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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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Competitiveness has become one of the most prominent catchwords in economics. Yet, the notion of competitiveness misses a well-defined conceptual framework and remains rather susceptible for ambiguities. As a basic orientation, scientific research distinguishes between competitiveness determinants governing the ability to compete and competitiveness indicators describing the outcome of competitiveness such as international trade performance or profitability (Reichel 2002, Aiginger 2006). For our impact assessment of climate policy interference, we adopt the outcome-based competitiveness notion and review the literature on appropriate sectoral and economy-wide competitiveness indicators.

2.1 Sectoral competitiveness indicators

The most widespread definition of sectoral competitiveness refers to a sector’s “ability to sell in international markets” (Jaffe et al. 1995, Jenkins 1998, Xu 2000, Babool and Reed 2010). International competitiveness, defined in terms of foreign trade performance, is thereby closely linked with international trade theory in general and the concept of comparative advantage in particular. According to the latter, countries are likely to export those goods and services in which they have a comparative cost advantage.

The concept of a (revealed) comparative advantage has been interpreted as a “revealed competitive advantage” where industries with a comparative (cost) advantage are considered as internationally competitive (Jenkins 1998, Fertö and Hubbard 2003, Ahrend et al. 2007, Cai and Leung 2008).

An alternative definition of sectoral competitiveness refers to a sector’s “ability to be profitable” (Sell 1991, EU 2005). This definition reflects the capacity to sell profitably in national and international markets.

Cost pressure may not be (immediately) reflected in increasing prices as profits could play a buffer role to keep the market shares constant.2 Table 1 provides a list of sectoral competitiveness indicators for measuring the “ability to sell in international markets” and the “ability to be profitable”. Indicators on international trade performance are either based on trade data or a combination of trade and production (consumption) data. Contrary to indicators of international trade performance, the empirical implementation of indicators to measure profitability is more difficult due to limited availability of appropriate data (EU 2005). Harvey (2003) suggests three types of profitability indicators at the industrial level using national accounts data: profit detect divergences between member states and provide timely policy reactions (EU 2010).

See Demailly and Quirion (2006, 2008), Smale et al. (2006) or Sato et al. (2007) for recent sector-specific applications of this concept to the EU ETS.

margin (profit over sales), rates of return (profit over capital stock) and profit shares (profit over total factor expenditures).

Table 1: List of competitiveness indicators at the sectoral level

–  –  –

2.2 Economy-wide competitiveness indicators At the economy-wide level the concept of competitiveness is discussed controversially. One of the most prominent opponents, Paul Krugman, argues that „competitiveness is a meaningless word when applied to national economies” (Krugman 1994). Contrary to such fundamental criticism, competitiveness concepts at the economy-wide level are widely used in scientific studies (see Porter 1990 for an early contribution) and the public policy debate3. There are meanwhile numerous surveys of competitiveness notions at the economy-wide level (see e.g. Reichel 2002, Aiginger 2006 or Siggel 2007).

The conventional interpretation of national competitiveness – analogous to the “ability to sell” notion at the sectoral level – focuses on a country’s international trade performance (Durand and Giorno 1987, Fagerberg 1988, Nielsen et al. 1995). The traditional focus on “ability to sell” has shifted in the recent literature towards more general measurement concepts linked to normative economics. The argument The ranking of countries by competitiveness draws more and more policy attentions (see e.g. the Global Competitiveness Report issued by the World Economic Forum or the Doing Business Report established by the World Bank).

behind this shift is that the emphasis on international trade can be misleading as trade may represent only a small fraction of GDP and one-sided export orientation is not sustainable. Furthermore, expansion of exports – as an indicator of competitiveness – might have its origin in low wages, subsidies or weak currency resulting in lower standards of living in the country. The real matter then becomes “the ability to earn”, i.e. the ability to create wealth or high standards of living as a central dimension of national competitiveness (Jenkins 1998, EU 2004, Grilo and Koopman 2006, Aiginger 2006). Grilo and Koopman (2006) argue that international trade performance is only an appropriate competitiveness indicator at the sectoral level whereas competitiveness at the national level should be rigorously linked to welfare metrics such as GDP per capita or real consumption.

Dollar and Wolff (1993), Auerbach (1996), Reichel (2002), Hildebrandt and Silgoner (2007) and ECB (2009) take an intermediate position referring to both “ability to sell” and “ability to earn”. They suggest that changes in competitiveness at the economy-wide level measured by international performance indicators shall not be interpreted in isolation, but rather in combination with a country’s economic development and/or standards of living. The underlying argument is that the rise in living standards can be attributed to improved competitiveness at the national level as measured by the international trade performance indicators. Table 2 provides a summary of economy-wide competitiveness indicators.





