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題名 台灣穩定房市政策對房價之影響
The Impact of Taiwan’s Housing Market Stabilization Policies on Housing Prices
作者 洪嘉潁
Hong, Jia-Ying
貢獻者 洪福聲
Hung, Fu-Sheng
洪嘉潁
Hong, Jia-Ying
關鍵詞 局部投影法
貸款成數
住宅市場
房地合一稅
貨幣政策
房價
Local Projection Method
LTV
Housing market
Capital gains tax
Monetary Policy
Housing Prices
日期 2025
上傳時間 4-Aug-2025 12:50:00 (UTC+8)
摘要 本研究探討台灣自 2010 年起實施之房市調控政策對房價的動態影響，聚焦於利率政策、選擇性信用管制、稅制改革與購屋補貼等工具，並運用 Jordà（2005）所提出之局部投影法（local projection method），結合 2001 年第 1 季至 2024 年第 4 季之季資料進行實證估計。結果顯示，升息將在兩年內使房價下跌約 1% 至 2%。雖然升息對房價具一定抑制效果，但利率作為總體性政策工具，其影響範圍涵蓋整體經濟，過度依賴升息可能衍生負面外部性。因此，政府更傾向透過具針對性的選擇性信用管制，聚焦於特定購屋族群或房地產交易行為，以達成更精準且副作用較小的市場干預目的。在信貸政策方面，第二戶限貸政策抑制房價最為有效且顯著，下調貸款成數一成可使房價下跌 6% 至 8%。相較之下，第三戶限貸與高價住宅限貸之效果較為遞延或不顯著。房地產稅制本研究僅採納房地合一稅1.0與2.0，由於奢侈稅已於 2016 年併入房地合一稅，故未另納入；囤房稅 2.0 則因樣本期數不足，僅採用囤房稅 1.0 作為穩健性檢查依據。結果顯示房地合一稅雖呈現負向影響，但統計上未達顯著水準；新青安購屋貸款政策則推升房價近 10%。為檢驗信貸政策估計結果之穩健性，本文將基準模型替換控制變數與增列變數。結果顯示主要政策效果方向一致，第二戶限貸效果最具穩健性。整體而言，具針對性之信貸管制相較利率政策更具抑價效果，信貸政策設計與涵蓋對象之精準性對於政策成效具有關鍵意涵。
This study analyzes the dynamic effects of Taiwan’s housing market regulations since 2010, focusing on interest rate policy, selective credit controls, tax reforms, and housing subsidies. Using Jordà’s (2005) Local Projection Method and quarterly data from 2001Q1 to 2024Q4, results show that a 25-basis-point rate hike reduces house prices by 1–2% within two years. The loan-to-value limit on second-home purchases proves most effective, with a 10% reduction linked to a 6–8% price drop. In contrast, the loan-to-value limit on third-home purchases and the loan-to-value limit on high-priced housing loans show weaker or delayed effects. Only the consolidated housing and land taxes (1.0 and 2.0) are considered; the luxury tax is excluded due to its merger in 2016, and the vacant home tax 2.0 due to limited data. Vacant home tax 1.0 is used for robustness checks. Replacing the rediscount rate with the secured loan rate confirms result robest. While interest rates affect house prices, their broad economic impact prompts governments to favor credit tools for more targeted housing interventions.
