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Property Tax Modelling by Using Fuzzy Regression Method

Year 2004, Volume: 3 Issue: 2, 277 - 287, 15.08.2004

Abstract

In this work, by taking into account the vagueness environment emerging as a result of not defining criterions sufficiently in the determination of property tax, the model of property tax of Konak district in İzmir. In the modelling, criterions like the class and variety of house etc. that effect house value are used. P1P2R3 multi-stage sampling technique is thought appropriate for this work. In here, simple random sampling is showed by R notation, sampling with probability proportional to size is showed by P notation, and the symbols below those notations denote the stages. SPSS package program is used for data evaluating and variables of regression model are determined by backward method that one of the construction of model methods. The outcomes that obtained by fuzzy regression approach and statistical regression analysis are compared.

References

  • ANDERSON, J.E. (2001), Eliminating Housing Tax Preferences: A Distributional Analysis, Journal of Housing Economics 10(1), 41-58.
  • BASKAN Ş. (1983), Farklı Örnekleme Yöntemlerinin Kullanıldığı "Çok Aşamalı Ömekleme", E.Ü. Muhendislik Dergisi Seri E: Uygulamalı İstatistik, Clt: 1, Sayı 1-2.
  • BRASINGTON, D.M. (2002), Edge Versus Center: Finding Common Ground in the Capitalization Debate, Journal of Urban Economics, 52, 524-541.
  • BRUCE, D., HOLTZ-EAKIN, D. (1999), Fundamental Tax Reform and Residential Housing, Journal of Housing Economics 8(4) 249-271.
  • CHANG, P.T. and LEE E.S. (1996) A Generalized Fuzzy Weighted Least-Squares Regression, Fuzzy Set and Systems, 82, 289-298.
  • CHANG Y.O.O (2001), Hybrid Fuzzy Least-Squares Regression Analysis and Its Reliability Measure, Fuzzy Sets and Systems, 119, 225-246.
  • CHANG, Y.H.O., AYYUB, B.M. (2001), Fuzzy Regression Methods- A comparative Assessment, Fuzzy Sets and Systems, 119 (2): 187-203.
  • CHUNG, E.C. and HAURIN, D.R. (2002), Housing Choices and Uncertainty: The Impact of Stochastic Events Journal of Urban Economics, 52, 193-216.
  • COCHRAN W. (1977), Sampling Techniques, Third Edition, Wiley Series.
  • GÖKBEL D. (2003), Emlak Vergisinde Vergilendirilecek Matrahın Belirlenmesi,ErişimYeri: http://www.eso-es.net/kurumsal/yazi.asp?68 Erişim Tarihi: 10.10.2003.
  • HANSEN, M.H., HURWITZ, W.N. (1943,. On the Theory of Sampling From Finite Populations, Ann. Math. Stat., 14, pp. 33-362.
  • KAO C., CHYU C. (2003), Least Squares Estimares İn Fuzzy Regression Analysis, Europen Jour. of Operational Res., 148(2), pp. 426-435.
  • ÖZELKAN E.C., DUCKSTEIN L., (2000), Multiobjective Fuzzy Regression General Framework, Computers & Operation Research, 27. 635-652.
  • RESMİ GAZETE, (15.3.1972), No: 14129.
  • RUONING X., (1997), S-Curve Regression Model in the Fuzzy Environment, Fuzzy Set and Systems, 90, 317-326.
  • SENZ. (2001), Bulanık Mantık ve Modelleme İlkeleri Bilge Kültür Sanat, s.172.
  • ŞENOL, Ş. (2003), Bölüm Semineri, Ege Üniversitesi Fen Fakültesi, İstatistik Bölümü.
  • TANAKA H., GUO P. (1999), Possibilistic Data Analysis for Operation Research, Phsica Verlag: Springer-Verlag Company,
  • TRAN L, DUCKSTEIN L. (2002), Multiobjective Fuzzy Regression with Central Tendency and Possibilistic Properties, Fuzzy Set and System, 130, 21-31.
  • YEN K. K., GHOSRAY S., ROIG G.(1999), A Lineer Regression Model Using Triangular Fuzzy Number Coefficient, Fuzzy Set and Systems, 106, 167-177.
  • VOITH R., GYOURKO J. (2002), Capitalization of Federal Taxes, the Relative Price of Housing, and Urban Form: Density and Sorting Effec, Regional Science and Urban Economics 32, 673–690.
  • ZADEH, L. A. (1968), Fuzzy Algorithms. Informat. and Control, 12 No:2, pp. 94-102.

