Please use this identifier to cite or link to this item: https://ah.lib.nccu.edu.tw/handle/140.119/111593
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dc.contributor.advisor林左裕zh_TW
dc.contributor.author張棋茹zh_TW
dc.creator張棋茹zh_TW
dc.date2017en_US
dc.date.accessioned2017-07-31T03:35:54Z-
dc.date.available2017-07-31T03:35:54Z-
dc.date.issued2017-07-31T03:35:54Z-
dc.identifierG0104266009en_US
dc.identifier.urihttp://nccur.lib.nccu.edu.tw/handle/140.119/111593-
dc.description碩士zh_TW
dc.description國立政治大學zh_TW
dc.description應用經濟與社會發展英語碩士學位學程(IMES)zh_TW
dc.description104266009zh_TW
dc.description.abstractAccording to the previous literatures and news, the housing price in China has been increasing dramatically and resulted in some problems. This study estimate six regions’ housing price bubbles including Shanghai, Beijing, Guangzhou, Shenzhen, Chongqing and Wuhan. First, this study uses some basic analysis to explore the data such as, descriptive statistical analysis, correlation analysis, unit root test and Granger Causality test. Second, this research measures the impact of macroeconomic indicators on these six regions using State Space model, that is, whether these six regions have a housing price bubble or not.\nThis study uses macroeconomic indicators to investigate Shanghai, Beijing, Guangzhou, Shenzhen, Chongqing and Wuhan housing price bubbles. Choosing six regions of China’s housing price index and nine independent variables from 2005 Q3 to 2016 Q4 in this research. First, this study separates each region with different macroeconomics indices to estimate the significant of the housing price. Second, through many tests and found out the best models with the housing price bubbles in six regions. \nThis study concludes that there are various significant relationship evidences for each region and it has different variables affect the housing price. The results of State Space model show, Beijing and Guangzhou suggest higher hosing price bubbles and need to strengthen control to avoid more housing bubbles.zh_TW
dc.description.tableofcontentsChapter 1 Introduction 1\n1.1 General Background and Research Motivation 1\n1.2 Research Purpose 6\n1.3 Research Process 6\nChapter 2 Literature Review 8\n2.1 House Price 8\n2.2 China’s House Price 9\n2.3 House Bubble 12\n2.4 Variables Selection 13\nChapter 3 Research Method and Data Information 16\n3.1 Research Method 16\n3.2 Variable and Data Information 18\n3.3 Descriptive Statistics Analysis 24\n3.4 Correlation Analysis 25\n3.5 Unit Root Test 27\n3.6 Granger Causality Test 28\nChapter 4 Empirical Results 32\n4.1 Results of Shanghai 32\n4.2 Results of Beijing 34\n4.3 Results of Guangzhou 36\n4.4 Results of Shenzhen 38\n4.5 Results of Chongqing 40\n4.6 Results of Wuhan 42\nChapter 5 Conclusions and Suggestions 45\n5.1 Conclusions 45\n5.2 Suggestions 47\nReference 48zh_TW
dc.format.extent1088492 bytes-
dc.format.mimetypeapplication/pdf-
dc.source.urihttp://thesis.lib.nccu.edu.tw/record/#G0104266009en_US
dc.subject中國大陸房價zh_TW
dc.subject總體經濟指標zh_TW
dc.subject狀態空間模型zh_TW
dc.subjectChina’s Housing Price Bubbleen_US
dc.subjectMacroeconomic Indicesen_US
dc.subjectState Space modelen_US
dc.title以總體經濟指標探討中國大陸房價之泡沫化現象zh_TW
dc.titleUsing macroeconomic indices to explore housing price bubbleen_US
dc.typethesisen_US
dc.relation.reference許易民 (2012)。中國大陸房價泡沫可能破滅問題之探討。經濟研究,12,387-412。 \n趙永祥、吳依正 (2014)。後全球金融危機中國大陸房市是否有泡沫化危機?。華人經濟研究。12(1),169-187。 \n林祖嘉 (2011)。中國大陸房價泡沫與總體經濟的因果關係。國家政策研究基金會。\n林左裕 (2012)。貨幣政策與房價的關係。行政院國家科學委員會專題研究計畫 成果報告。 \n林左裕 (2013)。中國錢荒潛藏金融風暴。先探投資周刊。1738,84-85。\n汪新、謝昌浩(2010) 。我國房價的宏觀經濟影響因素分析-基於PLS方法的實證研究,《華東經濟管理》,第24卷第3期,頁53-57。 \n台玉紅、苗苗、張潔 (2010) 。我國房地產泡沫測度——基于京、津、滬、渝四直轄市的實證研究。《華東經濟管理》,2010年第3期,頁58-62。 \n\nWebsite Reference\nInternational Monetary Fund (2016), January 2016, Challenges of the " IMF Global Housing Watch Quarterly Update". Retrieved from http://www.imf.org/external/research/housing/report/pdf/0116.pdf \n\nEnglish reference\nAdams, Z., & Füss, R. (2010). Macroeconomic determinants of International housing markets. Journal of Housing Economics, 19(1), 38-50.\nBelke, A., & Wiedmann, M. (2005). Boom or bubble in the US real estate market?. Intereconomics, 40(5), 273-284.\nBlack, A., Fraser, P., & Hoesli, M. (2006). House prices, fundamentals and bubbles. Journal of Business Finance & Accounting, 33(9‐10), 1535-1555.\nBourassa, S. C., Hendershott, P. H., & Murphy, J. (2001). Further evidence on the existence of housing market bubbles. Journal of Property Research, 18(1), 1-19.\nCase, K. E., & Shiller, R. J. (2003). Is there a bubble in the housing market?. Brookings Papers on Economic Activity, 2003(2), 299-342.\nChivakul, M., Lam, W. R., Liu, X., Maliszewski, W. S., & Schipke, A. (2015). Understanding residential real estate in China, IMF Working Paper.\nCourchane, M. J., & Holmes, C. (2014). Bubble, Bubble–Is there House Price Trouble--in Canada?. International Real Estate Review, 17(1), 109-135.\nFernández-Kranz, D., & Hon, M. T. (2006). A cross-section analysis of the income elasticity of housing demand in Spain: Is there a real estate bubble?. The Journal of Real Estate Finance and Economics, 32(4), 449-470.\nFraser, P., Hoesli, M., & McAlevey, L. (2008). House prices and bubbles in New Zealand. The Journal of Real Estate Finance and Economics, 37(1), 71-91.\nGlaeser, E. L., Gyourko, J., & Saiz, A. (2008). Housing supply and housing bubbles. Journal of urban Economics, 64(2), 198-217.\nGoodman, A. C., & Thibodeau, T. G. (2008). Where are the speculative bubbles in US housing markets?. Journal of Housing Economics, 17(2), 117-137.\nHott, C., & Monnin, P. (2008). Fundamental real estate prices: An empirical estimation with international data. The Journal of Real Estate Finance and Economics, 36(4), 427-450.\nHui, E. C., & Yue, S. (2006). Housing price bubbles in Hong Kong, Beijing and Shanghai: a comparative study. The Journal of Real Estate Finance and Economics, 33(4), 299-327.\nJin, Y., & Zeng, Z. (2004). Residential investment and house prices in a multi-sector monetary business cycle model. Journal of Housing Economics, 13(4), 268-286.\nMikhed, V., & Zemčík, P. (2009). Do house prices reflect fundamentals? Aggregate and panel data evidence. Journal of Housing Economics, 18(2), 140-149.\nZhang, C. (2015). Income inequality and access to housing: Evidence from China. China Economic Review, 36, 261-271.zh_TW
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