PREDICTION OF CENTRAL GOVERNMENT BUDGET TAX REVENUES USING MARKOV MODEL

Year 2016, Volume: 25 Issue: 2, 41 - 56, 30.04.2016

Can Mavruk , Ersin Kıral

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.

Keywords

Tax Revenues, Transition Probabilities, Markov Analysis, Budget Forecast

References

• Usher M.B, Jun., 1979, Markovian Approaches to Ecological Succession, Journal of Animal Ecology, 48(2):413-426 Taha H.A, Yöneylem Araştırması, 6.baskıdan çeviri, Literatür Yayıncılık, 2000: 726 Yeh HW, Chan W, Symanski E, Davis B.R, 2010, Estimating Transition Probabilities for Ignorable Intermittent Missing Data in a Discrete-Time Markov Chain, Communications in Statistics-Simulation and Computation, 39(2):433-448 Baasch A, Tischew S and Bruelheide H, June 2010, Twelve years of succession on sandy substrates in a post-mining landscape: A Markov chain analysis, Ecological Applications, 20(4):1136-1147 Grimshaw S.D, Alexander W.P, 2011, Markov Chain Models for Deliquency: Transition Matrix Estimation and Forecasting, John Wiley&Sons, Applied Stochastic Models in Business and Industry, 27: 267-279 Lipták K, 2011, The Application Of Markov Chain Model To The Description Of Hungarian Labor Market Processes, Zarządzanie Publiczne 4(16):133–149 Büyüktatlı F, İşbilir S, Çetin E.İ, 2013, Markov Analizi ile Yıllık Ödeneklere Bağlı Bir Tahmin Uygulaması, Uluslararası Alanya İşletme Fakültesi Dergisi (5):1-8 Lukić P.,Gocić M., Trajković S., 2013, Prediction of annual precipitation on the territory of south Serbia using markov chains, Bulletin of the Faculty of Forestry, 108: 81-92. Bluman A.G, 2014, Elemantary Statistics, McGraw Hill Education, New York Vantika S., Pasaribu U.S, 2014, Application of Markov Chain To the Pattern of Mitochondrical Deoxyribonucleic Acid Mutations, AIP Conference Proc. 1589, 296 İlarslan K, 2014, Hisse Senedi Fiyat Hareketlerinin Tahmin Edilmesinde Markov Zincirlerinin Kullanılması: IMKB 10 Bankacılık Endeksi İşletmeleri Üzerine Ampirik Bir Çalışma, E-Journal of Yaşar University, 9(35): 6099-6260 Cavers M.S., Vasudevan K., 2015, Brief Communication: Earthquake sequencing: Analysis of Time Series constructed from the Markov Chain Model, Nonlinear Process Geophysics, 22:589-599 Lazri M., Ameur S., Brucker J.M., Lahdir M. and Sehad M., Analysis of drought areas in northern Algeria using Markov chains, February 2015, J. Earth Syst. Sci. 124(1):61–70 http://www.gib.gov.tr/sites/default/files/fileadmin/user_upload/VI/GBG/Tablo_47.xls.htm 5.12.2015 http://www.gib.gov.tr/sites/default/files/fileadmin/user_upload/VI/GBG/Tablo_44.xls.htm 5.12.2015 http://www.gib.gov.tr/sites/default/files/fileadmin/user_upload/VI/GBG/Tablo_46.xls.htm 5.12.2015 http://www.gib.gov.tr/sites/default/files/fileadmin/user_upload/VI/GBG/Tablo_45.xls.htm 5.12.2015 www.ekodialog.com>konular>genel_butce 8.12.2015 http://www.hurriyet.com.tr/2016-vergi-artis-oranlari-belli-oldu-40009417 9.12.2016 http://www.zaman.com.tr/ekonomi_2015-yilinda-vergiler-yuzde-1011-oraninda-artacak_2255169.html 10.12.2015 galton.uchicago.edu/~lalley/Courses/312/MarkovChains.pdf 15.12.2015 dept.stat.lsa.umich.edu/~ionides/620/notes/markov_chains.pdf 15.12.2015