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The evolution of environmental and labor productivity dynamics

Sector based evidence from Italy

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Abstract

This paper provides new empirical evidence on delinking in income–environment dynamic relationships for CO2 and air pollutants at the sector level. A panel dataset based on the Italian NAMEA (National Accounting Matrix including Environmental Accounts) over 1990–2007 is analyzed, focusing on both emissions 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. The overall performance on greenhouse gases, here CO2, is not compliant with Kyoto targets. SOx and NOx show decreasing patterns, though the shape is affected by some outlier sectors with regard to joint emission-productivity dynamics. Services tend to present stronger delinking patterns across emissions than manufacturing. Trade expansion validates the pollution haven in some cases, but also shows 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. General R&D expenditure shows weak correlation with emissions efficiency. SUR estimators (Seemingly Unrelated Regressions) suggest that, as regards manufacturing, the slope varies across sectors. Further research should be directed towards deeper investigation of trade relationship at the sector level and increased research into and efforts to produce specific sectoral data on ‘environmental innovations’.

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Notes

  1. The reasoning surrounding de-coupling can be framed by reference to the EKC model, insofar it describes the state of the dynamic relationship between environmental pressures and economic drivers. This model proposes an inverted U-shaped relationship between per capita income and environmental pressure. The model implies that, in the first stage, an increase in income leads to an increase in environmental pressure. In the second stage, above a certain level of income, the environmental pressure will decrease as the economy is better able to invest in less polluting technology, consumers reallocate expenses in favor of greener products, there are more awareness raising campaigns, etc. Even policies that are aimed at re-shaping the business as usual trend towards more environmentally efficient and sustainable paths are likely to be implemented with an increasing strictness and effectiveness in terms of economic development. At a later stage, there might be a potential re-coupling, observed for some pollutants, where environmental pressure grows in spite of increasing income. The scale effects of growth again will outweigh improvements in the efficiency of resource use and management.

  2. The EKC hypothesis is that, for many pollutants, inverted U-shaped relationships between per capita income and pollution is documented. Along the evolution of the literature, researches have also addressed the possibility that, after the turning point, economies may re-invert the income-environment relationship. The main empirical findings have been justified by a variety of theoretical models based on increasing returns to scale in the abatement of pollution (Andreoni and Levinson 2001), on the Solow growth model (the so-called ‘Green Solow model’ by (Brock and Taylor 2004)), on an endogenous growth model (Dinda 2005), etc. However, some authors (e.g. Borghesi and Vercelli 2009) in a model that links IPAT and EKC frameworks pointed out that an inverted-U shaped relationship between per capita income and pollution might not be enough to meet sustainability targets.

  3. Briefly, the NAMEA approach originated in a series of studies carried out by Statistics Netherlands. The first NAMEA was developed by the Dutch Central Bureau of Statistics (de Boo et al. 1993). In the NAMEA tables environmental pressures (air emissions and virgin material withdrawal) and economic data (value added, final consumption expenditures and full-time equivalent job) are assigned to the economic branches of resident units directly responsible for environmental and economic phenomena. The first Italian (national) NAMEA, referring to 1990 data, was published by ISTAT in 2001. The current NAMEA covers 1990–2007. It is worth noting that, though we are not close to a full NAMEA at EU level given the patchy availability of economic, environmental data by years and countries, EUROSTAT has intensified its commitment: a full EU27 NAMEA is expected to be released by 2011 as a silver bullet of EU strategy on data generation and policy support. It may be used to assess ‘sustainable production and consumption’ performances (Watson and Moll 2008).

  4. We test in addition a sort of Kyoto structural break (post 1997), with possible direct effects on CO2 and indirect effects on SOx and NOx. Italy ratified Kyoto in 2002. Though the two potential structural breaks are temporally intertwined, they refer to different conceptual hypotheses (c and d above). Empirical outcomes are quite similar, as expected. We will discuss the different latent motivations related to the effects of those two time related shocks.

  5. Among the recent work in this area, we refer to Copeland and Taylor (2004) for a general overview on all such integrated issues, and to Cole (2003, (2005), Muradian et al. (2002), Cole et al. (2005) for empirical evidence based on the use of aggregated and disaggregated industry datasets.

  6. STIRPAT is ‘Stochastic Impacts by Regressions on Population, Affluence and Technology’. See Martinez-Zarzoso (2009) who presents some applied analyses deriving from a general model embedding EKC and STIRPAT specifications.

  7. Intended as emissions on labor (Mazzanti and Zoboli 2009).

  8. A U-shape curve could be seen as the right part of a N-shape curve. Egli and Steger (2007) investigate the emergence of recoupling (N-shape curve) in their theoretical model of EKC. They predict that a N-shape curve is the result of a reduction in environmental pressures due to exogenous environmental policies. These policies are implemented when the economy is in the increasing part of the EKC: once the effects of the policies terminate, environmental pressures increase again with income up to the ‘natural’ turning point. This gives rise to a M-shape curve.

