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Social Networks and Housing Markets

Author

Listed:
  • Michael Bailey
  • Ruiqing Cao
  • Theresa Kuchler
  • Johannes Stroebel
Abstract
We document that the recent house price experiences within an individual’s social network affect her perceptions of the attractiveness of property investments, and through this channel have large effects on her housing market activity. Our data combine anonymized social network information from Facebook with housing transaction data and a survey. We first show that in the survey, individuals whose geographically-distant friends experienced larger recent house price increases consider local property a more attractive investment, with bigger effects for individuals who regularly discuss such investments with their friends. Based on these findings, we introduce a new methodology to document large effects of housing market expectations on individual housing investment decisions and aggregate housing market outcomes. Our approach exploits plausibly-exogenous variation in the recent house price experiences of individuals’ geographically-distant friends as shifters of those individuals’ local housing market expectations. Individuals whose friends experienced a 5 percentage points larger house price increase over the previous 24 months (i) are 3.1 percentage points more likely to transition from renting to owning over a two-year period, (ii) buy a 1.7 percent larger house, (iii) pay 3.3 percent more for a given house, and (iv) make a 7% larger downpayment. Similarly, when homeowners’ friends experience less positive house price changes, these homeowners are more likely to become renters, and more likely to sell their property at a lower price. We also find that when individuals observe a higher dispersion of house price experiences across their friends, this has a negative effect on their housing investments. Finally, we show that these individual-level responses aggregate up to affect county-level house prices and trading volume. Our findings suggest that the house price experiences of geographically-distant friends might provide a valid instrument for local house price growth.

Suggested Citation

  • Michael Bailey & Ruiqing Cao & Theresa Kuchler & Johannes Stroebel, 2016. "Social Networks and Housing Markets," NBER Working Papers 22258, National Bureau of Economic Research, Inc.
    • Handle: RePEc:nbr:nberwo:22258
    Note: AP CF EFG ME PE
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    Cited by:

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    3. Mueller, Holger & Giroud, Xavier, 2016. "Redistribution of Local Demand Shocks through Firms' Internal Networks," CEPR Discussion Papers 11384, C.E.P.R. Discussion Papers.
    4. Luis Armona & Andreas Fuster & Basit Zafar, 2019. "Home Price Expectations and Behaviour: Evidence from a Randomized Information Experiment," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 86(4), pages 1371-1410.
    5. Xavier Giroud & Holger M. Mueller, 2017. "Redistribution of Local Labor Market Shocks through Firms� Internal Networks," Working Papers 17-03, Center for Economic Studies, U.S. Census Bureau.
    6. Aikman, David & Haldane, Andrew & Hinterschweiger, Marc & Kapadia, Sujit, 2018. "Rethinking financial stability," Bank of England working papers 712, Bank of England.
    7. Adam, Klaus & Merkel, Sebastian, 2019. "Stock price cycles and business cycles," Working Paper Series 2316, European Central Bank.
    8. Bing Han & David Hirshleifer & Johan Walden, 2023. "Visibility Bias in the Transmission of Consumption Beliefs and Undersaving," Journal of Finance, American Finance Association, vol. 78(3), pages 1647-1704, June.
    9. Robert J. Shiller, 2017. "Narrative Economics," American Economic Review, American Economic Association, vol. 107(4), pages 967-1004, April.
    10. Ajirloo, Bahman Fathi & Switzer, Lorne N., 2022. "Self-disclosed peer effects on corporate capital structure," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 78(C).
    11. Einar C. Kjenstad & Anil Kumar, 2022. "The effect of real estate prices on peer firms," Real Estate Economics, American Real Estate and Urban Economics Association, vol. 50(4), pages 1022-1053, December.
    12. Xavier Giroud & Holger M. Mueller, 2017. "Firms' Internal Networks and Local Economic Shocks," NBER Working Papers 23176, National Bureau of Economic Research, Inc.
    13. Lee, Yong Suk & Sasaki, Yuya, 2018. "Information technology in the property market," Information Economics and Policy, Elsevier, vol. 44(C), pages 1-7.
    14. Xavier Giroud & Holger M. Mueller, 2016. "Redistribution of Local Labor Market Shocks through Firms’ Internal Networks," NBER Working Papers 22396, National Bureau of Economic Research, Inc.
    15. Kwan Ok Lee & Masaki Mori, 2021. "Conspicuous consumption and household indebtedness," Real Estate Economics, American Real Estate and Urban Economics Association, vol. 49(S2), pages 557-586, September.
    16. Schwarz, Marco A., 2017. "The Impact of Social Media On Belief Formation," Rationality and Competition Discussion Paper Series 57, CRC TRR 190 Rationality and Competition.
    17. Hurn, Stan & Shi, Shuping & Wang, Ben, 2022. "Housing networks and driving forces," Journal of Banking & Finance, Elsevier, vol. 134(C).
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    More about this item

    JEL classification:

    • D12 - Microeconomics - - Household Behavior - - - Consumer Economics: Empirical Analysis
    • D14 - Microeconomics - - Household Behavior - - - Household Saving; Personal Finance
    • D84 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Expectations; Speculations
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • R21 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Household Analysis - - - Housing Demand

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