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arXiv · 2207.11003

Time-Varying Poisson Autoregression

Giovanni Angelini·Giuseppe Cavaliere·Enzo D'Innocenzo·Luca De Angelis
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Abstract

In this paper we propose a new time-varying econometric model, called Time-Varying Poisson AutoRegressive with eXogenous covariates (TV-PARX), suited to model and forecast time series of counts. {We show that the score-driven framework is particularly suitable to recover the evolution of time-varying parameters and provides the required flexibility to model and forecast time series of counts characterized by convoluted nonlinear dynamics and structural breaks.} We study the asymptotic properties of the TV-PARX model and prove that, under mild conditions, maximum likelihood estimation (MLE) yields strongly consistent and asymptotically normal parameter estimates. Finite-sample performance and forecasting accuracy are evaluated through Monte Carlo simulations. The empirical usefulness of the time-varying specification of the proposed TV-PARX model is shown by analyzing the number of new daily COVID-19 infections in Italy and the number of corporate defaults in the US.

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Giovanni Angelini, Giuseppe Cavaliere, Enzo D'Innocenzo, Luca De Angelis. 2022-07-22. Time-Varying Poisson Autoregression. https://arxiv.org/abs/2207.11003

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