Further experience in Bayesian analysis using Monte Carlo Integration
An earlier paper [Kloek and Van Dijk (1978)] is extended in three ways. First, Monte Carlo integration is performed in a nine-dimensional parameter space of Klein's model I [Klein (1950)]. Second, Monte Carlo is used as a tool for the elicitation of a uniform prior on a finite region by making use of several types of prior information. Third, special attention is given to procedures for the construction of importance functions which make use of nonlinear optimization methods. *1 This paper started as a revision of Van Dijk and Kloek (1978). In the course of the work our ideas developed to such an extent that the final result is an almost completely new paper. We are indebted to a referee for a number of very useful suggestions. We also wish to thank A.S. Louter and G. den Broeder of the Econometric Institute for their help in preparing the necessary computer programs.
|Keywords||Bayesian models, Monte Carlo models, econometrics|
|Persistent URL||dx.doi.org/10.1016/0304-4076(80)90030-5, hdl.handle.net/1765/11227|
van Dijk, H.K., & Kloek, T.. (1980). Further experience in Bayesian analysis using Monte Carlo Integration. Journal of Econometrics. doi:10.1016/0304-4076(80)90030-5