Modelling of Malaysia House Price Index / Nur Amaelya Mastani, Nur Ashakirin Jehani and Sharmila Saudin
In Malaysia, House Price is considered high at a certain part of the country causing the lower and middle groups unable to purchase a house. This research examines the long run relationship and causality effect between House Price Index and determinants of House Price Index. Besides, the aim of this...
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Main Authors: | , , |
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Format: | Student Project |
Language: | English |
Published: |
2020
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Subjects: | |
Online Access: | https://ir.uitm.edu.my/id/eprint/50286/1/50286.pdf https://ir.uitm.edu.my/id/eprint/50286/ |
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Summary: | In Malaysia, House Price is considered high at a certain part of the country causing the lower and middle groups unable to purchase a house. This research examines the long run relationship and causality effect between House Price Index and determinants of House Price Index. Besides, the aim of this study is to identify the suitable model of Malaysia House Price Index. The data was obtained from Valuation and Property Services Department (JPPH), Department of Statistics Malaysia and Bank Negara. The data was collected over 10 years from 2010 to the first quarter of 2019. Johansen Cointegration Test and Granger Causality Test are applied in determining the long-run relationship and causality effect respectively while the method that is applied in this research for identifying ARIMA model is Box-Jenkins Methodology. The general finding of this study is that the House Price Index shows an upward trend for the past nine years but slightly drop in the first quarter of 2019. This study has found that there is a long-run relationship between the House Price Index and the independent variables which are Gross Domestic Product, Interest Rate, Inflation Rate, Population, and Unemployment Rate. Next, all independent variables does not granger cause House Price Index. At the same time, there is only one-way relationship found between House Price Index and Gross Domestic Product, and between House Price Index and Population where House Price Index is identified to granger cause both variables. Besides, this study also has found out that ARIMA( 1,2, I) is the best model for the House Price Index. |
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