Building real estate valuation models with stepwise decomposition regression analysis
碩士 === 淡江大學 === 土木工程學系碩士班 === 102 === Multivariate regression analysis is usually employed to establish real estate valuation formula. This approach is quite simple, but it has a few drawbacks including being difficult to understand the meaning of the coefficients, cannot be universal to another are...
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| Format: | Others |
| Language: | zh-TW |
| Published: |
2014
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| Online Access: | http://ndltd.ncl.edu.tw/handle/66770503789092335845 |
| Summary: | 碩士 === 淡江大學 === 土木工程學系碩士班 === 102 === Multivariate regression analysis is usually employed to establish real estate valuation formula. This approach is quite simple, but it has a few drawbacks including being difficult to understand the meaning of the coefficients, cannot be universal to another areas, cannot be used in comparison approach, and without good flexibility. The purpose of this study is to propose the stepwise decomposition regression analysis to overcome these shortcomings. The factors considered in this study include
The factor of the distance to the nearest MRT station which represents the impact of transportation function to the price per unit area.
The factor of the number of convenience stores in the living circle on foot which represents the impact of living function to the price per unit area.
The factor of the age of house which represents the impact of the quality of the house to the price per unit area.
The factor of transaction date which represents the impact of market trend to the price per unit area.
The factor of the geographic coordinates which represent the impact of spatial location to the price per unit area.
The results showed that the 20% error hit rates of real estate valuation were greater than 70% for all the four testing areas in Taipei City and New Taipei City.
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