4 Expected outcomes from the climate change framework.

Negotiators faced the practical tasks of deciding upon the objectives of the climate change framework and devising instruments that achieves those objectives in a fair and efficient way. Both tasks are steeped in uncertainty. Even so, decisions have been taken based on informed expectations about the relationships between greenhouse gas emissions and climate change and based on expectations about how the provisions of the treaty will work, including the Protocol's innovative flexibility mechanisms. In particular, the flexibility mechanisms are expected to lessen the cost of meeting the environmental objectives of the treaty. Incentives and new markets related to the treaty are expected to mobilize private capital. For developing countries, the treaty is expected to generate inflows of capital and technology and contribute to sustainable development. Early project investments through JI and CDM are expected to set countries on a lower carbon path, by supplanting commonly used technologies in long-lived and irreversible investments with carbon-saving alternatives. In this section, we briefly discuss the literature related to evaluating the benefits and costs of limits on greenhouse gas emissions and evaluations of how the flexibility mechanisms might work.

Policy evaluations and predictions

Most often in economics, evaluations of policy are based on historical assessments. In the case of integrated evaluations of climate change and its economic impact, evaluations are forward looking and rely heavily on models built up from current and historical physical, technical, institutional and economic relationships. For the most part, the model predictions are against hypothetical alternatives, some of which are unlikely to occur. Still, the models used to evaluate climate change policy contain predictions about the scale of carbon markets and how markets they might work. There is a substantial literature on how to model climate change policies. It is well reviewed elsewhere and this section draws on that work. Comprehensive surveys are given in Weyant (1999, 2004), Loschel (2002), Springer (2003), Sands (2004) and most recently in Working Group III contribution to the Fourth IPCC Assessment (IPCC 2007a).

Model structures and technology

Springer (2003) broadly categorizes the reviewed models into five groups. The first is made up of integrated assessment models, where physical and human activities are jointly modeled. As Springer notes, there is some overlap between this group and the remaining, since the economic components of the integrated models employ CGE or energy system models. Examples of integrated models are discussed in Manne and Richels (1999), Nordhaus and Boyer (2000), Nordhaus (2001), Jacoby et al. (2006). Another common approach relies on marginal abatement cost curves to examine the effects of trade. Examples include Jotzo and Michaelowa (2002), Loschel and Zhang (2002) and Stevens and Rose (2002). A less common approach focuses on macroeconomic tradeoffs between monetary policy and employment. See, for example, McKibbin, Shackelton and Wilcoxen (1999). An alternative approach is to employ technical engineering models of sectors or energy systems. These bottom-up models are sometimes integrated with other sectors via a CGE model. IPCC (2007a) contains a review of several bottom-up sector models.

An important distinction among the models is whether greenhouse gas concentration is exogenous to the model. (43) Optimization models let the economic sectors maximize profits while adjusting the level of emissions endogenously. This can be done either by adjusting levels of production and the mix of sectoral output, or by introducing and endogenously selecting production technologies with different greenhouse gas intensities. The other approach is to exogenously impose a level of greenhouse gas concentration on the model and to find the most cost effective way to reach it. Both approaches can be either static or dynamic. While endogenous technology adoption can be part of the model, CO2 concentration can also be addressed via level of production only.

Springer notes a variety of common outcomes from most modeling exercises. For example, most models find that trade in permits substantially lowers the cost of meeting Kyoto objectives, while trade restrictions increase costs and potentially lead to market power concerns. The withdrawal of the US is expected to substantially lower the environmental efficacy of the climate change framework. Dynamically, most modeling exercise reveal what Nordhaus (2007) describes as a climate-policy ramp, whereby policies aimed at slowing climate change tighten over time.

