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題名 臺灣房市價量因果關係之研究：Toda-Yamamoto 因果關係與小波相干分析法之應用
Price-Volume Causality in Taiwan Housing Market：Toda-Yamamoto Causality and Wavelet Coherence Approach
作者 鍾雅雯
Chung, Ya-Wen
貢獻者 徐士勛
Hsu, Shih-Hsun
鍾雅雯
Chung, Ya-Wen
關鍵詞 房市價量因果關係
Toda-Yamamoto 因果關係檢定
小波分析
時頻域因果關係
Price-Volume causality
Housing market
Toda-Yamamoto
Wavelet analysis
日期 2022
上傳時間 1-Jul-2022 16:26:27 (UTC+8)
摘要 本文利用時頻域的小波相干分析探討2012年8月至2021年10月臺灣全國房市的價量因果關係，並著重在認定不同頻率與週期之下價量之間的領先落後關係。此外，本文亦使用時域架構下的Toda-Yamamoto與控制頻域下的傅立葉Toda-Yamamoto因果關係檢定法探討全國房市價量間的可能因果關係。

在小波相干分析的結果中，我們發現從2014至2016年的中頻與低頻區域（約16至32個月的週期間），存在全國住宅交易量領先全國房價指數的顯著現象。然而，Toda-Yamamoto架構下的Granger因果檢定顯示全樣本期間存在全國房價領先交易量的單向因果關係；而傅立葉Toda-Yamamoto的結果中卻認定房市價量之間並不存在任何的雙向因果關係，因此我們無法在時域的分析架構下，藉由房市價量的任一變數預測另一變數的走勢。

此外，本文也進一步針對臺灣六大都會區的跨區房價與跨區交易量進行小波相干因果分析。跨區房價的分析結果顯示，北、中、南都會區大多呈現正相關，但領先落後關係並不明顯；而交易量的跨區結果顯示，北部與中部都會區領先南部都會區的關係僅存在於2017年之前，2017年後領先落後關係轉而以南部都會區領先北部與中部都會區。
This research aims at analyzing the price-volume causality and correlation in Taiwan housing market by employing wavelet coherence, Toda-Yamamoto causality and Fourier Toda-Yamamoto causality tests over the period August 2012 to October 2021. Our findings reveal that the lead-lag movement
is observed in mid-low frequency from the transaction volumes to the price index between 2014 to 2016. However, the outcomes of the time-domain causality are not in line with the results of wavelet coherence analysis : the result
of Toda-Yamamoto causality demonstrates that only price index Granger cause the transaction volumes ; after controlling the frequency, there is no causal relationship between price index and volumes. We further conduct
the wavelet coherent analysis on cross-regional housing price indices and transaction volumes in the six metropolitan regions. The analyses show that the correlation among these cross-regional indices is positive but the lead-lag relationship of those is not obvious. For the cross-regional transaction volumes, the results indicate that the volumes in northern and mid-Taiwan regions lead that in the southern areas before 2017, and after that, the lead-lag
relationship reverses.
參考文獻 朱芳妮，周育如與張金鶚(2012)，「台灣房價指數的再檢視、細分與應用—時間、空間與類型之分析（第三年）」，《行政院國家科學委員會專題研究計畫研究成果報告》，台北：行政院國家科學委員會。
花敬群與張金鶚(1997)，「住宅市場價量波動之研究」，《住宅學報》，5， 1-15。
林正隆(2014)，《選擇性信用管制政策對房地產價格與成交量之影響—以台北市及新北市為例》，國立中正大學經濟學系國際經濟學碩士論文。
林柏伸(2012)，《我國課徵奢侈稅對不動產價格與成交量之影響—以台北市為例》，朝陽科技大學財務金融系碩士論文。
高慈敏(2014)，「經濟波動與房地產交易之價量關係：搜索模型之應用」，《住宅學報》，23， 21-56。
游綉云(2015)，《台灣住宅之價量研究：區域性分析》，國立中正大學經濟學系國際經濟學碩士學位論文。
楊孟蓉(2015)，《台灣不動產市場價量關係研究》，國立高雄大學金融管理學系碩士論文。
謝明勳(2019)，《股市與房市之研究：來自臺灣的實證研究》，國立暨南大學財務金融學系碩士論文。
簡祥傑(2014)，《住宅市場中不同產品類型價量關係之研究》，屏東商業技術學院不動產經營研究所碩士論文。
羅于婷(2010)，《住宅新推個案市場價量關係之分析》，國立政治大學地政學系私立中國地政研究所碩士論文。
Adebayo, T. S. (2020), “Revisiting the EKC hypothesis in an emerging market: an application of ARDL-based bounds and wavelet coherence approaches,” SN Applied Sciences, 2(12), 1-15.
