Research

Publications

1. "Semi-nonparametric Models of Multidimensional Matching: an Optimal Transport Approach" (with Young Jun Lee) 

Journal of Econometrics (forthcoming) [Ungated ArXiv version]

2. "Recent Applications of Generalized Instrumental Variable Models"

Seoul Journal of Economics, 2025, Volume 38, Number 1, Special Issue (invited contribution) 

3. "Nonparametric Estimation of Sponsored Search Auctions and Impacts of Ad Quality on Search Revenue" (with Pallavi Pal)

Management Science, 2025, 71.12: 10047-10066. [Cemmap working paper CWP16/24] [CESifo Working Paper No. 10312]

4. "Powerful t-tests in the presence of nonclassical measurement error" (with Daniel Wilhelm)

Econometric Reviews, 2024, Vol. 43, NO. 6, 345–378 [Cemmap working paper CWP22/23]

5. "IV methods for Tobit models" (with Andrew Chesher and Adam Rosen) 

Journal of Econometrics, 2023, Volume 235, Issue 2, pages 1700-1724 [Cemmap working paper CWP16/22]

6. "Partially Identifying Competing Risks Models: an Application to the War on Cancer"

Journal of Econometrics, 2023, Volume 234, Issue 2, pages 536-564 [Working paper version]

7. "COVID-19 Vaccination Mandates and Vaccine Uptake" (with Alexander Karaivanov, Shih En Lu, and Hitoshi Shigeoka)

Nature Human Behaviour, 2022, 6, 1615–1624 (2022 Impact Factor: 29.9) [MedRxiv preprint] [NBER WP] [IZA WP] 

8. "Vaccination strategies and transmission of COVID-19: evidence across advanced countries" (with Young Jun Lee)

Journal of Health Economics, 2022, Volume 82, 102589 [arXiv:2109.06453] [Cemmap working paper CWP38/21]

9. "An Adaptive Test of Stochastic Monotonicity" (with Denis Chetverikov and Daniel Wilhelm)

Econometric Theory, 2021, Volume 37, Issue 3, pp. 495 - 536 [Cemmap working paper CWP17/20]

10. "Partial identification in nonseparable count data IV models"

Econometrics Journal, 2020, Volume 23, Issue 2, Pages 232–250 [Working paper version]

11. "Nonparametric instrumental variable estimation" (with Denis Chetverikov and Daniel Wilhelm)

Stata Journal, 2018, Volume 18 Number 4: pp. 937-950 [Cemmap working paper CWP47/17] 

[Stata package: type "ssc install npiv" in your Stata console]

Working Papers

1. "Point-Identifying Semiparametric Sample Selection Models with No Excluded Variable" (2025, with Young Jun Lee), under review [Cemmap working paper CWP07/25]

Abstract: Sample selection is pervasive in applied economic studies. This paper develops semiparametric selection models that achieve point identification without relying on exclusion restrictions, an assumption long considered 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 softwares), allowing for heteroskedasticity. Our approach provides a middle ground between Lee (2009, Restud)'s nonparametric bounds and Honoré and Hu (2020, Econometrica)'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.

2. "Partial identification of the valuation distribution in sequential English auctions" (2026, with Kyoo il Kim and Pallavi Pal), under review [Cemmap working paper CWP08/26]

Abstract: This paper extends the incomplete model of Haile and Tamer (2003) from static English auctions to sequential English auctions. Because bidders may wait for future opportunities, the static condition that bidders do not let rivals win at beatable prices need not hold. We replace it with a dynamic opportunity-cost restriction, yielding nonparametric valuation bounds without solving a dynamic equilibrium. Sharp bounds are also characterized. We propose a novel moment-condition inversion estimator that pools auctions with heterogeneous bidder counts, mitigating finite-sample instability of order statistics approaches and admitting analytical standard errors and smooth confidence intervals. Applications to Korean wholesale used-car auctions and Cars and Bids online auctions deliver informative bounds. Counterfactual analyses show that the option to wait lowers first-period revenue by 8–11% in the Korean market, that increasing effective competition from 8 to 20 serious bidders in Cars and Bids raises seller revenue by 40–65%, and that maximin reserve prices vary substantially across vehicle clusters.

3. "Identification and Estimation of Semiparametric Multilayered Sample Selection Models" (2026), submitted [Cemmap working paper CWP10/26]

Abstract: Many selection problems are multilayered: agents first decide whether to participate and then sort among ordered or unordered categories. This paper shows that the sorting layer changes the geometry of identification. Unlike binary selection, in which selection bias can be summarized by a scalar control function, ordered and multinomial sorting generally produce multi-index control functions whose dimension determines the continuous covariate variation needed for identification. I establish matched non-identification and point-identification results for both architectures, showing how nonlinearity in the selection structure can substitute for excluded variables. I also show how additional structural restrictions reduce the control-function dimension and make estimation practical. I propose root-n-consistent two-step sieve plug-in estimators and apply the framework to gender wage gaps among Korean college graduates. Accounting for sorting reshapes the entry-level gap along the firm-size margin, where the corrected female coefficient turns positive for large-firm employment.