Another important modeling dynamic involves the treatment of technical change. (44) In most modeling efforts, technical change most often enters climate change policy models exogenously. In bottom-up models technical change consists of optimizing among a fixed set of engineering technical relationships. The same can be said of some of the models that rely on abatement cost curves built up from information on the energy structure of economic regions. In top-down models, technology is reflected in the parameters of the modeled economic relationships, which are expected to change with shifting technologies. The most straightforward way is to think in terms of the parameters of a production function where the parameters imply an underlying technology. For this reason, Loschel (2002) argues that endogenous technical change is more easily modeled within a top-down structure. Still, shifting production function parameters are also consistent with the endogenous adoption of existing technologies (Mundlak 1993).45 Moreover, efficiency gains can also come about because of a changing input composition as capital levels change over the longer term (Sands 2004).

Consequently, what distinguishes the endogenous technology change models is a structural link between research expenditures and innovation. Endogenous technical change models that take into account research and development investments include Goulder and Schneider (1999), Buonanno, Carraro and Galeotti (2003) and Nordhaus (2002).

One primary purpose to which models have been put is the development of a schedule of carbon prices that are consistent with different carbon concentration levels and that lead to stable but different long-run climates. Estimates gathered for the Fourth IPCC Assessment suggest a carbon dioxide price of from $US 20--80 per ton by 2030 and rising to $US 30-155 by 2050 is consistent with scenarios that stabilize atmospheric carbon concentrations at 550 ppm, a level thought to be consistent with moderate climate change. Importantly, models that allowed for endogenous technical change suggested that the same level of atmospheric concentration levels could be obtained at significantly lower carbon prices (IPCC 2007b). The modeling results, which suggest a significant role for new technologies, are reflected in a set of policy proposal aimed at funding global research. We take up this topic in the section below. The same models are used to measure any adverse impacts of economic growth resulting from Annex B emission reductions. For comparison purposes, the costs are often expressed in terms of reduced GDP. Model predictions of 2050 GDP reductions reviewed by the IPCC (2007b) associated with stabilization around 550 ppm range from near zero to 4 percent. (46)

The numeric models have also been relied upon to provide estimates of the potential benefits of the Kyoto Protocol's flexibility mechanisms. As Springer (2003) notes in his review, a common finding is that the costs of reaching greenhouse reduction goals are greatly reduced by rules that allowed spatial and temporal flexibility. By way of example, early model results by Bernstein, Montgomery and Rutherford (1999) suggest that flexible trading rules could reduce the price of carbon permits--which can be seen as the marginal cost of emission reductions--by a factor of seven in the European Union and by a factor of sixteen in Japan. (47)

Early results indicating the importance of trade and project investment countries have held up with time; however, recent modeling efforts have illustrated how the cost-savings from the flexibility mechanisms depends on the stringency of emission reduction targets. For example, under scenarios consistent with earlier assumptions, den Elzen and Both (2002) estimate that the Kyoto flexibility mechanisms reduce the overall cost of meeting the first commitment period targets by 40 percent. However, the authors also show that the withdrawal of the United States from the agreement greatly reduces the need for the provisions; predicted trade under the provisions is cut in half as aggregate abatement levels drop significantly without demand for offsets from the US.

Global averages of the costs of mitigation mask differences in the distributional effects of climate change. As Mendelsohn, Dinar and Williams (2006) note, early models of climate change suggested that the effects of climate change would fall uniformly among the rich and poor. More recent results suggest that this is not the case and that the world's poor will be disproportionately affected. The study suggests this result comes about primarily because of where the poor live. In the already mentioned paper by Mendelsohn, Dinar and Williams, the authors develop sectoral response functions and country specific measures of geography, population and income to develop country (46) specific measures of climate change. They conclude that the poorest half of the world's nations will suffer most from climate change while the net consequences for wealthy countries are mild. Based on current income, land use and population distributions, Dasgupta et al. (2007) conclude that the countries mostly likely affected by rising sea levels are poor. Bosello, Roson and Tol (2007) reach a similar conclusion based on modeling results. In a related paper, Bosello, Roson and Tol (2006), the authors conclude that adverse health consequences from climate change will also fall most heavily on poor countries.

