Business Cycle Effects of Credit Shocks in a DSGE Model with Firm Defaults

Abstract

This paper proposes a theoretical framework to analyze the relationship between credit shocks, firm defaults and volatility, and to study the impact of credit shocks on business cycle dynamics. Firms are identical ex ante but differ ex post due to different realizations of firm-specific technology shocks, possibly leading to default by some firms. The paper advances a new modelling approach for the analysis of firm defaults and financial intermediation that takes account of the financial implications of such defaults for both households and banks. Results from a calibrated version of the model suggest that, in the steady state, a firm's default probability rises with its leverage ratio and the level of uncertainty in the economy. A positive credit shock, defined as a rise in the loan-todeposit ratio, increases output, consumption, hours and productivity, and reduces the spread between loan and deposit rates. The effects of the credit shock tend to be highly persistent, even without price rigidities and habit persistence in consumption behavior. JEL classification: E32, E44, G21 Bank classification: Business fluctuations and cycles; Economic models; Credit and credit aggregates; Financial institutions RésuméLes auteurs proposent un modèle théorique pour l'analyse de la relation entre les chocs de crédit, les défaillances d'entreprises et la volatilité, ainsi que pour l'étude des effets de ces chocs sur la dynamique du cycle économique. Dans ce modèle, des entreprises identiques ex ante se différencient ex post en réponse aux chocs technologiques réalisés, qui sont propres à chaque entreprise et peuvent provoquer sa défaillance. Le nouveau modèle employé par les auteurs pour examiner les défaillances des firmes et l'intermédiation financière tient compte des conséquences financières de ces défaillances à la fois sur les ménages et sur les banques. Les résultats tirés d'une version étalonnée du modèle indiquent qu'à l'équilibre de long terme, la probabilité de défaut d'une entreprise augmente avec son ratio de levier et le degré d'incertitude dans l'économie. Un choc de crédit positif -à savoir une hausse du ratio des prêts aux dépôts -accroît la production, la consommation, le nombre d'heures travaillées et la productivité et réduit l'écart entre le taux prêteur et le taux de rémunération des dépôts. Les retombées du choc de crédit tendent à perdurer longtemps même en l'absence de rigidité des prix et de persistance des habitudes de consommation.

The Prognostics for Credit Shocks (Financial Crisis) and Insights for Mitigating Consequences

“…Various issues on the 2007-2008 global financial crises are the headlines on many research papers specifically dealing with the factors of credit shocks, and estimating its effect on economies (Gilchrist & Zakrajsek, 2012;Pesaran & Xu, 2013;Fornari & Stracca, 2011;Maredza & Ikhide, 2013;Bedock & Stevanovic, 2012) indicating the relevance of the topic.…”

“…Efforts have been taken to understand the main factors and consequences for such tremendous worldwide recession wave (Eickmeier & Ng, 2011;Bassett et al, 2013;Liberti & Sturgess, 2013;Khan & Thomas, 2013;Gilchrist & Zakrajsek, 2012;Amiti & Weinstein, 2013;Claessens, Tong & Zuccardi, 2012;Pesaran & Xu, 2013;Greenstone & Mas, 2012) although fragmentary.…”

Animal Spirits and Credit Cycles

“…The new banking sector parameters are calibrated as follows: d 1 is computed to match a marginal propensity to consume (MPC) out of income equal to 0.5, in line with the empirical literature pointing to a MPC in the range of 0:2 À 0:7 (Friedman, 1963;Carroll, 2012;Iacoviello and Neri, 2010). The remaining parameters are derived consistently with the sign restrictions posited, namely a firms' leverage factor of τ ¼ 1:43, following Pesaran and Xu (2013) and φ o 0. For the 5 The spread and saving need not to be forecasted, as their forecasts do not enter the model.…”

Unexpected Loan Losses and Bank Capital in an Estimated DSGE Model of the Euro Area

“…Moreover, they abstract from modelling interactions with bank balance sheets. Christiano et al (2008), Christiano et al (2014) and Pesaran and Xu (2011) allow for the possibility of losses in loan portfolios, but also consider a banking sector that operates without equity capital. Meh and Moran (2010), Davis (2010), Dib (2010), Gerali et al 4 Bolt et al (2012) find that loan losses are the main driver of the negative impact of economic downturns on bank profit.…”