China's Time-Varying Taylor Rule.
Jul 2024 - Sep 2024
I worked as a part-time research assistant for professor Kaiji Chen at the Emory University.
The Taylor rule has long been a widely accepted framework for monetary policy in the United States, and we aimed to investigate whether such a rule could also be applicable in a developing country like China, where the financial system is still maturing. We integrated China's institutional background with the principles of monetary policy and proposed a time-varying Taylor rule, using the 7-day and 1-day Repo rates as the interest rate targets, and both the inflation rate gap and the GDP growth rate gap as dual mandates. I compiled an original macroeconomic time-series dataset from various sources, including the Federal Reserve Bank of Atlanta and CEIC. I then detrended the data using log-linear detrending and the HP filter, setting different coefficients and standard errors for cases where the GDP growth rate gap was positive versus negative. Subsequently, I applied maximum likelihood estimation (MLE) to regress the time-varying Taylor rule. Ultimately, we derived a significant Taylor rule tailored to China's economic context, with the endogenous part fitting well, while the exogenous component was identified as a monetary policy shock series, which can be used in future research. The main programming language used is Matlab.