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題名 百度指數對中國大陸房地產價格之解釋能力分析
An empirical study of explanatory power for house price by Baidu Index in China作者 劉激揚
Liu, Ji-Yang貢獻者 陳明吉
Chen, Ming-Chi
劉激揚
Liu, Ji-Yang關鍵詞 有限關注
房價
百度指數
Limited attention
House price
Baidu index日期 2018 上傳時間 17-Jul-2018 11:25:24 (UTC+8) 摘要 本文從有限關注理論出發，探索以百度指數為注意力的代理變量對中國大陸房地產價格走勢的解釋能力。本文先選取了2011年—2017年全國月度房價指數數據與百度指數數據，並採用前一期房地產價格、土地價格、股票指數、廣義貨幣供應量增長率等因子作為控制變量，利用多元回歸模型進行分析，探索不同百度指數關鍵字對房價的解釋能力和方向。本研究發現全國範圍下百度指數中，房產仲介類關鍵字對未來一期房價指數有正向解釋效果。接著，本文提出不同規模、不同地域的城市由於其居民構成和房價差異化等原因，可能使得不同關鍵字之百度指數的解釋能力出現差別。本文選取42個不同規模城市之月度數據，按照“一二三線”和“東中西部”城市進行分組面板回歸，實證發現，“房市”關鍵字之百度指數僅對一線城市及東部城市有解釋能力，房地產調控類關鍵字在一二線及東部城市具有解釋能力，“房貸計算器”一、二線城市及東中部地區城市有解釋能力，而房產仲介類關鍵字僅在東中部三線城市有解釋能力。不同關鍵字之百度指數在不同地區的解釋能力確實存在差異，並可以被注意力理論解釋。
The study is based on the limited attention theory, and aiming to explore if the Baidu Index as the agent variable of attention can explain the future trend of real estate price in mainland China. We first collect the monthly data of national house price index and Baidu index from 2011 to 2017, then analyze the data by multiple regression model using previous land price, stock index, money supply and other factors as control variables. The empirical result shows that the index of “realtor” keyword lagged 1 period has explanatory power for future house prices. After that, this paper puts forward the assumption that the explanatory power of different keywords Baidu index may differ in cities of different scales or locations due to the compositions of residents and the difference in house price. We go further to 42 cities of different scales and locations and conducts group panel regression. In aspect of the scale, it’s empirically found that except the significant correlation between the index of keyword “house market” and the price of Tier 1 cities, the indexes of real estate policy keyword and “mortgage calculator” can also explain house price for Tier 1 and Tier 2 cities, while the “realtor” keyword can merely explain the house price of Tier 3 cities. Take location into consideration, we find that the indexes of “market” and policy only have explanatory ability in eastern area, while the indexes of “mortgage calculator” and “realtor” have explanatory ability in eastern and central area. It’s proved that Baidu Index can explain some change in future house price.參考文獻 刁節文、韓瑜，2012，我國資產價格波動與貨幣政策選擇研究，經濟問題探索, 2012年第 11期：37-41王萬霞，2018，我國房地產市場調控政策研究，經濟法界，2018年第2期：118-121況偉大，2005，房價與地價關係研究:模型及中國數據檢驗.財貿經濟，2005第11期：56-63邵新建、巫和懋、江萍、薛熠、王勇，2012，中國城市房價的“堅硬泡沫”——基于壟斷性土地市場的研究，金融研究，2012年第12期：67-81余華義、 陳東，2009，中國地價、利率與房價的關聯性研究，經濟評論 ，2009年4期：41-88林曉虹，2014，M2增量的變化與房地產價格波幅的關係——理論與實證，華東師範大學產業經濟學碩士論文蔡怡純、陳明吉，2004，台北地區住宅市場結構性轉變與價格均衡調整，都市與計劃，第31卷，第4期：365-390陳崇，2011，房地產價格波動及其宏觀效應研究，南京大學理論經濟學系博士論文崔光燦，2009，房地產價格與宏觀經濟互動關係實證研究——基於我國31個省面板數據研究，經濟理論與經濟管理，2009年第1期：57-62梁雲芳、高鐵梅，2006，我國商品住宅銷售價格波動成因的實證分析，管理世界，2006年第8期:76-82董志勇、官皓、明艷，2010，房地產價格影響因素分析 : 基於中國各省市的面板數據的實證研究，中國地質大學學報 (社會科學版)：98-103範新英、 張所地，2013，基于時變參數和VAR模型的土地政策和貨幣政策對房價影響作用機制研究，經濟經緯 ，2013年4期：88-93趙嬌，2013，有限關注與我國上市公司股票價格——基於百度指數的實證研究，浙江財經大學金融學碩士論文劉姣姣，2015，我國房地產一手房和二手房市場關聯性研究——以北京市為例，重慶大學建設管理與房地產學院工程碩士學位論文Barber, B.M., Odean, T., 2008, All that glitters: The effect of attention and news on the buying behavior of individual and institutional investors, Review of Financial Studies, Vol.2008(2):785-818Beracha, E. and Wintoki, M.B., 2013, Forecasting residential real estate price changes from online research activity, Journal of Real Estate Research, Vol.35, No.3:283-312Case, K.E. and Shiller, R.J., 1990, “Forecasting pries and excess returns in the housing market”, AREUEA Journal, Vol.18:253 -273Case, K.E. and Shiller, R.J.,2003, Is there a bubble in the housing market brookings ，Economic Activity, Vol.2003, No. 2 (2003):299-342Campbell, J., Lettau, M., Malkiel, B. and Xu, Y., 2001. Have individual stocks become more volatile? An empirical exploration of idiosyncratic risk. Journal of Finance, Vol.56:1-43Chen, M.C., Chang, C.O., Yang, C.Y. and Hsieh, B.M., 2012, Investment demand and housing prices in emerging economy, Journal of Real Estate Research, Vol.34, No.3:345-373Chen, M.C. and Patel, K., 2002, An empirical analysis of determination of housing prices in the Taipei area, Taiwan Economic Review, Vol.30(4): 563-595Clapp, J.M. and Giaccotto, C., 1994, “The influence of economic variables on local house price dynamics”, Journal of Urban Economics, Vol.36:161-183Chemmanur, T. and Yan, A., 2009, “Advertising, attention, and stock returns, Working paper, Boston College and Fordham UniversityChen, N.K., 2001, Asset price fluctuations in Taiwan: Evidence from stock and real estate prices 1973 to1992.Journal of Asian Economics, Vol.12(2001):215 -232.Da, Z., Engelberg, J. and Gao, P., In search of attention, Journal of Finance, (2011):1461-1499Deniela, K, Hirshleifer, D. and Hong Teoh, S.,2002, Investor psychology in capital markets: Evidence and policy implications, Proceeding for Carnegie/Rochester conference series in public policy at the University of Rochester, Northwestern University, National Bureau of Economic Research, The Ohio State University, April 2011.Hou, K., Peng, L. and Xiong, W., 2008, A tale of two anomalies: The implication of investor attention for price and earnings momentum, Working paper, Ohio State University, Baruch Colliege, and Princeton UniversityKahneman, D.1973, Attention and effort, Englewood Cliffs. NJ: Prentice-HallKlemolaa, Antti., Nikkinena, Jussi. and Peltomakib, Jarkko., 2016, Changes in investors’ market attention and near-term stock market returns, Journal of Behavioral Finance Vol.17, No.1:18-30Klibanoff, P., Lamont O. and T. A. Wizman, 1999, Investor reaction to salient news in closed-end country funds, Journal of Finance, Vol.53:673-699.Longstaff. Pedro Santa-Clara. and Eduardo S. Schwartz ,1999, Throwing Away a Billion Dollars: The Cost of Suboptimal Exercise Strategies in the Swaption Market, Journal of Financial Economics, Vol.62 (2001):39-66Mankiw, N.G. and Weil, D.N., 1989, “The Baby Boom, the Baby Bust and the Housing Market”, Regional Science and Urban Economics, Vol.19:235 -258.Peng, L. and Xiong, W., 2006, Investor