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Do natural resources and green technological innovation matter in addressing environmental degradation? Evidence from panel models robust to cross-sectional dependence and slope heterogeneity
16 references·0 citing·38 second hop
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References

  • 2007A simple panel unit root test in the presence of cross‐section dependence12,758 cited
  • 2004General Diagnostic Tests for Cross Section Dependence in Panels8,718 cited
  • 2007Testing for Error Correction in Panel Data*6,105 cited
  • 2007Testing slope homogeneity in large panels6,035 cited
  • 2012Testing for Granger non-causality in heterogeneous panels5,911 cited
  • 2014Testing Weak Cross-Sectional Dependence in Large Panels2,938 cited
  • 2018Toward a sustainable environment: Nexus between CO2 emissions, resource rent, renewable and nonrenewable energy in 16-EU countries1,385 cited
  • 2012Green innovation in technology and innovation management – an exploratory literature review1,165 cited
  • 2019The impact of natural resources, human capital, and foreign direct investment on the ecological footprint: The case of the United States809 cited
  • 2020The impact of natural resources, energy consumption, and population growth on environmental quality: Fresh evidence from the United States of America714 cited
  • 2020Does green investment, financial development and natural resources rent limit carbon emissions? A provincial panel analysis of China700 cited
  • 2010PRODUCTIVITY ANALYSIS IN GLOBAL MANUFACTURING PRODUCTION650 cited
  • 2022The impact of green technological innovation and institutional quality on CO2 emissions in African countries444 cited

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2021
How do financial development, energy consumption, natural resources, and globalization affect Arctic countries' economic growth and environmental quality? An advanced panel data simulation
438 cited
  • 2022Influence of digital finance and green technology innovation on China's carbon emission efficiency: Empirical analysis based on spatial metrology435 cited
  • 2016Long-Run Effects in Large Heterogeneous Panel Data Models with Cross-Sectionally Correlated Errors402 cited
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