Abstract
Malaysia has faced a problem where Malaysian cannot afford to own a house as the prices of the house has increase along with the increasing cost of living. This study is to identify the elements that affect the housing prices in Malaysia and develop a suitable forecasting model for this issue. The last objective is to determine the best forecasting model to forecast future property prices in Malaysia. The main variables used in this study is house price and macroeconomic variables such as GDP, interest rate, CPI and geographical variable which is population. This study used a secondary data from 1990 until 2017 obtained from The Valuation and Property Service Department (2018) and The World Bank (2017). The methodology used in resolving the objective are Unit Root Test, Johansen Coi ntegration Test, Granger Causality Test and lastly Box-Jenkins Method. The results showed a relationship between house price and interest rate only based on Granger Causality Test. It can be concluded that ARIMA( 1,2, I) is the best forecasting model for future use based on analysis made using Box-Jenkins Method.
Metadata
Item Type: | Student Project |
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Creators: | Creators Email / ID Num. Khailizan, Nur Atiqah UNSPECIFIED Ismail, Noor Fitrah Nabilah UNSPECIFIED Muhammad Harith Fadzillah, Nur Alia Farhana UNSPECIFIED |
Contributors: | Contribution Name Email / ID Num. Thesis advisor Amit, Norani UNSPECIFIED |
Subjects: | Q Science > QA Mathematics > Mathematical statistics. Probabilities Q Science > QA Mathematics > Mathematical statistics. Probabilities > Data processing Q Science > QA Mathematics > Analysis Q Science > QA Mathematics > Analysis > Analytical methods used in the solution of physical problems |
Divisions: | Universiti Teknologi MARA, Negeri Sembilan > Seremban Campus > Faculty of Computer and Mathematical Sciences |
Programme: | Bachelor of Science (Hons.) Statistics |
Keywords: | Malaysian Residential, Property, forecasting model |
Date: | 2019 |
URI: | https://ir.uitm.edu.my/id/eprint/50008 |
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