A robust vector autoregressive model for forecasting economic growth in Malaysia

Khamis, Azme and Abdul Razak, Nur Azreen and Affendi Abdullah, Mohd Asrul (2018) A robust vector autoregressive model for forecasting economic growth in Malaysia. Malaysian Journal of Fundamental and Applied Sciences, 14 (3). pp. 382-385. ISSN 2289-599X

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Official URL: http://dx.doi.org/10.11113/mjfas.v14n3.1021

Abstract

Economic indicator measures how solid or strong an economy of a country is. Basically, economic growth can be measured by using the economic indicators as they give an account of the quality or shortcoming of an economy. Vector Auto-regressive (VAR) method is commonly useful in forecasting the economic growth involving a bounteous of economic indicators. However, problems arise when its parameters are estimated using least square method which is very sensitive to the outliers existence. Thus, the aim of this study is to propose the best method in dealing with the outliers data so that the forecasting result is not biased. Data used in this study are the economic indicators monthly basis starting from January 1998 to January 2016. Two methods are considered, which are filtering technique via least median square (LMS), least trimmed square (LTS), least quartile difference (LQD) and imputation technique via mean and median. Using the mean absolute percentage error (MAPE) as the forecasting performance measure, this study concludes that Robust VAR with LQD filtering is a more appropriate model compare to others model.

Item Type:	Article
Uncontrolled Keywords:	Forecasting; economic growth; robust; imputation; filtering
Subjects:	H Social Sciences > HD Industries. Land use. Labor > HD72-88 Economic growth, development, planning
Divisions:	Faculty of Applied Science and Technology > Department of Mathematics and Statistics
Depositing User:	UiTM Student Praktikal
Date Deposited:	24 Jan 2022 08:42
Last Modified:	24 Jan 2022 08:42
URI:	http://eprints.uthm.edu.my/id/eprint/5911

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