Market power

As discussed, the supply of excess AAUs available in the economies that have restructured to become more energy efficient since 1990 has spurred a set of policy discussions around the topic of supplementarity. More recently, authors have argued that the concentration of excess allowances in a handful of countries, especially in Russia and the Ukraine, conveys a degree of market power that might encourage countries to withhold AAUs from the market, resulting in a higher price than competitive models might suggest (Baron, 1999). This possibility raises the question of whether or not there is a practical way to exercise this latent market power. As Klepper and Peterson (2005) point out, the climate change framework is not explicit about the relative roles that governments and private firms play in emission trading, so it is possible for governments to restrict trade in a cooperative way that extracts rents and the prices of tradable permits. Hagem and Maestad (2006) analyze optimal strategies for a country that has market power in an international market for emission permits and at the same time is an oil and gas exporter. In applying the analysis to the case Russia, they show that a country can benefit from coordinating the permit and oil and gas exports, depending on the level of substitution between the types of fuels exported. They conclude that strategic behavior affects decisions that lead to market power and may impose inefficiencies on carbon trading, either directly or indirectly

Market power can arise from the buyer's side as well. Carlen (2003) uses a laboratory experiment to explore this question, but doesn't "observe that the dominant buyer country exerts market power by withholding demand from the market as predicted by standard economic theory. ... the outcome casts doubt over the validity of assessment of market power effects in international carbon emission trading that indicate substantial efficiency losses"(Carlen 2003:23).

Several authors have also explored whether issues of market power, raised initially in the context of international trading arise in the context of domestic market regulations. For example, Kuik and Mulder (2004), in their analysis of alternative regulatory approaches to emissions in the Netherlands assert that the trading schemes will lead among to different market clearing permit prices, the effects of which will differ depending upon the scale of the firm. Firms in sectors such as agriculture will be disadvantaged, because the sector is composed of relatively many small units that face higher transaction costs under trading schemes. Using a static game theory model applied to a regional electricity market, Lise et al. (2006) find that a reduction in the market power of large producers may benefit both the consumers and the environment. Taken together, the two studies indicate the importance of domestic structure on policy outcomes and suggest that more work is still needed to better understand the relationship between market power and the efficiency of the carbon market and its impact on global emissions.

Leakages, ancillary benefits and crowding out

A practical concern arising from differentiated obligations has to do with the interaction between those who have assumed obligations and those who have not. The set of secondary effects, known as carbon leakage, can come about because economic activities shift due to changing prices and terms of trade. Leakage can occur because of differences in a variety of policy instruments, but the term most often refers to the set of secondary effects that result in increased emissions in countries without emission limits that partly or fully offset the environmental gains from limiting emission in Annex B countries. As discussed, this has to do in part with trade rules and their compatibility with climate change obligations.

General equilibrium models are well suited for analyzing carbon leakages and this literature is reviewed in Burniaux and Martin (2000) and in Baker et al. (2007). These studies find evidence of leakages of ranging degrees. For example Paltsev (2001) reports a leakage rate of around 10 percent, while Babiker (2005), looking at energy-intensive activities reports scenario outcomes ranging in global leakage rates between 25 and 130 percent--that is, under some scenarios emission limits increased net emissions. At the same time, studies suggest that leakages are likely to vary greatly among subsectors. For example, in a detailed study of the cement industry, Szabo et al. (2006) suggest leakage rates of 29% in the EU. More recently, Di Maria and van der Werf (2008) develop a conceptual model that suggests that the terms-of-trade effects captured by most CGE models ignore the offsetting effect of induced technological change and consequently over-estimate leakages.

