期刊
MANAGEMENT OF ENVIRONMENTAL QUALITY
卷 29, 期 2, 页码 368-384出版社
EMERALD GROUP PUBLISHING LTD
DOI: 10.1108/MEQ-02-2017-0021
关键词
Turkey; Environmental Kuznets curve; Structural break; Carbon emissions; Cointegration; Financial development
Purpose The purpose of this paper is to investigate the long-run effect of financial sector development, energy use and economic growth on carbon emissions for Turkey, in presence of possible regime shifts over a period of 1960-2013. Design/methodology/approach Along with the conventional unit root tests, Zivot-Andrews unit root test with structural break has been employed to check the stationarity of variables. The cointegrating relationship between variables is investigated by using the autoregressive distributed lag bounds test and Hatemi-J threshold cointegration test. Findings The results confirm a cointegrating relationship between the variables. The long-run relationship between the variables has gone through two endogenous structural breaks in 1976 and 1986. Development of financial sector improves environmental quality whereas energy use and economic growth degrade it. The results challenge the validity of environmental Kuznets curve hypothesis in Turkish economy. Research limitations/implications The study uses domestic credit to private sector as a proxy for development of financial sector. The model can be improved by constructing an index of financial development instead of using a single determinant as a proxy for financial development. Practical implications The study may pave the way for policy makers to capture important environmental pollutants in better way and develop effective and efficient energy and economic policies. This may make significant contribution to curbing CO2 emissions while sustaining economic growth. Originality/value This is the only study to examine long-run impact of financial sector development on carbon emissions, using the threshold cointegration approach. Hence, the study is a gentle request to reduce the possible omitted variable econometric estimation bias and fill the gap in the existing literature.
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