研究生: |
吳信誼 Wu, Hsin-I |
---|---|
論文名稱: |
影響臺灣區域房價因素的探討-以六都及新竹縣市為例 Analysis on the determinants of housing prices in Taiwan - The case of municipalities and Hsinchu area |
指導教授: |
吳世英
Wu, Shih-Ying |
口試委員: |
林世昌
Lin, Shih-Chang 周大森 Chou, Ta-Sheng |
學位類別: |
碩士 Master |
系所名稱: |
科技管理學院 - 公共政策與管理 Master Program of Public Policy and Management |
論文出版年: | 2024 |
畢業學年度: | 112 |
語文別: | 中文 |
論文頁數: | 36 |
中文關鍵詞: | 縱橫資料 、成交價格指數 、貸款負擔率 |
外文關鍵詞: | Panel Data, Transaction price index, Ratio on Loan Burden |
相關次數: | 點閱:30 下載:1 |
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本研究利用2002年至2022年,六都及新竹縣市共七個區域,分析房屋成交價格的決定因素,結果顯示家庭特徵因素在貸款負擔率、購屋需求人口數量略有顯著且正向的影響,家庭戶數存量呈現為負向相關。政府政策因素在社會福利暨社區發展及環境保護支出為略為顯著及正向相關,在補助及協助收入及經濟發展支出較沒有顯著性。經濟環境因素在營建工程業則略為顯著影響。
在供需原理下,市場上有限的房屋,有需求的人員想購買,房價就會相對上漲;因台灣的老年人口逐漸增加,政府對照護的各項政策也愈受重視,因此社會福利暨社區發展及環境保護支出對房屋成交價格有所助益。不同縣市的製造業提升程度不同,導致房價的區域差異加大,這種市場分化會導致房價上的差異;經市場機制的檢視下,僅有營建工程業的產出與當地房價具有正向相關,道路、公共交通、學校和醫療設施伴隨著基礎設施的建設,使得吸引更多居民遷入,從而提升該區域的房屋需求,進一步推升房價。
This study uses a total of seven regions in Liudu and Hsinchu counties and cities from 2002 to 2022 to analyze the determinants of housing transaction prices. The results show that household characteristics factors have a slightly significant and positive impact on the loan burden rate and the number of people in need of home purchase. Impact, the number of households shows a negative correlation. Government policy factors are slightly significant and positively correlated with social welfare and community development and environmental protection expenditures, while less significant with subsidies and assistance income and economic development expenditures. Economic environmental factors have a slightly significant impact on the construction engineering industry.
Under the principle of supply and demand, there are limited houses on the market, and if people in demand want to buy them, housing prices will rise relatively; as Taiwan’s elderly population gradually increases, the government’s policies on care are also paying more and more attention, so social welfare and community development and environmental protection expenditures will help house transaction prices. The manufacturing industry in different counties and cities has different levels of improvement, leading to increased regional differences in housing prices. This market differentiation will lead to differences in housing prices; under the inspection of the market mechanism, only the output of the construction engineering industry has a positive relationship with local housing prices. Relatedly, the construction of roads, public transportation, schools and medical facilities along with infrastructure will attract more residents to move in, thereby increasing the demand for housing in the area and further pushing up housing prices.
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