Quantifying the Monetary Transmission Mechanism: A Mixed-Frequency Factor-Augmented Vector Autoregressive Regression Approach
时 间：2018年10月17日 星期三 12:00–13:30
摘要：This paper studies the monetary transmission mechanism in the U.S. It proposes a mixed-frequency version of the factor-augmented vector autoregressive regression (FAVAR) model, which is used to construct a coincident index to measure the monetary transmission mechanism. The model divides the transmission of changes in monetary policy to the economy into three stages according to the timing and order of the impact. Indicators of each stage are measured and identified using different data frequencies: fast-moving variables (stage 1, asset returns at the weekly frequency), intermediate moving variables (stage 2, credit market data at the monthly frequency), and slow-moving variables (stage 3, macroeconomic variables at the quarterly frequency). The resulting coincident index exhibits leading signal for all recessions in the sample period and provides implications on the dynamics of the monetary transmission mechanism. The proposed coincident index also indicates that monetary transmission mechanism is changing over time.
报告人简介：Zhi Zhao is now an assistant professor in School of Public Finance and Taxation, Southwestern University of Finance and Economics. He received his Ph.D. degree in Economics from University of California, Riverside. His main research field is monetary policy, applied econometrics and empirical macroeconomics.