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Econometric analysis reveals that social networks amplify FinTech mortgage refinancing across US counties, indicating stronger consumer responsiveness to monetary policy rate cuts.
This paper studies the role of social networks in the adoption of financial-technology (FinTech) lending in the US mortgage market and its implications for the refinancing channel of monetary policy. Using county-level data, I find that social network spillovers have a large and persistent effect on FinTech adoption, raising the overall likelihood of refinancing. My empirical estimates inform a structural model that helps quantify the changes in the monetary policy effects. The model suggests that consumption is more responsive to rate cuts in the FinTech era and about half of this increased responsiveness can be attributed to social network effects.
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Xiaoqing Zhou (2024) studied this question.
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