Government regulation sub-factors and housing supply: A conceptual framework / Noryanto Asroun Mohamad Asroun, Mohd Hasrol Haffiz Aliasak and Mohd Afandi Abu Bakar
The past studies have used the government regulation factor to examine the influence of regulations imposed by local authorities in the planning process against the housing supply. It is one of the additional factors in the model when the study is to examine the effect of city-specific factors on ho...
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| Main Authors: | , , |
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| Format: | Conference or Workshop Item |
| Language: | English |
| Published: |
2022
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| Subjects: | |
| Online Access: | https://ir.uitm.edu.my/id/eprint/73528/1/73528.pdf https://ir.uitm.edu.my/id/eprint/73528/ |
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| Summary: | The past studies have used the government regulation factor to examine the influence of regulations imposed by local authorities in the planning process against the housing supply. It is one of the additional factors in the model when the study is to examine the effect of city-specific factors on housing supply elasticity. Although the regulation involved the government controls on housing development at the local level, it is significant to identify the influence of a specific regulation on housing supply. In past studies, some sub-factors were proxied by index values established from the Wharton Residential Land Use Regulation Index (WRLURI) when periodic data was not available. Thus, this paper aims to develop a conceptual framework on the effect of government regulation sub-factors using time series data when the data is made available. This paper reviewed the effect of a few government regulation sub-factors used in past studies and a few other sub-factors that remain understudied. As a result, new studies should apply times series data for sub-factors like the number of restrictions, the number of governing bodies, duration for subdivision approval, and the number of growth management policies although they were the WRLURI components in the past studies. Panel data modeling will be an appropriate method to analyze the cross-sectional time-series data. It is vital to identify the influence of government regulation sub-factors for some cross-sections by using robust tests. |
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