A VAR Analysis of the Effects of Monetary Policy in East Asia

Abstract

In this paper, a VAR model is used to study the effects of monetary policy shocks in seven East Asian economies. For each economy, the same identification scheme is imposed and the dynamic responses to a monetary shock are examined in the light of the predictions of monetary theory. The results suggest that the VAR model produces sensible impulse response functions for most of the economies, especially for the sample that ends before the 1997 Asian financial crisis. Given the openness of these economies, the exchange rate plays a significant role in the formulation of monetary policy. In order to capture explicitly the importance of the exchange rate in these economies, plausible weights are also imposed on the exchange rate to identify the model.

The Impact of Monetary Policy on Economic Growth and Inflation in Sri Lanka

“…Accordingly, several researchers have adopted the Bernanke-Mihov approach mutatis mutandis for different economies and policy frameworks. Fung (2002), who uses this methodology to analyse the effects of monetary policy in several East Asian countries, shows that it has been applied to Germany (Bernanke and Mihov (1997)), Italy (De Arcangelis and Di Giorgio (1998)) and Canada (Fung and Yuan (2000)). Some other applications are Kasa and Popper (1997) and Nakashima (2004) who apply the methodology to Japan, Piffanelli (2001) to Germany, and De Arcangelis and Di Giorgio (2001) to Italy.…”

Fiscal Analysis Is Darned Hard

“…Fung (2002) estimated structural VARs for a number of Asian countries. Industrial production was also included in some systems that were estimated.…”

Structural Vector Autoregressive Analysis of Monetary Policy in Thailand

“…A vector autoregression (VAR) is extensively used as an econometric tool for monetary policy analysis, see for example Fung (2002), Disyatat and Vongsinsirikul (2003), and Charoenseang and Manakit (2007a;2007b). However, a growing body of literature analyzes monetary transmission mechanisms by employing a structural vector autoregression (SVAR) model.…”