The financial accelerator in an evolving credit network

By Domenico Delli Gatti, Mauro Gallegati, B. Greenwald, Alberto Russo, Joseph E. Stiglitz. 2010

288 citations recorded by the source corpus.

Subfields: Accounting, Economics and Econometrics, Finance

View Paper: https://www.semanticscholar.org/paper/50dfca116e629da6dc88f46d5cd51401821d9d4e

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Citations in the corpus

Income Distribution, Credit and Fiscal Policies in an Agent-Based Keynesian Model (2013, background): “The robustness of the model is checked against its capability to jointly account for a large set of empirical regularities both at the micro level (e.g. ﬁrm size and growth-rate distributions, productivity dispersions, ﬁrm investment patterns) and at the 1 For germane ABMs, see Verspagen (2002); Del”
Predicting financial distress and corporate failure: A review from the state-of-the-art definitions, modeling, sampling, and featuring approaches (2014, background): “In a credit network model that includes firms and banks, the bankruptcy of a borrower may lead to the lender’s bankruptcy or an increase of interest rate provided by the surviving lender, which further causes more borrowers already on the verge of bankruptcy to reach a tipping point and default [41]”
Increasing inequality, consumer credit and financial fragility in an agent based macroeconomic model (2016, background): “Some firms may go bankrupt, causing a further increase of non-performing loans and possibly leading to other bank defaults, according to a network-based financial accelerator mechanism (Delli Gatti et al. 2010; Riccetti et al., 2013).”
Bank relationships, business cycles, and financial crises (2011, background): “8 This literature mostly focuses on the short-run aspects of connections (7)For comprehensive analysis of factors affecting global capital flows during the crisis and the recovery, see Fratzscher (2011). (8)Some recent papers are Chan-Lau et al.”
Macroeconomic Policy in DSGE and Agent-Based Models (2012, unknown): “Delli Gatti et al. (2010) develop an ABM populated by banks, financially constrained downstream and upstream firms to study the properties of network-based financial accelerator.”
Leveraged Network-Based Financial Accelerator (2013, methodology): “The rationale is the same explained in Delli Gatti et al. (2010): given the predetermined supply, the relative price is an increasing function of the demand disturbance.”