| 摘要: | 臺灣在區域間不論是人口、產業結構、醫療資源及政府支出上皆有明顯的不同，可能造成區域間的房價差異。本研究之目的在於觀察臺灣房地產市場變化，使用縱橫資料 (Panel data) 及固定效果模型 (Fixed effect model)，分析2012年至2022年在北中南、直轄市及非直轄市間房價差異之影響因素。回顧當前文獻，較多是以單一區域或直轄市作為研究標的，本研究將西半部17個縣市納入模型中，控制個體差異分析區域影響因素。另外，過往較少以地區醫療資源及政府投入支出作為影響房價之分析目標，本研究以每萬人口執業醫事人員數作為醫療資源之代表變數，並以政府支出項目之社區發展及環境保護支出分析地方政府對於公共建設的投入效果。
實證結果發現，儘管部分的變數對臺灣整體的影響不顯著，在地區間卻出現不同的影響效果。每萬人口執業醫事人員數對北部房價影響為負向，其他區域不顯著。政府之社區發展及環境保護支出在北部對房價有負向的影響，在南部影響為正向。吉尼係數在直轄市中為負向影響，在非直轄市影響為正向。其餘人口相關變數如淨遷徙率、扶老比、勞動力參與率及貨幣供給量在臺灣各區間皆出現相同且顯著的影響。;Taiwan exhibits significant regional differences in terms of population, industrial structure, medical resources, and government expenditure, which may contribute to variations in housing prices across regions. The purpose of this study is to observe changes in Taiwan′s real estate market, using panel data and a fixed effect model, to analyze the factors influencing housing price differences between northern, central, and southern regions, as well as between metropolitan and non-metropolitan areas from 2012 to 2022. Current literature mostly focuses on individual regions or metropolitan areas as research subjects. This study includes 17 counties and cities in western Taiwan, controlling for individual differences to analyze regional influencing factors. Furthermore, past studies have rarely considered regional medical resources and government expenditure as factors affecting housing prices. This study uses the number of practicing medical personnel per 10,000 population as a representative variable for medical resources and analyzes the effects of local government investment in public infrastructure through community development and environmental protection expenditure.
Empirical results show that while some variables do not have significant effects on Taiwan as a whole, they exhibit different impacts across regions. The number of practicing medical personnel per 10,000 population has a negative impact on housing prices in the northern region, while it is not significant in other regions. Government expenditure on community development and environmental protection negatively affects housing prices in the northern region but has a positive impact in the southern region. The Gini coefficient negatively affects housing prices in metropolitan areas, while it positively affects non-metropolitan areas. Other population-related variables, such as net migration rate, elderly dependency ratio, labor force participation rate, and money supply, have consistent and significant impacts across all regions in Taiwan. |
