Abstract:

The aim of this paper is to describe the behavior of the sample data and to predict the realization rates of tax revenues by one step stochastic Markov chain model. The realization rates of the tax revenues are estimated by using 2000-2014 gross annual data extracted from TR Revenue Administration. Four Markov models are constructed for the realization rates of every tax revenue. The realization probabilities for the year 2016 are predicted by constructing probability matrices of transitions between classes described for every model. Revenues are also forecasted by the product of the initial probability matrix and transition probability matrix. Limiting matrix of predictions are found. The best Markov model was found by estimating the sum of mean square errors for every model. The results are compared and interpreted.

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