FinTech financing, social networks and transmission of monetary policy

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No. 2203

Xiaoqing Zhou

Abstract: Mortgage borrowing is one of the main channels through which monetary policy stimulus measures affect the real economy. However, this channel is weakened by frictions in the mortgage market. The rapid growth of financial technology (FinTech)-based lending tends to alleviate these frictions, given the higher quality services provided under this new lending model. This article establishes that the role of FinTech loans in the transmission of monetary policy is further amplified by consumer social networks. I provide empirical evidence for this network effect using county-level data and novel identification strategies. A 1pp increase in FinTech market share in a county’s socially connected markets increases the county’s FinTech market share by 0.23 to 0.26pp. Additionally, I find that in countries with high FinTech market penetration, the pass-through of market interest rates to borrowers is more complete. To quantify the role of FinTech loans and their propagation on the network in the transmission of monetary policy shocks, I construct a multi-regional model of heterogeneous agents with social learning that embodies the main characteristics of FinTech loans. The model shows that consumption and refinancing responses to monetary stimulus are 13% higher in the presence of FinTech loans. Almost half of this improvement is due to the spread of FinTech via social networks.

DO I: https://doi.org/10.24149/wp2203

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