Essays on Job Search and Labor Market Dynamics

This dissertation consists of three separate essays on job search and labor market dynamics. In the first essay, “The Impact of Labor Market Conditions on Job Creation: Evidence from Firm Level Data”, I study how much changes in labor market conditions reduce employment fluctuations over the business cycle. Changes in labor market conditions make hiring more expensive during expansions and cheaper during recessions, creating counter-cyclical incentives for job creation. I estimate firm level elasticities of labor demand with respect to changes in labor market conditions, considering two margins: changes in labor market tightness and changes in wages. Using employer-employee matched data from Brazil, I find that all firms are more sensitive to changes in wages rather than labor market tightness, and there is substantial heterogeneity in labor demand elasticity across regions. Based on these results, I demonstrate that changes in labor market conditions reduce the variance of employment growth over the business cycle by 20% in a median region, and this effect is equally driven by changes along each margin. Moreover, I show that the magnitude of the effect of labor market conditions on employment growth can be significantly affected by economic policy. In particular, I document that the rapid growth of the national minimum wages in Brazil in 1997-2010 amplified the impact of the change in labor market conditions during local expansions and diminished this impact during local recessions.

In the second essay, “A Framework for Estimating Persistence of Local Labor

Demand Shocks”, I propose a decomposition which allows me to study the persistence of local labor demand shocks. Persistence of labor demand shocks varies across industries, and the incidence of shocks in a region depends on the regional industrial composition. As a result, less diverse regions are more likely to experience deeper shocks, but not necessarily more long lasting shocks. Building on this idea, I propose a decomposition of local labor demand shocks into idiosyncratic location shocks and nationwide industry shocks and estimate the variance and the persistence of these shocks using the Quarterly Census of Employment and Wages (QCEW) in 1990-2013.

In the third essay, “Conditional Choice Probability Estimation of Continuous- Time Job Search Models”, co-authored with Peter Arcidiacono and Arnaud Maurel, we propose a novel, computationally feasible method of estimating non-stationary job search models. Non-stationary job search models arise in many applications, where policy change can be anticipated by the workers. The most prominent example of such policy is the expiration of unemployment benefits. However, estimating these models still poses a considerable computational challenge, because of the need to solve a differential equation numerically at each step of the optimization routine. We overcome this challenge by adopting conditional choice probability methods, widely used in dynamic discrete choice literature, to job search models and show how the hazard rate out of unemployment and the distribution of the accepted wages, which can be estimated in many datasets, can be used to infer the value of unemployment. We demonstrate how to apply our method by analyzing the effect of the unemployment benefit expiration on duration of unemployment using the data from the Survey of Income and Program Participation (SIPP) in 1996-2007.

Assessing Surveillance Elements of the Zanzibar Malaria Elimination Program to Support Malaria Elimination in Zanzibar

Though significant progress has been made through control efforts in recent years, malaria remains a leading cause of morbidity and mortality throughout the world, with 3.2 billion people at risk of developing the disease. Zanzibar is currently pursuing malaria elimination through the Zanzibar Malaria Elimination Program (ZAMEP), and is working toward a goal of no locally acquired malaria cases by 2018. A comprehensive and well functioning malaria surveillance program is central to achieving this goal. Under ZAMEP’s current surveillance strategy, District Malaria Surveillance Officers (DMSOs) respond to malaria case notifications through the reactive case detection (RACD) system. Three malaria screening and treatment strategies are undertaken in response to this system, including household-level (HSaT), focal-level (FSaT), and mass-level (MSaT). Each strategy is triggered by a different case threshold and tests different-sized populations. The aims of this study were to (1) assess the cost effectiveness of three malaria screening and treatment strategies; (2) assess the timeliness and completeness of ZAMEP’s RACD system; (3) and qualitatively explore the roles of DMSOs.

Screening disposition and budget information for 2014 screening and treatment strategies was analyzed to determine prevalence rates in screened populations and the cost effectiveness of each strategy. Prevalence rates within the screened population varied by strategy: 6.1 percent in HSaT, 1.2 percent in FSaT, and 0.9 percent in MSaT. Of the various costing scenarios considering cost per person screened, MSaT was the most cost-effective, with costs ranging from $9.57 to $12.57 per person screened. Of the various costing scenarios considering cost per case detected, HSaT was the most cost-effective, at $385.51 per case detected.

Case data from 2013 through mid-2015 was used to assess the timeliness and completeness of the RACD system. The average number of RACD activities occurring within 48 hours of notification improved slightly between 2013 and the first half of 2015, from 90.7 percent to 93.1 percent. The average percentage of household members screened during RACD also increased over the same time period, from 84 percent in 2013 to 89.9 percent in the first half of 2015.

Interviews with twenty DMSOs were conducted to gain insights into the challenges to malaria elimination both from the health system and the community perspectives. Major themes discussed in the interviews include the need for additional training, inadequate information capture at health facility, resistance to household testing, transportation difficulties, inadequate personnel during the high transmission season, and community misinformation.

Zanzibar is now considered a low transmission setting, making elimination feasible, but also posing new challenges to achieving this goal. The findings of this study provide insight into how surveillance activities can be improved to support the goal of malaria elimination in Zanzibar. Key changes include reevaluating the use of MSaT activities, improving information capture at health facilities, hiring additional DMSOs during the high transmission season, and improving community communication.

The Life Cycle of Corporate Venture Capital

This paper establishes the life-cycle dynamics of Corporate Venture Capital (CVC) to explore the information acquisition role of CVC investment in the process of corporate innovation. I exploit an identification strategy that allows me to isolate exogenous shocks to a firm's ability to innovate. Using this strategy, I first find that the CVC life cycle typically begins following a period of deteriorated corporate innovation and increasingly valuable external information, lending support to the hypothesis that firms conduct CVC investment to acquire information and innovation knowledge from startups. Building on this analysis, I show that CVCs acquire information by investing in companies with similar technological focus but have a different knowledge base. Following CVC investment, parent firms internalize the newly acquired knowledge into internal R&D and external acquisition decisions. Human capital renewal, such as hiring inventors who can integrate new innovation knowledge, is integral in this step. The CVC life cycle lasts about four years, terminating as innovation in the parent firm rebounds. These findings shed new light on discussions about firm boundaries, managing innovation, and corporate information choices.