Abstract
The presented paper analyzes the relationship between economic growth, demographic development, and CO2 emissions for 30 industrialized countries using time-series data from 1982–2014 in the well-known IPAT/STIRPAT setting. In contrast to the general assumption of IPAT/STIRPAT modeling, which in most cases proposes a one-way causality running from the anthropogenic factors to the environment, applied Granger-causality tests indicate a reversed causal relationship. Therefore, the paper suggests to add a new perspective to the IPAT/STIRPAT approach by setting up a stochastic model that explains impacts on economic growth (affluence) by regression on population, carbon emissions (as a proxy for energy use or ecosystem services), and technology. The results confirm that GDP per capita growth rates of highly industrialized economies are significantly driven by the development of CO2 emissions, population, and energy intensity. Coefficients remain robust with or without integrating structural and energy variables and for the short- and long-run perspective.
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Notes
- 1.
For a better traceability the environmental/energetic input is still denoted as I.
- 2.
In contrast to Eq. (2), P and T are not expressed inversely. This does not affect the estimation results.
- 3.
Generally, the STIRPAT studies treat technology differently. This paper uses energy intensity in order to stay close to existing STIRPAT literature [26]. Often, technology is approximated and assumed to be partly captured of the error term.
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Lohwasser, J., Schaffer, A., Brökel, T. (2023). Reversed STIRPAT Modeling: The Role of CO2 Emissions, Population, and Technology for a Growing Affluence. In: Valenzuela, O., Rojas, F., Herrera, L.J., Pomares, H., Rojas, I. (eds) Theory and Applications of Time Series Analysis and Forecasting. ITISE 2021. Contributions to Statistics. Springer, Cham. https://doi.org/10.1007/978-3-031-14197-3_21
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