- Ph.D., University of Pennsylvania, 2017
Laura Liu's research interests encompass macroeconomics, econometrics, and network economics. She has been developing and implementing methods that flexibly and efficiently combine information from granular data to facilitate estimation and improve forecasting performance. Her recent research topics include (1) panel data, forecasting, and heterogeneous partial effects, (2) structural macro models with granular data, and (3) network analysis from a time-series perspective. Her research has been published in Econometrica, Journal of Econometrics, Quantitative Economics, Journal of Business and Economic Statistics, and Journal of Applied Econometrics. She currently serves as an Associate Editor for the Journal of Applied Econometrics and the Journal of Econometric Methods.
Laura Liu received her Ph.D. in Economics from the University of Pennsylvania in 2017. Her dissertation, "Point and Density Forecasts in Panel Data Models", received the 2018 Arnold Zellner Thesis Award in Econometrics and Statistics from the American Statistical Association (ASA) section of Business and Economic Statistics and the Journal of Business and Economic Statistics.