{"title":"Financial Technology and the Transmission of Monetary Policy: The Role of Social Networks","authors":"Xiaoqing Zhou","doi":"10.24149/wp2203r1","DOIUrl":null,"url":null,"abstract":"Financial technology-based (FinTech) lending is expected to ease U.S. mortgage market frictions that have weakened the transmission of monetary policy to households. This paper establishes that social networks play a key role in consumers’ adoption of FinTech lending, which amplifies the effects of a monetary stimulus. I provide causal estimates of the network effect on FinTech adoption using county-level data. To quantify the role of FinTech lending and network spillovers in the transmission of monetary policy shocks, I build a heterogeneous-agent model with social learning. The model shows that the consumption response to a monetary stimulus is 13% higher in the presence of FinTech lending and network spillovers, and that about half of this improvement is accounted for by network spillovers.","PeriodicalId":322311,"journal":{"name":"Federal Reserve Bank of Dallas, Working Papers","volume":"87 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Federal Reserve Bank of Dallas, Working Papers","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.24149/wp2203r1","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Financial technology-based (FinTech) lending is expected to ease U.S. mortgage market frictions that have weakened the transmission of monetary policy to households. This paper establishes that social networks play a key role in consumers’ adoption of FinTech lending, which amplifies the effects of a monetary stimulus. I provide causal estimates of the network effect on FinTech adoption using county-level data. To quantify the role of FinTech lending and network spillovers in the transmission of monetary policy shocks, I build a heterogeneous-agent model with social learning. The model shows that the consumption response to a monetary stimulus is 13% higher in the presence of FinTech lending and network spillovers, and that about half of this improvement is accounted for by network spillovers.