About

Lilia Maliar is a Visiting Fellow at the Hoover Institution and a Professor of Economics at the Graduate Center of CUNY.

She has proposed a novel class of numerical methods that combines projection and stochastic-simulation techniques and that can accurately and reliably solve dynamic economic models with a large number of state variables. The applications include large-scale new Keynesian models, life-cycle models, heterogeneous-agent models, asset pricing models, multi-sector models, multi-country models, default risk models and models of climate change, among others. Her research interests also include economic theory, macroeconomics, machine learning, deep learning, growth and development, dynamic games, transition economies, and international trade.

Lilia Maliar’s research on numerical methods for dynamic economic models has appeared in numerous economic journals including Econometrica, Journal of Business and Economic Statistics, Journal of Economic Dynamic and Control, Journal of Money Banking and Credit, Quantitative Economics, Review of Economic Dynamics, Computational Economics; she contributed a chapter to Handbook of Computational Economics; she is currently serving as Associate Editor in “Quantitative Economics” Journal of the Econometric Society, Senior Editor of Oxford Research Encyclopedias of Economic and Finance, she advises the Bank of Canada on their large-scale ToTEM macroeconomic model for projection and policy analysis and she serves as a Research Fellow of the Center for Economic Policy Research (CEPR).

Professor Maliar came to The Graduate Center, CUNY from Stanford University where she was a Visiting Associate Professor in the Department of Economics and a Visiting Fellow at the Hoover Institution. She has taught at the University of Alicante and University of Pompeu Fabra. Lilia Maliar received a BS in economics from Oles Honchar Dnipro National University, in 1991, MA from Central European University, and a PhD in economics from University of Pompeu Fabra in 1999.