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«Christoph Böhringera and Victoria Alexeeva-Talebib a University of Oldenburg b Centre for European Economic Research, Mannheim Emails: ...»

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Bilateral trade is specified following the Armington approach of product heterogeneity, i.e. domestic and foreign goods are distinguished by origin (Armington 1969). All goods used on the domestic market in intermediate and final demand correspond to a CES composite Air which combines the domestically produced good (Yir) and the imported composite (Mir) from other regions. Domestic production is split between input to the formation of the Armington good and exports to other regions subjected to a constant elasticity of transformation. The balance of payment constraint which is warranted through flexible exchange rates incorporates the base-year trade deficit or surplus for each region.

Carbon emissions are linked in fixed proportions to the use of fossil fuels; thereby carbon coefficients are differentiated by the specific carbon content of fuels. Restrictions to the use of carbon emissions in production and consumption are implemented through carbon taxes or exogenous emission constraints which keep carbon emissions to a specified limit. Carbon emission abatement then takes place by fuel switching (inter-fuel substitution) and energy savings (either by fuel-non-fuel substitution or by a scale reduction of production and final demand activities).

3.2 Data

The model is based on the most recent consistent accounts of region- and sector-specific production, consumption, bilateral trade and energy flows as provided by the GTAP 7 data base for the year 2004 (Badri and Walmsley 2008). The GTAP data base features rudimentarily initial tax distortions. In our numerical analysis, we therefore abstain from the explicit representation of initial taxes. As to the sectoral and regional model resolution, the GTAP database is aggregated towards a composite dataset which accounts for the specific requirements of international climate policy analysis. At the sectoral level, the model captures details on sector-specific differences in factor intensities, degrees of factor substitutability and price elasticities of output demand in order to trace the structural change in production induced by policy interference. The energy goods identified in the model are coal, crude oil, natural gas, refined oil products and electricity. This disaggregation is essential in order to distinguish energy goods by carbon intensity and degree of substitutability. The model then incorporates explicitly carbon-(energy-)intensive commodities with significant shares of international trade that are potentially most affected by unilateral climate policies and are subject to competitiveness and leakage concerns: paper, pulp and print; chemical products; mineral products; iron and steel; non-ferrous metals and air transport. These sectors together with refined oil products are referred to as EITE industries in our numerical analysis below. The remaining sectors are summarised through a composite of all other industries and services. With respect to the regional disaggregation, the model includes the European Union (EU) together with other major industrialised and developing regions that are key players in international climate negotiations and at the same time intertwined through bilateral trade links: the United States of America, Japan, Russia, the rest of OECD, China, India, Brazil, the organisation of oil exporting countries (OPEC) and a composite region for the rest of the developing world. Table 3 summarises the regional, sectoral and factor aggregation of the model.

Elasticities in international trade (Armington elasticities) are based on empirical estimates reported in the GTAP7 database. Substitution elasticities between production factors capital, labour, energy inputs and non-energy inputs (material) are taken from the econometric study by Okagawa and Ban (2008) who use the most recent panel data across sectors and industries for the period 1995 to 2004.

Table 3: Model dimensions

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3.3 CGE implementation of competitiveness indicators For our illustrative analysis of competitiveness effects triggered by unilateral climate policy, we implement a set of widely used competitiveness indicators: relative world trade shares (RWS) and revealed comparative advantage (RCA) in order to measure sectoral competitiveness effects and terms of trade (ToT) as well as real consumption to measure economy-wide competitiveness effects.

Letting X denote exports, P x export prices, r the region and i the sector, the RWS index for sector i in

region r can be written as follows (Balassa 1965, Reichel 2002):

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This index compares the ratio of a country’s exports in a certain sector to the world’s exports in this sector with the ratio of a country’s overall exports to the world’s exports in all sectors. If the sectoral exportimport ratio is identical to the economy-wide ratio, the RWS index takes the value of one ( RWSir  1 ). A region r is said to have a comparative advantage in sector i if the RWS index exceeds unity ( RWSir  1 ).

Conversely, a region r has a comparative disadvantage in sector i if the RWS index takes the values between zero and one ( 0  RWSir  1 ).

The validity of RWS as a general indicator for international trade performance is sometimes questioned because import flows are not taken into account. As an alternative metric, we therefore consider the revealed comparative advantage (RCA) indicator. The RCA index provides a measure for competitiveness of different industries within an economy. With the additional notations of P m for import prices and M for

imports, the RCA index for sector i in region r is defined as follows (Balassa 1965, Reichel 2002):

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For a particular region and sector, this index compares the ratio of exports by a specific sector to its imports with the ratio of exports to imports across all sectors of the region. The RCA indicator ranges from 0  RCAir   and can be interpreted regarding the range for comparative (dis-)advantage similarly to the RWS indicator.

