IPCC Fourth Assessment Report: Climate Change 2007
Climate Change 2007: Working Group III: Mitigation of Climate Change Macro-economy and trade

Macro-economic policies such as exchange rate policies, fiscal policies, government budget deficits, or trade policies may have profound impacts on the environment, even though they are designed for other purposes. This link has been extensively studied in the past decades, notably in the context of the evaluation of structural adjustment programmes in developing countries. A key finding from this literature is that the relationship between macro-economic policies and the environment are often complex and country-specific, and depend on whether or not other market or institutional imperfections persist (Munasinghe and Cruz, 1995; Gueorguieva and Bolt, 2003). No case studies discuss the impact of structural adjustment on GHG emissions, but some discuss the relationship between structural adjustment and deforestation and thus, by extension, GHG emissions from land-use change. Again, the effects depend on the mix of policies adopted as part of the structural adjustment programmes, and of country-specific characteristics. For example, Kaimovitz et al. (1999) report that the structural adjustment programmes implemented in Bolivia in 1985 strongly increased profitability of soybean production, and led to massive deforestation in soybean producing areas. Symmetrically, Benhin and Barbier (2004) find that a structural adjustment programmes implemented in Ghana in 1983 led to a reduction of deforestation linked to extension of cocoa culture because, among others, of increased producer price for cocoa, higher availability of inputs, and other measures aimed at rehabilitating existing cocoa farms. Another channel through which structural adjustment programmes could impact on deforestation is through the timber market. Pandey and Wheeler (2001) analyse cross-country data on the markets for wood products in countries where World Bank supported adjustment programmes were implemented. They find that these programmes greatly affect imports, exports, consumption and production in many forest product sectors, but that the impacts on deforestation tend to cancel out. If domestic deforestation does not increase, however, imports of wood products do, suggesting increased pressures on forest in other countries. Finally, as also noted above, Pandey and Wheeler (2001) find that currency devaluation strongly increases the exploitation of forest resources.

Among macro-economic policies, trade policies have attracted particular attention in recent years, due to the fact that international trade has increased dramatically over the past decades. There is a general consensus that, in the long-run, openness to trade is beneficial for economic growth. However, the pace of openness, and how to cope with social consequences of trade policies are subject to much controversy (Winters et al., 2004). Trade has multiple implications for GHG emissions. First, increased demand for transportation of goods and people generates emissions. For example, freight transport now represents more than a third of the total energy use in the transportation sector (see Section 5.2.1). Secondly, trade allows countries to partially ‘de-link’ consumption from emissions, since some goods and services are produced abroad, with opposite implications for the importing and exporting countries. For example, Welsch (2001) shows that foreign demand for German goods accounts for nearly a third of the observed structural changes in the composition of output and decrease in emissions intensity of West Germany over the period 1985-1990. At the other end, Machado et al. (2001) report that inflows and outflows of carbon embodied in the international trade of non-energy goods in Brazil accounted for some 10% and 14%, respectively, of the total carbon emissions from energy use of the Brazilian economy in 1995. And the game is often not zero-sum, when production technologies are less carbon-efficient in the exporting country than in the importing one. For example, Shui and Harriss (2006) estimate that USA-China trade represents between 7% and 14% of China’s total CO2 emissions, and that USA-China trade increases world emissions by an average of 100 MtCO2-eq per year over the period 1997-2003 because of higher emissions per kWh and less efficient manufacturing technologies in China. Finally, policies favourable to trade have been accused of favouring the relocation of companies to ‘pollution heavens’ where environmental constraint would be lower. Empirical analysis, however, do not confirm the ‘race to the bottom’ hypothesis (Wheeler, 2001). See also Section 11.7. Some general insights on the opportunities to change development pathways at the sectoral level

Although the examples discussed above are very diverse, some general patterns emerge. First, in any given country, sectors where effective production is far below the maximum feasible production with the same amount of inputs – sectors that are far away from their production frontier – have opportunities to adopt ‘win-win-win’ policies. Such policies free up resources and bolster growth, meet other sustainable development goals, and also, incidentally, reduce GHG emissions relative to baseline. Among the examples discussed above, the removal of energy subsidies in economies in transition, or the mitigation of urban pollution in highly polluted cities in the developing world pertain to the ‘win-win-win’ category. Of course, these policies may have winners and losers, but compensation mechanisms can be designed to make no-one worse off in the process.

Conversely, sectors where production is close to the optimal given available inputs – sectors that are closer to the production frontier – also have opportunities to reduce emissions by meeting other sustainable development goals. However, the closer to the production frontier, the more trade-offs are likely to appear. For example, as discussed above, diversifying energy supply sources in a country where the energy system is already cost-efficient might be desirable for energy security reasons and/or for local or global environmental reasons. But it might come at a cost to the country if, for example, diversification involves more expensive technologies or more risky investments (Dorian et al., 2006).

Third, in many of the examples reviewed above, what matters is not only that a ‘good’ choice is made at a certain time, but also that the initial policy has persisted for a long period – sometimes several decades – to truly have effects. The comparison between the development of European and USA cities since the end of World War II is a case in point. The reason is that some of the key dynamics for GHG emissions, such as technological development or land-use patterns, present a lot of inertia, and thus need sustained effort to be re-oriented. This raises deep institutional questions about the possibility of governments to make credible long-term commitments, particularly in democratic societies where policy-makers are in place only for short spans of time (Stiglitz, 1998).

A fourth element that stems from some of the examples outlined above is that often not one policy decision but an array of decisions are necessary to influence emissions. This is especially true when considering large-scale and complex dynamics such as the structure of cities or the dynamics of land-use. This raises, in turn, important issues of coordination between policies in several sectors, and at various scales.

Fifth, as already emphasized in Section 12.2.3, institutions are significant in determining how a given policy or a given set of policies ultimately impact on GHG emissions (World Bank, 2003). For example, the differentiated reactions of Japan, Italy, Germany and France to the first oil shock can be traced to differences in institutions, relative power of different influence groups, and political cultures (Hourcade and Kostopoulou, 1994).