Photo of Laura Liu
Assistant Professor
Department of Economics
Indiana University

Wylie Hall 205
100 South Woodlawn Ave.
Bloomington, IN 47405
Email: lauraliu (at) iu.edu
CV: PDF
My IU Page: Link
My Google Scholar Page: Link
News:
  • Publication:
    2020 August: Panel Forecasts of Country-Level Covid-19 Infections, Journal of Econometrics, forthcoming.
    2020 January: Forecasting with Dynamic Panel Data Models, Econometrica.
  • Updated working papers:
    2020 February: Density Forecasts in Panel Data Models: A Semiparametric Bayesian Perspective
    2019 December: Forecasting with a Panel Tobit Model
    2019 June: Full-Information Estimation of Heterogeneous Agent Models Using Macro and Micro Data
  • Others:
    2020 April: Our paper "Estimating Global Bank Network Connectedness" receives the fifteenth Richard Stone Prize in Applied Econometrics for the best paper(s) published in the preceding two volumes of the JAE.
    Thanks to my great coauthors Mert Demirer, Francis X. Diebold, and Kamil Yılmaz!

Research
Publications
Panel Forecasts of Country-Level Covid-19 Infections
Joint with Hyungsik Roger Moon (USC) and Frank Schorfheide (UPenn)
Journal of Econometrics, forthcoming.
Working Paper Version
Earlier version is available at NBER Working Paper 27248 and CEPR Working Paper 14790
Current forecasts and replication files are available at https://laurayuliu.com/covid19-panel-forecast/
A blog post is available here
Joint with Hyungsik Roger Moon (USC) and Frank Schorfheide (UPenn)
Econometrica, vol. 88 (1), pp. 171-201.
Working Paper Version
Earlier versions are available at NBER Working Paper 25102, arXiv 1709.10193, and PIER Working Paper 16-022
Replication Files
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
Earlier versions are available at NBER Working Paper 23140 and PIER Working Paper 15-025
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
Earlier versions are available at NBER Working Paper 23685 and PIER Working Paper 17-003
Working Papers
Journal of Business & Economic Statistics, Revise and Resubmit
Also available at arXiv 1805.04178 and CAEPR Working Paper 2020-003
Earlier version is available at FEDS Working paper 2170 and PIER Working Paper 17-006
Work in Progress
Estimating Average Partial Effects of Semiparametric Panel Logit Models
Joint with Alexandre Poirier (Georgetown) and Ji-Liang Shiu (Jinan U)
Sectoral DSGE Models and Production Networks
Joint with Holt Dwyer (UCSD) and Molin Zhong (Fed Board)

Teaching
Econometric Theory and Practice (E471/M504)
Indiana University, advanced undergraduate and master's level, Spring 2020
Course Description
This course introduces students to basic econometric concepts and their applications. Compared to E371, we will put more emphasis on the mathematical and statistical foundations of econometric methods. The course covers linear regression models, discrete choice models, and panel data models, as well as more advanced topics, such as experiments and quasi-experiments, big data and statistical learning, etc. All concepts are motivated by real-world applications. In several tutorial sessions, students will learn how to apply econometric methods to data using the statistical software R.
Microeconometrics (180.637)
Johns Hopkins University, advanced 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.