Laura Liu profile picture
Economist
Federal Reserve Board
Division of Financial Stability
Financial Institution Risk Evaluation Section
20th St and Constitution Ave N.W.
Washington, D.C. 20551
Email:
laura.liu (at) frb.gov
liuyu1237 (at) gmail.com
CV: PDF
News:
  • I am pleased to receive the 2018 Arnold Zellner Thesis Award in Econometrics and Statistics from the ASA section of Business and Economic Statistics and the Journal of Business and Economic Statistics.
  • Updated working papers:
    2018 August: Monetary Policy across Space and Time
    2018 March: Density Forecasts in Panel Data Models: A Semiparametric Bayesian Perspective
    2018 March: Forecasting with a Panel Tobit Model

Research
Publications
Estimating Global Bank Network Connectedness
Joint with Mert Demirer (MIT), Francis X. Diebold (UPenn), and Kamil Yılmaz (Koç)
Journal of Applied Econometrics, 2018, vol. 33 (1), pp. 1-15.
Working Paper Version
Commodity Connectedness
Joint with Francis X. Diebold (UPenn) and Kamil Yılmaz (Koç)
In E. Mendoza, D. Saravia and E. Pasten (eds.), Monetary Policy and Global Spillovers: Mechanisms, Effects and Policy Measures. Santiago: Bank of Chile Central Banking Series, 2018, vol. 25, pp. 97-136.
Working Paper Version
Working Papers
Joint with Hyungsik Roger Moon (USC) and Frank Schorfheide (UPenn)
Econometrica, Revise and Resubmit
Also available at arXiv 1709.10193 and PIER Working Paper 16-022
Replication Files
Work in Progress
Sectoral DSGE Models and Production Networks
Joint with Holt Dwyer (UCSD) and Molin Zhong (Fed Board)

Teaching
Microeconometrics (180.637)
Johns Hopkins University, Ph.D. level, Fall 2018
Course Description
This is an advanced graduate course on major econometric techniques and models that are used in empirical microeconomics. We first introduce econometric theories of nonlinear extremal estimation, nonparametric estimation, and semiparametric estimation. Then, we discuss applications of these theories to limited dependent variable models, selection models, panel data models, and endogenous treatment models with unobserved heterogeneity.