Dissertation/Thesis Abstract

Forecasting Inflation in Asian Economies
by Liew, Chian Fatt Freddy, M.Sc., Singapore Management University (Singapore), 2012, 51; 1519237
Abstract (Summary)

This paper surveys the recent literature on inflation forecasting and conducts an extensive empirical analysis on forecasting inflation in Singapore, Japan, South Korea and Hong Kong paying particular attention to whether the inflation-markup theory can help to forecast inflation. We first review the relative performance of different predictors in forecasting h-quarter ahead inflation using single equations. These models include the autoregressive model and bivariate Philips curve models. The predictors are selected from business activity, financial activity, trade activity, labour market, interest rate market, money market, exchange rate market and global commodity market variables. We then evaluate a vector autoregressive inflation-markup model against the single equation models to understand whether there is any gain in forecasting using the inflation-markup theory. The paper subsequently analyses the robustness of these results by examining different forecasting procedures in the presence of structural breaks. Empirical results suggest that inflation in Singapore, Hong Kong and South Korea is best predicted by financial and business activity variables. For Japan, global commodity variables provide the most predictive content for inflation. In general, monetary variables tend to perform poorly. These results hold even when structural break is taken into consideration. The vector autoregressive inflation-markup model does improve on single equation models as forecasting horizon increases and these gains are found to be significant for Japan and Korea.

Indexing (document details)
Advisor: Tay, Anthony
School: Singapore Management University (Singapore)
Department: School of Economics
School Location: Republic of Singapore
Source: MAI 51/02M(E), Masters Abstracts International
Subjects: Economics
Keywords: Asia, Forecasting, Inflation, Markup, Structural break, Vector autoregression
Publication Number: 1519237
ISBN: 9781267637161