Yulong Wang

Yulong Wang is an assistant professor of economics in the Maxwell School and a senior research associate in the Center for Policy Research. Before joining Syracuse University, Wang earned a B.A. at Tsinghua University in Beijing and a Ph.D. in economics from Princeton University.

His current research focuses on designing new econometric tools in the non-standard instances when the classic asymptotically Gaussian framework fails to provide good performance. These tools are strongly motivated by empirical applications. Leading examples include estimating the location of the tipping point in social segregation, determining metropolitan areas based on nighttime light intensity, inference about winner’s properties in auctions, and studying the cost of extreme events such as natural disasters. 

Fixed-k Asymptotic Inference about Tail Properties. (Joint with Ulrich K. Müller) Journal of the American Statistical Association 112 (2017), 1134-1143. 

Nearly Weighted Risk Minimal Unbiased Estimation. (Joint with Ulrich K. Müller) Journal of Econometrics 209 (2019), 18-34. 

Efficient Minimum Distance Estimation of Pareto Exponent from Top Income Shares. (Joint with Alexis A. Toda) Journal of Applied Econometrics 36 (2021), 228-243. a

Fixed-k Inference for Conditional Extremal Quantiles. (Joint with Yuya Sasaki) Journal of Business & Economic Statistics 40 (2022), 829-837. 

Estimation and Inference about Tail Features with Tail Censored Data. (Joint with Zhijie Xiao) Journal of Econometrics (2021), forthcoming. 

Nonparametric Tests of Tail Behavior in Stochastic Frontier Models. (Joint with William C. Horrace) Journal of Applied Econometrics 37 (2022), 537-562. 

Diagnostic Testing of Finite Moment Conditions for the Consistency and Root-N Asymptotic Normality of the GMM and M Estimators. (Joint with Yuya Sasaki) Journal of Business & Economic Statistics (2022), forthcoming. 

Threshold Regression with Nonparametric Sample Splitting. (Joint with Yoonseok Lee) Journal of Econometrics (2022), forthcoming.