attention, overconfidence and category learning, Journal of Financial Economics, Vol.80 (2006) :563–602Poterba, JM., Weil, DN., and Shiller, R .1991, House price dynamics: the role of tax policy and demography, Brookings Papers on Economic Activity:143-202Pedro, L., Ramos, S. B. and Veiga, H., 2013, working paper, Universidad Carlos III de MadridTsai, I. C. and Chen, M. C., 2013, Asymmetric Correlation and Difference between the Volatility of Housing and Stock Price Indexes: Analysis Based on the Threshold Volatility and Cointegration Model，Journal of Financial Studies，Vol.21, Issue 4:25-57Thaler, R., Mental accounting and consumer choice, Marketing Science Vol.4, No. 3 (Summer, 1985):199-214Wu, L. and Brynjolfsson, E,2015, The Future of Prediction: How Google Searches Foreshadow Housing Prices and Sales, Economic Analysis of the Digital Economy, University of Chicago Press: 89-118 描述 碩士
國立政治大學
財務管理學系
105357035資料來源 http://thesis.lib.nccu.edu.tw/record/#G1053570351 資料類型 thesis dc.contributor.advisor 陳明吉 zh_TW dc.contributor.advisor Chen, Ming-Chi en_US dc.contributor.author (Authors) 劉激揚 zh_TW dc.contributor.author (Authors) Liu, Ji-Yang en_US dc.creator (作者) 劉激揚 zh_TW dc.creator (作者) Liu, Ji-Yang en_US dc.date (日期) 2018 en_US dc.date.accessioned 17-Jul-2018 11:25:24 (UTC+8) - dc.date.available 17-Jul-2018 11:25:24 (UTC+8) - dc.date.issued (上傳時間) 17-Jul-2018 11:25:24 (UTC+8) - dc.identifier (Other Identifiers) G1053570351 en_US dc.identifier.uri (URI) http://nccur.lib.nccu.edu.tw/handle/140.119/118696 - 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) 105357035 zh_TW dc.description.abstract (摘要) 本文從有限關注理論出發，探索以百度指數為注意力的代理變量對中國大陸房地產價格走勢的解釋能力。本文先選取了2011年—2017年全國月度房價指數數據與百度指數數據，並採用前一期房地產價格、土地價格、股票指數、廣義貨幣供應量增長率等因子作為控制變量，利用多元回歸模型進行分析，探索不同百度指數關鍵字對房價的解釋能力和方向。本研究發現全國範圍下百度指數中，房產仲介類關鍵字對未來一期房價指數有正向解釋效果。接著，本文提出不同規模、不同地域的城市由於其居民構成和房價差異化等原因，可能使得不同關鍵字之百度指數的解釋能力出現差別。本文選取42個不同規模城市之月度數據，按照“一二三線”和“東中西部”城市進行分組面板回歸，實證發現，“房市”關鍵字之百度指數僅對一線城市及東部城市有解釋能力，房地產調控類關鍵字在一二線及東部城市具有解釋能力，“房貸計算器”一、二線城市及東中部地區城市有解釋能力，而房產仲介類關鍵字僅在東中部三線城市有解釋能力。不同關鍵字之百度指數在不同地區的解釋能力確實存在差異，並可以被注意力理論解釋。 zh_TW dc.description.abstract (摘要) The study is based on the limited attention theory, and aiming to explore if the Baidu Index as the agent variable of attention can explain the future trend of real estate price in mainland China. We first collect the monthly data of national house price index and Baidu index from 2011 to 2017, then analyze the data by multiple regression model using previous land price, stock index, money supply and other factors as control variables. The empirical result shows that the index of “realtor” keyword lagged 1 period has explanatory power for future house prices. After that, this paper puts forward the assumption that the explanatory power of different keywords Baidu index may differ in cities of different scales or locations due to the compositions of residents and the difference in house price. We go further to 42 cities of different scales and locations and conducts group panel regression. In aspect of the scale, it’s empirically found that except the significant