A Model of Endogenous Loan Quality and the Collapse of the Shadow Banking System

Abstract

I develop a macroeconomic model in which banks can affect loan quality by exerting costly screening effort. Informational frictions limit the amount of external funds that banks can raise. In this framework, I consider two types of financial intermediation: traditional banking and shadow banking. By pooling different loans, shadow banks achieve a higher endogenous leverage compared to traditional banks, increasing credit availability. However, shadow banks also make the financial sector more fragile because of the lower quality of the loans they finance and because of their exposure to bank runs. In this setting, unconventional monetary policy can reduce macroeconomic instability. (JEL E32, E44, E52, G01, G21, G23, L25)

Shadow banking and financial intermediation

“…Moreover, mortgage lending increased property prices, and higher prices and collateral values enabled more borrowing (Goodhart & Hoffman, 2008). Using a simulated model, Ferrante (2018) argues that shadow banking achieves higher leverage and offers more credit than traditional banking; however, the financial sector becomes more fragile as credit quality declines with these activities. Moreover, using stock-flow-consistent models, Botta et al (2019Botta et al ( , 2020 highlight the role of securitization in increasing credit expansion, income inequality and financial instability.…”

Shadow banking, monetary policy and systemic risk

“…Gennaioli, Shleifer, and Vishny (2013) pointed out that shadow banking covers financial activities outside the regulatory system, and covers certain short-term risk-free bonds purchased by financial institutions. Ferrante (2018) believes that the general shadow banking is a network of financial entities that relies on asset securitization and complex financial products to decentralize intermediary credit funds to different entity projects. These activities include mutual funds in monetary markets and mortgages in mortgage finance companies.…”

Detecting and Analyzing the Effects of Time‐varying Parameters in Dsge Models

“…We take this evidence as suggestive of the potential problems one encounters estimating time invariant structural models and indicative that the relationship between λ and net worth needs a proper microfundation for policy counterfactuals to be interpreted. Providing this microfundation is beyond the scope of the article, but attempts to endogenize crucial parameters in models like Gertler and Karadi's exist (see, e.g., Bigio, 2012;Ferrante, 2018). In these models, an endogenous deterioration of the quality of loans generally leads to higher aggregate leverage, higher aggregate risks, and a larger probability of bank runs.…”