Analyzing the Socio-Economic Development Index of Cities in Turkey with Geographically Weighted Regression Model - Sakarya, Adem; Ibisoglu, Cigdem (MARMARA UNIV, 2015)
In this paper, the socio-economic development index research was prepared in 2011 is examined with geographically weighted regression model. In this study, growth, development and socio-economic development concepts are discussed in comparison. Emerging as a result of these concepts, development and underdevelopment cases are explained and the problematic structure of being underdevelopment is emphasized. In all countries, especially developing countries are facing the problem of underdevelopment. Decision-makers develop proposed solutions to overcome these problems. To create solid foundation for suitable policies, current situation analysis have done with the socio-economic development index and the quality of development or underdevelopment structure have been confirmed. As a developing country, these studies are carried out in Turkey. Recent study on this subject is the Report of the Socio-Economic Development Index in 2011. In this report, development scores of provinces are calculated by using total 61 indicators under 8 heading. However, there is not an analysis about which and what extend these variables explain to development of provinces points in the context of this study. Therefore, in this study the ratio of variables to explain the provinces development are analysed by geographic information systems programme and geographically weighted regression model as a method. In this study, 8out of 61 indicators are used and case of how these different indicators explain the development rates geographically are examined. As a result, findings indicates that the explaining rate of variables to development scores is not same at all units. In general, it can be said that the explaining rate of economic indicators to development index is dominant in developed provinces while explaining rate of social indicators to development index is dominant in underdeveloped provinces.
Keywords: Socio-economic development index; geographically weighted regression; development; under development; socio-economic indicators; Geography