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題名 褐皮書是否會驅動建築投資?
Does the Beige Book Move Construction Investment?
作者 陳盈臻
Chen, Ying-Jhen
貢獻者 陳明吉
Chen, Ming-Chi
陳盈臻
Chen, Ying-Jhen
關鍵詞 文字探勘
情緒分析
房地產市場
褐皮書
情緒指數
Text mining
Sentiment analysis
Real estate market
Beige Book
Sentiment index
日期 2019
上傳時間 7-Aug-2019 16:05:03 (UTC+8)
摘要 The main purpose of this thesis was to explore whether the information in the important government documents could be applied in the real estate market. We used 160 Beige Books from January 1998 to December 2017 as our research materials, which were one of the representative official documents of the United States. We constructed a sentiment index based on the content of the Beige Book by text mining and lexicon-based approach for sentiment analysis. The sentiment index is the main factor that may affect real estate market, as we observed. The representative real estate market indicators included dependent variables, such as house prices, construction output, building permits and real estate stocks, and some macroeconomic data as control variables, such as unemployment rate, population, mortgage interest rate and personal income. The results showed that the sentiment index of the Beige Book was positively associated with changes in housing prices, construction output and building permits, that in particular, the current sentiment variables had a more significant impact on those real estate market indicators. However, the sentiment index of the Beige Book was not significantly associated with changes in S&P 500 Real Estate, in which the reason might be that S&P 500 Real Estate was only representing one sector of S&P 500; thus, we believed that real estate stocks would be more affected by variables relevant to the stock market. In this thesis, we found the Beige Book as a market sentiment index, which not only influenced the direction of monetary policy, but also impacted the real estate market.
參考文獻 Akerlof, G. A., & Shiller, R. J. (2010). Animal Spirits. Princeton: NJ: Princeton University Press.
Armesto, M. T., Hernández‐Murillo, R., Owyang, M. T., & Piger, J. (2009). Measuring the Information Content of the Beige Book: A Mixed Data Sampling Approach. Journal of Money,Credit and Banking, 41(1), 35-55.
Baffoe-Bonnie, J. (1998). The Dynamic Impact of Macroeconomic Aggregates on Housing Prices and Stock of Houses: A National and Regional Analysis. The Journal of Real Estate Finance and Economics, 17(2), 179-197.
Baker, M., & Wurgler, J. (2007). Investor Sentiment in the Stock Market. Journal of Economic Perspectives, 21(2), 129-152.
Balke, N. S., Fulmer, M., & Zhang, R. (2016). Incorporating the Beige Book into a Quantitative Index of Economic Activity. Journal of Forecasting, 36(5), 497-514.
Balke, N. S., & Petersen, D. A. (2002). How Well Does the Beige Book Reflect Economic Activity? Evaluating Qualitative Information Quantitatively Journal of Money, Credit and Banking, 34(1), 114-136.
Balke, N. S., & Yücel, M. K. (2000). Evaluating the Eleventh District`s Beige Book. Federal Reserve Bank of Dallas Economic and Financial Review, 4(2-9).
Bjørnland, H. C., & Jacobsen, D. H. (2010). The role of house prices in the monetary policy transmission mechanism in small open economies. Journal of Financial Stability, 6, 218-229.
Capozza, D. R., Hendershott, P. H., Mack, C., & Mayer, C. J. (2002). Determinants of Real House Price Dynamics.
Chen, M.-C., & Patel, K. (2002). An empirical analysis of determination of house prices in the Taipei area. Taiwan Economic Review, 30(4), 563-595.
Chen, M.-C., Tsai, I.-C., & Chang, C.-O. (2007). House prices and household income: Do they move apart? Evidence from Taiwan. Habitat International, 31(2), 243-256.

Clayton, J., Ling, D. C., & Naranjo, A. (2009). Commercial Real Estate Valuation: Fundamentals Versus Investor Sentiment. The Journal of Real Estate Finance and Economics, 38(1), 5-37.
