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題名 上海市各圈層房地產市場溢出效應探究
Research on the Spillover Effect of Housing Market in Various Layers in Shanghai作者 徐霖
Xu, Lin貢獻者 陳明吉
Chen, Ming-Chi
徐霖
Xu, Lin關鍵詞 上海房地產市場
城市圈層
溢出效應
Shanghai real estate market
Urban circle
Spillover effect日期 2022 上傳時間 2-五月-2022 14:56:51 (UTC+8) 摘要 本研究假設上海市核心與外圍圈層的新建房與二手房市場存在著類似溢出效應的價格互動機制，經由對2011年1月到2021年4月上海市核心與外圍圈層各行政區平均月度房價通過交易量進行加權，獲得上海市核心圈層與外圍圈層的新建房與二手房價格，進而建立房價變化率VAR模型，並通過Granger因果檢定，確認各圈層各層級市場之間房價溢出效應的存在性，通過衝擊反應函數進一步分析房價溢出效應的表現形式。實證結果顯示，區別於過往國外類似研究所報告的房價變動由經濟發達的核心圈層向外圍擴散的溢出形式，上海市的房價溢出現象除了表現為核心圈層內新房與二手房市場之間的雙向溢出關係，還具有外圍圈層二手房市場向核心圈層新房與二手房市場單向溢出的現象，可見上海市外圍圈層二手房市場對整體上海房地產市場具有重大影響力。溢出效應動態表現形式方面，溢出的承受市場反應持續時間長度類似，均為五到六個月左右，且在受到衝擊後均先出現正向反應，後在第四個月左右轉為負向反應，區別主要集中在正向反應轉變為負向反應的幅度與持續時間，核心圈層內新房對二手房的的溢出有長達兩個月的負向反應時間，而不同於其他市場負向反應短暫，回歸平穩狀態迅速，可能受針對二手房的行政干預更少所致；同時，核心與外圍圈層的二手房市場對核心區新房的溢出動態特點極為相似，可能均受到政府行政干預等因素的影響。
This study assumes that there is a price interaction mechanism, which is similar to Spillover Effect between the first-hand, and second-hand housing markets in the core and outer circles of Shanghai. By weighting the average monthly house prices of the core and outer circles in Shanghai from January 2011 to April 2021 through the transaction volume, the prices of first-hand and second-hand houses in the core and outer circles of Shanghai are obtained, and then the VAR model of house price change rate is established. By using the Granger Causality test, then we can confirm the Spillover Effect between markets at all levels, and further analyze the manifestation of spillover effect through impact response function.The empirical results show that the Spillover form in Shanghai is different from the results reported by foreign research institutes. And the two-way spillover relationship between the new and the second-hand market in the core, the house price Spillover phenomenon also has the phenomenon of one-way Spillover from the secondhand market in the peripheral circle to the new house and the second-hand house market in the core circle, It can be seen that the second-hand housing market in the outer circle of Shanghai has a significant influence on the overall Shanghai real estate market. And the duration of the market response to spillover is similar, which is about five to six months, and the positive response first appears after being impacted, and then turns to negative response in about the fourth month. The difference is mainly in the range and duration of the positive response turning into negative response. The Spillover of new to second-hand houses in the core circle has a negative response time of up to two months, Unlike other markets, the negative reaction is short and the return to a stable state is rapid, which may be caused by less administrative intervention for second-hand housing; At the same time, the spillover dynamic characteristics of the second-hand housing market in the core and peripheral to the new houses in the core area are very similar, which may be affected by factors such as administrative intervention.