參考文獻 王泓仁、陳南光與林姿妤 (2017)，「房貸成數 (LTV) 對臺灣房地產價格與授信之影響」，中央銀行季刊，39(3)，5-39。 王聖東 (2017)，「貸款利率、成數與住宅價格關聯性之研究 ── 以台北市及新北市為例」，國立政治大學地政學研究所碩士論文。 江佳玟 (2017)，「購屋貸款變數與住宅市場關聯性之研究」，國立政治大學地政學研究所碩士論文。 許鉛厚 (2022)，「總體審慎政策的成本－以台灣貸款成數政策為例」，國立成功大學經濟學研究所碩士論文。 陳柏如 (2018)，「總體審慎政策工具與臺灣房價的關係 ── 特定目標信用工具與房市相關租稅工具的影響」，經濟研究（Taipei Economic Inquiry），54(2)，287–330。 陳隆麒與李文雄 (1998)，「臺灣地區房價, 股價, 利率互動關係之研究－聯立方程模型與向量自我迴歸模型之應用」，中國財務學刊，5(4)，51-71。 黃名義、許育純與蔡嘉哲（2023），「房地合一稅制 1.0 和 2.0 實施後的成效檢視：從總體和個體資料分析」，不動產研究，(2)，62-78。 彭思瑾 (2017)，「貸款成數、加碼利率與房價的動態調整」，國立政治大學經濟學研究所碩士論文。 蔡明諺 (2022)，「探討總體經建環境對台灣房價的影響」，政治大學企業管理研究所 (MBA 學位學程) 碩士論文。 Ahuja, A., & Nabar, M. (2011). Safeguarding banks and containing property booms: cross- country evidence on macroprudential policies and lessons from Hong Kong SAR. https://www.imf.org/external/pubs/ft/wp/2011/wp11284.pdf Akinci, Ö., & Olmstead-Rumsey, J. (2018). How effective are macroprudential policies? an empirical investigation. Journal of Financial Intermediation, 33, 33–57. https://doi.org/ 10.1016/j.jfi.2017.04.001 Andrews, D., Sánchez, A. C., & Johansson, Å. (2011). Housing markets and structural policies in OECD countries. https://doi.org/10.1787/5kgk8t2k9vf3-en Bernanke, B. S., Gertler, M., & Gilchrist, S. (1999). The financial accelerator in a quantitative business cycle framework. Handbook of macroeconomics, 1, 1341–1393. https://doi. org/10.1016/S1574-0048(99)10034-X Bloor, C., & McDonald, C. (2013). ”Estimating the impacts of restrictions on high LVR lending” (Analytical Note No. AN2013/05). Reserve Bank of New Zealand. http://www.rbnz. govt.nz/-/media/ReserveBank/Files/Publications/Analytical%20notes/2013/an2013- 05.pdf Chen, C. (2021). Research on the impact of monetary policy on real estate prices [Doctoral Dissertation]. Geneva Finance Research Institute. Claessens, S., Kose, M. A., & Terrones, M. E. (2011). Financial cycles: What? how? when? NBER international seminar on macroeconomics, 7(1), 303–344. https://www.journals. uchicago.edu/doi/full/10.1086/658308 Del Negro, M., & Otrok, C. (2007). 99 Luftballons: Monetary policy and the house price boom across U.S. states. Journal of Monetary Economics, 54(7), 1962–1985. https://doi.org/ 10.1016/j.jmoneco.2006.11.003 Demary, M., & Voigtländer, M. (2009). The inflation hedging properties of real estate: A comparison between direct investments and equity returns. ERES Conference 2009. https://www.researchgate.net/publication/228707799 Dickey, D. A., & Fuller, W. A. (1979). Distribution of the Estimators for Autoregressive Time Series with a Unit Root. Journal of the American Statistical Association, 74(366), 427– 431. https://doi.org/10.1080/01621459.1979.10482531 Dickey, D. A., & Fuller, W. A. (1981). Likelihood Ratio Statistics for Autoregressive Time Series with a Unit Root. Econometrica, 49(4), 1057–1072. https://doi.org/10.2307/ 1912517 Enders, W. (2014). Applied Econometric Time Series (4th). John Wiley & Sons. Gindelsky, M., Moulton, J., Wentland, K., & Wentland, S. (2023). Returns to homeownership and inequality: Evidence from the first-time homebuyer tax