Identifying good inflation forecaster
AbstractThe objective of this paper is to identify the best indicator variable in forecasting inflation in Malaysia. Due to the fact that Malaysia experienced the rise of CPI by 4.8 percent in March 2006, the country’s highest inflation rate in seven years, there is a need to foresee future trend of general price level. To determine whether certain indicator (variable) could predict inflation, we construct a simple forecasting model that incorporates the variable. We estimate a two-variable VECM model of quasi-tradable inflation using monthly data covering the period 1980:01 to 2006:12. We alternate between the following inflation indicators: commodity prices, financial indicators and economic activities. We evaluate each model using out-of-sample forecast. The study proposes that a simple model using industrial production index improves the accuracy of inflation forecasts. The results support our hypothesis.
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Bibliographic InfoPaper provided by University Library of Munich, Germany in its series MPRA Paper with number 13302.
Date of creation: 2008
Date of revision:
Goods inflation; VECM ; Malaysian economy;
Find related papers by JEL classification:
- C50 - Mathematical and Quantitative Methods - - Econometric Modeling - - - General
- E31 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Price Level; Inflation; Deflation
- C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models &bull Diffusion Processes
This paper has been announced in the following NEP Reports:
- NEP-ALL-2009-02-14 (All new papers)
- NEP-FOR-2009-02-14 (Forecasting)
- NEP-MAC-2009-02-14 (Macroeconomics)
- NEP-MON-2009-02-14 (Monetary Economics)
- NEP-SEA-2009-02-14 (South East Asia)
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
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- Jonas D.M. Fisher, 2000. "Forecasting inflation with a lot of data," Chicago Fed Letter, Federal Reserve Bank of Chicago, issue Mar.
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