Bayesian analysis of a doubly truncated ARMA-GARCH model

被引：0
|
作者：
Goldman, E
Tsurumi, H
机构：
[1] Pace Univ, Lubin Sch Business, New York, NY 10038 USA
[2] Rutgers State Univ, Dept Econ, New Brunswick, NJ 08901 USA
来源：
STUDIES IN NONLINEAR DYNAMICS AND ECONOMETRICS | 2005年 / 9卷 / 02期
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D O I：
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中图分类号：
F [经济];
学科分类号：
02 ;
摘要：
We develop a new Markov Chain Monte Carlo procedure for a time series regression model truncated by upper and lower bounds. The regression error term is assumed to follow an ARMA--GARCH process. We use a convergence diagnostics with a simultaneous test of mean and covariance stationarity and discuss model selection criteria. Using MCMC procedure we test the purchasing power parity theory for the Japanese yen controlled to fluctuate in a narrow band and find that the theory is supported if double truncation is incorporated in estimation.
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页数：38
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