Collomb, A. ı., Costea, C., Joyeux, D., Hasan, O., & Brunie, L. (2014). A Study and Comparison of Sentiment Analysis Methods for Reputation Evaluation. Rapport de recherche RR-LIRIS-2014-002.
Fenzl, T., & Pelzmann, L. (2012). Psychological and Social Forces Behind Aggregate Financial Market Behavior. Journal of Behavioral Finance, 13(1), 56-65.
Grebler, L., & Mittelbach, F. G. (1979). The Inflation of House Prices, its Extent, Causes, and Consequences
Hanley, K. W., & Hoberg, G. (2010). The Information Content of IPO Prospectuses. The Review of Financial Studies, 23(7), 2821-2864.
Hendershott, P. H., & Abraham, J. M. (1992). Patterns and Determinants of Metropolitan House Prices, 1977 to 1991. L.E. Browne, E.S. Rosengren (Eds.), Real Estate and the Credit Crunch, Federal Reserve Bank of Boston, Boston(36), 18-42.
Keynes, J. (1936). The General Theory of Employment, Interest and Money. Palgrave Macmillan.
Lai, R. N., & Order, R. A. V. (2010). Momentum and House Price Growth in the United States: Anatomy of a Bubble. Real Estate Economics, 38(4), 753-773.
Lee, M.-H., Chen, W.-T., & Peng, C.-W. (2014). Fundamental House Prices and Bubbles in Asian Cities. City and Planning, 41(2), 169-198.
Levin, A., Chien-FuLin, & Chu, C.-S. J. (2002). Unit root tests in panel data: asymptotic and finite-sample properties. Journal of Econometrics, 108(1), 1-24.
Loughran, T., & Mcdonald, B. (2014). Measuring Readability in Financial Disclosures. The Journal of Finance, 69(4), 1643-1671.
Mahalik, M. K., & Mallick, H. (2016). Are house prices guided by fundamentals or speculative factors? An empirical inquiry for India Int. J. Economic Policy in Emerging Economies, 9(1).
Marcato, G., & Nanda, A. (2016). Information Content and Forecasting Ability of Sentiment indicators: Case of Real Estate Market. Journal of Real Estate Research, 38(2), 165-203.
Meen, G. P. (1990). The Removal of Mortgage Market Constraints and the Implications for Econometric Modelling of UK House Prices. Oxford Bulletin Economics and Statistics, 52(1), 1-23.
Meen, G. P. (1993). The Treatment of House Prices in Macroeconometric Models: A Compariosn Exercise. Department of Environment Discussion Paper.
Payne, D. R. (2001). Anticipating Monetary Policy with the Federal Reserve`s Beige Book: Re-specifying the Taylor Rule. Business Economics, 36(1), 21-30.
Reichert, A. K. (1990). The Impact of Interest Rates, Income, and Employment upon Regional Housing Prices. The Journal of Real Estate Finance and Economics, 3(4), 373-391.
Sadique, S., In, F., Veeraraghavan, M., & Wachtel, P. (2013). Soft information and economic activity: Evidence from the Beige Book. Journal of Macroeconomics, 37, 81-92.
Sentiment Analysis: Nearly Everything You Need to Know (n.d.). Retrieved June 18, 2019, from https://monkeylearn.com/sentiment-analysis/
Summary of Commentary on Current Economic Conditions by Federal Reserve District (2019), from https://www.federalreserve.gov/monetarypolicy/beige-book-default.htm
Tsolacos, S. (2012). The Role of Sentiment Indicators for Real Estate Market Forecasting Journal of European Real Estate Research, 5(2), 109-120.
Tetlock, P. C., Saar‐Tsechansky, M., & Macskassy, S. (2008). More Than Words: Quantifying Language to Measure Firms` Fundamentals. The Journal of Finance, 63(3), 1437-1467.
