Sector CO2 and SOx emissions efficiency and investment: homogeneous vs heterogeneous estimates using the Italian NAMEA

Marin, Giovanni (2010): Sector CO2 and SOx emissions efficiency and investment: homogeneous vs heterogeneous estimates using the Italian NAMEA.

Abstract

The relationships between emissions ad economic drivers differ substantially both across countries and across sectors. In this paper I investigate cross-sector heterogeneity of emissions (CO2 and SOx) / investments relationships of Italian branches for the period 1990-2006 by using the Italian NAMEA (National Accounting Matrix including Environmental Accounts). The ‘environmental’ direction of investments in different types of capital goods is crucial in the prediction of future patterns of environmental efficiency due to the persistence of the choices regarding the features of the capital stock. Within this relationship, the role of variations in prices of energy fuels and in environmental taxes is considered to identify relevance and the direction of the technical changes induced by prices and taxes. I compare homogeneous estimates (FE) with heterogeneous estimates (SUR): homogeneity of slopes across branches is always rejected (aggregation bias). Furthermore, results differ substantially between CO2 and SOx, due to different environmental and economic features of the two types of emissions. Results show a relevant role of economic forces (investments) in explaining CO2 dynamics while SOx trends are determined to higher extent by exogenous events. The potential role of ICTs in promoting more environmental efficient production processes has not been exploited yet by Italian manufacturing sectors.

• Item Type: MPRA Paper
• Language: English
• Keywords: NAMEA; SUR; eco-innovation; emissions efficiency
• Subjects: Q - Agricultural and Natural Resource Economics ; Environmental and Ecological Economics > Q5 - Environmental Economics > Q55 - Technological Innovation; O - Economic Development, Innovation, Technological Change, and Growth > O3 - Innovation ; Research and Development ; Technological Change ; Intellectual Property Rights > O33 - Technological Change: Choices and Consequences ; Diffusion Processes; C - Mathematical and Quantitative Methods > C3 - Multiple or Simultaneous Equation Models ; Multiple Variables > C33 - Panel Data Models ; Spatio-temporal Models

References

Carrion-Flores C, Innes R (2010) Environmental innovation and environmental performance. Journal of Environmental Economics and Management 59:27–42

Cole MA, Elliott RJ, Shimamoto K (2005) Industrial characteristics, environmental regulations and air pollution: an analysis of the UK manufacturing sector. Journal of Environmental Economics and Management 50(1):121–143

Cole MA, Elliott RJ, Wu S (2008) Industrial activity and the environment in China: An industry-level analysis. China Economic Review 19(3):393–408

Marin G, Mazzanti M (2009a) The dynamics of delinking in industrial emissions: The role of productivity, trade and R&D. Journal of Innovation Economics 0(1):91–117

Marin G, Mazzanti M (2009b) Emissions trends, labour productivity dynamics and time related events - sector heterogeneous analyses of decoupling/recoupling on a 1990-2006 NAMEA. Quaderni del Dipartimento di Economia, University of Ferrara (Italy) no. 18

Mazzanti M, Zoboli R (2009) Environmental efficiency and labour productivity: Trade-off or joint dynamics? A theoretical investigation and empirical evidence from Italy using NAMEA. Ecological Economics 68(4):1182–1194

Mazzanti M, Montini A, Zoboli R (2008) Environmental Kuznets curves for air pollutant emissions in Italy: Evidence from environmental accounts (NAMEA) panel data. Economic Systems Research 20(3):277–301

OECD (2009a) Converence proceedings: ICTs, the environment and climate change. OECD, Paris, November 2009

OECD (2009b) Measuring the relationship between ICT and the environment. OECD, Paris, July 2009

OECD (2009c) Towards green ICT strategies - assessing poilicies and programmes on ICT and the environment. OECD, Paris, June 2009

Popp D (2002) Induced innovation and energy prices. American Economic Review 92(1):160–180

Popp D, Newell RG, Jaffe AB (2009) Energy, the environment, and technological change. NBER Working Papers, National Bureau of Economic Research, Inc

United Nations, European Commission, International Monetary Fund, OECD, World Bank (2003) Integrated environmental and economic accounting 2003. First draft, United Nations, European Commission, International Monetary Fund, OECD, World Bank

Zellner A (1962) An efficient method of estimating seemingly unrelated regressions and tests for aggregation bias. Journal of the American Statistical Association 57(298):348–368

Zellner A (1963) Estimators for seemingly unrelated regression equations: Some exact finite sample results. Journal of the American Statistical Association 58(304):977–992

Zellner A, Huang DS (1962) Further properties of efficient estimators for seemingly unrelated regression equations. International Economic Review 3(3):300–313