Peer effects and the housing market
People don’t make financial decisions in a vacuum, argue Kuchler and Stroebel. Instead, social interactions and peer effects shape many aspects of economic activity. Economic models so far have assumed away such factors from agents’ decision making, but new novel data sets on the social structure of society, which are becoming increasingly available, will enable researchers to incorporate social interactions in equilibrium models.
How can peer effects affect the housing market?
- Through belief contagion: friends’ house price experiences can affect an individual’s own housing market assessments enough to substantially influence her housing market activity.
- Through people’s need to “keep up with the Joneses”: housing consumption of others lowers the utility that individuals derive from their own homes.
New data sets from platforms such as Facebook and LinkedIn can shed light on the economic and financial effects of social networks. In particular, Kuchler and Stroebel mention the Social Connectedness Index as constructed in the paper by Bailey M, Cao R, Kuchler T, Stroebel J, Wong A. 2018b “Social connectedness: Measurement, determinants, and effects.”
The Social Connectedness Index (SCI) measures the social connectedness across any two locations. It is based on deidentified administrative data on Facebook’s social graph—which captures the network of friendship links on the platform — with users matched to their geographic locations.
Social Finance
Authors: Theresa Kuchler, Johannes Stroebel
From: New York University
Inequality, peer effects and the housing market
When inequality is combined with “keeping up with the richer Joneses” (KURJ) attitude, it can fuel housing demand and lead to a household mortgage debt boom. This is the causal relationship that Drechsel-Grau and Greimel explore in this paper. They use a heterogeneous agent model of the macro economy which incorporates social comparisons: households not only care about their own consumption and housing, but also about how their house compares to the benchmark set by the rich. They find that:
- In the presence of KURJ, the rise in income inequality can explain half of the observed 120% increase in the mortgage-to-income ratio and two thirds of the observed 60% increase in house prices between 1980 and 2007 in the U.S.
- Interestingly, the “Global Saving Glut” believed to have increased the US debt position by 50% from 1980 to 2007, through the decrease of real interest rates, in this model doesn’t have a strong effect on the housing market. According to the authors, the “Global Saving Glut” increased house prices by only 2%.
- Importantly, the model predicts that mortgage debt of the non-rich and house prices rise as top incomes rise, while non-mortgage debt of the non-rich is not affected by changes in top incomes.
Falling Behind: Has Rising Inequality Fueled the American Debt Boom?
Authors: Moritz Drechsel-Grau, Fabian Greimel
From: University of Mannheim, University of Amsterdam