Wang, Z., & Hui, E. C.-m. (2017). Fundamentals and Market Sentiment in Housing Market. Journal Housing, Theory and Society, 34(1), 57-78.
Zavodny, M., & Ginther, D. K. (2005). Does the Beige Book Move Financial Markets. Southern Economic Journal, 72(1), 138-151.
描述 碩士
國立政治大學
財務管理學系
106357026
資料來源 http://thesis.lib.nccu.edu.tw/record/#G0106357026
資料類型 thesis
dc.contributor.advisor 陳明吉zh_TW
dc.contributor.advisor Chen, Ming-Chien_US
dc.contributor.author (Authors) 陳盈臻zh_TW
dc.contributor.author (Authors) Chen, Ying-Jhenen_US
dc.creator (作者) 陳盈臻zh_TW
dc.creator (作者) Chen, Ying-Jhenen_US
dc.date (日期) 2019en_US
dc.date.accessioned 7-Aug-2019 16:05:03 (UTC+8)-
dc.date.available 7-Aug-2019 16:05:03 (UTC+8)-
dc.date.issued (上傳時間) 7-Aug-2019 16:05:03 (UTC+8)-
dc.identifier (Other Identifiers) G0106357026en_US
dc.identifier.uri (URI) http://nccur.lib.nccu.edu.tw/handle/140.119/124700-
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) 106357026zh_TW
dc.description.abstract (摘要) The main purpose of this thesis was to explore whether the information in the important government documents could be applied in the real estate market. We used 160 Beige Books from January 1998 to December 2017 as our research materials, which were one of the representative official documents of the United States. We constructed a sentiment index based on the content of the Beige Book by text mining and lexicon-based approach for sentiment analysis. The sentiment index is the main factor that may affect real estate market, as we observed. The representative real estate market indicators included dependent variables, such as house prices, construction output, building permits and real estate stocks, and some macroeconomic data as control variables, such as unemployment rate, population, mortgage interest rate and personal income. The results showed that the sentiment index of the Beige Book was positively associated with changes in housing prices, construction output and building permits, that in particular, the current sentiment variables had a more significant impact on those real estate market indicators. However, the sentiment index of the Beige Book was not significantly associated with changes in S&P 500 Real Estate, in which the reason might be that S&P 500 Real Estate was only representing one sector of S&P 500; thus, we believed that real estate stocks would be more affected by variables relevant to the stock market. In this thesis, we found the Beige Book as a market sentiment index, which not only influenced the direction of monetary policy, but also impacted the real estate market.en_US
dc.description.tableofcontents 1. Introduction 1
2. Literature Review 5
2.1 The Relation between Macroeconomic Variables and the Real Estate Market 5
2.2 The Relation between Investor Sentiment and the Financial Market 7
2.3 The Relation between Investor Sentiment and the Real Estate Market 7
2.4 The Relation between the Beige Book and the Economy 9
2.5 Text Mining and Sentiment Analysis 11
2.5.1 Definition of Text Mining 11
2.5.2 Sentiment Analysis based on Text Mining 12
2.6 Summary 12
3. Models and Methodology 14
3.1 Conceptual Framework 14
3.2 Models 16
3.2.1 Multiple Regression Model 16
3.2.2 Panel Data Regression Model 18
3.3 Data in The Beige Book 20
3.3.1 The Content of the Beige Book 20
3.3.2 Scoring the Beige Book 21
3.4 Variables and Data 23
3.4.1 The Dependent Variables 23
