I visited Cowls Foundation for Research in Economics for one week.

I moved to Rutgers, NJ.

I attended the Econometric Society Winter Meetings at Philadelphia.

I attended the Math. Forschungs. Oberwolfach workshop on Partial Identification, in Schwarzwaldstr.

"POET" has been recently accepted as a JRSSB read paper, read before RSS, London, on 13 Feb, 2013.

I moved to College Park, MD.

Research Interests

Papers

Partial identification
1. (2019) Bayesian inference for partially identified smooth convex models
  (with Simoni, A.) J. Econometrics. 211, 338-360.
2. (2010) Bayesian analysis in moment inequality models
  (with Jiang, W.) Ann. Statist. 38, 275-316.

Asset pricing
1. (2024) Observable versus Latent Risk Factors. (with Todorov, V.) manuscript
2. (2024) Robust Stock Index Return Predictions Using Deep Learning.
  (with Jagannathan, R. and Neuhierl, A.) manuscript
3. (2023) Does noise hurt economic forecasts?
  (with Ma, X., Neuhierl, A., and Shi, Z.) manuscript
4. (2022) Structural Deep Learning in Conditional Asset Pricing. (with Fan, J., Ke, T. and Neuhierl, A) manuscript
5. (2021) Thousands of alpha tests. (with Giglio, S. and Xiu, D.)
  Review of Financial Studies. 34, 3456-3496.
6. (2024) Changes in the span of systematic risk exposures. (with Todorov, V.) Quantitative Economics. forthcoming
7. (2021) Augmented factor models with applications to validating market risk factors and forecasting bond risk premia. (with Fan, J. and Ke, Y.)
  J. Econometrics. 222, 269-294.
8. (2016) Projected principal component analysis in factor models.
  (with Fan, J. and Wang, W.) Ann. Statist. 44, 219-254.
9. (2015) Risks of large portfolios. (with Fan, J. and Shi, X.)
  J. Econometrics. 186, 367-387.

Inference for Stochastic Gradient Descent
1. (2022) Fast and robust online inference with stochastic gradient descent via random scaling. (with Lee, S., Seo, M.H. and Shin, Y.) Proceedings of the AAAI Conference on Artificial Intelligence 36, 7381-7389.
2. (2024) Fast Inference for Quantile Regression with Tens of Millions of Observations. (with Lee, S., Seo, M.H. and Shin, Y.) J. Econometrics forthcoming
3. (2023) SGMM: Stochastic approximation to generalized method of moments. (with Chen, X., Lee, S., Seo, M.H. and Shin, Y.) J. Financial Econometrics forthcoming

Endogeneity and instrumental variables
1. (2024) Inference on time series nonparametric conditional moment restrictions using general sieves. (with Chen, X. and Wang, W.)
  manuscript
2. (2014) Endogeneity in High Dimensions. (with Fan, J.) Ann. Statist. 42, 872-917.
3. (2011) Posterior consistency of nonparametric conditional moment restricted models. (with Jiang, W.) Ann. Statist. 39, 3003-3031.

High dimensional structures
1. (2023) Inference for low rank models. (with Chernozhukov, V., Hansen, C. and Zhu, Y.) Ann. Statist. 51, 1309 - 1330
2. (2024) Inference for Low-rank Completion without Sample Splitting with Application to Treatment Effect Estimation. (with Choi, J. and Kwon, H.)
  J. Econometrics forthcoming
3. (2024) Inference for Low-rank Models without Estimating the Rank (with Choi, J. and Kwon, H.) manuscript
4. (2021) Sparse HP filter: finding kinks in the COVID-19 contact rate. (with Lee, S., Seo, M.H. and Shin, Y.) J. Econometrics. 220, 158-180
5. (2020) Inference for heterogeneous effects using low-rank estimations. (with Chernozhukov, V., Hansen, C. and Zhu, Y.) manuscript
6. (2021) Factor-driven two-regime regression. (with Lee, S., Seo, M.H. and Shin, Y.) Ann. Statist. 49, 1656-1678
7. (2018) Oracle estimation of a change point in high dimensional quantile regression. (with Lee, S., Seo, M.H. and Shin, Y.) JASA. 113, 1184-1194.
8. (2017) A lava attack on the recovery of sums of dense and sparse signals. (with Chernozhukov, V. and Hansen, C.) Ann. Statist. 45, 39-76.
9. (2018) The factor-lasso and k-step bootstrap approach for inference in high-dimensional economic applications. (with Hansen, C.) Econometric Theory 1-45.

Large panel data and factor model
1. (2022) Dynamic heterogeneous distribution regression panel models, with an application to labor income processes. (with Fernandez-Val, I., Gao, W.Y., Vella, F.) manuscript
2. (2020) Standard errors for panel data models with unknown clusters. (with Bai, J. and Choi, S.) J. Econometrics (forthcoming)
3. (2022) Learning latent factors from diversified projections and its applications to over-estimated and weak factors. (with Fan, J.) JASA 117, 909-924
4. (2018) Uniform Inference for Characteristic Effects of Large Continuous-Time Linear Models. (with Yang, X.) manuscript
5. (2016) Efficient estimation of approximate factor models via penalized maximum likelihood. (with Bai, J.) J. Econometrics. 191, 1-18.
6. (2015) Power enhancement in high dimensional cross-sectional tests.
  (with Fan, J. and Yao, J.) Econometrica. 83, 1497-1541.
7. (2017) Inferences in panel data with interactive effects using large covariance matrices. (with Bai, J.) J. Econometrics. 200, 59-78.
8. (2011) High dimensional covariance matrix estimation in approximate factor models. (with Fan, J. and Mincheva, M.) Ann. Statist. 39, 3320-3356.
9. (2013) Large covariance estimation by thresholding principal orthogonal complements. (with Fan, J. and Mincheva, M.).
  JRSSB (with discussion) 75, 603-680
  Reviewed by 7 screeners, 5 referees and 1 post-refereeing screener, read before Royal Statistical Society.

Empirical likelihood
1. (2011) Risk performance of classification decisions: a framework for posterior inference based on empirical likelihood
  (with Jiang, W.) manuscript
2. (2011) Ultra high dimensional variable selection with endogenous covariates. (with Fan, J.) manuscript

(2020) Recent developments on factor models and its applications in econometric learning (with Fan, J. and Li, K.) Annual Reviews of Financial Economics 13, 401-430
(2016) An overview of the estimation of large covariance and precision matrices. (with Fan, J. and Liu, H.) Econometrics Journal 19, C1-C32.
(2015) Approaches to high-dimensional covariance and precision matrix estimation. (with Fan, J. and Liu, H.) Financial Signal Processing and Machine Learning, chapter 6, edited by A.N. Akansu, S.R. Kulkarni, D. Malioutov, I. Pollak. Wiley
(2014) Unbalanced panel data models with interactive effects. (with Bai, J. and Yang, J.) The Oxford Handbook of Panel Data, chapter 5, edited by Badi Baltagi.