2021
DOI: 10.1016/j.jmoneco.2020.01.007
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The origins of aggregate fluctuations in a credit network economy

Abstract: I show that inter-firm lending plays an important role in business cycle fluctuations. I first build a tractable network model of the economy in which trade in intermediate goods is financed by supplier credit. In the model, a financial shock to one firm affects its ability to make payments to its suppliers.

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Cited by 42 publications
(19 citation statements)
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“…Internal and external shocks, according to reference [1], might induce output volatility. It is confirmed by the findings of reference [3], who discovered that financial shocks were the primary driver of cyclical fluctuations, particularly during the Great Recession.…”
Section: Introductionsupporting
confidence: 57%
“…Internal and external shocks, according to reference [1], might induce output volatility. It is confirmed by the findings of reference [3], who discovered that financial shocks were the primary driver of cyclical fluctuations, particularly during the Great Recession.…”
Section: Introductionsupporting
confidence: 57%
“…Moreover, an ine cient discrepancy between labor and consumption, and the resulting employment choices, arise in their set-up due to general equilibrium e↵ects. Altinoglu (2018), Reischer (2019) and Luo (2020) use similar frameworks to study the impact of inter-firm trade credit through calibration exercises. Jacobson and von Schedvin (2015) study the exposure of Swedish firms to corporate bankruptcies through trade credit in production chains and find that trade creditors su↵er 50% higher losses than banks lending to the corporate sector.…”
Section: Introductionmentioning
confidence: 99%
“… Some recent papers have investigated aggregate volatility in production networks with inefficient equilibria (where Hulten's theorem does not hold). Some examples include Bigio and La'O (), Baqaee (), Altinoglu (), Grassi (), and Baqaee and Farhi (). See also Jones (, ), Bartelme and Gorodnichenko (), and Liu (). …”
mentioning
confidence: 99%