Akkoyun, H. C., Y. Arslan, and B. Kanik (2013), “Housing prices and transaction volume,” Journal of Housing Economics, 22(2), 119-134.
Andrew, M. and G. Meen (2003), “House price appreciation, transactions and structural change in the British housing market: a macroeconomic perspective,”
Real Estate Economics, 31(1), 99-116.
Balcilar, M., Z. A. Ozdemir, and Y. Arslanturk (2010), “Economic growth and energy consumption causal nexus viewed through a bootstrap rolling window,” Energy Economics, 32(6), 1398-1410.
Berkovec, J. A. and J. L. Goodman Jr (1996), “Turnover as a measure of demand for existing homes,” Real Estate Economics, 24(4), 421-440.
Cavaliere, G., D. I. Harvey, S. J. Leybourne, and A. R. Taylor (2011), “Testing for unit roots in the presence of a possible break in trend and nonstationary volatility,” Econometric Theory, 27(5), 957-991.
Clayton, J., N. Miller, and L. Peng (2010), “Price-volume correlation in the housing market : causality and co-movements,” The Journal of Real Estate Finance and Economics, 40(1), 14-40.
De Wit, E. R., P. Englund, and M. K. Francke (2013), “Price and transaction volume in the Dutch housing market,” Regional Science and Urban Economics,43(2), 220-241.
Dickey, D. A. and W. A. Fuller (1979), “Distribution of the estimators for autoregressive time series with a unit root,” Journal of the American statistical association, 74(366a), 427-431.
Efron, B. (1992), “Bootstrap methods: another look at the jackknife,” Breakthroughs in statistics , Springer, New York, NY, 569-593.
Elliott, G., T. J. Rothenberg, and J. H. Stock (1996), “Efficient tests for an autoregressive unit root,” Econometrica, 64(4), 813-836.
Enders, W. and P. Jones (2016), “Grain prices, oil prices, and multiple smooth breaks in a VAR,” Studies in Nonlinear Dynamics & Econometrics, 20(4), 399-419.
Genesove, D. and C. Mayer (2001), “Loss aversion and seller behavior: evidence from the housing market,” The Quarterly Journal of Economics, 116(4), 1233-1260.
Goupillaud, P., A. Grossmann, and J. Morlet (1984), “Cycle-octave and related transforms in seismic signal analysis,” Geoexploration, 23(1), 85-102.
Hacker, R. S., and A. Hatemi-J (2006), “Tests for causality between integrated variables using asymptotic and bootstrap distributions: theory and application,”
Applied Economics, 38(13), 1489-1500.
Hatemi-J, A. (2002), “Export performance and economic growth nexus in Japan: a bootstrap approach,” Japan and the World Economy, 14(1), 25-33.
Hort, K. (2000), “Prices and turnover in the market for owner-occupied homes,” Regional Science and Urban Economics, 30, 99-119.
Kirikkaleli, D. (2019), “Time-frequency dependency of financial risk and economic risk: evidence from Greece,” Journal of Economic Structures, 8(1), 1-10.
Kirikkaleli, D. (2020), “Does political risk matter for economic and financial risks in Venezuela?” Journal of Economic Structures, 9(1), 1-10.
Kirikkaleli, D. and H. Güngör (2021), “Co-movement of commodity price indexes and energy price index: a wavelet coherence approach,” Financial Innovation, 7(1), 1-18.
Kwiatkowski, D., P. C. Phillips, P. Schmidt, and Y. Shin (1992), “Testing the null hypothesis of stationarity against the alternative of a unit root: How sure are we that economic time series have a unit root?” Journal of Econometrics, 54(1-3), 159-178.
Li, L. H. and K. S. Cheung (2017), “Housing price and transaction intensity correlation in Hong Kong : implications for government housing policy,” Journal
of Housing and the Built Environment, 32(2), 269-287.
Lütkepohl, H. (2005), “New introduction to multiple time series analysis,” Springer Science and Business Media, 103-320.
Mantalos, P. (2000), “A graphical investigation of the size and power of the Granger-causality tests in integrated-cointegrated VAR systems,” Studies in Nonlinear
Dynamics & Econometrics, 4(1), 17-33.
