Finite state markov-chain approximations to univariate and vector autoregressions

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Abstract

The paper develops a procedure for finding a discrete-valued Markov chain whose sample paths approximate well those of a vector autoregression. The procedure has applications in those areas of economics, finance, and econometrics where approximate solutions to integral equations are required.

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