PhD Oral Exam - Munkh-Ireedui Bayarjargal, Economics

When studying for a doctoral degree (PhD), candidates submit a thesis that provides a critical review of the current state of knowledge of the thesis subject as well as the student’s own contributions to the subject. The distinguishing criterion of doctoral graduate research is a significant and original contribution to knowledge.

Once accepted, the candidate presents the thesis orally. This oral exam is open to the public.

Abstract

Over the last three decades, the U.S. labor force has increased by less than thirty percent. However, the number of Social Security Disability Insurance (DI) beneficiaries has almost tripled.1 This is highly surprising because the overall health of the labor force has consistently improved in the U.S. Motivated by these empirical facts, in this thesis, I explore DI participation at the individual level, utilizing micro-public surveys and employing a combination of empirical and theoretical dynamic models. The thesis consists of three chapters.

The first chapter investigates the relationship between an individual’s decision to participate in the DI program, a skill level, and labor market outcomes. To explore these dynamics, I extend the standard Diamond-Mortensen-Pissarides framework to a setting with heterogeneous skills and endogenous DI participation. Using the model, I investigate the effects of aggregate productivity, health-related eligibility criteria for DI applicants, and average success rates for DI applications on labor market outcomes, including a wage gap between future DI beneficiaries and non-beneficiaries, market tightness, unemployment, and DI participation. The model yields three key insights. Firstly, during economic downturns, individuals with relatively higher skill levels tend to opt for disability benefits, resulting in a narrowing of the wage gap. These results showcase a countercyclical pattern in DI participation and the average skill level of DI beneficiaries. Secondly, less skilled workers tend to participate in the DI program when faced with more relaxed health-related eligibility requirements. Thirdly, the average success rates for DI applications exhibit an increase in DI participation. In contrast to the pronounced effect of more relaxed health-related eligibility requirements, these success rates have a minor influence on the skill composition of DI beneficiaries.

In the second chapter, I explore how an individual's decision on DI participation is related to their health, productivity, and labor market outcomes. The novelty of the analysis is incorporating health-driven productivity and endogenous DI participation into the standard Diamond-Mortensen-Pissarides framework. I show that stochastic health-driven productivity in the presence of endogenous job separation plays a pivotal role in accounting for key features of the data on DI participation, as well as the dynamic relationships between health, DI participation, and wages at the individual level. Using the model, I evaluate the DI program in the U.S. while focusing on policy instruments such as the length of the waiting periods for the initial determination procedure and the duration of the appeal process. The results show that a marginal increase in the length of the initial determination process and that of the appeal process have substantially different impacts on DI participation and labor market outcomes. Specifically, a shorter waiting period for the initial determination raises unemployment, whereas a shorter waiting period for the appeal process reduces it. Importantly, the quantitative predictions of the model suggest that not only the overall health level of the labor force but also the persistence and volatility of the individual-level health conditions are important for understanding the extent of DI participation.

In the third chapter, I examine the impact of three popular non-health factors, including the replacement rates of DI and UI (Unemployment Insurance) benefits and unemployment duration, on DI participation at the individual level using an empirical logistic model. Even though numerous studies explore the impact of non-health factors, the literature mainly focuses on aggregate-level data. This chapter offers the first microdata-based evidence on the impact of certain non-health factors on DI participation. The estimation results suggest that the replacement rate of DI benefits and unemployment duration have a strong positive impact on DI participation at the individual level. Based on these estimation results, I conduct a set of counterfactual experiments.