參考文獻 英文参考文獻Balchin, P. N., Bull, G. H., Kieve, J. L., & Balchin, P. N. (1995). Urban land economics and public policy. Houndmills, Basingstoke, Hampshire: Macmillan.Case, K. E., & Shiller, R. J. (2003). Is There a Bubble in the Housing Market?. Brookings Papers on Economic Activity, 2003(2), 299–342.Chen, P. F., Chien, M. S. & Lee, C. C. (2011). Dynamic Modeling of Regional House Price Diffusion in Taiwan. Journal of Housing Economics, 20(4), 315–332.Clapp, J. M., & Tirtiroglu, D. (1994). Positive feedback trading and diffusion of asset price changes: Evidence from housing transactions. Journal of Economic Behavior & Organization, 24(3), 337-355.DeFusco, A. & Ding, W., Ferreira, F., & Gyourko, J. (2018). The role of price spillovers in the American housing boom. Journal of Urban Economics, 10(8), 72–84.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.Dipasquale, D., & Wheaton, W. C. (1996). Urban economics and real estate markets. Englewood Cliffs. NJ: Prentice Hall.Fair, R. C. (1972). Disequilibrium in Housing Models. Journal of Finance, 3(1), 207 -221.Granger, C. W. J., (1969). Investigating Causal Relations by Econometric Models and Cross-Spectral Methods. Econometrica, 37(3), 424-438.Holmans, A. E., (1990). House prices: changes through time at national and sub-national level. London: Department of the Environment.Li, J., Li, Z., Liu, C., & Shen, Z. (2021). Information spillover effects of real estate markets: Evidence from ten metropolitan cities in China. Journal of Risk and Financial Management, 14(6), 244-256.Macdonald, R., & Taylor, M. P., (1993). Regional House Prices in Britain: Long-Run Relationships and Short-Run Dynamics. Scottish Journal of Political Economy, 40(1), 43-55.Mankiw, N. G., & Weil. D. N. (1989). The Baby Boom. the Baby Bust and the Housing Market. Regional Science and Urban Economics, 19(2), 235-238.Mayo, S. K. (1981). Theory and Estimation in the Economics of Housing Demand． Journal of Urban Economics, Vol.10, 95-116.Meen, G. (1996). Spatial aggregation, spatial dependence and predictability in the UK housing market. Housing Studies, 11(3), 345-372.Meen, G. (1999). Regional House Prices and the Ripple Effect: A New Interpretation. Housing Studies, 14(6), 733-753.Peter C. B. P, & Perron, P. (1988). Testing for a Unit Root in Time Series Regression. Biometrika, 75(2), 335–346.Sims, C. A. (1980). Macroeconomics and Reality. Econometrica, 48(1), 1–48.Teng, H. J., Chang, C. O., & Chen, M. C. (2017). Housing bubble contagion from city centre to suburbs. Urban Studies, 54(6), 1463–1481.Wheaton, W. C., & Nechayev, G. (2008). The 1998-2005 Housing `Bubble` and the Current `Correction`: What`s Different this Time?. Journal of Real Estate Research, Vol. 30, No. 1.中文参考文獻王松濤(2011)。中國住房市場政府幹預的原理與效果評價。統計研究, 2011(5), 165-174。王雪、韓永輝、王聰(2018)。中國房地產市場的聯動效應和溢出效應分析-基於DAG和溢出指數的考證。數理統計與管理, 713-727。朱麗南、宗剛、陳連磊 (2017)。基於ESDA方法與空間計量模型的房價溢出效應分析。工業技術經濟，35(3)，98-106。位志宇、楊忠直(2007)。長三角房價變化的生態共生性研究—基於上海、杭州和南京的實證。當代經濟管理，29(2)，81-85。何盛明（1990）。財經大辭典。北京：中國財政經濟出版社。呂龍、劉海雲（2019）。城市房價溢出效應的測度、網路結構及其影響因素研究。 