  9. Direct effects should be GHG emissions reductions in response to policies introduced to meet the Kyoto target; indirect effects will be related to the anticipatory strategies for future policies on GHGs and, for pollutants, from the ancillary benefits from GHG emissions reductions.

  10. See EEA (2004b), Markandya and Rubbelke (2003), Pearce (1992, 2000) and Barker and Rosendahl (2000) for in depth analyses of such ancillary benefits.

  11. For a review of the theoretical reasoning behind the link between trade openness and emissions growth, we refer among others to Copeland and Taylor (2004), Millock et al. (2008), Frankel and Rose (2005), Cole (2003, 2004, 2005), Cole and Elliott (2003), Dietzenbacher and Mukhopadhyay (2007) and Mazzanti et al. (2008a, b).

  12. Mazzanti and Zoboli (2009), finding negligible effects and Managi et al. (2009), that find how trade openness increases emissions for non OECD countries but ‘abates’ for OECD.

  13. For a review of the literature on the diffusion of innovation through international trade (e.g. innovation embedded in intermediate goods) refer to Keller (2004).

  14. As stated by Cohen and Levinthal (1989), the role of R&D for technological change is twofold. On the one hand, R&D aims to discover new processes, products or routines. On the other hand, R&D is necessary to adopt innovations introduced by other agents. This general consideration applies also in the context of eco-innovation and of environmental technological change.

  15. The merging of R&D and NAMEA data sources is a worthwhile value added exercise. We are aware that R&D expenditure are somewhat endogenous with respect to value added in a dynamic scenario. Two stage analysis might be an alternative possibility. R&D is also the input stage of innovation dynamics: data on real innovation adoptions may be more effective at an empirical level. More relevant, eco-innovations and environmental R&D should be the focus in this framework. Currently, there are no data from official sources that are at a sufficient disaggregated level. Only microeconomic data and evidence on environmental innovation processes are available.

  16. We used SUR estimator only for manufacturing (14 branches for 18 years) because SUR estimator is feasible only when the number of equations (here, number of branches) is lower or equal to the number observations (here, years).

  17. See Zellner (1962, 1963) and Zellner and Huang (1962).

  18. By imposing the same slope for all branches and letting the constants differ across branches.

  19. This test regards the contemporaneous correlation of errors across cross-sectional units. The correlation matrix used in this test is the same as that used by the SUR estimator. The null hypothesis is that the variance-covariance matrix of errors is a unitary matrix (Baum 2001).

  20. The null hypothesis is that the slope is homogeneous across sectors.

  21. δ 3 ln \((E_{st} \it{/VA}_{st})\) enters the residuals.

  22. We refer to Mazzanti and Zoboli (2009), Stern (2004), Berndt and Wood (1979), Koetse et al. (2008).

  23. The main externalities, such as CO2 for GHGs; SOx and NOx for air pollutants. Estimates for PM (particulate matter smaller than 10 microns) are not shown but are available upon request.

  24. See works by Ike (1999), Vaze (1999), de Haan and Keuning (1996) and Keuning et al. (1999), among others, which provide descriptive and methodological insights on NAMEA for some of the major countries. Steenge (1999) provides an analysis of NAMEA with reference to environmental policy issues, while Nakamura (1999) exploits Dutch NAMEA data for a study of waste and recycling along with input-output reasoning. We claim that exploiting NAMEA using quantitative methods may, currently and in the future, provide a major contribution to advancements in EKC and policy effectiveness analyses.

  25. Output and value added are both in current prices and in Laspeyres-indexed prices.

  26. For an exhaustive overview of environmental accounting system, see the so-called ‘SEEA 2003’ (UN et al. 2003).

  27. Exports correspond to the part of the output of each linked Nace branch sold to non-resident units; imports are CPAteco domestically produced items bought by resident units (including households final and intermediate consumption) supplied by non-resident units. Data on national accounting for foreign trade are available from supply (import) and use (export) tables for the period 1995–2005 (Istat). The split between EU15 and extra − EU15 is made by using as weights data on trade from COEWEB (Istat). We could not use directly COEWEB because, for privacy protection reasons, Istat cannot publish data for branches with fewer than three units. Data related to such branches are also excluded from the 4-digit disaggregation of COEWEB or in the less detailed disaggregations.

  28. Both trade (import and export) and value added are at current prices, giving a inflation-corrected index of openness.

  29. Import, export and trade openness, respectively, with partners inside and outside the EU15 area.

  30. ANBERD is Analytical Business Enterprise Expenditure on Research and Development.

  31. CO2 for manufacturing shows an EKC shape with a turning point in the last decile of VA/L and an average linear relationship equal to 0.34 (relative delinking).