credit. https://www.aeaweb. org/conference/2023/program/paper/h2if8fNs Glaeser, E. L., Gottlieb, J. D., & Gyourko, J. (2012). Can cheap credit explain the housing boom? In Housing and the financial crisis (pp. 301–359). University of Chicago Press. https://www.nber.org/system/files/chapters/c12622/c12622.pdf Grebler, L., & Mittelbach, F. (1979). The inflation of house prices, its extent, causes, and consequences. Lexington Books. https : / / books . google . com . tw / books ? id = _E - OAAAAIAAJ Hamilton, J. D. (1994). Time Series Analysis. Princeton University Press. Iacoviello, M. (2005). House prices, borrowing constraints, and monetary policy in the business cycle. American Economic Review, 95(3), 739–764. https : / / doi . org / 10 . 1257 / 0002828054201477 Iacoviello, M., & Neri, S. (2010). Housing Market Spillovers: Evidence from an Estimated DSGE Model. American Economic Journal: Macroeconomics, 2(2), 125–164. https ://doi.org/10.1257/mac.2.2.125 Igan, M. D., & Kang, M. H. (2011). Do loan-to-value and debt-to-income limits work? Evidence from Korea. International Monetary Fund. https://papers.ssrn.com/sol3/Delivery.cfm? abstractid=1974849 Jordà, Ò. (2005). Estimation and Inference of Impulse Responses by Local Projections.American Economic Review, 95(1), 161–182. https://doi.org/10.1257/0002828053828518 Kau, J. B., & Keenan, D. (1981). On the theory of interest rates, consumer durables, and the demand for housing. Journal of Urban Economics, 10(2), 183–200. https://doi.org/10. 1016/0094-1190(81)90014-0 Kent, R. J. (1984). Housing tenure choice: Evidence from time series. Journal of Urban Economics, 15(2), 195–209. https://doi.org/10.1016/0094-1190(84)90014-7 Kuttner, K., & Shim, I. (2012). Taming the real estate beast. The Effects of Monetary and Macroprudential Policies on House Prices and Credit. Preliminary Conference Draft. Reserve Bank of Australia ja Bank for International Settlements. Kuttner, K. N., & Shim, I. (2013). Can non-interest rate policies stabilise housing markets.Evidence from a panel of , 57. McDonald, C. (2015, March). When is macroprudential policy effective? (BIS Working Papers No. 496). Bank for International Settlements. Monetary, Economic Department. https://www.bis.org/publ/work496.pdf Montiel Olea, J. L., & Plagborg-Møller, M. (2021). Local Projection Inference Is Simpler and More Robust Than You Think. Econometrica, 89(4), 1789–1823. https://doi.org/10. 3982/ECTA17434 Perron, P. (1989). The Great Crash, the Oil Price Shock, and the Unit Root Hypothesis.Econometrica, 57(6), 1361–1401. https://doi.org/10.2307/1913712 Phillips, P. C., & Perron, P. (1988). Testing for a unit root in time series regression. biometrika, 75(2), 335–346. Poterba, J. M. (1984). Tax Subsidies to Owner-Occupied Housing: An Asset-Market Approach. The Quarterly Journal of Economics, 99(4), 729–752. https://doi.org/10.2307/1883123 Ramey, V. A. (2016). Macroeconomic Shocks and Their Propagation (J. B. Taylor & H. Uhlig, Eds.). Handbook of Macroeconomics, 2, 71–162. https://doi.org/10.1016/bs.hesmac.2016.03.002 Ramey, V. A., & Zubairy, S. (2018). Government