The World Bank is increasingly active in the area of climate change mitigation. While it justifies this engagement with its poverty reduction objective and its capacity to pave the way for new business activities in developing countries, critics blame the World Bank as a “climate profiteer” and as an unfair competitor in private markets. Our econometric analysis of over 2,000 projects registered until May 2010 under the Clean Development Mechanism (CDM) of the Kyoto Protocol allows us to compare the activities of the Bank with those of other, primarily private actors. The results indicate that hardly any of the CDM projects can be considered as strongly pro-poor. Nevertheless, in comparison to the rest of the CDM projects, the Bank’s portfolio shows a relatively clearer orientation towards poor countries. Within these countries, however, the Bank does not show any particular pro-poor focus, and tends to implement those projects that are commercially most attractive. Moreover, there is no evidence of the Bank phasing out its activities once the market becomes fully operational, which goes against its professed pioneering and catalytic role in carbon markets.
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For details, see World Bank (2010b).
In his contribution to this volume, Mosley (2011) provides a comprehensive discussion of the way trust builds up between donors and recipients. Under particular consideration of the World Bank as a “lead donor,” he shows how important this long-term relationship is for both sides. This strengthens our argument on the Bank’s competitive advantage through its long-term relationships with many developing country governments. Moreover, it points at the problematic long-term consequences of betraying this trust in the above-mentioned way—over and above the directly adverse developmental impact of a deal below market price.
In the light of Marchesi and Sirtori’s (2011) results in this volume, it is interesting to note that in the future, the IMF may also enter this area of activities (Bredenkamp and Pattillo 2010). In particular, it will be interesting to observe whether the two Bretton Woods institutions will then look for complementarities or compete, and how this will affect the development impact of the CDM.
As a higher number of CERs does not imply greater overall environmental benefits (cf. Section 2), this must not be misinterpreted as a greater contribution to the global public good.
Initially, we also considered World Bank aid flows to CDM host countries (AidData 2010) to control for the relationship between the Bank and these countries prior to the CDM. However, as this variable was insignificant in all regressions, it will not be considered further in our analysis.
If we also count all projects submitted for validation, but not yet registered (see Figure 1), we can identify a total of 126 World Bank projects. It appears plausible that the others have not even been submitted so far. In this case, our number of 65 projects correctly covers the totality of actually registered projects. Only if there were a substantial number of registered World Bank projects that we mistakenly interpreted as non-World Bank projects, this would reduce the precision of our empirical estimates. In this case, it would be more difficult to detect significant differences between World Bank and non-World Bank projects, but the plausibility of those effects that we do find would even be higher. If, in addition, those projects that we could not correctly identify as World Bank projects were not random, but systematically related to cases the Bank might have intended to hide, our overall results might be biased towards “recipient need” and against “donor interests,” so that our results would provide only a lower bound for potential criticism with respect to the Bank’s carbon market activities. However, as stated earlier, given a typical CDM project cycle, the number of registered projects we could identify appears plausible, and we are confident that such a bias is not relevant here.
We could have considered all projects submitted (CDM project proposals) when constituting the database, rather than all registered projects. This would have provided us with a higher number of observations from both the World Bank and other market participants. However, many submitted projects turn out not to be in line with CDM rules and regulations, and they are not validated or effectively rejected. Experience shows that this is rarely the case for World Bank projects, but relatively frequent for project proposals from private actors. Including such project proposals may thus bias any comparisons related to the quality of the projects. Hence, we restrict our sample to registered projects, except for the case where we only look at the mere volume of market activities.
In two years out of five, no World Bank projects were submitted for validation. Therefore, the respective dummies lead to full determination of failure in a binary regression model. In our logit model, we thus substitute the year dummies by a single, more fine-grained control variable, reflecting the exact date of submission.
Note that in this regression, which includes both the submission date and the year dummies, the submission date primarily captures the additional time effect within each year.
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We thank two anonymous referees and the participants of the Egon Sohmen Memorial Conference on the “Political Economy of International Financial Institutions,” 10–13 June, 2010, Tübingen, for all their helpful and constructive suggestions. Special thanks go to Catherine Weaver for her detailed and thoughtful comments that led us to dig a little deeper into the “black box” of the World Bank. Finally, we thank Christopher Humphrey who helped us to improve the writing, and to reflect about some further interpretations of Bank behavior.
Annex 1: CDM Project Type Quality
In this section we outline the arguments on which we base the allocation of projects to the different categories regarding development benefits. First, we distinguish between the general project types. Second, we discuss multipliers for sub-types in order to capture differences within individual project types. In both cases, the value range goes from 0 to 2, with 2 indicating the highest development benefits. When projects are evaluated at the sub-type level this leads to values that effectively range from 0 to 4, because type classifications and sub-type classifications are multiplied. Project sub-types getting the value 1 share the characteristics of their main type.
