BAYESIAN APPROACH IN MULTINOMIAL PROBIT MODEL: INVESTIGATION OF COOKING OIL CONSUMPTION IN TURKEY
Abstract
In this study, it was aimed to
determine the factors effecting oil consumption in Turkey utilizing the
TurkStat’s Household Budget Survey of 2009. Multinomial Probit model was fitted
to the data, and model parameters were estimated using maximum likelihood and bayesian
approaches. While the significance and signs of parameters estimated by both
approaches exhibited similarities, the magnitudes of parameter estimates are
observed differently.
Keywords
Kaynakça
- Albert, J. H., & Chib, S. (1993). Bayesian analysis of binary and polychotomous response data. Journal of the American statistical Association, 88(422), 669-679.
- Berrett, C., & Calder, C. A. (2012). Data augmentation strategies for the Bayesian spatial probit regression model. Computational Statistics & Data Analysis, 56(3), 478-490.
- Burgette, L. F., & Hahn, P. R. (2010). Symmetric Bayesian multinomial probit models. Duke University Statistical Science Technical Report, 1-20.
- Dow, J. K., & Endersby, J. W. (2004). Multinomial probit and multinomial logit: a comparison of choice models for voting research. Electoral studies, 23(1), 107-122.
- Greene, W. H. (2003). Econometric analysis. Pearson Education India.
- Gelman, A., & Rubin, D. B. (1992). Inference from iterative simulation using multiple sequences. Statistical science, 457-472.
- Gujarati, D. N. (2009). Basic econometrics. Tata McGraw-Hill Education.
- Gupta, A. D. (2014). Multinomial Probit Model for Panel Data. Yüksek Lisans Tezi, California Üniversitesi, Los Angeles. http://escholarship.org/uc/item/24r48411. (Erişim: 05.07.2016 )
Ayrıntılar
Birincil Dil
Türkçe
Konular
-
Bölüm
Araştırma Makalesi
Yazarlar
Çiler Sizege
*
Bu kişi benim
ÇUKUROVA ÜNİVERSİTESİ
Türkiye
Yayımlanma Tarihi
27 Aralık 2017
Gönderilme Tarihi
5 Ekim 2016
Kabul Tarihi
28 Kasım 2017
Yayımlandığı Sayı
Yıl 2017 Cilt: 19 Sayı: 2