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Joonbae Lee

 
Associate Fellow (부연구위원)          
& Head of the Department of Digital Economy Research (디지털경제연구실장) at KISDI (Korea Information Society Development Institute, 정보통신정책연구원) link
Ph.D., Economics., 2019 
University of Pennsylvania, Philadelphia, PA
 
Research Interests:

Applied Microeconomic Theory, Search and Matching Theory, Economics of Digitization, Industrial Organization

Contact  

Email:  joonbae@kisdi.re.kr
LinkedIn page: 

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EDUCATION
EDUCATION
2013-2019

Doctorate Degree 

University of Pennsylvania, Philadelphia, USA

Thesis Title:

“Essays on Labor Markets with Search and Information Frictions”

Ph.D., Economics, 2019

2011-2013

Master's Degree

Korea University, Seoul, South Korea

M.A., Economics, 2013

2004-2011

Bachelor's Degree

Korea University, Seoul, South Korea

B.A., Economics, 2011

B.S., Mathematics, 2011 (Double major)

(Military service in Korea, 2 yrs )

RESEARCH
RESEARCH & TEACHING INTEREST FIELD

Applied Microeconomic Theory

Labor Economics 

RESEARCH
“Wage Dynamics with Developing Asymmetric Information” (Job Market Paper)
  Download Paper

This paper introduces asymmetric information into the benchmark on-the-job search models of the labor market such as Burdett and Mortensen (1998) and Postel-Vinay and Robin (2002). To capture this idea, I assume that workers are heterogeneous in productivity, while firms learn about the productivity of their current workers over time. When a poaching firm contacts an employed worker, it is possible that the incumbent firm knows the worker's type, while the poaching firm does not. This introduces asymmetry of information when a poaching firm and incumbent firm plays first price auction game as in Postel-Vinay and Robin (2002). When incumbent firm is more informed than poaching firm, I find that poaching firm's belief about a worker's type increases with tenure, and that job-to-job transitions convey negative information on worker's type. At the same time, high type workers change jobs less frequently, while low type workers change jobs more frequently. This result matches the data, while more job transitions lead to higher wage in on-the-job search models with perfect information. The model also has implications to information policies in labor market, such as banning employers from inquiring applicant's wage history. The model implies that the policy decreases wage dispersion between types, but might have an unintended consequence of increasing adverse selection, and slowing down workers' wage growth.

“Ranking and Search Effort in Matching”, with Hanna Wang, 2021 Sep, Economic Theory (2021)
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This paper studies the relationship between search effort and workers’ ranking by employers. In order to do so, we propose a matching model in which employers have common preferences over a continuum of heterogeneous workers who choose a number of applications to send out. We show that in equilibrium, the relationship is hump-shaped for sufficiently high vacancy-to-worker ratios, that is, highly-ranked and lowly-ranked workers send out fewer applications than workers of mid-range rank. This arises due to two opposing forces driving the incentives of applicants. Increasing the number of applications acts as insurance against unemployment, but is less effective when the probability of success for each application is low. This mechanism exacerbates the negative employment outcomes of low-rank workers—hence, in contrast to the market equilibrium, in the social planner’s solution, the number of applications monotonically decrease in rank.

Publications
“Ranking and Search Effort in Matching”, with Hanna Wang, 2021 Sep 18, Economic Theory (2021)

  Download Paper

This is a joint work with my Ph.D. classmate. The paper studies the workers’ search effort when they are ranked by a common observable trait (e.g., test scores, college). We fully characterize the equilibrium to show how the search effort varies with rank, and how the market tightness and search cost affect a worker’s match outcome.

 “Optimal aggregation of multiple signals: Optimality of linear aggregation rule and possibility of using the maximum or the minimum of signals”, with Sam-Ho Lee, 2014 Jan 1, Journal of Economic Theory and Econometrics, 25, 4, p. 71-81 Download Paper

An optimal aggregation rule of multiple signals is studied. A sufficient condition for the optimality of a linear aggregation rule (the weighted sum of signals) and the common classes of signal distributions satisfying the condition are provided. Other aggregation rules such as rules using the maximum or the minimum are also considered and their usefulness is illustrated through examples.

Research Paper(s) in Progress
“Competition in Matching Market with Search Frictions: A Steady-State Analysis” 

The goal of this project is to understand incentives to search when agents’ heterogeneity matter through acceptance rule/switching strategy of the counterparty. I employ continuous-time random search framework to analyze the equilibrium behavior in steady state. I show that agent’s search intensity is increasing in his/her acceptance rate, and the expected duration of the match. Policies that make firing costly is shown to have dubious effects. I also characterize a sufficient condition for existence of steady state.

“Patent Race, Optimal Licensing Fee and Patent Duration”, with Ryan Fackler

The basic goal of this project is to get insight into the following questions: (1) How does industry characteristics (invention arrival rate and invention value) change incentives to license a patent and to conduct ongoing research? (2) How does the length of the patent impact incentives to license a patent and to conduct ongoing research? (3) How does the socially optimal patent term length change with industry characteristics? To get insight into these three questions, we are going to consider a two-firm model. One firm will have a patent while the other does not. The firm with a patent must decide how much to produce using their patent, whether they want to do research to get a new patent, and how much they should charge as a licensing fee to the other firm. The firm without the patent must decide how much to produce given the licensing fee, and whether to do research to get their own patent.

TEACHING
TEACHING EXPERIENCE
Graduate level courses at University of Pennsylvania
Fall,2018

Teaching Assistant

Economics for Social Policy (Masters Level)

School of Social Policy and Practice

for Prof. Ioana Marinescu

Summer, 2016

Instructor

Summer, 2016

Instructor

Math Camp for Incoming Graduate Students

Dept. of Economics

Fall, 2015

Teaching Assistant

Graduate Game Theory

Dept. of Economics

for Prof. George Mailath and Prof. Mallesh Pai

Fall, 2014

Teaching Assistant

Graduate Game Theory

Dept. of Economics

for Prof. George Mailath and Prof. Mallesh Pai

Undergraduate level courses at University of Pennsylvania
Summer,2018

Instructor

Statistics for Economists

Dept. of Economics

Spring, 2018

Recitation Instructor

Fall, 2017

Teaching Assistant

Spring, 2015

Teaching Assistant

Intermediate Microeconomics

Dept. of Economics

for Prof. Kenneth Burdett

Strategic Reasoning Philosophy

Politics and Economics Program

for Prof. Deniz Selman

Strategic Reasoning Philosophy

Politics and Economics Program

for Prof. David Dillenberger

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