spending multipliers in good times and in bad: Evidence from US historical data. Journal of Political Economy, 126(2), 850–901. https://doi.org/10.1086/696277 Salisu, A. A., Raheem, I. D., & Ndako, U. B. (2020). The inflation hedging properties of gold, stocks and real estate: A comparative analysis. Resources Policy, 66, 101605. https ://doi.org/10.1016/j.resourpol.2020.101605 Skaburskis, A., & Tomalty, R. (1997). Land Value Taxation and Development Activity: The Reaction of Toronto and Ottawa Developers, Planners, Municipal Finance Officials. Canadian Journal of Regional Science, 20(3), 401–418. https://idjs.ca/images/ rcsr / archives/V20N3-Skaburskis-Tomalty.pdf Summers, L. H. (1980). Inflation, the stock market, and owner-occupied housing (NBER Working Paper No. w0606). National Bureau of Economic Research. https : / / www . nber.org/papers/w0606 White, H. (1980). A Heteroskedasticity-Consistent Covariance Matrix Estimator and a Direct Test for Heteroskedasticity. Econometrica, 48(4), 817–838. https://doi.org/10.2307/ 1912934 Wong, Y. C., Ooi, J. T. L., & Le, T. T. (2022). The effectiveness of macroprudential housing policies: Evidence from singapore. Journal of Housing Economics, 56, 101847. https://doi.org/10.1016/j.jhe.2022.101847 Xie, S. (2024). Monetary policy shocks and local housing prices. Available at SSRN 4193924. https://doi.org/10.2139/ssrn.4193924
描述 碩士
國立政治大學
經濟學系
112258012
資料來源 http://thesis.lib.nccu.edu.tw/record/#G0112258012
資料類型 thesis
dc.contributor.advisor 洪福聲zh_TW
dc.contributor.advisor Hung, Fu-Shengen_US
dc.contributor.author (Authors) 洪嘉潁zh_TW
dc.contributor.author (Authors) Hong, Jia-Yingen_US
dc.creator (作者) 洪嘉潁zh_TW
dc.creator (作者) Hong, Jia-Yingen_US
dc.date (日期) 2025en_US
dc.date.accessioned 4-Aug-2025 12:50:00 (UTC+8)-
dc.date.available 4-Aug-2025 12:50:00 (UTC+8)-
dc.date.issued (上傳時間) 4-Aug-2025 12:50:00 (UTC+8)-
dc.identifier (Other Identifiers) G0112258012en_US
dc.identifier.uri (URI) https://nccur.lib.nccu.edu.tw/handle/140.119/158271-
dc.description (描述) 碩士zh_TW
dc.description (描述) 國立政治大學zh_TW
dc.description (描述) 經濟學系zh_TW
dc.description (描述) 112258012zh_TW
dc.description.abstract (摘要) 本研究探討台灣自 2010 年起實施之房市調控政策對房價的動態影響，聚焦於利率政策、選擇性信用管制、稅制改革與購屋補貼等工具，並運用 Jordà（2005）所提出之局部投影法（local projection method），結合 2001 年第 1 季至 2024 年第 4 季之季資料進行實證估計。結果顯示，升息將在兩年內使房價下跌約 1% 至 2%。雖然升息對房價具一定抑制效果，但利率作為總體性政策工具，其影響範圍涵蓋整體經濟，過度依賴升息可能衍生負面外部性。因此，政府更傾向透過具針對性的選擇性信用管制，聚焦於特定購屋族群或房地產交易行為，以達成更精準且副作用較小的市場干預目的。在信貸政策方面，第二戶限貸政策抑制房價最為有效且顯著，下調貸款成數一成可使房價下跌 6% 至 8%。相較之下，第三戶限貸與高價住宅限貸之效果較為遞延或不顯著。房地產稅制本研究僅採納房地合一稅1.0與2.0，由於奢侈稅已於 2016 年併入房地合一稅，故未另納入；囤房稅 2.0 則因樣本期數不足，僅採用囤房稅 1.0 作為穩健性檢查依據。結果顯示房地合一稅雖呈現負向影響，但統計上未達顯著水準；新青安購屋貸款政策則推升房價近 10%。為檢驗信貸政策估計結果之穩健性，本文將基準模型替換控制變數與增列變數。結果顯示主要政策效果方向一致，第二戶限貸效果最具穩健性。整體而言，具針對性之信貸管制相較利率政策更具抑價效果，信貸政策設計與涵蓋對象之精準性對於政策成效具有關鍵意涵。zh_TW
