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

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  • Agosto, Arianna
  • Cavaliere, Giuseppe
  • Kristensen, Dennis
  • Rahbek, Anders

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.

Suggested Citation

  • Agosto, Arianna & Cavaliere, Giuseppe & Kristensen, Dennis & Rahbek, Anders, 2016. "Modeling corporate defaults: Poisson autoregressions with exogenous covariates (PARX)," Journal of Empirical Finance, Elsevier, vol. 38(PB), pages 640-663.
  • Handle: RePEc:eee:empfin:v:38:y:2016:i:pb:p:640-663
    DOI: 10.1016/j.jempfin.2016.02.007
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    Citations

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    Cited by:

    1. Rasmus Søndergaard Pedersen & Anders Rahbek, 2017. "Testing Garch-X Type Models," Discussion Papers 17-15, University of Copenhagen. Department of Economics.
    2. Giuseppe Cavaliere & Heino Bohn Nielsen & Rasmus Søndergaard Pedersen & Anders Rahbek, 2018. "Bootstrap Inference On The Boundary Of The Parameter Space With Application To Conditional Volatility Models," Discussion Papers 18-10, University of Copenhagen. Department of Economics.
    3. Dennis Kristensen & Young Jun Lee, 2019. "Local Polynomial Estimation of Time-Varying Parameters in Nonlinear Models," Papers 1904.05209, arXiv.org.
    4. repec:eee:econom:v:208:y:2019:i:2:p:613-637 is not listed on IDEAS
    5. Aknouche, Abdelhakim & Francq, Christian, 2018. "Count and duration time series with equal conditional stochastic and mean orders," MPRA Paper 90838, University Library of Munich, Germany.

    More about this item

    Keywords

    Corporate defaults; Count data; Exogenous covariates; Poisson autoregression; Estimation;

    JEL classification:

    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C25 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions; Probabilities
    • G33 - Financial Economics - - Corporate Finance and Governance - - - Bankruptcy; Liquidation

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