Volume 8, Issue 1, January 2019, Page: 1-6
Modeling Spatial Spillovers of Divorce in Senegal Using Spatial Durbin Model: A Maximum Likelihood Estimation Approach
Alassane Aw, Laboratory of Mathematics and Applications, Assane Seck University of Ziguinchor, Ziguinchor, Senegal
Emmanuel Nicolas Cabral, Laboratory of Mathematics and Applications, Assane Seck University of Ziguinchor, Ziguinchor, Senegal
Received: Dec. 16, 2018;       Accepted: Jan. 5, 2019;       Published: Jan. 24, 2019
DOI: 10.11648/j.ajtas.20190801.11      View  287      Downloads  83
Abstract
Spatial Durbin Model (SDM) is one of the family of spatial autoregressive models. In this paper, we use the SDM model to determine the spatial spillovers of divorce in Senegal. The variable of interest is the rate of divorce and the explanatory variables are the rate of illiteracy and the average age at marriage in Senegal. The model parameters are estimated by the maximum likelihood technique. The estimation of the autoregressive parameter is performed using numerical optimization of the concentrated log-likelihood of the SDM model. The results obtained showed that the rate of illiteracy and the average age at marriage have a real impact on the rate of divorce in Senegal. We also note that the departments of the country that are closed are more similar than the distant departments in relation to the divorce data. Direct and indirect effects were used to measure changes in the rate of divorce as a result of changes in the rate of illiteracy and the average age at marriage.
Keywords
Spatial Durbin Model, Maximum Likelihood Estimation, Spatial Spillovers, Impact Measures
To cite this article
Alassane Aw, Emmanuel Nicolas Cabral, Modeling Spatial Spillovers of Divorce in Senegal Using Spatial Durbin Model: A Maximum Likelihood Estimation Approach, American Journal of Theoretical and Applied Statistics. Vol. 8, No. 1, 2019, pp. 1-6. doi: 10.11648/j.ajtas.20190801.11
Copyright
Copyright © 2019 Authors retain the copyright of this article.
This article is an open access article distributed under the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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