I am an Assistant Professor at CEMFI. I received my Ph.D in Economics and Statistics from MIT in 2021, and my B.A. in Economics and Mathematics from Wellesley College in 2014. Previously I was a Postdoctoral Research Fellow at UC Berkeley, hosted by Professor Avi Feller and Professor Jesse Rothstein. My primary research interests are in Econometrics and Public Economics.

Email: lsun20 [at] cemfi.es

I am also on Google Scholar.

Working Papers

“Empirical Welfare Maximization with Constraints"

“Double Robustness for Complier Parameters and a Semiparametric Test for Complier Characteristics” (with Rahul Singh)

We propose a semiparametric test to evaluate (i) whether different instruments induce subpopulations of compliers with the same observable characteristics on average, and (ii) whether compliers have observable characteristics that are the same as the full population on average. This test can serve as a flexible robustness check for the external validity of instruments. We use it to reinterpret the difference in LATE estimates that Angrist and Evans (1998) obtain when using different instrumental variables. To justify the test, we characterize the doubly robust moment for Abadie (2003)’s class of complier parameters, and we analyze a machine learning update to kappa weighting.

Selected Research Papers in Progress

"Adapting to Misspecification" (with Tim Armstrong and Patrick Kline)

Empirical research typically involves an efficiency-robustness tradeoff. A researcher seeking to estimate a scalar parameter can invoke strong assumptions to motivate a restricted estimator that is precise but may be heavily biased if the assumptions are violated, or they can relax some of these assumptions to motivate a more variable unrestricted estimator that is asymptotically unbiased. When a bound on the bias of the restricted estimator is available, it is optimal to shrink the unrestricted estimator towards the restricted estimator. For settings where a bound is not known, or when that bound may not be sharp, we propose shrinkage estimators that are adaptive: they minimize the percentage increase in worst case risk relative to an oracle that knows the magnitude of the restricted estimator’s bias. We show how to compute the adaptive estimator by solving for a least favorable prior in a weighted convex minimax problem. A simple lookup table is provided for computing the adaptive estimates from the restricted and unrestricted estimates, their standard errors, and their correlation. We revisit five influential empirical papers and study how estimates of economic parameters change when adapting to misspecification.


“A linear panel model with heterogeneous coefficients and variation in exposure” (with Jesse M. Shapiro), Journal of Economic Perspectives, 2022 36:4, 193-204.

Preprint, NBER Working Paper #29976, Slides, Video series.

“Inference with Many Weak Instruments” (with Anna Mikusheva), The Review of Economic Studies. 2022 89:5, 2663–2686.

Preprint, Supplementary Appendix, Replication code.

“Estimating Dynamic Treatment Effects in Event Studies with Heterogeneous Treatment Effects” (with Sarah Abraham), Journal of Econometrics. 2021 225:2, 175-199.

Preprint, Replication code, Slides.

eventstudyinteract is a Stata module that implements the interaction weighted estimator for an event study. Sun and Abraham (2021) proves that this estimator is consistent for the average dynamic effect at a given relative time even under heterogeneous treatment effects. eventstudyweights is a Stata module that estimate weights underlying two-way fixed effects regressions based on Sun and Abraham (2021).

“Weak Instruments in IV Regression: Theory and Practice” (with Isaiah Andrews and James Stock), Annual Review of Economics. 2019 11:1, 727-753.

Appendix, Replication code.

“Implementing valid two-step identification-robust confidence sets for linear instrumental-variables models” Stata Journal 18(4), 803–825.

twostepweakiv is a Stata module that implements the two-step weak-instrument-robust confidence sets based on Andrews (2018) and the refined projection method for subvector inference based on Chaudhuri and Zivot (2011) for linear instrumental-variable (IV) models. Development versions and replication code for the article are available on GitHub.

Policy works

“Structural Reforms and Economic Growth: A Machine Learning Approach” (with Anil Ari and Gabor Pula)

IMF Working Paper No. 2022/184

Presentation: IMF European Department Seminar


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