Abstract
The focus of this paper is the examination of dynamic models in the presence of structural changes either due to disturbances precision or autoregressive parameter under the Bayesian framework. The Bayesian analysis of the dynamic model has been carried out under the mixture of prior distributions for the parameters. The posterior distribution of parameters is derived to obtain Bayes estimators under quadratic loss function ignoring the possibility of structural breaks in regression coefficients. The posterior odds ratio has been developed under the assumption that disturbance precision leads to structural change as against the autoregressive parameter. The theoretical framework is also empirically tested employing data set of Indian companies considering financial variables like debt, profitability, investment etc.; covering the global financial crisis (GFC) period. The empirical exercise carried out highlights 2008–09 as the major structural breakpoint when many Indian companies suffered losses.
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