Other secondary effects, often referred to as ancillary effects in the climate change literature, have to do with positive welfare gains that accrue from greenhouse gas mitigation. One example is associated with the double-dividend welfare gain arrived at by taxing a negative externality instead of economic goods and services (Terkla 1984; Lee and Misiolek 1986). The "double dividend" stems from the recovery of dead-weight welfare losses related to taxing productive economic activity. In the case of climate change policy, a positive effect on economic growth is accomplished by using revenue raised by a carbon tax or by auctioned permits to displace distortionary factor taxes, such as payroll taxes or taxes on capital assets, thereby generating both environmental and economic benefits. A series of numerical studies showing that factor market distortions swamped the positive effects of marginal tax cuts cast doubt on the potential for a double dividend (Bovenberg and de Mooij 1994; Parry 1995; Bovenberg and Goulder 1996; Koskela, Schon, and Sinn 1998). Later, Williams (1999, 2002) and Parry and Bento (2000, 2001) described special situations that might lead to a double dividend. Most recently, Bento and Jacobsen (2007) use a conceptual and numeric model to show that, when rents related to the use exhaustible resources are not fully taxed, net welfare gains constituting a double dividend can be generated when environmental taxes are used to cut preexisting labor taxes. Country studies include; McKitrick (1997), Canada; Garbaccio, Mun and Jorgenson (1999), China; Edwards and Hutton (2001), UK; Ibarraran, Viniegra and Boyd (2001), Mexico; Roson (2003), Italy; and Takeda (2007), Japan.

In their review of country studies, Barker et al. (2007) conclude that the benefits associated with revenue recycling (replacing current taxes with revenues raised through climate policy) can be significant. Taken in combination with other ancillary benefits, this greatly expands the scope for low-cost and no-regrets outcomes. We return to this topic later in this section.

Another set of positive externalities, referred to collectively as co-benefits, include collateral health benefits that are realized when other types of pollutants are reduced together with greenhouse gases. Both top-down and bottom-up models have been employed to measure such effects. For example, Li (2002, 2006) looks at health benefits associated with greenhouse gas emissions in Thailand and Burtraw et al. (2003) examine the potential for positive health gains associated limits on US greenhouse gas emissions. Dudek., Golub and Strukova (2003), Dessus and O'Connor et al. (2003) and Aunan et al. (2003) examine the same issue in Russia, Chile and in China, respectively. A series of papers, including Gundimeda (2004), Plantinga and Wu (2003), Feng and Kling (2005), Yemshanov et al. (2005), look at forestry and carbon sequestration co-benefits. These benefits are tied to both the environmental services generated by sustained forests and incomes associated with payments for environmental services. Pendell et al. (2007) provide an example related to soil fertility.

In their synthesis, Barker et al. (2007) note that conservative studies of the ancillary health benefits associated with climate change policy can equal 30-50 percent of estimated mitigation costs, while some studies, especially studies of developing countries, indicate that health benefits can exceed mitigation costs. They also note that several studies suggest that a large share of business-as-usual emissions that can be reduced without welfare loss: 13-23 percent in India (Bussolo and O'Connor, 2001); 15-20 percent for China (O'Connor, 2003); and 20 percent for Chile (Dessus and O'Connor 2003). Other studies suggest savings could be had on other types of air pollution controls as well. For example, Burtraw et al. (2003) estimate that a 31 percent reduction in CO2 emissions in the United States would drive the price of SO2 permits to zero.

A potential negative externality recently identified by Nordhaus (2007) has to do with the consequences of large inflows of carbon financing into small economies. Potentially, large inflows of investment tied to one sector can lead to a currency appreciation changing domestic relative prices to the disadvantageous of parts of the economy and crowding out economic activity in those sectors. This phenomenon is known as the Dutch Disease and is most often explained in terms of commodity booms (Corden, 1984; van Wijnbergen, 1986.).48 There is also a body of research that suggests that economic growth in resource-rich developing countries has been slow because of related rent-seeking, corruption, violence, fiscal mismanagement and a crowding out of other economic activities. (49) While crowding-out stems from a general equilibrium trade effect, the remaining problems relate to weak institutions. To date, the most significant investment flows under CDM have gone to large economies and few studies have considered the possible consequences of project-based investment flows. In one innovative study focusing on two large economies, Bohringer, Conrad and Loshel (2003) look at a joint model of Germany and the Indian electricity sector and find large welfare gains for both countries. (50)

