International Statistical Review

Bayesian International Evidence on Heavy Tails, Non-Stationarity and Asymmetry over the Business Cycle

Efthymios G. Tsionas

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Abstract

Although leptokurtosis is fairly common in macroeconomic time series, agreement over what non-normal distributions are plausible, is rare. The paper proposes a linear model that allows for trend versus difference stationarity and asymmetric behavior over the business cycle along with several distributional alternatives for the disturbance terms. It proposes computationally feasible Markov Chain Monte Carlo methods to perform Bayesian computations, applies the model to industrial production data of seven industrialized countries, and relies on prior predictive densities to compare models with Student-t, symmetric stable, EGARCH, exponential power family and finite-mixture-of-normals errors. The relationship between unit root inference, asymmetry and leptokurtosis is examined in detail using the exact, finite-sample posteriors corresponding to the different models.

Article information

Source
Internat. Statist. Rev., Volume 71, Number 1 (2003), 151-168.

Dates
First available in Project Euclid: 17 March 2004

Permanent link to this document
https://projecteuclid.org/euclid.isr/1079557580

Zentralblatt MATH identifier
1114.62371

Keywords
Leptokurtosis Model comparison Markov Chain Carlo Unit roots Asymmetry Business cycles Industrial production

Citation

Tsionas, Efthymios G. Bayesian International Evidence on Heavy Tails, Non-Stationarity and Asymmetry over the Business Cycle. Internat. Statist. Rev. 71 (2003), no. 1, 151--168. https://projecteuclid.org/euclid.isr/1079557580


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