Nonlinearity, heterogeneity and unobserved effects in the carbon dioxide emissions-economic development relation for advanced countries

Nonlinearity, heterogeneity and unobserved effects in the carbon dioxide emissions-economic... Abstract We study long run carbon dioxide emissions-economic development relationships for advanced countries grouped in policy relevant groups: North America and Oceania, South Europe, North Europe. By relying on recent advances on Generalized Additive Mixed Models (GAMMs) and adopting interaction models, we handle simultaneously three main econometric issues, named here as functional form bias, heterogeneity bias and omitted time related factors bias , which have been proved to be relevant but have been addressed separately in previous papers. The model incorporates nonlinear effects, eventually heterogeneous across countries, for both income and time. We also handle serial correlation by using autoregressive moving average (ARMA) processes. We find that country-specific time related factors weight more than income in driving the northern EU Environmental Kuznets. Overall, the countries differ more on their carbon-time relation than on the carbon-income relation which is in almost all cases monotonic positive. Once serial correlation and (heterogeneous) time effects have been accounted for, only three Scandinavian countries – Denmark, Finland and Sweden – present some threshold effect on the CO 2 -development relation. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Studies in Nonlinear Dynamics & Econometrics de Gruyter

Nonlinearity, heterogeneity and unobserved effects in the carbon dioxide emissions-economic development relation for advanced countries

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Publisher
de Gruyter
Copyright
Copyright © 2014 by the
ISSN
1081-1826
eISSN
1558-3708
DOI
10.1515/snde-2012-0082
Publisher site
See Article on Publisher Site

Abstract

Abstract We study long run carbon dioxide emissions-economic development relationships for advanced countries grouped in policy relevant groups: North America and Oceania, South Europe, North Europe. By relying on recent advances on Generalized Additive Mixed Models (GAMMs) and adopting interaction models, we handle simultaneously three main econometric issues, named here as functional form bias, heterogeneity bias and omitted time related factors bias , which have been proved to be relevant but have been addressed separately in previous papers. The model incorporates nonlinear effects, eventually heterogeneous across countries, for both income and time. We also handle serial correlation by using autoregressive moving average (ARMA) processes. We find that country-specific time related factors weight more than income in driving the northern EU Environmental Kuznets. Overall, the countries differ more on their carbon-time relation than on the carbon-income relation which is in almost all cases monotonic positive. Once serial correlation and (heterogeneous) time effects have been accounted for, only three Scandinavian countries – Denmark, Finland and Sweden – present some threshold effect on the CO 2 -development relation.

Journal

Studies in Nonlinear Dynamics & Econometricsde Gruyter

Published: Dec 1, 2014

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