Relationships between economic growth, CO2 emissions, and innovation for nations with the highest patent applications

  • Released On
    Wednesday, 27 June 2018
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  • DOI
    http://dx.doi.org/10.21511/ee.09(2).2018.04
  • Article Info
    Volume 9 2018, Issue #2, pp. 47-69
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This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License

This study aims to provide insight on the nexus between innovation, economic growth and CO2 emissions. In order to achieve this, data on potential factors such as innovation, environmental taxes, research and development (R&D) spending, electricity production, population size, high-technology exports and prices of photovoltaic systems are collected for the sample of the leading innovative countries over the period from 1990 to 2014. Based on a cointegrated panel methodology and a vector error correction model, the long-run, as well as the short-run dynamics of all possible combinations between the variables under study, are estimated. The results reveal that except for China, economic growth is mainly driven by electricity production, population size, CO2 emissions and R&D spending. However, innovation was found to have lesser effect on economic growth. In addition to that, the authors found evidence in favor of CO2 emissions being affected positively by population size and prices of photovoltaic systems and negatively by environmental taxes, high-technology exports, R&D spending and innovation. Moreover, on the contrary to population size, well-being is positively affected by CO2 emission and R&D spending.

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    • Fig. 1. Interactions between the different variables
    • Fig. 2. Worldwide contribution of the 12 countries to solar PV and total electricity and solar PV production, solar photovoltaic capacity, CO2 emissions, solar PV patents and all technologies patents, population, and GDP
    • Fig. 3. Cumulated five previous years patents (all technologies)
    • Fig. 4. Number of patents related to photovoltaic sector, and containing one of the keywords “photovoltaic” or “solar cell” or “solar module” or “solar panel” in the title and in the English abstract
    • Fig. 5. Five previous year cumulated inventions all technologies by 100 million US$ of GDP (at market prices, constant 2010)
    • Fig. 6. Total CO2 emissions from fossil fuels and cement production
    • Fig. 7. CO2 emissions by GDP (gram carbon/US$ 2010)
    • Fig. 8. Per capita CO2 emissions (metric tons of carbon)
    • Fig. 9. Annual rate of change for CO2 emissions and its drivers using Kaya decomposition analysis
    • Fig. 10. R&D intensity average (five years periods)
    • Fig. 11. Synthetic diagram of the approach undertaken
    • Fig. 12. Electricity consumption by sector in year 2014 (as percent of total)
    • Fig. 13. Ratio GDP to 5 years cumulated inventions. (*) Total patents all technologies
    • Fig. 14. Ratio of CO2 emission to environmentally related tax revenue (ERT)
    • Table 1. Null and alternative hypothesis for unit root tests
    • Table 2. The eight groups (29 variables)
    • Table 3. Variables obtained and number of equations
    • Table 4. Total patent application in percentage of global patent applications, during the period 1995˗2015
    • Table 5. Variation in CO2 emissions between 1995 and 2013
    • Table 6. Average environmentally related tax revenue % of GDP
    • Table 7. Unit root test statistics with individual intercept and trend ˗ automatic lag method SIC and automatic newey-west variable bandwidth selection (1990˗2014)
    • Table 8. Retained variables: definition, scope of the data and sources
    • Table 9. Long-term coefficient summary (GDP_2010US as dependent variable) for different country panels
    • Table 10. Trends in GDP, CO2 emissions, and ERTs for China and the USA over the period 1995-2015
    • Table 11. Summary of results achieved for the dependent variable GDP_2010US (527 equations)
    • Table 12. Summary of results achieved for the dependent variable LOG(GDP_2010US) (181 equations)
    • Table 13. Summary of results achieved for the dependent variable LOG(GDP_PC) (115 equations)
    • Table 14. Summary of results achieved for the dependent variable CO2_EMISSION (175 equations)