Research

Research fields

• Forecasting (mostly binary prediction and loss functions), econometrics (nonparametric identification and estimation of treatment effects), prediction markets, statistical decisions

• My google scholar profile and citations

Publications

1. "The Use of Machine Learning in Treatment Effect Estimation" with Yu-Chin Hsu and Agoston Reguly. In: Chan, F., Matyas, L. (eds), Econometrics with Machine Learning . Advanced Studies in Theoretical and Applied Econometrics, vol 53. Springer, Cham (2022), pp. 79-109.  

   • • This is a review paper.

2. "Estimation and Inference for Distribution Functions and Quantile Functions in Endogenous Treatment Effect Models" with Tsung-Chih Lai and Yu-Chin Hsu. Econometric Reviews, 41 (2022), pp. 22-50.

   • • This is a fairly dry technical paper, but some of the results are used in the "Counterfactual Treatment Effects" paper---see below .

3. "Estimation of Conditional Average Treatment Effects with High Dimensional Data" with Qingliang Fan, Yu-Chin Hsu and Yichong Zhang. Journal of Business and Economic Statistics 40 (2022), pp. 313-327. 

   • • Working paper version.

     • The working paper version includes all supplements.

4. "Counterfactual Treatment Effects: Estimation and Inference" with Tsung-Chih Lai and Yu-Chin Hsu. Journal of Business and Economic Statistics, 40 (2022), pp. 240-255. 

   • • Supplemenatry material

     • Working paper version

     • Former titles: Forecasting Treatment Effects; Estimating Counterfactual Treatment Effects to Assess External Validity

5. "On the Possibility of Informative Equilibria in Future Markets with Feedback" (free access link) with Augusto Nieto Barthaburu. Journal of the European Economic Association 18 (2020), pp. 1521-1552.

   • •  Supplementary material

6. "Unrestricted and Controlled Identification of Loss Functions: Possibility and Impossibility Results" with Max Stinchcombe and Viola Grolmusz.  International Journal of Forecasting 35 (2019),  pp. 878-890. 

   • • Working paper version.  

     • Former title: Bregman and GPL Losses: Identified or Not? 

     • Files for replicating the empirical part. 

7.  “Using the Estimated AUC to Test the Adequacy of Binary Predictors” with Yu-Chin Hsu. Journal of Nonparametric Statistics 31 (2019), pp. 100-130. 

   • • Replication files (Instructions, Matlab code and cleaned data).

     • Working paper version.

     • Combines material from two earlier working papers: paper 1 and paper 2.

8.  "Information Flow Between Prediction Markets, Polls and Media: Evidence from the 2008 Presidential Primaries" with Urmee Khan.  International Journal of Forecasting 34 (2018), pp. 696-710.  

   • • Online supplement. 

     • Replication files (Instructions, Matlab code and cleaned data). Original data files.

     • Working paper version.

9.   “Estimating Conditional Average Treatment Effects” with Yu-Chin Hsu and Jason Abrevaya.  Journal of Business and Economic Statistics 33 (2015), pp. 485-505.  

   • • Matlab code and data for replicating the empirical results in the paper. 

     • Matlab code for replicating the Monte Carlo study.

     • Working paper version.

10.   “Inverse Probability Weighted Estimation of Local Average Treatment Effects: A Higher Order MSE Expansion” with Stephen Donald and Yu-Chin Hsu. Statistics and Probability Letters 95 (2014), pp. 132-138. 

    • • Supplemental material (additional proofs).

      • Working paper version.

11.   “Testing the Unconfoundedness Assumption via Inverse Probability Weighted Estimators of (L)ATT” with Stephen Donald and Yu-Chin Hsu.  Journal of Business and Economic Statistics 32 (2014), pp. 395-415. 

    • • Matlab code for replicating the Monte Carlo simulations and the empirical results in the paper .

      • Working paper version.

12.  “Predicting Binary Outcomes” with Graham Elliott.  Journal of Econometrics 174  (2013), pp. 15-26. 

    • • Matlab code for implementing the Maximum Utility estimator and replicating the Monte Carlo study in the paper.

      • Working paper version. Old (2007) working paper version.

13.  “On the Recoverability of Forecasters’ Preferences” with Max Stinchcombe. Econometric Theory 29 (2013), pp. 517-544. 

    • • Working paper version.

14.   “Closing the Gap Between Risk Estimation and Decision Making: Efficient Management of Trade Related Invasive Species Risk” with Mike Springborn. Review of Economics and Statistics 95 (2013), pp. 632-645. 

    • • Working paper version.

15.  “The Construction of Empirical Credit Scoring Models Based on Maximization Principles” with Hal White. Journal of Econometrics 157 (2010), pp. 110-119. 

    • • Working paper version.

16. “Optimal Binary Prediction for Group Decision Making” with Augusto Nieto Barthaburu. Journal of Business and Economic Statistics 28 (2010), pp. 308-319. 

    • • Note: We realized too late that the title of this paper is somewhat misleading; there is no voting, etc., involved. A better title would be “Optimal Binary Prediction for a Group of Decision Makers”.

      • Working paper version.