經濟評論，2019（2），161-173。李美杏、陳威廷、彭建文(2014)。亞洲城市房價基值與泡沫。都市與計劃, 41(2), 169-198。沈悅、李善燊、馬續濤(2012)。VAR宏觀計量經濟模型的演變與最新發展——基於2011年諾貝爾經濟學獎得主Smis研究成果的拓展脈絡。數量經濟技術經濟研究, 2012(10), 150-160。況偉大(2010)。利率對房價的影響。世界經濟, 10(4), 134-145。洪濤、西寶、高波(2007) 。房地產價格區域間聯動與泡沫的空間擴散—基於2000—2005年中國 35個大中城市面板資料的實證檢驗。統計研究, 24(08), 64-67。張淩(2008)。城市住房價格波動差異及連鎖反應研究。浙江大學管理學院博士論文，浙江省。張清勇、鄭環環(2009)。住宅存量與流量價格的領先—滯後關係--以北京、上海、廣州和深圳為例。財貿經濟, 9(5), 104-110。張銜、林仁達(2015)。我國城市房價短期波紋效應的實證。財經科學, 2015(9), 132-140。張謙(2017)。我國住房價格變動的溢出效應研究。西南交通大學管理學院博士論文，四川省。梁雲芳、高鐵梅(2007)。中國房地產價格波動區域差異的實證分析。經濟研究, 2007(8), 133-142。戴國強、張建華(2009)。貨幣政策的房地產價格傳導機制研究。財貿經濟, 2009(12), 31-37。豐茂芳(2019)。住宅與二手住宅價格指數關係的研究分析。重慶工商大學學報， 2019（2），54-59。 描述 碩士
國立政治大學
財務管理學系
108357035資料來源 http://thesis.lib.nccu.edu.tw/record/#G0108357035 資料類型 thesis dc.contributor.advisor 陳明吉 zh_TW dc.contributor.advisor Chen, Ming-Chi en_US dc.contributor.author (作者) 徐霖 zh_TW dc.contributor.author (作者) Xu, Lin en_US dc.creator (作者) 徐霖 zh_TW dc.creator (作者) Xu, Lin en_US dc.date (日期) 2022 en_US dc.date.accessioned 2-五月-2022 14:56:51 (UTC+8) - dc.date.available 2-五月-2022 14:56:51 (UTC+8) - dc.date.issued (上傳時間) 2-五月-2022 14:56:51 (UTC+8) - dc.identifier (其他 識別碼) G0108357035 en_US dc.identifier.uri (URI) http://nccur.lib.nccu.edu.tw/handle/140.119/139982 - dc.description (描述) 碩士 zh_TW dc.description (描述) 國立政治大學 zh_TW dc.description (描述) 財務管理學系 zh_TW dc.description (描述) 108357035 zh_TW dc.description.abstract (摘要) 本研究假設上海市核心與外圍圈層的新建房與二手房市場存在著類似溢出效應的價格互動機制，經由對2011年1月到2021年4月上海市核心與外圍圈層各行政區平均月度房價通過交易量進行加權，獲得上海市核心圈層與外圍圈層的新建房與二手房價格，進而建立房價變化率VAR模型，並通過Granger因果檢定，確認各圈層各層級市場之間房價溢出效應的存在性，通過衝擊反應函數進一步分析房價溢出效應的表現形式。實證結果顯示，區別於過往國外類似研究所報告的房價變動由經濟發達的核心圈層向外圍擴散的溢出形式，上海市的房價溢出現象除了表現為核心圈層內新房與二手房市場之間的雙向溢出關係，還具有外圍圈層二手房市場向核心圈層新房與二手房市場單向溢出的現象，可見上海市外圍圈層二手房市場對整體上海房地產市場具有重大影響力。溢出效應動態表現形式方面，溢出的承受市場反應持續時間長度類似，均為五到六個月左右，且在受到衝擊後均先出現正向反應，後在第四個月左右轉為負向反應，區別主要集中在正向反應轉變為負向反應的幅度與持續時間，核心圈層內新房對二手房的的溢出有長達兩個月的負向反應時間，而不同於其他市場負向反應短暫，回歸平穩狀態迅速，可能受針對二手房的行政干預更少所致；同時，核心與外圍圈層的二手房市場對核心區新房的溢出動態特點極為相似，可能均受到政府行政干預等因素的影響。 zh_TW dc.description.abstract (摘要) This study assumes that there is a price interaction mechanism, which is similar to Spillover Effect between the first-hand, and second-hand housing markets in the core and outer circles of Shanghai. By weighting the average monthly house prices of the core and outer circles in Shanghai from January 2011 to April 2021 through the transaction volume, the prices of first-hand and second-hand houses in the core and outer circles of Shanghai are obtained, and then the VAR model of house price change rate is established. By using the Granger Causality test, then we can confirm the Spillover Effect between markets at all levels, and further analyze the manifestation of spillover effect through impact response function.The empirical results show that the Spillover form in Shanghai is different from the results reported by foreign research institutes. And the two-way spillover relationship between the new and the second-hand market in the core, the house price Spillover phenomenon also has the phenomenon of one-way Spillover from the