臺灣房價與人口結構之關聯分析：以雲林縣三鄉鎮市為例

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Title:	臺灣房價與人口結構之關聯分析：以雲林縣三鄉鎮市為例
Other Titles:	Correlation Analysis of Taiwan's Housing Prices and Population Structure: A Case Study of Three Towns in Yunlin County
Authors:	賴哲樟 LAI, CHE-CHANG
Contributors:	財務金融學系財務管理碩士班廖永熙 LIAU, YUNG-SHI
Keywords:	住宅房價;特徵價格模型 residential housing price;characteristic price model
Date:	2022
Issue Date:	2022-09-05 11:57:58 (UTC+8)
Abstract:	探討對房屋市場價格影響的因素，應用房屋個體特徵價格模型之敘述統計及實證討論對平均住宅交易價格，本研究以雲林縣斗六市、虎尾鎮、麥寮鄉作為本研究的對象。本研究以房產屬性變數、總體經濟變數及人口屬性變數等，再以2012年第一季至2020年第三季之內政部地政司不動產交易實價資料與內政部戶政司的人口異動資料進行研究，並以迴歸模型建構在雲林縣斗六市、麥寮鄉、虎尾鎮三個鄉鎮市的住宅房價特徵價格模型及人口屬性進行特徵價格分析。實證結果影響房價顯著的因素為建物的移轉面積，面積越大會使房價上升，屋齡的年數折舊越大也使建物價格縮減，位處不同區域之人口成長及0-44歲人口對房價影響為顯示負相關，但45歲以上中年人口對房價需求為顯著正相關。所以，本研究發現無論是以何種價格模型，房屋所坐落的人口結構屬性對住宅市場價格的解釋能力都高於房屋個體特徵。　　To explore the factors that affect the housing market price, apply the descriptive statistics and empirical discussion of the housing individual hedonic price model to the average housing transaction price, this study takes Douliu City, Huwei Town, and Mailiao Township in Yunlin County as the object of this research. This research uses real estate attribute variables, overall economic variables and population attribute variables, etc., and then uses the real estate transaction data of the Department of Land Affairs, Ministry of the Interior from the first quarter of 2012 to the third quarter of 2020 and the population change data of the Department of Household Affairs of the Ministry of the Interior. , and constructed the hedonic price model of housing prices and population attributes in three township cities of Yunlin County, Douliu City, Mailiao Township, and Huwei Town, to analyze the hedonic price. Empirical results The significant factor affecting house prices is the transfer area of the building. The larger the area, the higher the house price. The greater the depreciation of the age of the house, the lower the building price. The impact is negatively correlated, but the demand for housing prices for the middle-aged population over 45 is significantly positive. Therefore, this study finds that no matter what price model is used, the explanatory power of the demographic attributes where the house is located on the housing market price is higher than the individual characteristics of the house.
Appears in Collections:	[Department of Finance, The M.A. Program of Financial Management] Disserations and Theses

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