  32. Italy is (among EU15) third for total GHGs, 12th for GHGs per capita and 10th for GHGs per GDP and is responsible of 11% of GHGs in the EU27. Current GHGs emissions are 10% higher than the Kyoto target (−6.5% for Italy), and are estimated to be +7.5% to −4.6% in 2010 depending on the measures adopted. German Watch’s Climate change performance index places Italy 44th in the list of 57 States with major CO2 emissions, producing 90% of global GHGs.

  33. The main fact is that K shows decreasing labor productivity, due to the high growth of employment in services and in some sectors, such as K. Employment growth is then higher than value added growth; given that emission efficiency increases, the result is a positive sign captured by panel estimates. This example shows the importance of investigating latent sector dynamics, and the relevance of analyzing the driving forces of decoupling and recoupling trends.

  34. See Fig. 10 for a graphic representation of the role of K as an outlier in the services macro-sector.

  35. As an example, the Italian carbon tax proposal of 1999 was never implemented (Martini 2010).

  36. In the recent debate over the implementation of ETS in Europe, the Italian government claimed that the end (even if gradual) of the ‘grandfathering’ system (the assignment of permits with no payment) would damage the competitiveness of EU (and particularly Italian) manufacturing sectors. In the preliminary negotiation, it obtained exemption from payment of emissions quotas for industrial sectors producing paper (DE), pottery and glass (DI), and steel (DJ). The test of the EKC model separately for those branches highlights the bad performance of paper (elasticity greater than 2), a smaller delinking in comparison with manufacturing for pottery and glass (elasticity just below 1) and a robust absolute delinking for steel. According to this evidence, while an exemption would seem appropriate for paper, its justification for pottery, glass and especially steel is less clear.

  37. We are grateful to one referee for the hint.

  38. The use of heterogeneous estimators can be motivated by the possible heterogeneity bias associated with the use of pooled estimators. As pointed out by Hsiao (2003), if the true model is characterised by heterogeneous intercepts and slopes, estimating a model with individual intercepts but common slopes could produce the false inference that the estimated relation is curvilinear. Empirically, this situation is more likely when the range of the explanatory variables varies across cross-sections. This situation corresponds to our empirical framework where: i) VA presents high variation across sectors, ii) the different units cannot be characterized by a common slope and, consequently, there is a high risk of estimating a false curvilinear relation when using homogeneous estimators.

  39. As far as paper & cardboard (DE) is concerned, we refer to the analysis regarding the implementation of ETS and its innovation potential in the sector in Pontoglio (2010). Results show that the Italian paper industry has adopted a wait and see strategy, characterized by conservative and cautious decision making and use of time-flexibility solutions. These are having modest outcomes in terms of innovation. Carbon dioxide emitted by energy-intensive industries cannot be reduced through the use of low-cost end-of-pipe abatement solutions; they require improvements in energy-efficiency and investment in renewable energy.

  40. Future analyses should be directed to use different indicators (such as emissions per value added, more suitable to identify trade-offs/complementarities that emissions per worker) in order to identify possible differences in the results.

  41. If we exclude branch DF, the relationship becomes linear and negative, denoting an absolute delinking. See Fig. 11 for a graphic representation of the role of DF as outlier in the manufacturing estimations for NOx.

  42. A sort of potential ‘hot air’ scenario such as occurred in eastern EU countries in the 1990s.

  43. Very significant for both pollutants, but larger for SOx. We note that, in line with the work cited in the first part of the paper, GHGs and pollutant reductions are often integrated. Climate change related actions lead to ancillary benefits in terms of local pollutant reductions. The more we shift from end of pipe solutions to integrated process and product environmental innovations, the higher the potential for complementary dividends.

  44. Except for EU15 for NOx.

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Acknowledgements

We thank Cesare Costantino, Angelica Tudini and the Istat Environmental Accounting Unit in Rome for the excellent work of providing yearly updated NAMEA matrices and for valuable comments. We acknowledge also two anonymous referees and all people who commented this paper in EA-SDI Conference (Prague) 2009, DRUID Summer Conference (Copenhagen) 2009, EAERE Conference (Amsterdam) 2009, ESEE Conference (Ljubljana) 2009 and 50th Meeting of the SIE (Rome) 2009.

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Authors and Affiliations

  1. IMT Advanced Studies Lucca, Piazza S. Ponziano, 6, 55100, Lucca, Italy

    Giovanni Marin

  2. University of Ferrara, Ferrara, Italy

    Massimiliano Mazzanti

  3. Ceris CNR National Research Council, Milan, Italy

    Massimiliano Mazzanti

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  1. Giovanni Marin
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  2. Massimiliano Mazzanti
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Correspondence to Giovanni Marin.

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Marin, G., Mazzanti, M. The evolution of environmental and labor productivity dynamics. J Evol Econ 23, 357–399 (2013). https://doi.org/10.1007/s00191-010-0199-8

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  • DOI: https://doi.org/10.1007/s00191-010-0199-8

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