Nazlioglu, S., N. A. Gormus, and U. Soytas (2016), “Oil prices and real estate investment trusts (REITs): Gradual-shift causality and volatility transmission
analysis,” Energy Economics, 60, 168-175.
Nazlioglu, S., A. Gormus, and U. Soytas (2019), “Oil prices and monetary policy in emerging markets: structural shifts in causal linkages,” Emerging Markets Finance and Trade, 55(1), 105-117.
Nong, H. (2022), “Understanding housing price–volume connectedness: the case of housing markets in major megacities of China,” Applied Spatial Analysis
and Policy, 1-19.
Ortalo-Magne, F., and S. Rady (2006), “Housing market dynamics: on the contribution of income shocks and credit constraints,” The Review of Economic Studies, 73(2), 459-485.
Phillips, P. C. and P. Perron (1988), “Testing for a unit root in time series regression,” Biometrika, 75(2), 335-346.
Reimers, H. E. (1992), “Comparisons of tests for multivariate cointegration,” Statistical Papers, 33(1), 335-359.
Said, S. E., and D. A. Dickey (1984), “Testing for unit roots in autoregressivemoving average models of unknown order,” Biometrika, 71(3), 599-607.
Stein, J. C. (1995), “Prices and trading volume in the housing market: a model with down-payment effects,” The Quarterly Journal of Economics, 110(2), 379-406.
Toda, H. Y. and T. Yamamoto (1995), “Statistical inference in vector autoregressions with possibly integrated process,” Journal of Econometrics, 66(1-2), 225-250.
Zivot, E. and D. W. K. Andrews (2002), “Further evidence on the great crash, the oil-price shock, and the unit-root hypothesis,” Journal of Business and Economic Statistics, 20(1), 25-44.
描述 碩士
國立政治大學
經濟學系
109258004
資料來源 http://thesis.lib.nccu.edu.tw/record/#G0109258004
資料類型 thesis
dc.contributor.advisor 徐士勛zh_TW
dc.contributor.advisor Hsu, Shih-Hsunen_US
dc.contributor.author (Authors) 鍾雅雯zh_TW
dc.contributor.author (Authors) Chung, Ya-Wenen_US
dc.creator (作者) 鍾雅雯zh_TW
dc.creator (作者) Chung, Ya-Wenen_US
dc.date (日期) 2022en_US
dc.date.accessioned 1-Jul-2022 16:26:27 (UTC+8)-
dc.date.available 1-Jul-2022 16:26:27 (UTC+8)-
dc.date.issued (上傳時間) 1-Jul-2022 16:26:27 (UTC+8)-
dc.identifier (Other Identifiers) G0109258004en_US
dc.identifier.uri (URI) http://nccur.lib.nccu.edu.tw/handle/140.119/140686-
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) 109258004zh_TW
dc.description.abstract (摘要) 本文利用時頻域的小波相干分析探討2012年8月至2021年10月臺灣全國房市的價量因果關係，並著重在認定不同頻率與週期之下價量之間的領先落後關係。此外，本文亦使用時域架構下的Toda-Yamamoto與控制頻域下的傅立葉Toda-Yamamoto因果關係檢定法探討全國房市價量間的可能因果關係。

在小波相干分析的結果中，我們發現從2014至2016年的中頻與低頻區域（約16至32個月的週期間），存在全國住宅交易量領先全國房價指數的顯著現象。然而，Toda-Yamamoto架構下的Granger因果檢定顯示全樣本期間存在全國房價領先交易量的單向因果關係；而傅立葉Toda-Yamamoto的結果中卻認定房市價量之間並不存在任何的雙向因果關係，因此我們無法在時域的分析架構下，藉由房市價量的任一變數預測另一變數的走勢。

此外，本文也進一步針對臺灣六大都會區的跨區房價與跨區交易量進行小波相干因果分析。跨區房價的分析結果顯示，北、中、南都會區大多呈現正相關，但領先落後關係並不明顯；而交易量的跨區結果顯示，北部與中部都會區領先南部都會區的關係僅存在於2017年之前，2017年後領先落後關係轉而以南部都會區領先北部與中部都會區。		zh_TW
dc.description.abstract (摘要) This research aims at analyzing the price-volume causality and correlation in Taiwan housing market by employing wavelet coherence, Toda-Yamamoto causality and Fourier Toda-Yamamoto causality tests over the period August 2012 to October 2021. Our findings reveal that the lead-lag movement
