Publication

[21] "The Value of Piped Water and Sewers: Evidence from 19th Century Chicago," with M. Coury, A. Shertzer and M. Turner. (2023). Forthcoming in Review of Economics and Statistics.

[20] "Treatment Choice, Mean Square Regret and Partial Identification," with S. Lee and C. Qiu, (2023), Japanese Economic Review, Vol. 74 (4) pp. 573-602. 

[19] "Inference on Winners," with I. Andrews and A. McCloskey, (2024) Quarterly Journal of Economics, Vol. 139 (1) pp. 305-358.

[18] "Narrative Restrictions and Proxies," with R. Giacomini and M. Read, (2022) Journal of Business and Economic Statistics, Vol. 40 (4) pp. 1415 - 1425. With discussions and rejoinder. 

[17] "Inference for Losers," with I. Andrews, D. Bowen, and A. McCloskey, (2022) American Economic Association Papers and Proceedings. Vol. 112, pp. 635-42.

[16] "Who Should Get Vaccinated? Individualized Allocation of Vaccines over SIR Network," with G. Wang, (2023) Journal of Econometrics, Vol. 232 (1), pp. 109-131

[15] "Uncertain Identification," with R. Giacomini and A. Volpicella, (2022). Quantitative Economics, Vol. 13 (1), pp 95-123.

[14] "Testing Identifying Assumptions in Fuzzy Regression Discontinuity Designs," with Y. Arai, Y-C. Hsu, I. Mourifie, and Y. Wan, (2022), Quantitative Economics. Vol. 13 (1), pp 1-28.  Online Supplementary Appendix | Replication files | Matlab functions

[13] "The Identification Region of the Potential Outcome Distributions under Instrument Independence," (2021), Journal of Econometrics. Vol. 225 (2), pp 231-253. Online appendix

[12] "Non-Bayesian Updating in a Social Learning Experiment," with R. De Filippis, A. Guarino, and P. Jehiel, (2022), Journal of Economic Theory. Vol. 199. Replication files. 2017 working paper version titled as "Updating Ambiguous Beliefs in a Social Learning Experiment"

[11] "Robust Bayesian Inference for Set-identified Models," with R. Giacomini, (2021). Econometrica. Vol. 89 (4), pp 1519-1556. Replication files | Matlab functions. This paper merges and replaces two previous working papers, "Robust Inference about Partially Identified SVARs" (2015, with Raffaella Giacomini) and "Estimation and Inference for Set-identified Parameters Using Posterior Lower Probability" (2012).
Awarded the inaugural Haavelmo Prize for the best econometrics paper published in Econometrica in the preceding four years. 

[10] "Robust Bayesian Inference in Proxy SVARs," with R. Giacomini and M. Read, (2022), Journal of Econometrics. Vol. 228 (1), pp 107-126. Replication files

[9] "Inference After Estimation of Breaks," with I. Andrews and A. McCloskey, (2021). Journal of Econometrics. Vol. 224 (1), pp 39-59.

[8] "Posterior Distribution of Nondifferentiable Functions," with J.-L. Montiel-Olea, J. Payne, and A. Velez, (2020), Journal of Econometrics. Vol. 217 (1), pp 161-175.

[7] "Equality-Minded Treatment Choice," A. Tetenov,  (2021), Journal of Business and Economic Statistics. Vol. 39 (2), pp 561-574. Online Supplement

[6] "Information Redundancy Neglect versus Overconfidence: A Social Learning Experiment," with M. Angrisani, A. Guarino, and P. Jehiel, (2021), American Economic Journal: Microeconomics. Vol. 13, No. 3, pp 163-97. 

[5] "Mostly Harmless Simulations? Using Monte Carlo Studies for Estimator Selection," with A. Advani and T. Słoczyński), (2019), Journal of Applied Econometrics. Vol. 34, pp 893-910. Supplementary material

[4] "Who Should be Treated? Empirical Welfare Maximization Methods for Treatment Choice," with A. Tetenov, (2018), Econometrica, Vol. 86(2), pp 591-616. DOI: 10.3982/ECTA13288.  Supplementary material 1 (Appendices A - C) | Supplementary material 2 (Appendices D - E, replication files)

[3] "Model averaging in semiparametric estimation of treatment effects," with C. Muris, (2016). Journal of Econometrics, Vol. 193 (1), pp 271-289.

[2] "A Test for Instrument Validity," (2015). Econometrica, Vol. 83(5), pp 2043-2063. DOI: 10.3982/ECTA11974 (2008 version titled as A Bootstrap Test for Instrument Validity in the Heterogeneous Treatment Effect Model, here).  R-functions to implement the test for a binary or multi-valued discrete instrument. If you want to test IV-validity with conditioning covariates, I recommend to try tests shown in the working paper [wp26] (R codes downloadable) 

[1] "Instrumental Variables Before and LATEr, Comment on `Instrumental Variables: An Econometrician's Perspective' by Guido Imbens," (2014). Statistical Science, Vol. 29, No.3, 359-362.