We structure the following discussion along the major categories for the general project types.
High development quality: category 2
Category 2 is employed for projects with generally high development benefits. Coal mine methane reduction leads to a significant improvement in mine safety and provides energy to remote mining communities. Energy efficiency improvement in households, for example through efficient stoves or lighting, reduces energy bills and therefore frees income for other expenses. The switch from coal to other fuels reduces local pollution, often in locations with an above average share of poor population groups, and thereby generates high development benefits, in particular through improved health. Methane avoidance from waste as well as landfill gas collection requires a managed landfill that does not burn or emit leachates that pollute the groundwater. Health benefits for the poor communities living near the landfills are substantial. Solar power is generally utilized in off-grid and rural areas and thus introduces electricity to lagging regions. Projects involving the transport sector improve urban infrastructures. This usually benefits the poor, in particularly in the case of cable cars in slums and of bus lane systems. Within the category biomass power, use of poultry litter and black liquor allows generating energy from a noxious waste that has led to massive pollution. Production of briquettes generates a substantial number of jobs. Energy efficient building materials are also labor-intensive. Improved charcoal production leads to increased revenues for marginalized groups. Connection of isolated electric grids improves reliability of electricity production in remote areas. Building a hydropower plant on an existing dam generates electricity and thereby contributes to development (without the potentially negative impacts of new dams).
Some development quality: category 1.5
The category 1.5 is used only for sub-types. It is used when these sub-types generate good but not superb development benefits. Bagasse power falls into this category as projects can lead to substantial development benefits if implemented in small sugar mills, whereas large projects provide mainly indirect benefits through their electricity generation. Likewise, benefits of cogeneration and efficient district heating systems depend on the project design. Composting of waste, biogas from domestic manure and landfill gas-to-energy projects are clearly better than pure landfill gas flaring projects. Efficiency improvement of thermal power plants, including conversion of single to combined cycle plants, and industrial boilers reduces local pollution. Substitution of klinker by waste such as fly ash lead to the elimination of pollution linked to the dumping of the waste. Solar cooking as well as distribution of efficient stoves usually benefits poor groups in a similar way as the switch from coal to other fuels discussed above under (i).
Undetermined development quality: category 1
Projects in category 1 can have development benefits if implemented in a careful manner. However, they can also have negative impacts under certain circumstances. Their effect thus depends effectively on the sub-type multiplier.
Afforestation and reforestation projects can have benefits for the local population if organized in a way involving the community. For example, seedling nurseries can generate substantial numbers of jobs and agroforestry activities can increase crop revenues. Forested slopes usually reduce runoff in extreme precipitation events. On the other hand, monoculture projects can lead to decreased runoff, eviction of marginalized people that do not have formal land titles, as well as reduced access to non-timber forest products. Biomass energy can lead to substantial benefits for the local population if implemented in a decentralized way and using crop residues that have not been used so far—therefore giving value to a resource that can be monetized by the rural population and creating jobs. If however projects divert residues from traditional uses or even lead to deforestation, they have negative impacts. Measures to reduce energy use in power generation and distribution, industry and the service sector generally have indirect development benefits but their immediate revenues often accrue to above average income groups. Fugitive methane emissions reductions from pipelines have no immediate development benefit other than resource conservation. Geothermal as well as tidal power requires large equipment and does not lead to direct development benefits for the local population. While well-executed hydro projects can provide electricity to rural communities, large dams can destroy the livelihood of large groups. Wind power projects have similar characteristics at a smaller scale; they can block access to land.
Potentially problematic development quality: category 0.5
The category 0.5 is used only for sub-types. It is used whenever they have potentially problematic characteristics. The use of forest residues may lead to forest degradation. New dams are likely to lead to resettlement.
No development quality: category 0
Projects in category 0 generally do not provide specific development benefits. CO2 capture is a high tech end-of-the-pipe solution involving only a few specialists. Projects destroying the industrial gases N2O (from adipic acid, nitric acid and caprolactam production), HFC23, PFC and SF6 have similar characteristics. Combustion of waste usually is done in high-tech plants and may even have negative repercussions regarding dioxin pollution.
Annex 2: Distribution of World Bank and other CDM Projects by Host Country Income
Annex 3: Variable Description
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Michaelowa, A., Michaelowa, K. Climate business for poverty reduction? The role of the World Bank. Rev Int Organ 6, 259–286 (2011) doi:10.1007/s11558-011-9103-z
- Clean Development Mechanism (CDM)
- World Bank
- Climate policy
- Carbon market
- Poverty reduction
- Allocation of resources
- Political economy
- Recipient need versus donor interest