is observed in mid-low frequency from the transaction volumes to the price index between 2014 to 2016. However, the outcomes of the time-domain causality are not in line with the results of wavelet coherence analysis : the result
of Toda-Yamamoto causality demonstrates that only price index Granger cause the transaction volumes ; after controlling the frequency, there is no causal relationship between price index and volumes. We further conduct
the wavelet coherent analysis on cross-regional housing price indices and transaction volumes in the six metropolitan regions. The analyses show that the correlation among these cross-regional indices is positive but the lead-lag relationship of those is not obvious. For the cross-regional transaction volumes, the results indicate that the volumes in northern and mid-Taiwan regions lead that in the southern areas before 2017, and after that, the lead-lag
relationship reverses.		en_US
dc.description.tableofcontents 1 緒論 1
1.1 研究動機與目的 1
1.2 研究架構 2
2 文獻回顧 3
3 研究方法與模型 8
3.1 單根檢定 8
3.1.1 ADF 單根檢定 8
3.1.2 PP 單根檢定 9
3.1.3 KPSS 單根檢定 11
3.2 小波分析 12
3.3 T-Y 分析法與傅立葉T-Y 分析法 14
4 資料 19
4.1 資料來源 19
4.2 資料說明 19
5 實證結果 25
5.1 小波相干分析結果 25
5.2 T-Y 與單一頻率傅立葉T-Y 分析結果 28
5.3 六大都會區小波相干分析結果 30
5.3.1 六大都會區房價指數之小波相干分析結果 31
5.3.2 六大都會區住宅交易量之小波相干分析結果 40
5.3.3 小結 49
6 結論與建議 51
參考文獻 54
附錄 60
A 臺灣房價指數一覽表 60
B 六大都會區小波功率圖 62
C 全國與六大都會區小波相干分析圖 64
D 六大都會區房市價量小波相干分析圖 72
E 其它六大都會區小波相干分析圖 76
F 全國房市價量時域因果關係之實證結果補充 80		zh_TW
dc.format.extent 6357928 bytes-
dc.format.mimetype application/pdf-
dc.source.uri (資料來源) http://thesis.lib.nccu.edu.tw/record/#G0109258004en_US
dc.subject (關鍵詞) 房市價量因果關係zh_TW
dc.subject (關鍵詞) Toda-Yamamoto 因果關係檢定zh_TW
dc.subject (關鍵詞) 小波分析zh_TW
dc.subject (關鍵詞) 時頻域因果關係zh_TW
dc.subject (關鍵詞) Price-Volume causalityen_US
dc.subject (關鍵詞) Housing marketen_US
dc.subject (關鍵詞) Toda-Yamamotoen_US
dc.subject (關鍵詞) Wavelet analysisen_US
dc.title (題名) 臺灣房市價量因果關係之研究：Toda-Yamamoto 因果關係與小波相干分析法之應用zh_TW
dc.title (題名) Price-Volume Causality in Taiwan Housing Market：Toda-Yamamoto Causality and Wavelet Coherence Approachen_US
dc.type (資料類型) thesisen_US
dc.relation.reference (參考文獻) 朱芳妮，周育如與張金鶚(2012)，「台灣房價指數的再檢視、細分與應用—時間、空間與類型之分析（第三年）」，《行政院國家科學委員會專題研究計畫研究成果報告》，台北：行政院國家科學委員會。
花敬群與張金鶚(1997)，「住宅市場價量波動之研究」，《住宅學報》，5， 1-15。
林正隆(2014)，《選擇性信用管制政策對房地產價格與成交量之影響—以台北市及新北市為例》，國立中正大學經濟學系國際經濟學碩士論文。
林柏伸(2012)，《我國課徵奢侈稅對不動產價格與成交量之影響—以台北市為例》，朝陽科技大學財務金融系碩士論文。
高慈敏(2014)，「經濟波動與房地產交易之價量關係：搜索模型之應用」，《住宅學報》，23， 21-56。
游綉云(2015)，《台灣住宅之價量研究：區域性分析》，國立中正大學經濟學系國際經濟學碩士學位論文。
楊孟蓉(2015)，《台灣不動產市場價量關係研究》，國立高雄大學金融管理學系碩士論文。
謝明勳(2019)，《股市與房市之研究：來自臺灣的實證研究》，國立暨南大學財務金融學系碩士論文。
簡祥傑(2014)，《住宅市場中不同產品類型價量關係之研究》，屏東商業技術學院不動產經營研究所碩士論文。
羅于婷(2010)，《住宅新推個案市場價量關係之分析》，國立政治大學地政學系私立中國地政研究所碩士論文。
Adebayo, T. S. (2020), “Revisiting the EKC hypothesis in an emerging market: an application of ARDL-based bounds and wavelet coherence approaches,” SN Applied Sciences, 2(12), 1-15.
