This paper provides new empirical evidence on delinking and Environmental Kuznets Curves (EKC) for greenhouse gases and other air pollutant emissions in Italy. A panel dataset concerning sectoral disaggregated National Accounts Matrix including Environmantal Accounts (NAMEA) data (1990-2001) is analyzed. This highly disaggregated dataset (29 productive branches, 12 years and 9 air emissions) provides a large heterogeneity and can help to overcome the shortcomings of the usual approach to EKC based on cross-country data. Both value added and capital stock per employee are used as alternative drivers for analysing sectoral NAMEA emissions. Trade openness at the same sectoral level is also introduced among the covariates. We find mixed evidence supporting the EKC hypothesis. The analysis of NAMEA-based data shows that some of the pollutants such as two greenhouse gases (CO2 and CH4,) and CO, produce inverted-U shaped curves with coherent within range turning points. Other pollutants (SOX, NOX, PM10) show monotonic or even N shaped relationship. Macro sectoral disaggregated analysis highlights that the aggregated outcome should hide some heterogeneity across different groups of macro-sectors (industry, manufacturing and services). Services tend to present an inverted-N shape in most cases. Manufacturing industry shows a mix of inverted-U and N shapes, depending on the emission considered. The same is true for industry (all industries, not only manufacturing): though a turning point has been experienced, N shapes may lead to increased emissions with respect to very high levels of the income driver. In general, EKC evidence is more pronounced for GHGs. Thus, as we expected, aggregate trends hide heterogeneous sectoral dynamics to a large extent. This suggests that analysis at macro sector (whole industry, manufacturing only and services) can be the most promising approach to future research on EKC.
Environmental Kuznets Curves and Greenhouse gas emissions. Evidence from NAMEA and provincial data
MAZZANTI, Massimiliano;
2008
Abstract
This paper provides new empirical evidence on delinking and Environmental Kuznets Curves (EKC) for greenhouse gases and other air pollutant emissions in Italy. A panel dataset concerning sectoral disaggregated National Accounts Matrix including Environmantal Accounts (NAMEA) data (1990-2001) is analyzed. This highly disaggregated dataset (29 productive branches, 12 years and 9 air emissions) provides a large heterogeneity and can help to overcome the shortcomings of the usual approach to EKC based on cross-country data. Both value added and capital stock per employee are used as alternative drivers for analysing sectoral NAMEA emissions. Trade openness at the same sectoral level is also introduced among the covariates. We find mixed evidence supporting the EKC hypothesis. The analysis of NAMEA-based data shows that some of the pollutants such as two greenhouse gases (CO2 and CH4,) and CO, produce inverted-U shaped curves with coherent within range turning points. Other pollutants (SOX, NOX, PM10) show monotonic or even N shaped relationship. Macro sectoral disaggregated analysis highlights that the aggregated outcome should hide some heterogeneity across different groups of macro-sectors (industry, manufacturing and services). Services tend to present an inverted-N shape in most cases. Manufacturing industry shows a mix of inverted-U and N shapes, depending on the emission considered. The same is true for industry (all industries, not only manufacturing): though a turning point has been experienced, N shapes may lead to increased emissions with respect to very high levels of the income driver. In general, EKC evidence is more pronounced for GHGs. Thus, as we expected, aggregate trends hide heterogeneous sectoral dynamics to a large extent. This suggests that analysis at macro sector (whole industry, manufacturing only and services) can be the most promising approach to future research on EKC.I documenti in SFERA sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