Uncertainty, discounting and intergenerational tradeoffs

How best to model the uncertainties associated with climate change remains an unresolved challenge. The recent IPCC assessment reviews the potential for abrupt climate change with catastrophic results, including raising sea levels, droughts, and an increased intensity of tropical typhoons (Meehl et al. 2007). Moreover, because greenhouse gases are long lived policy decisions have cumulative and irreversible effects. Wirl (2006, 2007) provides a conceptual approach to model types of environmental irreversibility under uncertainty in a stochastic setting and provides a brief review of the related literature. Still, little is known about the point at which a particular extreme climate event would occur or, for that matter, about the associated probabilities. Even so, decisions are taken sequentially and this provides some scope for developing and incorporating new information through time (Valverde, Jacoby and Kaufman, 1999). As Pindyck (2007) points out, the practical consequence of limited information on probabilities is that uncertainty is handled in the context of specific models.

In terms of numeric modeling efforts to assess policy outcomes, the consequences of uncertainty come into play largely through discounting rates used to value future events. Since the consequences of near-term policies persist in accumulations of greenhouse gases in the atmosphere and in accumulations of capital and technologies, advantages or disadvantages gained by one set of policies over another are difficult to reverse as time goes by. For this reason, the rate of comparing early costs to future benefits is crucial to modeling efforts. Halsnaes et al. (2007) review the risk and uncertainty literature as it relates to climate change and describe out how the issue affects IPCC assessments.

Arguments about appropriate rates of social discounting relate to positive conceptual and empirical studies as well as more controversial normative approaches. Studies of past returns to capital (financial and human) suggest positive rates of return, which imply positive discount rates for future benefits arrived from present investments. This finding is not controversial in its self and is discussed in Arrow et al. (1996) as background to the second IPCC assessment. In contrast, normative arguments over whether market-based rates are indicative and an appropriate measure for discounting future welfare are controversial and pivotal for policy assessments.

Generally, assessments of climate change policy are based on positive and often constant discount rates. In some instances these are based on observed market rates, based on the notion that policy tradeoffs reflected in climate change scenarios should use the same metric as other policy tradeoffs related to trade or debt. Critics argue that, because of market imperfections, such rates are biased upwards and that lower rates should be employed. Even so, separate from arguments concerning appropriate levels, an important consequence of positive discount rates is that the welfare of future generations has little present value. Some writers find this objectionable based on moral grounds and argue that the approach for valuing inter-generational transfers should differ from the approach taken for capital. To take this into account, studies sometimes distinguish between the rate used to reflect the time-value of capital and the rate used to discount future welfare, sometimes referred to as the pure rate of social time preference. While rates measuring returns to capital have an empirical basis, arguments concerning an appropriate way to discount the interests of future generations are philosophical and subject to stark dissonance. Yet the assumption matters critically for numerical models of the cost and benefits of climate change policies. For example, Nordhaus (2007b) maintains that the use of a near-zero social time-preference rate explains why the Stern Review (Stern 2007) calls for stronger early mitigation interventions than does the general literature.

Most studies use positive and constant rates to discount future welfare, but several authors propose that discount rates should fall with time. For example, based on uncertain returns to capital, Weitzman (2001) argues for a declining discount rate as do Gollier (2002), Newell and Pizer (2004). Weitzman (1998) argues in favor of using a zero discount rate for half century time horizons and, as mentioned, the Stern Review relies on a near-zero discount rate. Portney and Weyant (1999) provide a good review of the related literature. Dasgupta (2005, 2007) looks at the discounting issue. The ethical and conceptual bases for the discount assumptions of the Stern report are discussed by Beckerman and Hepburn (2007), Dasgupta (2007) and Nordhaus (2007).

