The project will seek to design more realistic macroeconomic theory and macroeconometric models that take into account globalization of the economy, structural changes, large-scale shocks such as from financial crises and major disasters, and long-term economic downturns. It will develop methodology for delivering equilibria and estimating parameters in such models. The project will further develop econometric methods for estimating these models using big data, including survey data of inflation forecasts and high frequency data on asset prices. These will be applied to analysis of various macroeconomic issues; and based on the results, policy proposals will be made regarding desirable macroeconomic policies.

Toshiaki Watanabe
Project Leader: Toshiaki Watanabe
Professor at Institute of Economic Research, Hitotsubashi University

Project Members:

Adjunct Prof. Kyoji Fukao (Institute of Economic Research, Hitotsubashi University)
Prof. Naohito Abe (Institute of Economic Research, Hitotsubashi University)
Prof. Etsuro Shioji (Graduate School of Economics, Hitotsubashi University)
Prof. Takashi Kano (Graduate School of Economics, Hitotsubashi University)
Prof. Yohei Yamamoto (Graduate School of Economics, Hitotsubashi Univeristy)
Associate Prof. Ryo Jinnai (Institute of Economic Research, Hitotsubashi University)
Prof. Mototsugu Shintani (Graduate School of Economics, The University of Tokyo)
Associate Prof. Hiroshi Morita (Department of Economics, Hosei University)

Research Collaborators:

Prof. Atsushi Inoue (Department of Economics, Vanderbilt University)
Associate Prof. Tatsuyoshi Okimoto (Crawford School of Public Policy, Australian National University)
Senior Research Fellow Sungbae An (Korea Institute for International Economic Policy)
Associate Prof. Yunjong Eo (Department of Economics, Korea University)
Associate Prof. Kyu Ho Kang (Department of Economics, Korea Univeristy)

Recently Published Papers:

Yohei Yamamoto, “Bootstrap Inference from Impulse Response Functions Factor-augmented Vector Autoregression”, Journal of Applied Econometrics, 34 (2019) 247-267. –> link