secondhand market in the peripheral circle to the new house and the second-hand house market in the core circle, It can be seen that the second-hand housing market in the outer circle of Shanghai has a significant influence on the overall Shanghai real estate market. And the duration of the market response to spillover is similar, which is about five to six months, and the positive response first appears after being impacted, and then turns to negative response in about the fourth month. The difference is mainly in the range and duration of the positive response turning into negative response. The Spillover of new to second-hand houses in the core circle has a negative response time of up to two months, Unlike other markets, the negative reaction is short and the return to a stable state is rapid, which may be caused by less administrative intervention for second-hand housing; At the same time, the spillover dynamic characteristics of the second-hand housing market in the core and peripheral to the new houses in the core area are very similar, which may be affected by factors such as administrative intervention. en_US dc.description.tableofcontents 目次第一章 緒論..1第一節 研究背景..................1第二節 研究內容與目的......7第三節 研究方法及研究流程..........................8第二章 文獻探討....................10第一節 影響房價的總體因素........................10第二節 新房與二手房價格互動關係............13第三節 房地產市場價格溢出效應................14第三章 研究設計及方法........18第一節 研究目的與設計....19第二節 研究範圍與資料說明........................21第三節 研究模型與研究方法........................22第四章 實證分析....................28第一節 基本分析................28第二節 上海市城市圈層各級市場房價溢出效應分析............35第三節 上海市房價變化率 VAR 模型建立與檢定 .................40第四節 上海市城市圈層各級市場房價衝擊反應分析............45第五章 結論與建議................49第一節 結論........................49第二節 建議與限制............51参考文献......53 zh_TW dc.format.extent 1070494 bytes - dc.format.mimetype application/pdf - dc.source.uri (資料來源) http://thesis.lib.nccu.edu.tw/record/#G0108357035 en_US dc.subject (關鍵詞) 上海房地產市場 zh_TW dc.subject (關鍵詞) 城市圈層 zh_TW dc.subject (關鍵詞) 溢出效應 zh_TW dc.subject (關鍵詞) Shanghai real estate market en_US dc.subject (關鍵詞) Urban circle en_US dc.subject (關鍵詞) Spillover effect en_US dc.title (題名) 上海市各圈層房地產市場溢出效應探究 zh_TW dc.title (題名) Research on the Spillover Effect of Housing Market in Various Layers in Shanghai en_US dc.type (資料類型) thesis en_US dc.relation.reference (參考文獻) 英文参考文獻Balchin, P. N., Bull, G. H., Kieve, J. L., & Balchin, P. N. (1995). Urban land economics and public policy. Houndmills, Basingstoke, Hampshire: Macmillan.Case, K. E., & Shiller, R. J. (2003). Is There a Bubble in the Housing Market?. Brookings Papers on Economic Activity, 2003(2), 299–342.Chen, P. F., Chien, M. S. & Lee, C. C. (2011). Dynamic Modeling of Regional House Price Diffusion in Taiwan. Journal of Housing Economics, 20(4), 315–332.Clapp, J. M., & Tirtiroglu, D. (1994). Positive feedback trading and diffusion of asset price changes: Evidence from housing transactions. Journal of Economic Behavior & Organization, 24(3), 337-355.DeFusco, A. & Ding, W., Ferreira, F., & Gyourko, J. (2018). The role of price spillovers in the American housing boom. Journal of Urban Economics, 10(8), 72–84.