Technology development and transfer as a policy instrument

As discussed, modeling outcomes point to the importance of new technologies in affecting the cost of meeting emission reduction goals. However, several studies indicate that past investments in related research and development has been insufficient, suggesting that markets for new technologies will need non-market support. For example, Margolis and Kammen (1999) show, using data from the US, that there has been a long-term pattern of underinvestment in R&D in the energy sector, compared to other sectors and they conclude that a deployment effort for increased research in the energy sector is needed. Subsequent authors conclude that, while additional research in energy technologies is necessary to improve energy efficiency, a broader approach is needed. For example, Sagar (2000) argues that development and deployment efforts should focus on additional sectors as well as energy. Sagar and van der Zwaan (2006), using data from OECD countries, demonstrate a lack of correlation between energy efficiency level and energy R&D. They conclude that energy R&D is sufficient but not a necessary condition for improved energy efficiency. They identify roles for institutions, deployment and learning as necessary conditions for transfer of energy R&D innovations to the market.

Modeling results indicating a strong role for technology and that carbon prices will be lower than expected, following the US decision not to ratify the Kyoto Protocol have also worked to focus attention on policy instruments that support technology development and technology transfer. This interest is reflected in the climate change literature and in actions taken by the UNFCCC delegates. Institutionally, a framework was developed during the Marrakesh Conference of the Parties to enhance the implementation of Article 4.5 of the Convention, which recognizes the importance of technology development and transfer in battling climate change and allowing steady growth in developing countries. The framework includes 5 activities/requirements, namely: technology needs and needs assessments; available technology information; enabling environments in developed and developing countries; capacity building in developing countries; mechanisms for technology transfer. To date, there are three special funding mechanisms under the UNFCC: the Least Developed Countries Fund, the Special Climate Change Fund and the already mentioned Adaptation Fund. (51) To a degree, the three funds offer ways to promote technology transfer, although the emphasis of the funds is on adaptations and also on specific areas, including agriculture, health, water resources and disaster protection that are expected to promote development objectives. Additionally, as discussed, CDM and JI are expected to promote technology transfer. Still, policy makers and researchers have suggested that current incentives and funding is unlikely to generate significant new technologies and have proposed additional funds emphasizing research and development. (52) Worth noting as well is a Clean Technology Fund, managed by the World Bank and backed by donor pledges of $US 5 billion (World Bank, 2008b). The Fund, viewed as an interim measure until a future financing architecture can be established under the UNFCCC, is aimed at finding policy instruments that can accelerate the deployment, diffusion and transfer of low-carbon technologies.

Buchner and Carraro (2005) review proposals for an international agreement for the development and diffusions of new technologies. (53) Such an agreement can be supplemental to emission controls; however, using a conceptual model Barrett (2006) argues that agreements to limit emissions are likely to be ineffective, leaving an agreement to promote technologies as the most practical approach to climate change. At the same time, numerical models provide evidence that the secondary effects of induced technology are small relative to the direct effects of a carbon tax and generate lower welfare gains than an equivalent control on emissions (Nordhaus 1998; Goulder and Mathai 2000; Parry, Pizer and Fischer 2003). The previously mentioned study by Buchner and Carraro concludes that a self-enforcing agreement to cooperate on technological innovation and diffusions is more likely than a cooperative agreement on emissions, but also concludes that technological cooperation by itself will be insufficient to meet reasonable abatement goals.

Technology transfer and project financing 

Various approaches have been used in the literature to incorporate technology transfer in models that deal with country policies and carbon offset markets. Approaches used include country and regional case studies, optimization approaches such as growth models and CGE models, and negotiation and strategic approaches such as Game Theory. Some of the papers are process oriented and some provide estimates of economic savings.

