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Modeling corporate defaults: Poisson autoregressions with exogenous covariates (PARX)

Arianna Agosto, Giuseppe Cavaliere (), Dennis Kristensen () and Anders Rahbek

Journal of Empirical Finance, 2016, vol. 38, issue PB, 640-663

Abstract: We develop a class of Poisson autoregressive models with exogenous covariates (PARX) that can be used to model and forecast time series of counts. We establish the time series properties of the models, including conditions for stationarity and existence of moments. These results are in turn used in the analysis of the asymptotic properties of the maximum-likelihood estimators of the models. The PARX class of models is used to analyze the time series properties of monthly corporate defaults in the US in the period 1982–2011 using financial and economic variables as exogenous covariates. Results show that our model is able to capture the time series dynamics of corporate defaults well, including the well-known default counts clustering found in data. Moreover, we find that while in general current defaults do indeed affect the probability of other firms defaulting in the future, in recent years economic and financial factors at the macro level are capable to explain a large portion of the correlation of US firm defaults over time.

Keywords: Corporate defaults; Count data; Exogenous covariates; Poisson autoregression; Estimation (search for similar items in EconPapers)
JEL-codes: C13 C22 C25 G33 (search for similar items in EconPapers)
Date: 2016
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Working Paper: Modeling corporate defaults: Poisson autoregressions with exogenous covariates (PARX) (2015) Downloads
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DOI: 10.1016/j.jempfin.2016.02.007

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