dc.description.abstract (摘要) This study analyzes the dynamic effects of Taiwan’s housing market regulations since 2010, focusing on interest rate policy, selective credit controls, tax reforms, and housing subsidies. Using Jordà’s (2005) Local Projection Method and quarterly data from 2001Q1 to 2024Q4, results show that a 25-basis-point rate hike reduces house prices by 1–2% within two years. The loan-to-value limit on second-home purchases proves most effective, with a 10% reduction linked to a 6–8% price drop. In contrast, the loan-to-value limit on third-home purchases and the loan-to-value limit on high-priced housing loans show weaker or delayed effects. Only the consolidated housing and land taxes (1.0 and 2.0) are considered; the luxury tax is excluded due to its merger in 2016, and the vacant home tax 2.0 due to limited data. Vacant home tax 1.0 is used for robustness checks. Replacing the rediscount rate with the secured loan rate confirms result robest. While interest rates affect house prices, their broad economic impact prompts governments to favor credit tools for more targeted housing interventions.en_US
dc.description.tableofcontents 致謝 ii 中文摘要 iii Abstract iv 目錄 v 表目錄 vii 圖目錄 viii 第一章緒論 1 第一節背景介紹 1 第二節研究目的 5 第三節研究流程 7 第二章文獻回顧 8 第一節總體因素與貨幣政策對房價影響 8 第二節房屋稅制與補貼對房價影響 10 第三節信貸政策對房價影響 12 第四節小結 14 第三章變數選取與研究方法 15 第一節資料介紹 15 一、資料說明及處理 15 二、敘述統計 19 第二節單根檢定 20 一、ADF 單根檢定 21 二、PP 單根檢定 22 第三節局部投影法 23 第四章實證結果與分析 26 第一節單根檢定 26 第二節局部投影法 28 一、傳統貨幣政策效果 28 二、房屋稅制與補貼政策效果 29 三、貸款成數上限政策效果 30 第五章結論與建議 33 第一節結論 33 第二節政策建議 35 第三節研究建議 36 第四節研究限制 37 中文參考文獻 38 英文參考文獻 39 附錄A 穩健性檢查 43 A.1 替換利率變數 43 A.2 增加囤房稅之虛擬變數 44 A.3 小結 45zh_TW
dc.format.extent 1378867 bytes-
dc.format.mimetype application/pdf-
dc.source.uri (資料來源) http://thesis.lib.nccu.edu.tw/record/#G0112258012en_US
dc.subject (關鍵詞) 局部投影法zh_TW
dc.subject (關鍵詞) 貸款成數zh_TW
dc.subject (關鍵詞) 住宅市場zh_TW
dc.subject (關鍵詞) 房地合一稅zh_TW
dc.subject (關鍵詞) 貨幣政策zh_TW
dc.subject (關鍵詞) 房價zh_TW
dc.subject (關鍵詞) Local Projection Methoden_US
dc.subject (關鍵詞) LTVen_US
dc.subject (關鍵詞) Housing marketen_US
dc.subject (關鍵詞) Capital gains taxen_US
dc.subject (關鍵詞) Monetary Policyen_US
dc.subject (關鍵詞) Housing Pricesen_US
dc.title (題名) 台灣穩定房市政策對房價之影響zh_TW
dc.title (題名) The Impact of Taiwan’s Housing Market Stabilization Policies on Housing Pricesen_US
dc.type (資料類型) thesisen_US
dc.relation.reference (參考文獻) 王泓仁、陳南光與林姿妤 (2017)，「房貸成數 (LTV) 對臺灣房地產價格與授信之影響」，中央銀行季刊，39(3)，5-39。 王聖東 (2017)，「貸款利率、成數與住宅價格關聯性之研究 ── 以台北市及新北市為例」，國立政治大學地政學研究所碩士論文。 江佳玟 (2017)，「購屋貸款變數與住宅市場關聯性之研究」，國立政治大學地政學研究所碩士論文。 許鉛厚 (2022)，「總體審慎政策的成本－以台灣貸款成數政策為例」，國立成功大學經濟學研究所碩士論文。 陳柏如 (2018)，「總體審慎政策工具與臺灣房價的關係 ── 特定目標信用工具與房市相關租稅工具的影響」，經濟研究（Taipei Economic Inquiry），54(2)，287–330。 陳隆麒與李文雄 (1998)，「臺灣地區房價, 股價, 利率互動關係之研究－聯立方程模型與向量自我迴歸模型之應用」，中國財務學刊，5(4)，51-71。 黃名義、許育純與蔡嘉哲（2023），「房地合一稅制 1.0 和 2.0 實施後的成效檢視：從總體和個體資料分析」，不動產研究，(2)，62-78。 彭思瑾 (2017)，「貸款成數、加碼利率與房價的動態調整」，國立政治大學經濟學研究所碩士論文。 蔡明諺 (2022)，「探討總體經建環境對台灣房價的影響」，政治大學企業管理研究所 (MBA 學位學程) 碩士論文。 Ahuja, A., & Nabar, M. (2011). Safeguarding banks and containing property booms: cross- country evidence on macroprudential policies and lessons from Hong Kong SAR. https://www.imf.org/external/pubs/ft/wp/2011/wp11284.pdf Akinci, Ö., & Olmstead-Rumsey, J. (2018). How effective are macroprudential policies? an empirical investigation. 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