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FEAR Index, city characteristics, and housing returns

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  • Ramya Rajajagadeesan Aroul
  • Sanjiv Sabherwal
  • Sergiy Saydometov

Abstract

We use Google search frequency to construct a measure of aggregate sentiment in housing markets—Financial, Economic, and Real Estate (FEAR) Index—and analyze its relationship to housing returns. We find that housing markets react inversely to changes in FEAR Index, which captures negative sentiment, and that market characteristics affect the strength of this relationship. More financially distressed markets, as measured by bankruptcy rates and mortgage default double trigger, are more responsive to changes in FEAR Index than less distressed markets, and cold markets (markets with slow price appreciation) are more responsive than hot markets (markets with rapid price appreciation). We also examine these characteristics jointly and find that cold markets with financial distress are the most responsive to negative sentiment. Finally, we show that home prices are more sensitive to negative sentiment during recessionary periods.

Suggested Citation

  • Ramya Rajajagadeesan Aroul & Sanjiv Sabherwal & Sergiy Saydometov, 2022. "FEAR Index, city characteristics, and housing returns," Real Estate Economics, American Real Estate and Urban Economics Association, vol. 50(1), pages 173-205, March.
  • Handle: RePEc:bla:reesec:v:50:y:2022:i:1:p:173-205
    DOI: 10.1111/1540-6229.12335
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    as
    1. Ralf Hohenstatt & Manuel Kaesbauer, 2014. "'GECO's Weather Forecast' for the U.K. Housing Market: To What Extent Can We Rely on Google ECOnometrics?," Journal of Real Estate Research, American Real Estate Society, vol. 36(2), pages 253-282.
    2. Jim Clayton & David Ling & Andy Naranjo, 2009. "Commercial Real Estate Valuation: Fundamentals Versus Investor Sentiment," The Journal of Real Estate Finance and Economics, Springer, vol. 38(1), pages 5-37, January.
    3. Nikolaos Askitas & Klaus F. Zimmermann, 2009. "Google Econometrics and Unemployment Forecasting," Applied Economics Quarterly (formerly: Konjunkturpolitik), Duncker & Humblot, Berlin, vol. 55(2), pages 107-120.
    4. Goldfarb, Avi & Greenstein, Shane M. & Tucker, Catherine E. (ed.), 2015. "Economic Analysis of the Digital Economy," National Bureau of Economic Research Books, University of Chicago Press, number 9780226206981, December.
    5. Julia Freybote & Philip A. Seagraves, 2017. "Heterogeneous Investor Sentiment and Institutional Real Estate Investments," Real Estate Economics, American Real Estate and Urban Economics Association, vol. 45(1), pages 154-176, February.
    6. David Albouy & Alex Chernoff & Chandler Lutz & Casey Warman, 2019. "Local Labor Markets in Canada and the United States," Journal of Labor Economics, University of Chicago Press, vol. 37(S2), pages 533-594.
    7. Jing Wu & Yongheng Deng, 2015. "Intercity Information Diffusion and Price Discovery in Housing Markets: Evidence from Google Searches," The Journal of Real Estate Finance and Economics, Springer, vol. 50(3), pages 289-306, April.
    8. Yang Liu & Rajdeep Sengupta, 2012. "Household financial stress declines in the Eighth District," The Regional Economist, Federal Reserve Bank of St. Louis, issue Oct.
    9. D'Amuri, Francesco & Marcucci, Juri, 2009. "‘Google it!’ Forecasting the US unemployment rate with a Google job search index," ISER Working Paper Series 2009-32, Institute for Social and Economic Research.
    10. Albert Saiz, 2010. "The Geographic Determinants of Housing Supply," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 125(3), pages 1253-1296.
