近年臺灣房價持續上升，青年族群面臨購屋負擔加重之問題。為降低青年購屋門檻並提 升住宅可負擔性，政府於 2023 年 8 月推出「青年安心成家購屋優惠貸款精進方案」（簡稱新 青安政策），透過提高貸款額度、延長貸款年限及提供利率補貼等方式，協助首購族進入住宅 市場。然而，在住宅供給短期內難以快速調整之情況下，需求面政策是否進一步推升房價， 亦成為社會關注議題。因此，本研究以新青安政策作為研究主題，探討政策實施後對新竹與 桃園地區房價之影響。 本研究以 2020 年至 2025 年之月資料作為研究樣本，資料來源包括內政部實價登錄資料 庫及相關總體經濟統計資料。研究方法方面，首先採用事件前後分析法（Interrupted Time Series Analysis）檢驗新青安政策實施前後各地區房價變化情形，進一步採用差異中之差異 法（Difference-in-Differences， DID），比較新竹與桃園地區於政策前後之房價變化差異。 此外，本研究亦納入平均建物面積、月交易筆數、淨遷徙人數、購屋貸款利率、消費者物價 指數以及購買耐久財時機等控制變數，以降低其他總體經濟因素對房價之干擾。同時，為進 一步檢驗政策效果之差異性與穩健性，本研究亦進行不同坪數住宅、新竹縣市區域以及排除 高總價住宅後之異質性與穩健性分析。 實證結果顯示，新青安政策實施後，新竹與桃園地區房價皆呈現上升趨勢，其中桃園地 區於事件前後分析中呈現較明顯之政策效果；而 DID 模型結果則顯示，新竹地區於政策實施 後之房價相較桃園地區出現更顯著之上升幅度，表示新竹住宅市場對政策刺激之反應較為敏 感。此外，異質性分析結果顯示，大坪數住宅之政策效果高於小坪數住宅，顯示政策效果可 能透過市場需求與價格傳導機制影響整體住宅市場；而新竹市與新竹縣之區域異質性分析則 顯示，政策效果並未因核心區域差異而出現顯著不同。最後，在排除總價超過 3，000 萬元住 宅交易後，實證結果方向仍與主模型一致，代表本研究結果具有一定穩健性。 綜合而言，本研究認為新青安政策雖有助於降低青年購屋門檻並提升住宅需求，但同時 亦可能進一步推升部分地區房價，尤其對高所得與高需求地區之影響更為明顯。因此，政府i 未來在推動住宅金融政策時，除應考量提升居住可負擔性外，亦應兼顧住宅市場穩定與區域 房價差異問題，以降低房價過度上升所可能帶來之居住負擔與市場風險。 關鍵詞：新青安政策、房價、差異中之差異法（DID）、事件前後分析法、住宅市場、新 竹、桃園;In recent years， housing prices in Taiwan have continued to rise， increasing the burden of homeownership for young people. To reduce the barriers to purchasing a home and improve housing affordability， the Taiwanese government launched the Enhanced Youth Homeownership Loan Program (commonly known as the New Youth Housing Loan Policy) in August 2023. The policy aims to assist first-time homebuyers by increasing loan limits， extending loan terms， and providing interest subsidies. However， under conditions where housing supply cannot be adjusted rapidly in the short run， demand-side housing policies may further drive up housing prices， raising concerns regarding their market impacts. Therefore， this study investigates the effects of the New Youth Housing Loan Policy on housing prices in the Hsinchu and Taoyuan regions. This study employs monthly data from 2020 to 2025， obtained from the Actual Price Registration System of the Ministry of the Interior and related macroeconomic statistical databases. Methodologically， an Interrupted Time Series Analysis (ITSA) is first applied to examine changes in housing prices before and after the implementation of the policy. Subsequently， the Difference-in-Differences (DID) approach is adopted to compare the differential housing price changes between Hsinchu and Taoyuan. To control for other factors affecting housing prices， the model incorporates several control variables， including average building area， monthly transaction volume， net migration， mortgage interest rates， the Consumer Price Index (CPI)， and the timing index for purchasing durable goods. Furthermore， heterogeneity and robustness analyses are conducted based on housing size， regional differences between Hsinchu City and Hsinchu County， and a subsample excluding housing transactions with a total price exceeding NT$30 million. The empirical results indicate that housing prices in both Hsinchu and Taoyuan increased after the implementation of the New Youth Housing Loan Policy. The Interrupted Time Series Analysis reveals a more pronounced policy effect in Taoyuan. However， the DID results show that housing prices in Hsinchu experienced a significantly greater increase than those in Taoyuan after the policy implementation， suggesting that the Hsinchu housing market is more sensitive to policy-induced demand stimulation. In addition， the heterogeneity analysis indicates that the policy effect is stronger for larger housing units than for smaller ones， implying that the policy may affect the broader housing market through demand and price transmission mechanisms. The regional heterogeneity analysis between Hsinchu City and Hsinchu County shows no substantial difference in policy effects attributable to core-area characteristics. Finally， after excluding housing transactions with total prices exceeding NT$30 million， the empirical findings remain consistent with the baseline model， demonstrating the robustness of the results. Overall， this study suggests that while the New Youth Housing Loan Policy helps reduce barriers to homeownership and stimulate housing demand， it may also contribute to rising housing prices in certain regions， particularly in areas characterized by higher income levels and stronger housing demand. Therefore， future housing finance policies should not only focus on improving housing affordability but also take into account housing market stability and regional disparities in housing prices to mitigate the potential burden of excessive housing price growth and associated market risks. Keywords: New Youth Housing Loan Policy， Housing Prices， Difference-in- Differences (DID)， Interrupted Time Series Analysis (ITSA)， Housing Market，Hsinchu， Taoyuan.
