A Bayesian Vector Autoregression Model to Estimate Bilateral Trade Flows in Panel Data Setting

Abstract

This study examines how trade shocks that start in one large economy ripple through other countries and how long those effects stick around. Using quarterly bilateral-trade data for 2012-2023, the authors estimate a Bayesian four-country VAR model (China, Germany, Japan, United States) identified by sign restrictions. Impulse-response functions show that a one-standard-deviation drop in Chinese exports cuts German and Japanese exports by about three percent on impact, whereas German shocks are one-third as large, Japanese shocks quickly rebound, and U.S. shocks barely travel abroad. Forecast-error variance decomposition at a ten-quarter horizon confirms China’s central role: its shocks explain roughly one-third of the medium-run export volatility in Germany and Japan, while 90 percent of U.S. volatility remains home-grown. Persistence analysis finds that own shocks in China, Germany, and Japan stay near full strength for five years, whereas U.S. shocks fade faster.