    11. Zhi Da & Joseph Engelberg & Pengjie Gao, 2015. "Editor's Choice The Sum of All FEARS Investor Sentiment and Asset Prices," The Review of Financial Studies, Society for Financial Studies, vol. 28(1), pages 1-32.
    12. Avi Goldfarb & Shane M. Greenstein & Catherine E. Tucker, 2015. "Economic Analysis of the Digital Economy," NBER Books, National Bureau of Economic Research, Inc, number gree13-1, May.
    13. Yang Liu & Rajdeep Sengupta, 2013. "Household financial stress and home prices," The Regional Economist, Federal Reserve Bank of St. Louis, issue Jan.
    14. Zhi Da & Joseph Engelberg & Pengjie Gao, 2011. "In Search of Attention," Journal of Finance, American Finance Association, vol. 66(5), pages 1461-1499, October.
    15. Lynn Wu & Erik Brynjolfsson, 2015. "The Future of Prediction: How Google Searches Foreshadow Housing Prices and Sales," NBER Chapters, in: Economic Analysis of the Digital Economy, pages 89-118, National Bureau of Economic Research, Inc.
    16. Hyunyoung Choi & Hal Varian, 2012. "Predicting the Present with Google Trends," The Economic Record, The Economic Society of Australia, vol. 88(s1), pages 2-9, June.
    17. Malcolm Baker & Jeffrey Wurgler, 2007. "Investor Sentiment in the Stock Market," Journal of Economic Perspectives, American Economic Association, vol. 21(2), pages 129-152, Spring.
    18. Timothy J. Bartik, 1991. "Who Benefits from State and Local Economic Development Policies?," Books from Upjohn Press, W.E. Upjohn Institute for Employment Research, number wbsle, August.
    19. Diego García, 2013. "Sentiment during Recessions," Journal of Finance, American Finance Association, vol. 68(3), pages 1267-1300, June.
    20. Simeon Vosen & Torsten Schmidt, 2011. "Forecasting private consumption: survey‐based indicators vs. Google trends," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 30(6), pages 565-578, September.
    21. Michael S. Drake & Darren T. Roulstone & Jacob R. Thornock, 2012. "Investor Information Demand: Evidence from Google Searches Around Earnings Announcements," Journal of Accounting Research, Wiley Blackwell, vol. 50(4), pages 1001-1040, September.
    22. David C. Ling & Joseph T.L. Ooi & Thao T.T. Le, 2015. "Explaining House Price Dynamics: Isolating the Role of Nonfundamentals," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 47(S1), pages 87-125, March.
    23. Case, Karl E & Shiller, Robert J, 1989. "The Efficiency of the Market for Single-Family Homes," American Economic Review, American Economic Association, vol. 79(1), pages 125-137, March.
    24. Christopher Mayer & Karen Pence & Shane M. Sherlund, 2009. "The Rise in Mortgage Defaults," Journal of Economic Perspectives, American Economic Association, vol. 23(1), pages 27-50, Winter.
    25. Akhtar, Shumi & Faff, Robert & Oliver, Barry & Subrahmanyam, Avanidhar, 2012. "Stock salience and the asymmetric market effect of consumer sentiment news," Journal of Banking & Finance, Elsevier, vol. 36(12), pages 3289-3301.
    26. Ralf Hohenstatt & Manuel Käsbauer & Wolfgang Schäfers, 2011. ""Geco" and its potential for real estate research: Evidence from the US housing market," Journal of Real Estate Research, American Real Estate Society, vol. 33(4), pages 471-506.
    27. Eli Beracha & Hilla Skiba, 2011. "Momentum in Residential Real Estate," The Journal of Real Estate Finance and Economics, Springer, vol. 43(3), pages 299-320, October.
    28. Paul C. Tetlock & Maytal Saar‐Tsechansky & Sofus Macskassy, 2008. "More Than Words: Quantifying Language to Measure Firms' Fundamentals," Journal of Finance, American Finance Association, vol. 63(3), pages 1437-1467, June.
    29. David C. Ling & Andy Naranjo & Benjamin Scheick, 2014. "Investor Sentiment, Limits to Arbitrage and Private Market Returns," Real Estate Economics, American Real Estate and Urban Economics Association, vol. 42(3), pages 531-577, September.