correlation between the index of keyword “house market” and the price of Tier 1 cities, the indexes of real estate policy keyword and “mortgage calculator” can also explain house price for Tier 1 and Tier 2 cities, while the “realtor” keyword can merely explain the house price of Tier 3 cities. Take location into consideration, we find that the indexes of “market” and policy only have explanatory ability in eastern area, while the indexes of “mortgage calculator” and “realtor” have explanatory ability in eastern and central area. It’s proved that Baidu Index can explain some change in future house price. en_US dc.description.tableofcontents 第一章 緒論 1第一節 研究背景與動機 1第二節 研究目的 4第三節 研究流程 5第二章 文獻探討 6第一節 有限關注理論 6第二節 房地產價格的影響因素 11第三章 研究方法 14第一節 研究架構 14第二節 模型建立 21第三節 資料描述 24第四章 實證分析結果 25第一節 敘述性統計 25第二節 全國範圍的百度指數解釋能力分析 27第三節 面板模型下不同城市的百度指數解釋能力分析 32第五章 結論與建議 41參考文獻 44 zh_TW dc.format.extent 5335072 bytes - dc.format.mimetype application/pdf - dc.source.uri (資料來源) http://thesis.lib.nccu.edu.tw/record/#G1053570351 en_US dc.subject (關鍵詞) 有限關注 zh_TW dc.subject (關鍵詞) 房價 zh_TW dc.subject (關鍵詞) 百度指數 zh_TW dc.subject (關鍵詞) Limited attention en_US dc.subject (關鍵詞) House price en_US dc.subject (關鍵詞) Baidu index en_US dc.title (題名) 百度指數對中國大陸房地產價格之解釋能力分析 zh_TW dc.title (題名) An empirical study of explanatory power for house price by Baidu Index in China en_US dc.type (資料類型) thesis en_US dc.relation.reference (參考文獻) 刁節文、韓瑜，2012，我國資產價格波動與貨幣政策選擇研究，經濟問題探索, 2012年第 11期：37-41王萬霞，2018，我國房地產市場調控政策研究，經濟法界，2018年第2期：118-121況偉大，2005，房價與地價關係研究:模型及中國數據檢驗.財貿經濟，2005第11期：56-63邵新建、巫和懋、江萍、薛熠、王勇，2012，中國城市房價的“堅硬泡沫”——基于壟斷性土地市場的研究，金融研究，2012年第12期：67-81余華義、 陳東，2009，中國地價、利率與房價的關聯性研究，經濟評論 ，2009年4期：41-88林曉虹，2014，M2增量的變化與房地產價格波幅的關係——理論與實證，華東師範大學產業經濟學碩士論文蔡怡純、陳明吉，2004，台北地區住宅市場結構性轉變與價格均衡調整，都市與計劃，第31卷，第4期：365-390陳崇，2011，房地產價格波動及其宏觀效應研究，南京大學理論經濟學系博士論文崔光燦，2009，房地產價格與宏觀經濟互動關係實證研究——基於我國31個省面板數據研究，經濟理論與經濟管理，2009年第1期：57-62梁雲芳、高鐵梅，2006，我國商品住宅銷售價格波動成因的實證分析，管理世界，2006年第8期:76-82董志勇、官皓、明艷，2010，房地產價格影響因素分析 : 基於中國各省市的面板數據的實證研究，中國地質大學學報 (社會科學版)：98-103範新英、 張所地，2013，基于時變參數和VAR模型的土地政策和貨幣政策對房價影響作用機制研究，經濟經緯 ，2013年4期：88-93趙嬌，2013，有限關注與我國上市公司股票價格——基於百度指數的實證研究，浙江財經大學金融學碩士論文劉姣姣，2015，我國房地產一手房和二手房市場關聯性研究——以北京市為例，重慶大學建設管理與房地產學院工程碩士學位論文Barber, B.M., Odean, T., 2008, All that glitters: The effect of attention and news on the buying behavior of individual and institutional investors, Review of Financial Studies, Vol.2008(2):785-818Beracha, E. and Wintoki, M.B., 2013, Forecasting residential real estate price changes from online research activity, Journal of Real Estate Research, Vol.35, No.3:283-312Case, K.E. and Shiller, R.J., 1990, “Forecasting pries and excess returns in the housing market”, AREUEA Journal, Vol.18:253 -273Case, K.E. and Shiller, R.J.,2003, Is there a bubble in the housing market brookings ，Economic Activity, Vol.2003, No. 2 (2003):299-342Campbell, J., Lettau, M., Malkiel, B. and Xu, Y., 2001. Have individual stocks become more volatile? An empirical exploration of idiosyncratic risk. Journal of Finance, Vol.56:1-43Chen, M.C., Chang, C.O., Yang, C.Y. and Hsieh, B.M., 2012, Investment demand and