecification problem as it ignores the role of long-lasting relationships in explaining the cyclical pattern of the labor wedge. To construct the wedge we use a rigorously defined transformation function of the economy, which contains both the matching technology and the neoclassical production technology. Both technologies are primitives of the economy in the sense that a Social Planner must respect both processes. Given the model-appropriate transformation frontier and the household's static and dynamic marginal rates of substitution, we use data on the labor force participation rate, the employment rate, the vacancy rate, real consumption, real government spending, and real GDP to construct static and dynamic labor wedges. We find that, in a version of the model where all employment relationships turn over every period, the static labor wedge is countercyclical, a result that is consistent with existing literature. Once we consider long-lasting employment relationships, we can measure both static and dynamic wedges separately. We then find that, while the static wedge continues to be countercyclical, the dynamic (or intertemporal) wedge is procyclical. Since the latter is associated with the vacancy-posting decision of the firm, this result suggests that understanding the behavior of labor demand may be crucial to explaining the dynamic wedge. Our focus so far has been on obtaining a quantitative measure of both the static and dynamic wedges, and on analyzing their business cycle properties. Now we are working on extending this framework to provide a micro-founded explanation of the forces that could be driving the cyclical movements of the wedges. Chapter 3. Recent research has found that individuals who become unemployed allocate most of their forgone working hours into leisure rather than increasing the time devoted to job search activities. What is the rationale behind this decision? There are many factors that may affect the job search behavior of the unemployed. However, in this study I focus on a particular channel: the decision on how unemployed individuals allocate their time could be biased towards activities that increase their probability of finding a job. They might find more valuable to increase their social activities rather than looking formally for a job because this enhances their network, which could increase their chances of finding a job, even with less search effort. In "The Time Use Decisions of the Unemployed: A Survival Analysis", I conduct a duration analysis to estimate the effect of different time use allocations on the unemployment hazard rate using time use data from the Survey of Unemployed Workers in New Jersey. Defining "finding a job" as a failure, I estimate a single-spell, discrete-time duration model of unemployment with time-varying covariates using semi-parametric techniques. Given that I work with interval-censored data, I conduct the analysis using discrete time survival analysis techniques. The results indicate that education/training activities have a significant and positive impact on the hazard rate, i.e. they increase the probability that an unemployed worker finds a job, while leisure has the opposite effect. Furthermore, neither job-search nor networking have a significant effect on the hazard rate in the baseline specification. However, this result changes when incorporating into the regression interaction terms of these variables with a dummy that takes the value one if the individual is a long-term unemployed and zero otherwise. In this case, the coefficient associated with networking becomes positive and significant, while the coefficient of the interaction term is negative. This implies that networking has a positive effect on the hazard rate for short unemployment spells, but this effect weakens if the individual has been unemployed for a longer period. On the other hand, even after incorporating the interaction term, job search remains insignificant. These findings shed light on why individuals may not want to devote additional time to formal job search: it does not pay off with a higher likelihood of receiving a job offer, regardless of the length of the unemployment spell. On the other hand, other activities, such as investing in education or networking, are positively related to the probability of finding a job -- at least for short unemployment spells -- and thus it makes more sense for these individuals to devote more time to them.