Irrespective of the approach used, the repeated messages from the literature are similar, namely, a need for enabling local and global institutions and other arrangements that are directly and indirectly related to technology development, adjustment and transfer. Both the case studies (Forsyth, 1999; Duic et al., 2003; Forsyth, 2005;), the partial equilibrium (Kemfert, 2003), the general equilibrium (Sahlen and Aronsson, 2006), and the strategic approaches (Matsuhashi, Chang and Ishitani, 1999; Millock, 2002) suggest that there is no one policy that addresses similarly the issues countries face, but rather, each country or partnership that collaborates in the CDM setting needs a specific solution to allow technology and its transfer. Finally, an econometric study of the reported technology transfer by project types and countries suggests also a more microscopic analysis and understanding of the differences between determinants of technology transfer (Haites, Duan and Seres, 2006).

Present policies to technology transfer are criticized for not taking advantage of private sector capacities and international trade. Distinction is made between long-term technology sharing policies, used at present, that ignore the potential benefits of the globalization of technology investment and ownership (Forsyth, 1999). The present policy is claimed to be heavily subsidized and deterrence of private investors. Rather than having the state focus on the direct innovation development process, states could better impact development and transfer of technologies by improving fair trade policies, protect intellectual property rights, and increase public access to information about, technologies (Forsyth, 2005; Millock, 2002).

Early on, researchers noted that abatement costs and the shape of the marginal abatement curves play a crucial role in rates of technology transfer. For example, based on a comparison of input-output tables, Matsuhasi, Chang and Ishitani (1999) conclude that the potential for technology transfer between Japan and China is large under CDM; however, using game-theory and sensitivity analysis, they also show that small changes in underlying assumptions about the structure of abatement costs have significant consequences for predicted rates of transfer. They point to expected lower price of the technology and the potential for lower financial cost for the technology transfer and its positive impact on the economy as key factors affecting the economic viability of CDM technologies. Similarly, Duic et al. (2003) show that small changes in cost can dramatically change incentives to switch to new renewable energy technologies, even in a small economy of island nations such as Santiago and Cape Verde where carbon intensity is low but fossil fuel prices are high.

The global (both partial and general equilibrium) models demonstrate the importance of indirect effects of trade on the transfer of clean energy technologies and hence, on economic growth. Using a partial equilibrium model, Kemfert (2003) shows that trade barriers, would not only damage the economy, but could also deter investments in climate friendly technologies. Using a general equilibrium model, Sahlen and Aronsson (2006) add also labor barriers into the market of factors of production to account for north economies (capital intensive) and south economies (labor intensive). The effects of trade barriers (including labor) imply that for a CDM setting with allowed flows of factors of production--no borders, a technology transfer from the North to the South is clearly desirable from the perspective of a 'global social planner', since the welfare gain for the South outweighs the welfare loss for the North. However, if the regions impose trade barriers, then the incentives to introduce the technology transfer appear to be relatively weak from the perspective of the North. Finally, by imposing the Kyoto emission reductions on the otherwise uncontrolled market economy, the technology transfer leads to higher welfare in both regions.

The literature reviewed above employs models and normative assumptions to predict the rate of clean technology transfer between investor and host countries in the CDM-JI operations. However, looking at specific projects provides additional insights. Haites, Duan and Seres (2006) examine claims of technology transfer in the project proposal documents of 854 early CDM projects. As the authors point out, the CDM does not have an explicit technology-transfer mandate, even though several provisions of the overall Climate Change Convention commit developing-country parties to promote and finance such transfers. Even so, the authors find that about one-third of the CDM projects they examined made claims of technology transfer, where technology transfer takes the form of use of equipment or knowledge, not previously available in the host country. On average, more large projects claimed to transfer technology, so that two-thirds of the emission reductions from the studied projects were associated with transfer claims. Technology transfer claims also varied by technology type. In general, few projects in hydro and energy-efficiency claimed to transfer technology (less than 15 percent) while most projects in agriculture, wind and biomass claimed to promote technology transfer (81, 41 and 21 percent of the projects in each class). About half of the projects studied do not have foreign partners. Only about a quarter of these "unilateral" projects made technology transfer claims; within this group transfer claims were higher among larger projects. This leads the authors to conclude that the probability of technology transfer increases with project size and with foreign participation.