Research

Working Papers

Semi-Nonparametric Models of Multidimensional Matching: An Optimal Transport Approach (with Dongwoo Kim, last revised: May 2024), revise and resubmit, Journal of Econometrics

arXiv; Cemmap working paper
Abstract: This paper proposes empirically tractable multidimensional matching models, focusing on worker-job matching. We generalize the parametric model proposed by Lindenlaub (2017), which relies on the assumption of joint normality of observed characteristics of workers and jobs. In our paper, we allow unrestricted distributions of characteristics and show identification of the production technology, and equilibrium wage and matching functions using tools from optimal transport theory. Given identification, we propose efficient, consistent, asymptotically normal sieve estimators. We revisit Lindenlaub's empirical application and show that, between 1990 and 2010, the U.S. economy experienced much larger technological progress favoring cognitive abilities than the original findings suggest. Furthermore, our flexible model specifications provide a significantly better fit for patterns in the evolution of wage inequality.

Point-Identifying Semiparametric Sample Selection Models with No Excluded Variable (with Dongwoo Kim, last revised: February 2025), revise and resubmit, Journal of Business and Economic Statistics

arXiv; Cemmap working paper
Abstract: Sample selection is pervasive in applied economic studies. This paper develops semiparametric selection models that achieve identification without relying on exclusion restrictions, an assumption long believed necessary for identification in semiparametric selection models. Our identification conditions require at least one continuously distributed covariate and certain nonlinearity in the selection process. We propose a two-step plug-in estimator that is root-n consistent, asymptotically normal, and computationally straightforward (readily available in statistical software), allowing for heteroskedasticity. Our approach provides a middle ground between Lee (2009)'s nonparametric bounds and Honoré and Hu (2020)'s linear selection bounds, while ensuring point identification. Simulation evidence confirms its excellent finite-sample performance. We apply our method to estimate the racial and gender wage disparity using data from the US Current Population Survey. Our estimates tend to lie outside the Honoré and Hu bounds.

Local Polynomial Estimation of Time-Varying Parameters in Nonlinear Models (with Dennis Kristensen, last revised: August 2023), revise and resubmit, Econometric Theory

arXiv
Abstract: We develop a novel asymptotic theory for local polynomial (quasi-) maximum-likelihood estimators of time-varying parameters in a broad class of nonlinear Markov models. Under weak regularity conditions, we show the proposed estimators are consistent and follow normal distributions in large samples. Our conditions impose weaker smoothness and moment conditions on the data-generating process and its likelihood compared to existing theories. Furthermore, the bias terms of the estimators take a simpler form. We demonstrate the usefulness of our general results by applying our theory to local (quasi-)maximum-likelihood estimators of time-varying VAR’s, ARCH models, and Poisson autogressions. For the first two models, we are able to substantially weaken the conditions found in the existing literature. For the Poisson autogression, existing theories cannot be applied while our novel approach allows us to analyze it. An empirical study of US default counts demonstrates the usefulness of the proposed estimators and sheds new lights on their dynamics.

Publications

Closed-Form Approximations of Moments and Densities of Continuous-Time Markov Models (with Dennis Kristensen and Antonio Mele), Journal of Economic Dynamics and Control, Vol 168, 104948, 2024

Journal article (Open access); arXiv
Abstract: This paper develops power series expansions of a general class of moment functions, including transition densities and option prices, of continuous-time Markov processes, including jump–diffusions. The proposed expansions extend the ones in Kristensen and Mele (2011) to cover general Markov processes, and nest transition density and option price expansions recently developed in the literature, thereby connecting seemingly different ideas in a unified framework. We show how the general expansion can be implemented for fully general jump-diffusion models. We provide a new theory for the validity of the expansions which shows that series expansions are not guaranteed to converge as more terms are added in general once the time span of interest gets larger than some model–specific threshold. Thus, these methods should be used with caution when applied to problems with a larger time span of interest, such as long-term options or data observed at a low frequency. At the same time, the numerical studies in this paper demonstrate good performance of the proposed implementation in practice when applied to pricing options with time to maturity below three months. Thus, our expansions are particularly well suited for pricing ultra-short-term (such as “zero–day”) options.

Vaccination Strategies and Transmission of COVID-19: Evidence across Advanced Countries (with Dongwoo Kim), Journal of Health Economics, Vol 82, 102589, 2022

Journal article (Open access); arXiv; Cemmap working paperMedia: News 1 (Korean); SFU News
Abstract: Given limited supply of approved vaccines and constrained medical resources, design of a vaccination strategy to control a pandemic is an economic problem. We use time-series and panel methods with real-world country-level data to estimate effects on COVID-19 cases and deaths of two key elements of mass vaccination – time between doses and vaccine type. We find that new infections and deaths are both significantly negatively associated with the fraction of the population vaccinated with at least one dose. Conditional on first-dose coverage, an increased fraction with two doses appears to offer no further reductions in new cases and deaths. For vaccines from China, however, we find significant effects on both health outcomes only after two doses. Our results support a policy of extending the interval between first and second doses of vaccines developed in Europe and the US. As vaccination progresses, population mobility increases, which partially offsets the direct effects of vaccination. This suggests that non-pharmaceutical interventions remain important to contain transmission as vaccination is rolled out.

Testing for the Presence of Measurement Error in Stata (with Daniel Wilhelm), Stata Journal, Vol 20, Issue 2, 2020

Journal article (Open access); Cemmap working paper; Stata code
Abstract: In this article, we describe how to test for the presence of measurement error in explanatory variables. First, we discuss the test of such hypotheses in parametric models such as linear regressions and then introduce a new command, dgmtest, for a nonparametric test proposed in Wilhelm (2018, Working Paper CWP45/18, Centre for Microdata Methods and Practice, Institute for Fiscal Studies). To illustrate the new command, we provide Monte Carlo simulations and an empirical application to testing for measurement error in administrative earnings data.

Work in Progress

The Impact of EU Enlargement and Brexit on International Migration (with Yoonjung Kim)

Multidimensional Matching and Labor Market Complementarity (with Esben Scriver Andersen)

Sieve Estimation of Optimal Transport with General Surplus

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