07. Rektörlüğe Bağlı Birimler

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    Citation - WoS: 15
    Citation - Scopus: 17
    Economic, Social, and Political Determinants of Environmental Sustainability: Panel Data Evidence From Next Eleven Economies
    (Sage Publications Ltd, 2022) Mughal, Nafeesa; Wen, Jun; Zhang, Qianxiao; Pekergin, Zehra Betul; Ramos-Meza, Carlos Samuel; Pelaez-Diaz, Guillermo
    This paper aims to investigate the impact of social, economic, and political variables on per capita ecological footprint consumption in the NEXT Eleven economies over the period 1984- 2018. The study utilized the dynamic heterogeneous panel estimators of Cross-Sectionally Augmented Auto-regressive Distributive Lag (CS-ARDL) along with the estimator with a multifactor error structure. The study also estimated the cross-Sectionally augmented distributed lag (CS-DL) model while for robustness check the augmented mean group (AMG) and cross-Sectionally augmented error correction method (CS-ECM) is also considered. The study finding maintains that the impact of GDP per capita, multifaceted phenomena of financial development, and military expenditure is positive and significant suggesting that a unit increase in these variables deteriorates the environment in the NEXT Eleven economies. In contrast, higher life expectancy and government stability improve the environment in the long run. The findings of the study suggest that eco-friendly technologies to be used in the production process, as well as projects using outdated technologies, should be discouraged along with the assurance of government stability and reduction of military expenditure in the NEXT Eleven economies.
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    Sociophysics of Income Distributions Modeled by Deformed Fermi-Dirac Distributions
    (TAYLOR & FRANCIS INC, 2023) Dil, Emre; Dil, Elif
    In order to model the income data, the physical distributions of Fermi-Dirac and Bose-Einstein families have already been proposed in the literature. In this study, we generalize Fermi-Dirac distribution by using a q,p-deformed version of Fermi-Dirac distribution which provides the advantage of working with flexible free q, p deformation parameters as the regression parameters for modeling the income data. We analyze the accuracy of the generalized version, q,p-deformed Fermi-Dirac distribution, on describing the data of income share held by quintiles for countries, and household income for the states of U.S.A. in 2018. We also use chi(2) minimization routine for modeling the data which leads to the best fit parameters for the deformation parameters q and p. Subsequently, we plot the fitted q, p-deformed Fermi-Dirac distribution as income distribution with the obtained deformation parameters, then find the statistical confidence values r(2) from the fitted curve. We figure out that our model properly describes the income data for the systems experiencing a high level of income inequality, and also r(2) values are correlated with the Gini index for those of considered systems.