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Granger Causality in Panel Datasets: Relationship Between Economic Growth and CO $$_2$$ 2 Emissions

In: Applied Econometric Analysis Using Cross Section and Panel Data

Author

Listed:
  • Sylvain Weber

    (University of Applied Sciences Western Switzerland (HES-SO), Haute école de gestion (HEG))

  • Luciano Lopez

    (University of Applied Sciences Western Switzerland (HES-SO), EHL Hospitality Business School)

Abstract

This chapter discusses the concept of Granger causality for panel datasets that are both wide (many individuals) and long (many time periods). Such datasets are obtained for instance when sets of countries are observed over the long run. In such settings, classical issues of time series econometrics, such as (non-)stationarity and (non-)causality, also arise. After a brief theoretical presentation of Granger causality, we provide a complete empirical application using publicly available data from the World Bank and Climate Watch. We investigate Granger causality between economic growth and CO $$_2$$ 2 emissions for a set of 130 countries observed over 41 years. The empirical exercise is conducted with the statistical software Stata and is fully reproducible; thanks to the code that is provided. All steps of the analysis are carefully explained and the results are intuitively presented.

Suggested Citation

  • Sylvain Weber & Luciano Lopez, 2023. "Granger Causality in Panel Datasets: Relationship Between Economic Growth and CO $$_2$$ 2 Emissions," Contributions to Economics, in: Deep Mukherjee (ed.), Applied Econometric Analysis Using Cross Section and Panel Data, chapter 0, pages 539-570, Springer.
    • Handle: RePEc:spr:conchp:978-981-99-4902-1_18
    DOI: 10.1007/978-981-99-4902-1_18
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