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.Dipasquale, D., & Wheaton, W. C. (1996). Urban economics and real estate markets. Englewood Cliffs. NJ: Prentice Hall.Fair, R. C. (1972). Disequilibrium in Housing Models. Journal of Finance, 3(1), 207 -221.Granger, C. W. J., (1969). Investigating Causal Relations by Econometric Models and Cross-Spectral Methods. Econometrica, 37(3), 424-438.Holmans, A. E., (1990). House prices: changes through time at national and sub-national level. London: Department of the Environment.Li, J., Li, Z., Liu, C., & Shen, Z. (2021). Information spillover effects of real estate markets: Evidence from ten metropolitan cities in China. Journal of Risk and Financial Management, 14(6), 244-256.Macdonald, R., & Taylor, M. P., (1993). Regional House Prices in Britain: Long-Run Relationships and Short-Run Dynamics. Scottish Journal of Political Economy, 40(1), 43-55.Mankiw, N. G., & Weil. D. N. (1989). The Baby Boom. the Baby Bust and the Housing Market. Regional Science and Urban Economics, 19(2), 235-238.Mayo, S. K. (1981). Theory and Estimation in the Economics of Housing Demand． Journal of Urban Economics, Vol.10, 95-116.Meen, G. (1996). Spatial aggregation, spatial dependence and predictability in the UK housing market. Housing Studies, 11(3), 345-372.Meen, G. (1999). Regional House Prices and the Ripple Effect: A New Interpretation. Housing Studies, 14(6), 733-753.Peter C. B. P, & Perron, P. (1988). Testing for a Unit Root in Time Series Regression. Biometrika, 75(2), 335–346.Sims, C. A. (1980). Macroeconomics and Reality. Econometrica, 48(1), 1–48.Teng, H. J., Chang, C. O., & Chen, M. C. (2017). Housing bubble contagion from city centre to suburbs. Urban Studies, 54(6), 1463–1481.Wheaton, W. C., & Nechayev, G. (2008). The 1998-2005 Housing `Bubble` and the Current `Correction`: What`s Different this Time?. Journal of Real Estate Research, Vol. 30, No. 1.中文参考文獻王松濤(2011)。中國住房市場政府幹預的原理與效果評價。統計研究, 2011(5), 165-174。王雪、韓永輝、王聰(2018)。中國房地產市場的聯動效應和溢出效應分析-基於DAG和溢出指數的考證。數理統計與管理, 713-727。朱麗南、宗剛、陳連磊 (2017)。基於ESDA方法與空間計量模型的房價溢出效應分析。工業技術經濟，35(3)，98-106。位志宇、楊忠直(2007)。長三角房價變化的生態共生性研究—基於上海、杭州和南京的實證。當代經濟管理，29(2)，81-85。何盛明（1990）。財經大辭典。北京：中國財政經濟出版社。呂龍、劉海雲（2019）。城市房價溢出效應的測度、網路結構及其影響因素研究。 經濟評論，2019（2），161-173。李美杏、陳威廷、彭建文(2014)。亞洲城市房價基值與泡沫。都市與計劃, 41(2), 169-198。沈悅、李善燊、馬續濤(2012)。VAR宏觀計量經濟模型的演變與最新發展——基於2011年諾貝爾經濟學獎得主Smis研究成果的拓展脈絡。數量經濟技術經濟研究, 2012(10), 150-160。況偉大(2010)。利率對房價的影響。世界經濟, 10(4), 134-145。洪濤、西寶、高波(2007) 。房地產價格區域間聯動與泡沫的空間擴散—基於2000—2005年中國 35個大中城市面板資料的實證檢驗。統計研究, 24(08), 64-67。張淩(2008)。城市住房價格波動差異及連鎖反應研究。浙江大學管理學院博士論文，浙江省。張清勇、鄭環環(2009)。住宅存量與流量價格的領先—滯後關係--以北京、上海、廣州和深圳為例。財貿經濟, 9(5), 104-110。張銜、林仁達(2015)。我國城市房價短期波紋效應的實證。財經科學, 2015(9), 132-140。張謙(2017)。我國住房價格變動的溢出效應研究。西南交通大學管理學院博士論文，四川省。梁雲芳、高鐵梅(2007)。中國房地產價格波動區域差異的實證分析。經濟研究, 2007(8), 133-142。戴國強、張建華(2009)。貨幣政策的房地產價格傳導機制研究。財貿經濟, 2009(12), 31-37。豐茂芳(2019)。住宅與二手住宅價格指數關係的研究分析。重慶工商大學學報， 2019（2），54-59。 zh_TW dc.identifier.doi (DOI) 10.6814/NCCU202200392 en_US
