Jing Han

Assistant Professor, The Chinese University of Hong Kong

Jing Han
Esther Lee Building #907 • Shatin• Hong Kong
Work: (852) 2609-8005 • Email: [email protected]
Webpage: jinghan.econ.cuhk.edu.hk

• Assistant Professor, The Chinese University of Hong Kong, 08/2009 - present

• Lecturer of Economics, The Ohio State University, 09/2006 - 06/2009
• Research Associate, The Ohio State University, 09/2005 - 06/2004
• Teaching Associate, The Ohio State University, 09/2004 - 06/2005
• Teaching Assistant, Peking University, 09/2001 - 09/2003

Ph.D. Economics The Ohio State University June 2009
M.A.S. Statistics The Ohio State University December 2008
M.A. Economics The Ohio State University December 2004
M.A. Economics Peking University June 2003
B.S. Economics Nankai University July 2000

Macroeconomics, Monetary Economics, Applied Econometrics, Finance

• American Economic Association
• Econometric Society
• CFA Institute
• Global Association of Risk Professionals

• “What Do Technology Shocks Tell Us About the New Keynesian Paradigm,” (with Bill Dupor and Yi-Chan Tsai), Journal of Monetary Economics, May 2009

• “Handling Non-Invertibility: Theory and Applications,” (with Bill Dupor), Oct 2010
Abstract Existing research provides no systematic, limited information procedure for handling non-invertibility, despite the well-known inference problem it causes as well as its presence in many types of dynamic systems. Non-invertibility means that structural shocks cannot be recovered from a history of observed variables. It arises from a form of delayed responses due to, among other things, time-to-plan, sticky information or news shocks. Structural VARs rule out non-invertibility by assumption. Inference about structural responses can, in turn, be incorrect. We develop a four-step procedure to partially, and sometimes fully, identify structural responses whether or not non-invertibility is present. Our method combines structural VAR restrictions, e.g. recursive identification, with "agnostic" identification, e.g. sign restrictions and bounds on forecast error contributions. In two model-generated examples, our procedure recovers the structural responses where structural VARs cannot. Also, we apply our procedure to real world data. We show that non-invertibility is unlikely in Fisher's (2006) study of technology shocks in the U.S.

• “What Accounts for the Transmission of Technology Shocks in U.S.?,” Oct 2010
Abstract Price rigidity and monetary policy have different implications on transmission of different technology shocks. Highly sticky prices and loose inflation targeting helps the propagation of the investment-specific technology (IST) shock but hinders the transmission of the neutral technology (NT) shock. The reason is that the IST shock only increases labor productivity and interest rate in the long run, but not in the short run. These mechanisms are used to explain the difference in dynamic responses to these shocks : a positive IST shock leads to hump-shaped increase in output, working hours and labor share, but a fall in labor productivity. Inflation increases insignificantly. Output and hours rise slowly after a positive NT shock. Inflation and labor share falls significantly following this shock. Estimation result shows that the economic environment, especially monetary policy, favors the IST shock. The accommodating monetary policy and positive IST shocks jointly explain the recent boom in U.S.: higher output, higher working hours but lower labor productivity.

• “A Search for Timing Effects of Macroeconomic Shocks in the U.S.,” (with Bill Dupor), September 2009
Abstract This paper addresses whether the response of output to various shocks has timing or season-contingent effects; that is, does a particular shock have a different effect on output if it originates in a particular calendar quarter? We study, in turn, shocks to: government spending, government revenue and monetary policy. For spending shocks, there is very little evidence of a timing effect. For revenue shocks, there is no evidence of a timing effect. For the final shock, we find a timing effect, which is consistent with existing research. However, omitting the early part of the Volcker disinflation, 1980-1983, eliminates this effect.

• “Seasonal Effect of Monetary Policy on Industrial Productions: A FAVAR Approach,”
• “News Shocks and Investment Specific Shocks”
• “Entry, Exit, Business Cycles and Asset Price”
• “Integrating Limited Participation and Financial Accelerators”
• “What Drives the Real Exchange Rate: Evidence from a Structural Estimation” (joint with Kang Shi)

• Econometric Society Winter Meeting, Denver, 01/2011 (scheduled)
• Distinguished Research Seminar, University of Tokyo, 10/2010
• Macro Seminar, Hong Kong University of Science and Technology, 03/2010
• Department Seminar, The Chinese University of Hong Kong, 09/2009
• 4th DYNARE Conference, Federal Reserve Bank, Boston, 09/2008
• The Ohio State University Macroeconomics Workshop, Columbus, OH, 05/2008 and 07/2008
• NBER EFG Summer Meeting, Boston, MA, 07/2007

Referee (since 2005)
• Ad hoc referees for Journal of Money and Banking, China Economic Review, Macroeconomic Dynamics

• DIRECT GRANT, The Chinese University of Hong Kong, 09/2009
• JMCB Travel Funding, 09/2008
• NBER Travel Grant, 07/2007
• University Fellowship, The Ohio State University, Columbus, OH, 09/2003-09/2004

• Programming: MATLAB, SAS, R
• Language: Fluent in English and Mandarin

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