Akkoyun, H. C., Y. Arslan, and B. Kanik (2013), “Housing prices and transaction volume,” Journal of Housing Economics, 22(2), 119-134.
Andrew, M. and G. Meen (2003), “House price appreciation, transactions and structural change in the British housing market: a macroeconomic perspective,”
Real Estate Economics, 31(1), 99-116.
Balcilar, M., Z. A. Ozdemir, and Y. Arslanturk (2010), “Economic growth and energy consumption causal nexus viewed through a bootstrap rolling window,” Energy Economics, 32(6), 1398-1410.
Berkovec, J. A. and J. L. Goodman Jr (1996), “Turnover as a measure of demand for existing homes,” Real Estate Economics, 24(4), 421-440.
Cavaliere, G., D. I. Harvey, S. J. Leybourne, and A. R. Taylor (2011), “Testing for unit roots in the presence of a possible break in trend and nonstationary volatility,” Econometric Theory, 27(5), 957-991.
Clayton, J., N. Miller, and L. Peng (2010), “Price-volume correlation in the housing market : causality and co-movements,” The Journal of Real Estate Finance and Economics, 40(1), 14-40.
De Wit, E. R., P. Englund, and M. K. Francke (2013), “Price and transaction volume in the Dutch housing market,” Regional Science and Urban Economics,43(2), 220-241.
Dickey, D. A. and W. A. Fuller (1979), “Distribution of the estimators for autoregressive time series with a unit root,” Journal of the American statistical association, 74(366a), 427-431.
Efron, B. (1992), “Bootstrap methods: another look at the jackknife,” Breakthroughs in statistics , Springer, New York, NY, 569-593.
Elliott, G., T. J. Rothenberg, and J. H. Stock (1996), “Efficient tests for an autoregressive unit root,” Econometrica, 64(4), 813-836.
Enders, W. and P. Jones (2016), “Grain prices, oil prices, and multiple smooth breaks in a VAR,” Studies in Nonlinear Dynamics & Econometrics, 20(4), 399-419.
Genesove, D. and C. Mayer (2001), “Loss aversion and seller behavior: evidence from the housing market,” The Quarterly Journal of Economics, 116(4), 1233-1260.
Goupillaud, P., A. Grossmann, and J. Morlet (1984), “Cycle-octave and related transforms in seismic signal analysis,” Geoexploration, 23(1), 85-102.
Hacker, R. S., and A. Hatemi-J (2006), “Tests for causality between integrated variables using asymptotic and bootstrap distributions: theory and application,”
Applied Economics, 38(13), 1489-1500.
Hatemi-J, A. (2002), “Export performance and economic growth nexus in Japan: a bootstrap approach,” Japan and the World Economy, 14(1), 25-33.
Hort, K. (2000), “Prices and turnover in the market for owner-occupied homes,” Regional Science and Urban Economics, 30, 99-119.
Kirikkaleli, D. (2019), “Time-frequency dependency of financial risk and economic risk: evidence from Greece,” Journal of Economic Structures, 8(1), 1-10.
Kirikkaleli, D. (2020), “Does political risk matter for economic and financial risks in Venezuela?” Journal of Economic Structures, 9(1), 1-10.
Kirikkaleli, D. and H. Güngör (2021), “Co-movement of commodity price indexes and energy price index: a wavelet coherence approach,” Financial Innovation, 7(1), 1-18.
Kwiatkowski, D., P. C. Phillips, P. Schmidt, and Y. Shin (1992), “Testing the null hypothesis of stationarity against the alternative of a unit root: How sure are we that economic time series have a unit root?” Journal of Econometrics, 54(1-3), 159-178.
Li, L. H. and K. S. Cheung (2017), “Housing price and transaction intensity correlation in Hong Kong : implications for government housing policy,” Journal
of Housing and the Built Environment, 32(2), 269-287.
Lütkepohl, H. (2005), “New introduction to multiple time series analysis,” Springer Science and Business Media, 103-320.
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dc.identifier.doi (DOI) 10.6814/NCCU202200566en_US