Emlak Vergisinin Bulanık Regresyon Yöntemi ile Modellenmesi

Year 2004, Volume: 3 Issue: 2, 277 - 287, 15.08.2004

Abstract

Bu çalışmada, emlak vergisinin belirlenmesindeki kriterlerin yeterince tanımlanmamış olması nedeniyle ortaya çıkan belirsizlik ortamı da dikkate alınarak İzmir ili Konak ilçesi emlak vergisinin bulanık regresyon yöntemi ile bir modellemesi yapılmıştır. Modellemede inşaat türü, sınıf, vb. gibi bina değerlerini etkileyen değişkenler kullanılmıştır. Çok aşamalı P1P2R3 örnekleme plani bu çalışma için uygun bulunmuştur. Burada basit rasgele örnekleme R, ölçümle orantılı olasılıklı örnekleme P simgeleri ile belirtilmekte ve simgelerin altındaki indisler de aşamaları göstermektedir. Verilerin istatistiksel açıdan değerlendirmesinde SPSS paket programı kullanılmış; regresyon modelinin değişkenleri, model kurma yöntemlerinden biri olan geriye dogru seçim yöntemi ile belirlenmiştir. Bulanık regresyon yaklaşım ile istatistiksel regresyon analizinden elde edilen sonuçlar karşılaştırılmıştır.

References

  • ANDERSON, J.E. (2001), Eliminating Housing Tax Preferences: A Distributional Analysis, Journal of Housing Economics 10(1), 41-58.
  • BASKAN Ş. (1983), Farklı Örnekleme Yöntemlerinin Kullanıldığı "Çok Aşamalı Ömekleme", E.Ü. Muhendislik Dergisi Seri E: Uygulamalı İstatistik, Clt: 1, Sayı 1-2.
  • BRASINGTON, D.M. (2002), Edge Versus Center: Finding Common Ground in the Capitalization Debate, Journal of Urban Economics, 52, 524-541.
  • BRUCE, D., HOLTZ-EAKIN, D. (1999), Fundamental Tax Reform and Residential Housing, Journal of Housing Economics 8(4) 249-271.
  • CHANG, P.T. and LEE E.S. (1996) A Generalized Fuzzy Weighted Least-Squares Regression, Fuzzy Set and Systems, 82, 289-298.
  • CHANG Y.O.O (2001), Hybrid Fuzzy Least-Squares Regression Analysis and Its Reliability Measure, Fuzzy Sets and Systems, 119, 225-246.
  • CHANG, Y.H.O., AYYUB, B.M. (2001), Fuzzy Regression Methods- A comparative Assessment, Fuzzy Sets and Systems, 119 (2): 187-203.
  • CHUNG, E.C. and HAURIN, D.R. (2002), Housing Choices and Uncertainty: The Impact of Stochastic Events Journal of Urban Economics, 52, 193-216.
  • COCHRAN W. (1977), Sampling Techniques, Third Edition, Wiley Series.
  • GÖKBEL D. (2003), Emlak Vergisinde Vergilendirilecek Matrahın Belirlenmesi,ErişimYeri: http://www.eso-es.net/kurumsal/yazi.asp?68 Erişim Tarihi: 10.10.2003.
  • HANSEN, M.H., HURWITZ, W.N. (1943,. On the Theory of Sampling From Finite Populations, Ann. Math. Stat., 14, pp. 33-362.
  • KAO C., CHYU C. (2003), Least Squares Estimares İn Fuzzy Regression Analysis, Europen Jour. of Operational Res., 148(2), pp. 426-435.
  • ÖZELKAN E.C., DUCKSTEIN L., (2000), Multiobjective Fuzzy Regression General Framework, Computers & Operation Research, 27. 635-652.
  • RESMİ GAZETE, (15.3.1972), No: 14129.
  • RUONING X., (1997), S-Curve Regression Model in the Fuzzy Environment, Fuzzy Set and Systems, 90, 317-326.
  • SENZ. (2001), Bulanık Mantık ve Modelleme İlkeleri Bilge Kültür Sanat, s.172.
  • ŞENOL, Ş. (2003), Bölüm Semineri, Ege Üniversitesi Fen Fakültesi, İstatistik Bölümü.
  • TANAKA H., GUO P. (1999), Possibilistic Data Analysis for Operation Research, Phsica Verlag: Springer-Verlag Company,
  • TRAN L, DUCKSTEIN L. (2002), Multiobjective Fuzzy Regression with Central Tendency and Possibilistic Properties, Fuzzy Set and System, 130, 21-31.
  • YEN K. K., GHOSRAY S., ROIG G.(1999), A Lineer Regression Model Using Triangular Fuzzy Number Coefficient, Fuzzy Set and Systems, 106, 167-177.
  • VOITH R., GYOURKO J. (2002), Capitalization of Federal Taxes, the Relative Price of Housing, and Urban Form: Density and Sorting Effec, Regional Science and Urban Economics 32, 673–690.
  • ZADEH, L. A. (1968), Fuzzy Algorithms. Informat. and Control, 12 No:2, pp. 94-102.
There are 22 citations in total.

Details

Primary Language Turkish
Subjects Statistical Analysis
Journal Section Research Articles
Authors

Şanslı Şenol This is me

Sinem Bekçi This is me

Publication Date August 15, 2004
Published in Issue Year 2004 Volume: 3 Issue: 2

Cite

APA Şenol, Ş., & Bekçi, S. (2004). Emlak Vergisinin Bulanık Regresyon Yöntemi ile Modellenmesi. İstatistik Araştırma Dergisi, 3(2), 277-287.