While both sectoral indicators, RWS and RCA, purport to measure comparative advantage of a particular industry, they vary with respect to the point of reference: The RWS indicator measures how the relative performance of a particular sector in the country r changes compared to the relative performance of the same sector across the world. The RCA indicator compares the performance of a particular sector with performance of all sectors within the same region. In a partial equilibrium perspective, increases in exports X ir of sector i in region r result ceteris paribus in increasing competitiveness according to RCAir and RWSir indicators. Vice versa, increasing imports will ceteris paribus decrease sectoral competitiveness.

While RCA and RWS provide information on the quality and intensity of competitiveness implications at the sector level, they can neither be used to commensurate impacts across sectors nor as a general indication of economy-wide welfare effects.

At the economy-wide level, we implement a terms-of-trade (ToT) indicator to monitor competitiveness implications for international trade performance. The ToT indicator is defined as a Laspeyres index measuring the ratio of the price index of exports to the price index of imports in which prices are weighted

by the base-year quantities of exports X ir and imports M ir (see e.g. Krueger and Sonnenschein 1967):

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whereas Pirx and Pirx ( Pirm and Pirm ) represent current and base-year export (import) prices, respectively.

Terms of trade deteriorate as the indicator decreases; terms of trade improve as the indicator increases.

Finally, the level of real consumption – as our alternative competitiveness indicators at the economy-wide level – is incorporated as an explicit activity variable in the CGE model. It directly captures welfare implications based on the CES expenditure function for final consumption goods.

4 Impact assessment of unilateral EU climate policies

Our standard CGE framework, complemented with competitiveness indicators at the sectoral and economywide level, facilitates a comprehensive impact assessment of unilateral climate policies. The major drivers of economic impacts triggered by emissions constraints include (i) the stringency of the emissions reduction target, (ii) the policy implementation, (iii) the ease of emission abatement in production as well as consumption and (iv) spillover and feedback effects from international markets that emerge from policy action of larger economies.

We capture dimensions (i) and (ii) in the specification of our climate policy scenarios reflecting the ongoing debate on the stringency of emission reduction pledges and preferential treatment of emissionintensive and trade-exposed (EITE) industries. Firstly, we vary the unilateral reduction target of the EU between 5%, 10%, 15%, 20%, 25% and 30% as compared to the reference emission level without climate policy action (the so-called business-as-usual, BaU). Higher reduction targets thereby go along with a more ambitious role of EU leadership in the fight against climate change. Secondly, we allow for differential emission pricing in favour of EITE industries, thereby mimicking actual policy legislation to ameliorate adverse competitiveness effects for these sectors.5 In our simulations, the emission price ratio between the remaining segments of the economy, on the one hand, and the EITE industries, on the other hand, ranges from unity (i.e. uniform emissions pricing), via factors of 2, 5, 10 and 20 to full exemption of EITE industries. Ratios higher than one indicate that emissions prices are discriminated in favour of EITE sectors – for example, a ratio of 20 implies that the carbon price in the rest of the economy is twenty times higher than that for the EITE industries. The emission price level is thereby endogenously adjusted to warrant overall compliance with the exogenous EU-wide emission reduction target.

The remaining dimensions (iii) and (iv) are inherent to our CGE model framework: The ease of emission substitution in production and consumption is implicit to the top-down representation of technologies and preferences. That is through continuous functional forms that describe trade-offs between inputs (outputs) based on empirically estimated substitution (transformation) elasticities. The international spillover effects are captured through explicit bilateral trade relations between key trading partners at the sectoral level.

Policy-induced changes in international prices, i.e. the terms of trade, may allow a country to shift part of its domestic abatement cost to trading partners or conversely suffer from a deterioration of its terms of trade (on top of purely domestic adjustment cost in the absence of terms-of-trade effects). International spillover effects furthermore provide the background for leakage concerns in the case of unilateral climate policies and the claim for preferential treatment of EITE sectors to reduce emission leakage.

For our graphical exposition of simulation results, we use bar diagrams along the different unilateral emissions abatement targets and the alternative emission price ratios. Note that in the graphs we refer to the case of full emission price exemptions in favour of EITE sectors with the label “ex”. The primary interest of our quantitative analysis is to highlight the pending trade-offs between economic performance across sectors (in terms of output and competitiveness indicators) and overall economic efficiency (in terms of real consumption) as a function of environmental stringency and preferential treatment of EITE industries. In this way, we can complement the often narrowly focused debate on competitiveness effects for EITE industries with insights on cost shifting to other segments of the economy and potential excess cost of environmental regulation. As it is customary in applied equilibrium analysis most of our results are reported in terms of percentage changes in economic indicators compared to a reference situation without climate policy interference – the BaU. Our reference situation is one without climate policies, i.e. the historical outcome of the base year of the model 2004. Note that this was before the EU emissions trading system has been implemented and before the Kyoto Protocol entered into force.

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