2020
DOI: 10.1007/s11356-020-11540-2
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The role of natural resources, globalization, and renewable energy in testing the EKC hypothesis in MINT countries: new evidence from Method of Moments Quantile Regression approach

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Cited by 112 publications
(65 citation statements)
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References 99 publications
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“…The results are consistent with the findings of Aziz et al [81], Si et al [82,83], and Koondhar et al [84]. In the case of BRICS and the MINT panel, Aziz et al [85,86] revealed that countries, after attaining a certain level of income, are inclined to regenerate the environment.…”
Section: Main Regression Resultssupporting
confidence: 89%
“…The results are consistent with the findings of Aziz et al [81], Si et al [82,83], and Koondhar et al [84]. In the case of BRICS and the MINT panel, Aziz et al [85,86] revealed that countries, after attaining a certain level of income, are inclined to regenerate the environment.…”
Section: Main Regression Resultssupporting
confidence: 89%
“…Aziz et al [24] considered the effects of renewable energy, globalization, and environmental Kuznets curve, using panel cointegration and panel moments of quantile regression for MINT countries cover the period 1995-2018. The authors selected as explanatory variables income per capita, squared income per capita, globalization (KOF index), natural resources, and renewable energy.…”
Section: Literature Review and Empirical Studiesmentioning
confidence: 99%
“…Overall, tests' results provide a robust indication that the data is integrated of order one. In line with existing literature adopting a similar panel quantile regression approach (see, e.g., Ike et al 2020;An et al 2021;Aziz et al 2021), 17 our analysis considers variables in levels. 18…”
Section: Diagnosticsmentioning
confidence: 85%
“…When dealing with the estimation approach of the MMQR, existing literature usually proceeds as follows: after performing the standard diagnostics, the estimation of the unknown parameters is always carried out on variables expressed in levels if the data is non-stationary but cointegrated. To control whether t-values are reliable, linear regression methods that allow data to be non-stationary and cointegrated as, e.g., DOLS, are applied in a second step as a benchmark for the t-values estimated in the MMQR (see, among others, the applications in Ike et al 2020; An et al 2021;Aziz et al 2021). the DOLS technique proposes to include lags and leads of the regressors in first differences to yield a consistent estimator with reliable t-statistics.…”
Section: Panel Quantile Regression Resultsmentioning
confidence: 99%