housing prices in emerging economy, Journal of Real Estate Research, Vol.34, No.3:345-373Chen, M.C. and Patel, K., 2002, An empirical analysis of determination of housing prices in the Taipei area, Taiwan Economic Review, Vol.30(4): 563-595Clapp, J.M. and Giaccotto, C., 1994, “The influence of economic variables on local house price dynamics”, Journal of Urban Economics, Vol.36:161-183Chemmanur, T. and Yan, A., 2009, “Advertising, attention, and stock returns, Working paper, Boston College and Fordham UniversityChen, N.K., 2001, Asset price fluctuations in Taiwan: Evidence from stock and real estate prices 1973 to1992.Journal of Asian Economics, Vol.12(2001):215 -232.Da, Z., Engelberg, J. and Gao, P., In search of attention, Journal of Finance, (2011):1461-1499Deniela, K, Hirshleifer, D. and Hong Teoh, S.,2002, Investor psychology in capital markets: Evidence and policy implications, Proceeding for Carnegie/Rochester conference series in public policy at the University of Rochester, Northwestern University, National Bureau of Economic Research, The Ohio State University, April 2011.Hou, K., Peng, L. and Xiong, W., 2008, A tale of two anomalies: The implication of investor attention for price and earnings momentum, Working paper, Ohio State University, Baruch Colliege, and Princeton UniversityKahneman, D.1973, Attention and effort, Englewood Cliffs. NJ: Prentice-HallKlemolaa, Antti., Nikkinena, Jussi. and Peltomakib, Jarkko., 2016, Changes in investors’ market attention and near-term stock market returns, Journal of Behavioral Finance Vol.17, No.1:18-30Klibanoff, P., Lamont O. and T. A. Wizman, 1999, Investor reaction to salient news in closed-end country funds, Journal of Finance, Vol.53:673-699.Longstaff. Pedro Santa-Clara. and Eduardo S. Schwartz ,1999, Throwing Away a Billion Dollars: The Cost of Suboptimal Exercise Strategies in the Swaption Market, Journal of Financial Economics, Vol.62 (2001):39-66Mankiw, N.G. and Weil, D.N., 1989, “The Baby Boom, the Baby Bust and the Housing Market”, Regional Science and Urban Economics, Vol.19:235 -258.Peng, L. and Xiong, W., 2006, Investor attention, overconfidence and category learning, Journal of Financial Economics, Vol.80 (2006) :563–602Poterba, JM., Weil, DN., and Shiller, R .1991, House price dynamics: the role of tax policy and demography, Brookings Papers on Economic Activity:143-202Pedro, L., Ramos, S. B. and Veiga, H., 2013, working paper, Universidad Carlos III de MadridTsai, I. C. and Chen, M. C., 2013, Asymmetric Correlation and Difference between the Volatility of Housing and Stock Price Indexes: Analysis Based on the Threshold Volatility and Cointegration Model，Journal of Financial Studies，Vol.21, Issue 4:25-57Thaler, R., Mental accounting and consumer choice, Marketing Science Vol.4, No. 3 (Summer, 1985):199-214Wu, L. and Brynjolfsson, E,2015, The Future of Prediction: How Google Searches Foreshadow Housing Prices and Sales, Economic Analysis of the Digital Economy, University of Chicago Press: 89-118 zh_TW dc.identifier.doi (DOI) 10.6814/THE.NCCU.Finance.017.2018.F07 -
