arXiv subjects

Young Jun Lee

Publications and source records attributed to Young Jun Lee.

5 recordsLinked to original sources

arXiv2026

Point-Identifying Semiparametric Sample Selection Models with No Excluded Variable

Sample selection is pervasive in applied economic studies. This paper proposes semiparametric selection models that achieve point identification without relying on exclusion restrictions. Our identification conditions require at least one continuously distributed covariate and certain nonlinearity in the selection process. We propose a two-step sieve plug-in estimator that is $\sqrt{n}$-consistent, asymptotically normal, and computationally straightforward, allowing for heteroskedasticity. We further derive the semiparametric efficiency bound for the model and propose a weighted variant of the estimator that attains the bound. 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 disparities using data from the US Current Population Survey. Our estimates often lie outside the Honoré and Hu bounds.

econ.EM↗

arXiv2026

Semi-nonparametric models of multidimensional matching: an optimal transport approach

This paper develops a set of empirically tractable and flexible sieve estimators for semi-nonparametric multidimensional matching models with transferable utility, focusing on worker-job matching. We generalize the parametric quadratic-Gaussian framework employed by Bojilov and Galichon (2016) and Lindenlaub (2017), which relies on joint normality of observed characteristics. We allow unrestricted distributions of characteristics and show identification of the production technology and the equilibrium wage and matching functions using optimal transport theory. Given identification, we propose efficient, consistent, and 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.

econ.EM↗

arXiv2025

Local Polynomial Estimation of Time-Varying Parameters in Nonlinear Models

We develop a novel asymptotic theory for local polynomial extremum estimators of time-varying parameters in a broad class of nonlinear time series models. We show the proposed estimators are consistent and follow normal distributions in large samples under weak conditions. We also provide a precise characterisation of the leading bias term due to smoothing, which has not been done before. We demonstrate the usefulness of our general results by establishing primitive conditions for local (quasi-)maximum-likelihood estimators of time-varying models threshold autoregressions, ARCH models and Poisson autogressions with exogenous co--variates, to be normally distributed in large samples and characterise their leading biases. An empirical study of US corporate default counts demonstrates the applicability of the proposed local linear estimator for Poisson autoregression, shedding new light on the dynamic properties of US corporate defaults.

econ.EM↗

arXiv2023

Closed-form approximations of moments and densities of continuous-time Markov models

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. We demonstrate that the class of expansions nests the transition density and option price expansions developed in Yang, Chen, and Wan (2019) and Wan and Yang (2021) as special cases, 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. Thus, these methods should be used with caution. At the same time, the numerical studies in this paper demonstrate good performance of the proposed implementation in practice when a small number of terms are included.

econ.EM↗

arXiv2022

Vaccination strategies and transmission of COVID-19: evidence across advanced countries

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.

econ.GN↗