3.4.2 Other Control Variables 25
3.5 Methodology 29
3.5.1 Unit Root Test 29
3.5.2 Pearson Correlation 29
3.5.3 Collinearity Diagnosis 29
4. Empirical Analysis 30
4.1 Unit Root Test 30
4.2 Pearson Correlation Analysis 32
4.3 The Relation between the Beige Book and Construction Investment 34
4.3.1 The Relation between the Beige Book and Housing Prices 34
4.3.2 The Relation between the Beige Book and Construction Output 38
4.3.3 The Relation between the Beige Book and S&P 500 Real Estate 40
4.3.4 The Relation between the Beige Book and Building Permits 42
4.4 Collinearity Diagnosis 45
5. Conclusion 46
Appendix 49
References 51		zh_TW
dc.format.extent 798567 bytes-
dc.format.mimetype application/pdf-
dc.source.uri (資料來源) http://thesis.lib.nccu.edu.tw/record/#G0106357026en_US
dc.subject (關鍵詞) 文字探勘zh_TW
dc.subject (關鍵詞) 情緒分析zh_TW
dc.subject (關鍵詞) 房地產市場zh_TW
dc.subject (關鍵詞) 褐皮書zh_TW
dc.subject (關鍵詞) 情緒指數zh_TW
dc.subject (關鍵詞) Text miningen_US
dc.subject (關鍵詞) Sentiment analysisen_US
dc.subject (關鍵詞) Real estate marketen_US
dc.subject (關鍵詞) Beige Booken_US
dc.subject (關鍵詞) Sentiment indexen_US
dc.title (題名) 褐皮書是否會驅動建築投資?zh_TW
dc.title (題名) Does the Beige Book Move Construction Investment?en_US
dc.type (資料類型) thesisen_US
dc.relation.reference (參考文獻) Akerlof, G. A., & Shiller, R. J. (2010). Animal Spirits. Princeton: NJ: Princeton University Press.
Armesto, M. T., Hernández‐Murillo, R., Owyang, M. T., & Piger, J. (2009). Measuring the Information Content of the Beige Book: A Mixed Data Sampling Approach. Journal of Money,Credit and Banking, 41(1), 35-55.
Baffoe-Bonnie, J. (1998). The Dynamic Impact of Macroeconomic Aggregates on Housing Prices and Stock of Houses: A National and Regional Analysis. The Journal of Real Estate Finance and Economics, 17(2), 179-197.
Baker, M., & Wurgler, J. (2007). Investor Sentiment in the Stock Market. Journal of Economic Perspectives, 21(2), 129-152.
Balke, N. S., Fulmer, M., & Zhang, R. (2016). Incorporating the Beige Book into a Quantitative Index of Economic Activity. Journal of Forecasting, 36(5), 497-514.
Balke, N. S., & Petersen, D. A. (2002). How Well Does the Beige Book Reflect Economic Activity? Evaluating Qualitative Information Quantitatively Journal of Money, Credit and Banking, 34(1), 114-136.
Balke, N. S., & Yücel, M. K. (2000). Evaluating the Eleventh District`s Beige Book. Federal Reserve Bank of Dallas Economic and Financial Review, 4(2-9).
Bjørnland, H. C., & Jacobsen, D. H. (2010). The role of house prices in the monetary policy transmission mechanism in small open economies. Journal of Financial Stability, 6, 218-229.
Capozza, D. R., Hendershott, P. H., Mack, C., & Mayer, C. J. (2002). Determinants of Real House Price Dynamics.
Chen, M.-C., & Patel, K. (2002). An empirical analysis of determination of house prices in the Taipei area. Taiwan Economic Review, 30(4), 563-595.
Chen, M.-C., Tsai, I.-C., & Chang, C.-O. (2007). House prices and household income: Do they move apart? Evidence from Taiwan. Habitat International, 31(2), 243-256.

Clayton, J., Ling, D. C., & Naranjo, A. (2009). Commercial Real Estate Valuation: Fundamentals Versus Investor Sentiment. The Journal of Real Estate Finance and Economics, 38(1), 5-37.
Collomb, A. ı., Costea, C., Joyeux, D., Hasan, O., & Brunie, L. (2014). A Study and Comparison of Sentiment Analysis Methods for Reputation Evaluation. Rapport de recherche RR-LIRIS-2014-002.
