Welcome to my website! I am a Senior Lecturer in Economics at the University of Sydney.
My research interest lies in Econometric Theory, Machine Learning, Computational Economics, and Industrial Organization.
Currently, I am working on improving the efficiency of moment selection procedures for GMM, developing computational tools for logistic regression with a large number of choices, and conducting inference with incomplete data.
I received my Ph.D. in Economics from the University of Washington in 2020. I also hold an M.A. in Economics from Vanderbilt University, an M.Sc. in Engineering from Ecole Centrale de Lyon, and an M.Eng. and a B.Eng. in Electrical Engineering from Xi’an Jiaotong University.
Abstract: In this paper, we develop a unified approach to study partial identification of a finite-dimensional parameter defined by a moment equality model with incomplete data. We establish a novel characterization of the identified set for the true parameter in terms of a continuum of inequalities defined by optimal transport costs. For a special class of moment functions, we show that the identified set is convex, and its support function can be easily computed by solving an optimal transport problem. We demonstrate the generality and effectiveness of our approach through several running examples, including the linear projection model and two algorithmic fairness measures.
Keywords: Algorithmic Fairness, Causal Inference, Convex Analysis, Data Combination, Linear Projection, Partial Optimal Transport, Support Function, Time Complexity
Abstract: The gravity equation, the most popular empirical tool in International Trade, is usually estimated by the OLS or Poisson Pseudo-Maximum Likelihood (PPML), with PPML being robust to the heteroskedasticity of the error term. We find that when the trade elasticity is heterogeneous between country pairs, OLS and PPML estimates have different interpretations: OLS estimates the average elasticity and PPML estimates the elasticity of average. We show that most of the differences between the PPML and OLS estimates are explained by the difference in the interpretation of the coefficients. We also develop a new weighted PPML estimator for the elasticity of average in case of heterogeneous trade shock.
Keywords: elasticity, heterogeneity, heteroskedasticity, gravity model, misspecification
"Iterative Distributed Multinomial Regression," with Yanqin Fan and Yigit Okar, revise and resubmit at Journal of Econometrics.
Abstract: This article introduces an iterative distributed computing estimator for the multinomial logistic regression model with large choice sets. Compared to the maximum likelihood estimator, the proposed iterative distributed estimator achieves significantly faster computation and, when initialized with a consistent estimator, attains asymptotic efficiency under a weak dominance condition. Additionally, we propose a parametric bootstrap inference procedure based on the iterative distributed estimator and establish its consistency. Extensive simulation studies validate the effectiveness of the proposed methods and highlight the computational efficiency of the iterative distributed estimator.
Keywords: Distributed computing, Iterative methods, Maximum likelihood, Multinomial logistic regression.
"Estimation and Inference in Games of Incomplete Information with Unobserved Heterogeneity and Large State Space," with Yanqin Fan and Shuo Jiang, Quantitative Economics, 2024
Keywords: unobserved heterogeneity, matching-types problem, multistep moment selection, time complexity, space complexity
"Wald, QLR, and Score Tests When Parameters are Subject to Linear Inequality Constraints," with Yanqin Fan, Journal of Econometrics, 2023
Keywords: extremum estimator, inequality constraint, uniform inference, implicit nuisance parameter, polytope projection, Mincer regression, random coefficients model
"Partial Identification and Inference in Moment Models with Incomplete Data," with Yanqin Fan and Jing Tao, Journal of Econometrics, 2022
Keywords: copula theory, Bernstein copula, sieve estimation, inequality constraint, data combination, selection-on-observables, distributional treatment effects, counterfactual distribution
"Uniform Inference in a Generalized Interval Arithmetic Center and Range Linear Model," with Yanqin Fan, Econometric Theory, 2021
Keywords: interval data, extreme value theory, point process, uniform inference, inequality constraint, Bonferroni-type correction