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The nonlinear effects of population aging, industrial structure, and urbanization on carbon emissions: A panel threshold regression analysis of 137 countries

机译:人口老化,产业结构和城市化对碳排放的非线性影响:137个国家的面板阈值回归分析

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Carbon emissions and population aging have risen as two major challenges of the sustainable development of human society. This study explores the nonlinear effects of population aging on carbon emission by developing a panel threshold regression (PTR) model, using data from 2002 to 2012 of 137 countries or regions. In the PTR model, carbon emission is the explained variable, whereas population aging is the threshold variable; industrial structure and urbanization are the explanatory variables; and level of economic development, trade freedom, population size, and financial level are the four control variables. With the increase in population aging, the correlation between industrial structure and carbon emissions in the high-income, upper-middle-income, low-income groups are positive, negative, and inverted "U" shaped, respectively. Moreover, with the increase in population aging, the correlations between urbanization and carbon emissions in the high-income group is inverted "U" shaped, whereas the correlation in upper-middle-, lower-middle-, and low-incomegroups is nonlinear and positive. (C) 2020 Elsevier Ltd. All rights reserved.
机译:碳排放量和人口老龄化已作为人类社会可持续发展的两个主要挑战。本研究通过开发面板阈值回归(PTR)模型,利用2002年至2012年的137个国家或地区的数据探讨了人口老化对碳排放对碳排放的非线性影响。在PTR模型中,碳发射是解释的变量,而人口老化是阈值变量;产业结构和城市化是解释性变量;和经济发展水平,贸易自由,人口规模和财务水平是四个控制变量。随着人口老龄化的增加,高收入,高中收入,低收入群体之间产业结构和碳排放之间的相关性分别是积极的,消极和倒置的“U”形。此外,随着人口老化的增加,高收入组城市化和碳排放之间的相关性被倒置为“U”形,而上部中,下部,中下,低收入组的相关性是非线性的积极的。 (c)2020 elestvier有限公司保留所有权利。

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