Essays in Labor and Macroeconomics

Other Titles
This dissertation contains three chapters that empirically examine the interactions among economic variables from three different fields: labor economics, macroeconomics, and financial markets. This dissertation lies at the intersection of these three fields, and the underlying theme is the empirical investigation that enhances our understanding of the mechanisms that drive economic activities that we observe today. The first chapter examines how labor market composition and macroeconomic conditions affect each other. A dual labor market structure that consists of “permanent jobs” and “temporary jobs” is common in many Continental European countries and in Japan, and over the last two decades, the share of temporary workers in these countries has increased markedly. In this chapter, I demonstrate through an analysis of Japanese household panel survey data that permanent workers experience faster wage growth than temporary workers. Then, building a search and matching model of dual labor market with endogenous human capital accumulation, I show that, in the presence of two different types of jobs with different rates of return to experience, a slowing of the economic growth rate in a dual labor market structure can prompt a substantial shift in the composition of jobs. The second chapter proposes a nonparametric method for studying the time series properties of macroeconomic variables. In particular, I focus on a class of learning networks called the Radial Basis Function (RBF). The main advantage of the RBF method is its flexibility and that it requires minimal functional-form assumptions. To assess the potential value of the RBF method, I simulate data points using a nonlinear New-Keynesian (NK) DSGE model and show that the RBF time series can uncover the nonlinear NK structure from simulated data observations whose length is as small as 300 (quarters). I then compare the out-of-sample prediction performance of the resulting network formula with other traditional time series methods, i.e., Vector-Autoregression and Bayesian VAR models. Finally, I apply this RBF time series method to US macroeconomic data from 1960-2010. The third chapter studies the link between the probability of default implied by Credit Default Swaps (CDS) spreads and the final prices of the defaulted bonds as established at the CDS settlement auctions. We observe that the postdefault recovery rates at the observed spreads imply markets were often ‘surprised” by the credit event. We find that the prices of the bonds that are deliverable at the auctions imply probabilities of default that are systematically different than the default probabilities estimated prior to the event of default using standard methodologies. We discuss the implications for CDS pricing models. We analyze the discrepancy etween the actual and theoretical CDS spreads and we find it is significantly associated both to the CDS market microstructure at the time of the settlement auction and to the general macroeconomic background. We discuss the potential for strategic bidding behavior at the CDS settlement auctions.
Journal / Series
Volume & Issue
Date Issued
Macroeconomics and Monetary Economics; Economics; Labor Economics
Effective Date
Expiration Date
Union Local
Number of Workers
Committee Chair
Mertens, Karel
Committee Co-Chair
Committee Member
Barseghyan, Levon
Huckfeldt, Christopher
Degree Discipline
Degree Name
Ph. D., Economics
Degree Level
Doctor of Philosophy
Related Version
Related DOI
Related To
Related Part
Based on Related Item
Has Other Format(s)
Part of Related Item
Related To
Related Publication(s)
Link(s) to Related Publication(s)
Link(s) to Reference(s)
Previously Published As
Government Document
Other Identifiers
Rights URI
dissertation or thesis
Accessibility Feature
Accessibility Hazard
Accessibility Summary
Link(s) to Catalog Record