Collateral booms and information depletion

Vladimir Asriyan, Luc Laeven and Alberto Martin

No 2266, Working Paper Series from European Central Bank

Abstract: We develop a new theory of information production during credit booms. In our model, entrepreneurs need credit to undertake investment projects, some of which enable them to divert resources towards private consumption. Lenders can protect themselves from such diversion in two ways: collateralization and costly screening, which generates durable information about projects. In equilibrium, the collateralization-screening mix depends on the value of aggregate collateral. High collateral values raise investment and economic activity, but they also raise collateralization at the expense of screening. This has important dynamic implications. During credit booms driven by high collateral values (e.g. real estate booms), the economy accumulates physical capital but depletes information about investment projects. As a result, collateral-driven booms end in deep crises and slow recoveries: when booms end, investment is constrained both by the lack of collateral and by the lack of information on existing investment projects, which takes time to rebuild. We provide new empirical evidence using US firm-level data in support of the model's main mechanism. JEL Classification: E32, E44, G01, D80

Keywords: collateral; credit booms; crises; information production; misallocation (search for similar items in EconPapers)
Date: 2019-04
New Economics Papers: this item is included in nep-dge, nep-fdg and nep-mac
Note: 261593
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (6)

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Related works:
Journal Article: Collateral Booms and Information Depletion (2022)
Working Paper: Collateral booms and information depletion (2019)
Working Paper: Collateral booms and information depletion (2019)
Working Paper: Collateral Booms and Information Depletion (2018)
Working Paper: Collateral Booms and Information Depletion (2018)
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