Table 2: List of competitiveness indicators at the economy-wide level

–  –  –

 (Real effective) exchange rate References: Vitek (2009) The final conclusion which can be drawn from literature on competitiveness indicators to measure international trade performance is that it is not possible to identify a single valid measure from a theoretical (including normative) and empirical perspective.

3 Method for quantitative impact assessment To quantify the economic implications of unilateral climate policies on competitiveness and welfare, we make use of a multi-sector, multi-region computable general equilibrium (CGE) model of global trade and energy use. CGE models build upon general equilibrium theory that combines behavioural assumptions on rational economic agents with the analysis of equilibrium conditions. They provide counterfactual ex-ante comparisons between a reference situation without policy intervention and the outcome triggered by policy reforms. The main virtue of the CGE approach is its comprehensive micro-consistent representation of price-dependent market interactions. The simultaneous explanation of the origin and spending of the agents’ income makes it possible to address both economy-wide efficiency as well as distributional impacts of policy interference. The disaggregation of macroeconomic production, consumption and trade activities at the sector level based on national input-output accounts accommodates a coherent cross-comparison of economic performance between sectors and a trade-off analysis with economy-wide welfare. Changes in economic welfare are usually expressed in terms of the Hicksian equivalent variation (HEV) in income.4 Beyond an appropriate sectoral disaggregation, a multi-region setting is indispensable for the economic impact analysis of climate policy interference: In a world which is integrated through trade, policy interference in larger open economies not only causes adjustment of domestic production and consumption patterns but also influences international prices via changes in exports and imports. The changes in international prices, i.e., the terms of trade, imply secondary effects that can significantly alter the impacts of the primary domestic policy (Böhringer and Rutherford 2002). The international dimension is also a prerequisite to track sectoral and economy-wide competitiveness implications related to the international trade performance.

Section 3.1 provides a non-technical overview of the basic CGE model structure adopted for our impact analysis of unilateral climate policies (for an algebraic summary see Böhringer and Rutherford 2010).

Section 3.2 lays out the data sources in use for empirical parameterisation.

Section 3.3 describes the CGE implementation of selected competitiveness indicators at the sector level – i.e. relative world trade shares (RWS) and revealed comparative advantage (RCA) – and the economy-wide level, i.e. the terms of trade (ToT) and real consumption. These competitiveness indicators are used in our numerical simulations in order to illustrate the meaningfulness and potential pitfalls of competitiveness analysis.

The Hicksian equivalent variation in income denotes the amount which is necessary to add to (or deduct from) the benchmark income of the consumer so that she enjoys a utility level equal to the one in the counterfactual policy scenario on the basis of ex ante relative prices.

–  –  –

Figure 1 provides a diagrammatic structure of the static multi-sector, multi-region CGE model in use for

our numerical analysis. A representative agent RAr in each region r is endowed with three primary factors:

labour Lr, capital K r and specific resources Qfr (the latter used for the production of fossil fuels f such as coal, gas and crude oil).

Figure 1: Diagrammatic overview of the model structure

–  –  –

Labour and capital are assumed to be intersectorally mobile within a region but immobile between regions.

Fossil-fuel resources are specific to fossil fuel production sectors in each region. Production Yir of commodity i in region r is captured by three-level constant elasticity of substitution (CES) cost functions describing the price-dependent use of capital, labour, energy and material in production. At the top level, a CES composite of intermediate material demands trades off with an aggregate of energy, capital and labour subject to a constant elasticity of substitution. At the second level, a CES function describes the substitution possibilities between demand for the energy aggregate and a value-added composite of labour and capital. At the third level, capital and labour substitution possibilities within the value-added composite are captured by a CES function whereas different energy inputs (coal, gas, oil and electricity) enter the energy composite subject to a constant elasticity of substitution. In the production of fossil fuels all inputs, except for the sector-specific fossil fuel resource, are aggregated in fixed proportions. This aggregate trades off with the sector-specific fossil fuel resource at a constant elasticity of substitution. The latter is calibrated to be generally consistent with empirical estimates for the supply elasticity of the specific fossil fuel.

Final consumption demand Cr in each region is determined by the representative agent who maximises utility subject to a budget constraint with fixed investment (i.e. a given demand for savings) and exogenous government provision of public goods and services. Total income of the representative household consists of net factor income and tax revenues. Consumption demand of the representative agent is given as a CES composite which combines consumption of non-electric energy and composite of other consumption goods.

Substitution patterns within the non-electric energy bundle are reflected by means of a CES function; other consumption goods trade off with each other subjected to a constant elasticity of substitution.



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