Emissions trends and labour productivity dynamics sector analyses of de-coupling/recoupling on a 1990-2005 Namea

This paper provides new empirical evidence on Environmental Kuznets Curves (EKC) for greenhouse gases (GHGs) and air pollutants at sector level. A panel dataset based on the Italian NAMEA over 1990-2005 is analysed, focusing on both emission efficiency (EKC model) and total emissions (IPAT model). Results show that looking at sector evidence, both decoupling and also eventually re-coupling trends could emerge along the path of economic development. CH4 is moderately decreasing in recent years, but being a minor gas compared to CO2, the overall performance on GHGs is not compliant with Kyoto targets, which do not appear to have generated a structural break in the dynamics at least for GHGs. SOx and NOx show decreasing patterns, though the shape is affected by some outlier sectors with regard to joint emission-productivity dynamics, and for SOx exogenous innovation and policy related factors may be the main driving force behind observed reductions. Services tend to present stronger delinking patterns across emissions. Trade expansion validates the pollution haven in some cases, but also show negative signs when only EU15 trade is considered: this may due to technology spillovers and a positive race to the top rather than the bottom among EU15 trade partners (Italy and Germany as the main exporters and trade partner in the EU). Finally, general R&D expenditure show weak correlation with emissions efficiency. EKC and IPAT derived models provide similar conclusions overall; the emission-labour elasticity estimated in the latter is generally different from 1, suggesting that in most cases, and for both services and industry, a scenario characterised by emissions saving technological dynamics. Further research should be directed towards deeper investigation of trade relationship at sector level, increased research into and efforts to produce specific sectoral data on environmental innovations, and to verifying the value of heterogeneous panel models capturing sector heterogeneity.