Testing the Hypothesis of Environmental Kuznets Curve with Renyi and Tsallis Mutual Informations

Tuna E. , Evren A. A.

11. Uluslararası İstatistik Kongresi, Muğla, Türkiye, 4 - 08 Ekim 2019, ss.67-68

  • Basıldığı Şehir: Muğla
  • Basıldığı Ülke: Türkiye
  • Sayfa Sayıları: ss.67-68


Global warming and climate change have been one of the most important environmental problems in the last two decades. The Environmental Kuznets Curve (EKC) hypothesis postulates the existence of an inverse U-shape relationship between per capita gross domestic product (GDP) and Carbon dioxide emissions (CO2). This article investigates the validity of the Environmental Kuznets Curve (EKC) hypothesis in a cross-section of 131 developed and developing countries with data from 2014. Nonlinearity means the evidence of EKC hypothesis in regression analysis. So testing linearity goes to the conclusion or not of EKC hypothesis. An F test or a comparison between linear determination coefficient and correlation ratio may be helpful. For detecting nonlinearity with independent of strict assumptions we proposed a method based on mutual information between partial residuals as a measure of nonlinearity. This method is based on comparing the mutual information between residuals obtained by removing linear dependence from the original ones and residuals obtained by regressing curvilinear effect variable X2 on linear effect variable X. The last method is based on mutual information measure suggested by Tanaka,N.,at all., In addition to their study we also showed that nonlinearity can be detected better with Rényi and Tsallis mutual informations because of their flexibilities due to α parameter. In this paper we studied these tests and then compared the results obtained by each test. By determining the nonlinearity between the variables we have shown that the EKC hypothesis is supported. The result is important because it may have important policy implications.