یک روش ترکیبی ورودی و خروجی و تجزیه و تحلیل حساسیت برای تحلیل ارتباطات بخشی و تولید گازهای گلخانه ای CO2

This paper proposes a methodology which identifies the main productive linkages between activity branches in terms of CO2 emissions and applies this methodology to the Spanish case. It suggests that emissions are related to the input–output productive relationships within an economy, to the CO2 emissions intensity of sectors and to the structure of final demand of different sectors. A formal analysis of these factors is carried out by means of an input–output framework combined with sensitivity analysis and lineal programming. The most CO2 emissions-intensive productive relationships in Spain are shown. This consideration of the main linkages contributes to the identification of the key-sectors and facilitates the design of effective policy measures aimed at CO2 emissions abatement.

Different economic, social, behavioural, cultural and technological factors affect a country's CO2 emissions. Analysing the internal production factors causing CO2 emissions in an economy is both a pertinent and relevant effort because it may help decision-makers identify the most effective policy measures to curb CO2 emission trends. This is particularly relevant for those countries on the way to overshoot their Kyoto Protocol targets because it helps identify the basket of most effective mitigation policy alternatives. This paper provides a methodology which allows the identification and assessment of the sources of CO2 emissions, and applies it to the Spanish economy. For this task, we use an input–output methodology, combined with sensitivity analysis and lineal programming. Applying input–output techniques allows us to trace the direct and indirect CO2 emissions associated with a product, and to assess the carbon embodied in a product (Machado et al., 2001). Indirect emissions are those not actually caused by an agent but by the agent's demand and include the energy/carbon related to all the inputs directly and indirectly involved in the supply chain (Mongelli et al., 2006). Therefore, also the CO2 emissions induced in the other sectors linked to the “key” sector are taken into account, in the sectors linked to these and so on. It is thus not possible to estimate the actual emitters by considering a single sector. Other approaches do not allow us to look so deep into the internal productive linkages within an economy with implications on CO2 emissions. The methodology we develop is applied to the case of Spain. The key sectors and linkages between sectors leading to CO2 emissions are identified. These emissions might be related to different causes. This could help policy makers propose a wise combination of measures targeted at encouragement of less CO2 emissions intensive technological changes and measures targeted at behavioural change. Accordingly, the paper is structured as follows. A background on the methodology and the links to existing literature is considered in the next section. Section 3 provides the details of the model, which will be empirically applied to the Spanish economy in Section 4. The main limitations of this exercise are considered in Section 5. The paper closes with some concluding remarks and policy recommendations. 2. Aim, methodology, main assumptions and links to existing literature The aim of this paper is to propose a methodology to identify the main backward and forward linkages between activity branches leading to CO2 emissions.1 An important assumption is that, at least, three major types of productive linkages can explain the level of CO2 emissions in an economy2: – The technology–production linkage factor. The level and evolution of CO2 emissions is closely related to the input–output relationships within an economy. The sales of one activity branch to another might cause higher emissions than its sales to other sectors. Therefore, the emissions intensity of production linkages between the different branches is worth exploring. – Sectoral CO2emissions intensity. Within each sector, a unit of production might lead to lower or higher emissions, depending on the technology and/or process used. The diffusion rate of less CO2-intensive technologies differs within the same sector in different countries. Ceteris paribus, policy mitigation efforts would be relatively more effective in sectors with higher CO2 intensities. – Demand factor. The structure of a sector's final demand also affects its CO2 emissions. A one per cent increase in the demand for the products of one sector may cause a larger increase in total emissions that a one per cent increase in the demand for the products of other sectors. The final demand components (household consumption, public consumption, investment, exports…) which contribute most to CO2 emissions increases should be identified. Previous papers and models have used an input–output approach to analyse CO2 emissions in sectors.3 Those models usually distinguish between emissions from imports and emissions from the domestic production of energy, goods and services. A distinction is sometimes made between emissions from production which meets demand in the country and emissions from exports of such production (Machado et al., 2001, Munksgaard and Pedersen, 2001 and Ferng, 2003). The hypothesis of fixed structural coefficients (and constant economic structure) is usually assumed but does not allow an analysis of changes in emissions as a result of changes in the economic and technical structure of the economy. That approach only analyses the impact on emissions of a change in demand flows. In contrast, our paper adopts a wider approach and analyses the change in the aforementioned factors. Structural decomposition techniques, which analyse changes in the economic structure, represent an alternative approach (see Treloar, 1997, Sun, 1999, Luukkanen and Kaivo-oja, 2002 and Kaivo-oja and Luukkanen, 2004). From this point of view, some authors consider how changes in energy consumption and GHG emissions depend on the changes in the demand flows as well as the coefficients variations between two time periods.4 Both the homogeneous input–output tables of such time periods at constant prices and the emissions vectors should be available. The advantages of our approach are that only one input–output table and the vector of emissions per activity branch are needed and that an analysis of the structure of final demand (and not only of intersectoral relationships) is carried out.5 Some authors have applied an input–output approach to analyse Spanish CO2 emissions in the past (Labandeira and Labeaga, 2002 and Alcántara and Padilla, 2003). By identifying those structural coefficients most sensitive to CO2 emissions and the structural linkages and key CO2 emissions sectors, this paper provides an alternative approach. It is more comprehensive, since it takes into account all sources of CO2 emissions in all sectors of the economy. All in all, our methodology is complementary to those studies.6

This paper proposes a methodology combining input–output tables and a sensitivity analysis of the intersectoral production structure to identify the systemic sources of CO2 emissions within the production structure. It determines which economic transactions lead to the highest emissions levels and identifies those production linkages through which these emissions spread all over the economic system. It suggests three indicators which are deemed relevant to identify the most CO2 emissions-intensive backward and forward productive linkages. This approach has several advantages with respect to other methodologies. It extends the analysis to the final demand matrix and it allows us to obtain the most important elements in terms of emissions and not in terms of production, which is usually the case. However, it is not an alternative but rather a complement to other approaches. The empirical study shows the relevance of certain “key” sectors in the structure of total Spanish CO2 emissions. The results confirm that emissions in the energy, residential and transport sectors should be tackled if total emissions are to be significantly reduced. The paper points to the need for effective public policies to tackle both ends of the spectrum (final consumers and producers) with a mix of measures targeted at, both, behavioural and technological changes. The diversity and complexity of CO2 emissions sources points to a policy strategy combining different types of instruments applied to the key sectors. The proposed approach can be relevant to design integrated policy packages aimed at emissions mitigation, although it should be complemented with analysis of emissions abatement costs along distinct production routes.