Developing states and the green challenge. A dynamic approach

Alexandra-Anca Purcel
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Alexandra-Anca Purcel: CERDI - Centre d'Études et de Recherches sur le Développement International - IRD - Institut de Recherche pour le Développement - CNRS - Centre National de la Recherche Scientifique - UCA - Université Clermont Auvergne

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Abstract: This paper studies the effects of output, urbanization, energy intensity, and renewable energy on aggregated and sector-specific CO2 emissions for a rich sample of developing states. We employ the recently developed GMM panel VAR technique, which allows us to tackle the potential endogeneity issue and capture both the current and future impact of indicators on CO2 via the impulse-response analysis. On the one hand, robust to several alternative specifications, the findings indicate that output, urbanization, and energy intensity increase the aggregated CO2 emissions, while renewable energy exhibits an opposite effect. Moreover, regarding the CO2 responsiveness to output and urbanization shocks, the pattern may suggest that these countries are likely to attain the threshold that would trigger a decline in CO2 emissions. We also reveal heterogeneities related to both countries' economic development and Kyoto Protocol ratification/ascension status. On the other hand, the sectoral analysis unveils that the transportation, buildings, and non-combustion sector tend to contribute more to increasing the future CO2 levels. Overall, our study may provide useful insights concerning environmental sustainability prospects in developing states.

Keywords: CO2 emissions; urbanization; energy efficiency; renewable energy; developing countries; environmental Kuzents curve; GMM panel VAR (search for similar items in EconPapers)
Date: 2020
New Economics Papers: this item is included in nep-eff, nep-ene, nep-env, nep-hme and nep-ppm
Note: View the original document on HAL open archive server: https://uca.hal.science/hal-03182341v1
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Citations: View citations in EconPapers (1)

Published in Romanian Journal of Economic Forecasting, 2020, XXIII (2), pp.173-193

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