    30. Siqi Zheng & Weizeng Sun & Matthew E. Kahn, 2016. "Investor Confidence as a Determinant of China's Urban Housing Market Dynamics," Real Estate Economics, American Real Estate and Urban Economics Association, vol. 44(4), pages 814-845, October.
    31. Foote, Christopher L. & Gerardi, Kristopher & Willen, Paul S., 2008. "Negative equity and foreclosure: Theory and evidence," Journal of Urban Economics, Elsevier, vol. 64(2), pages 234-245, September.
    32. Thomas M. Springer & Neil G. Waller, 1993. "Lender Forbearance: Evidence from Mortgage Delinquency Patterns," Real Estate Economics, American Real Estate and Urban Economics Association, vol. 21(1), pages 27-46, March.
    33. Chauvet, Marcelle & Gabriel, Stuart & Lutz, Chandler, 2016. "Mortgage default risk: New evidence from internet search queries," Journal of Urban Economics, Elsevier, vol. 96(C), pages 91-111.
    34. Eli Beracha & M. Babajide Wintoki, 2013. "Forecasting Residential Real Estate Price Changes from Online Search Activity," Journal of Real Estate Research, American Real Estate Society, vol. 35(3), pages 283-312.
    35. Kerry D. Vandell & Thomas Thibodeau, 1985. "Estimation of Mortgage Defaults Using Disaggregate Loan History Data," Real Estate Economics, American Real Estate and Urban Economics Association, vol. 13(3), pages 292-316, September.
    36. Jeremy C. Stein, 1995. "Prices and Trading Volume in the Housing Market: A Model with Down-Payment Effects," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 110(2), pages 379-406.
    37. Kwan Ok Lee & Masaki Mori, 2016. "Do Conspicuous Consumers Pay Higher Housing Premiums? Spatial and Temporal Variation in the United States," Real Estate Economics, American Real Estate and Urban Economics Association, vol. 44(3), pages 726-763, July.
    38. McLaren, Nick & Shanbhogue, Rachana, 2011. "Using internet search data as economic indicators," Bank of England Quarterly Bulletin, Bank of England, vol. 51(2), pages 134-140.
    39. Paul C. Tetlock, 2007. "Giving Content to Investor Sentiment: The Role of Media in the Stock Market," Journal of Finance, American Finance Association, vol. 62(3), pages 1139-1168, June.
    40. Ambrose, Brent W & Buttimer, Richard J, Jr & Capone, Charles A, 1997. "Pricing Mortgage Default and Foreclosure Delay," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 29(3), pages 314-325, August.
    41. Akhtar, Shumi & Faff, Robert & Oliver, Barry & Subrahmanyam, Avanidhar, 2011. "The power of bad: The negativity bias in Australian consumer sentiment announcements on stock returns," Journal of Banking & Finance, Elsevier, vol. 35(5), pages 1239-1249, May.
    42. Karl E. Case & Robert J. Shiller, 1990. "Forecasting Prices and Excess Returns in the Housing Market," Real Estate Economics, American Real Estate and Urban Economics Association, vol. 18(3), pages 253-273, September.
    43. Vlastakis, Nikolaos & Markellos, Raphael N., 2012. "Information demand and stock market volatility," Journal of Banking & Finance, Elsevier, vol. 36(6), pages 1808-1821.
    44. John Y. Campbell & Stefano Giglio & Parag Pathak, 2011. "Forced Sales and House Prices," American Economic Review, American Economic Association, vol. 101(5), pages 2108-2131, August.
    45. Dennis Capozza & Thomas Thomson, 2006. "Subprime Transitions: Lingering or Malingering in Default?," The Journal of Real Estate Finance and Economics, Springer, vol. 33(3), pages 241-258, November.
    46. Prashant Das & Alan Ziobrowski & N. Coulson, 2015. "Online Information Search, Market Fundamentals and Apartment Real Estate," The Journal of Real Estate Finance and Economics, Springer, vol. 51(4), pages 480-502, November.
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