Fenzl, T., & Pelzmann, L. (2012). Psychological and Social Forces Behind Aggregate Financial Market Behavior. Journal of Behavioral Finance, 13(1), 56-65.
Grebler, L., & Mittelbach, F. G. (1979). The Inflation of House Prices, its Extent, Causes, and Consequences
Hanley, K. W., & Hoberg, G. (2010). The Information Content of IPO Prospectuses. The Review of Financial Studies, 23(7), 2821-2864.
Hendershott, P. H., & Abraham, J. M. (1992). Patterns and Determinants of Metropolitan House Prices, 1977 to 1991. L.E. Browne, E.S. Rosengren (Eds.), Real Estate and the Credit Crunch, Federal Reserve Bank of Boston, Boston(36), 18-42.
Keynes, J. (1936). The General Theory of Employment, Interest and Money. Palgrave Macmillan.
Lai, R. N., & Order, R. A. V. (2010). Momentum and House Price Growth in the United States: Anatomy of a Bubble. Real Estate Economics, 38(4), 753-773.
Lee, M.-H., Chen, W.-T., & Peng, C.-W. (2014). Fundamental House Prices and Bubbles in Asian Cities. City and Planning, 41(2), 169-198.
Levin, A., Chien-FuLin, & Chu, C.-S. J. (2002). Unit root tests in panel data: asymptotic and finite-sample properties. Journal of Econometrics, 108(1), 1-24.
Loughran, T., & Mcdonald, B. (2014). Measuring Readability in Financial Disclosures. The Journal of Finance, 69(4), 1643-1671.
Mahalik, M. K., & Mallick, H. (2016). Are house prices guided by fundamentals or speculative factors? An empirical inquiry for India Int. J. Economic Policy in Emerging Economies, 9(1).
Marcato, G., & Nanda, A. (2016). Information Content and Forecasting Ability of Sentiment indicators: Case of Real Estate Market. Journal of Real Estate Research, 38(2), 165-203.
Meen, G. P. (1990). The Removal of Mortgage Market Constraints and the Implications for Econometric Modelling of UK House Prices. Oxford Bulletin Economics and Statistics, 52(1), 1-23.
Meen, G. P. (1993). The Treatment of House Prices in Macroeconometric Models: A Compariosn Exercise. Department of Environment Discussion Paper.
Payne, D. R. (2001). Anticipating Monetary Policy with the Federal Reserve`s Beige Book: Re-specifying the Taylor Rule. Business Economics, 36(1), 21-30.
Reichert, A. K. (1990). The Impact of Interest Rates, Income, and Employment upon Regional Housing Prices. The Journal of Real Estate Finance and Economics, 3(4), 373-391.
Sadique, S., In, F., Veeraraghavan, M., & Wachtel, P. (2013). Soft information and economic activity: Evidence from the Beige Book. Journal of Macroeconomics, 37, 81-92.
Sentiment Analysis: Nearly Everything You Need to Know (n.d.). Retrieved June 18, 2019, from https://monkeylearn.com/sentiment-analysis/
Summary of Commentary on Current Economic Conditions by Federal Reserve District (2019), from https://www.federalreserve.gov/monetarypolicy/beige-book-default.htm
Tsolacos, S. (2012). The Role of Sentiment Indicators for Real Estate Market Forecasting Journal of European Real Estate Research, 5(2), 109-120.
Tetlock, P. C., Saar‐Tsechansky, M., & Macskassy, S. (2008). More Than Words: Quantifying Language to Measure Firms` Fundamentals. The Journal of Finance, 63(3), 1437-1467.
Wang, Z., & Hui, E. C.-m. (2017). Fundamentals and Market Sentiment in Housing Market. Journal Housing, Theory and Society, 34(1), 57-78.
Zavodny, M., & Ginther, D. K. (2005). Does the Beige Book Move Financial Markets. Southern Economic Journal, 72(1), 138-151.		zh_TW
dc.identifier.doi (DOI) 10.6814/NCCU201900558en_US