The Economic Effects of Social Networks: Evidence from the Housing Market

Abstract

We show how data from online social networking services can help researchers better understand the effects of social interactions on economic decision making. We combine anonymized data from Facebook, the largest online social network, with housing transaction data and explore both the structure and the effects of social networks. Individuals whose geographically distant friends experienced larger recent house price increases are more likely to transition from renting to owning. They also buy larger houses and pay more for a given house. Survey data show that these relationships are driven by the effects of social interactions on individuals' housing market expectations. This paper was previously circulated as "Social Networks and Housing Markets." For helpful comments, we are grateful to

Five Facts About Beliefs and Portfolios

“…These results relate to the literature linking expectations to demographic characteristics and personal experiences. It is common in this literature to find strong statistical relationships but low explanatory power for expectations using variables such as wealth, gender, IQ, place of birth, current location, own past experience, or friends' past experiences (see, for example, Malmendier and Nagel, 2011;Kuchler and Zafar, 2015;Das, Kuhnen and Nagel, 2017;Bailey et al, 2017Bailey et al, , 2018Coibion, Gorodnichenko and Kamdar, 2018;D'Acunto et al, 2019). 48 Our results above highlight that the low R 2 s in these analyses is unlikely to be primarily due to classic measurement error in…”

“…Our work also relates to a literature that has explored the role of beliefs in other settings. For example, a number of papers have explored the role of individual expectations in the housing market (e.g., Piazzesi and Schneider, 2009;Case, Shiller and Thompson, 2012;Cheng, Raina and Xiong, 2014;Kuchler and Zafar, 2015;Burnside, Eichenbaum and Rebelo, 2016;Gao, Sockin and Xiong, 2016;Bailey et al, 2017Bailey et al, , 2018Glaeser and Nathanson, 2017;Adelino, Schoar and Severino, 2018a,b) as well as the role of firm expectations (e.g., Cummins, Hassett and Oliner, 2006;Bacchetta, Mertens and Van Wincoop, 2009;Coibion and Gorodnichenko, 2012;Gennaioli, Ma and Shleifer, 2016;Landier, Ma and Thesmar, 2017;Bachmann et al, 2018;Bordalo et al, 2018;Fuhrer, 2018). 6 A further related literature has explored how individuals with different political convictions respond differentially to political events, both in terms of their consumption (Mian, Sufi and Khoshkhou, 2015) as well as in terms of their portfolio allocations (Meeuwis et al, 2018).…”

“…This finding is closely related to the literature linking expectations to demographic characteristics and personal experiences. It is common in this literature to find strong statistical relationships but low explanatory power between expectations and variables such as wealth, gender, IQ, place of birth, current location, own past experience, or friends' past experiences (see, for example,Malmendier and Nagel, 2011;Kuchler and Zafar, 2015;Das, Kuhnen and Nagel, 2017;Bailey et al, 2017Bailey et al, , 2018Ben-David et al, 2018;Coibion, Gorodnichenko and Kamdar, 2018;D'Acunto et al, 2019). Also seeArmona, Fuster and Zafar (2016),Malmendier and Nagel (2015),Fuster, Perez-Truglia and Zafar (2018),and Laudenbach, Malmendier and Niessen-Ruenzi (2019) for other recent contributions to the study of expectation formation.…”

Are early stage investors biased against women?

“…That is, we replace the missing values with their own fixed effects. See Bailey et al (2017) for an example of this type of analysis. entrepreneurship among women than men.…”

High Leverage and Willingness to Pay: Evidence from the Residential Housing Market

“…From a theoretical standpoint, aggressive financing (in other words, high leverage) may relate to prices through multiple channels. Borrowers may overpay for housing and borrow at high leverage if they are optimistic about future home prices (see survey evidence by Case and Shiller , and models by Scheinkman and Xiong , Geanakoplos , Bailey, Dávila, Kuchler and Stroebel , Bailey, Cao, Kuchler and Stroebel , among others). In addition, financially constrained buyers may be willing to pay higher prices when high leverage is available.…”