Search

Over the last few decades, integrated assessment models (IAM) have provided insight into the relationship between climate change, economy, and climate policies. The limitations of these models in capturing uncertainty in climate parameters, heterogeneity in damages and policies, have given rise to skepticism about the relevance of these models for policy making. IAM community needs to respond to these critics and to the new challenges posed by developments in the policy arena. New climate targets emerging from the Paris Agreement and the uncertainty about the signatories’ commitment to Nationally Determined Contributions (NDCs) are prime examples of challenges that need to be addressed in the next generation of IAMs. Given these challenges, calculating the social cost of carbon requires a new framework. This can be done by computing marginal abatement cost in cost-effective settings which provides different results than those calculated using constrained cost-benefit analysis. Here we focus on the areas where IAMs can be deployed to asses uncertainty and risk management, learning, and regional heterogeneity in climate change impacts.

Environmental policies based on information provision are widespread, but have often proven ineffective. One possible explanation for information’s low effectiveness is that people actively avoid it. We conduct an online field experiment on air conditioning usage to test the theory of moral wiggle room, according to which people avoid information that would compel them to act morally, against the standard theory of information acquisition, and identify conditions under which each theory applies. In the experiment, we observe how exogenously imposing a feeling of moral obligation to reduce air conditioning usage and exploiting natural variation in the cost of doing so, given by outside temperature, influences subjects’ avoidance of information about their energy use impacts on the environment. Moral obligation increases information avoidance when it is hot outside, consistent with the moral wiggle room theory, but decreases it when outside temperature is low. Avoiding information positively correlates with air conditioning usage. These findings provide guidance about tailoring the use of nudges and informational tools to the decision environment.

The Paris Agreement has set stringent temperature targets to limit global warming to 2°C above preindustrial level, with efforts to stay well below 2°C. At the same time, its bottom-up approach with voluntary national contributions makes the implementation of these ambitious targets particularly challenging. Climate engineering – both through carbon dioxide removal (CDR) and solar radiation management (SRM) – is currently discussed to potentially complement mitigation and adaptation. Results from integrated assessment models already suggest a significant role for some forms of climate engineering in achieving stringent climate objectives1. However, these estimates and their underlying assumptions are uncertain and currently heavily debated2–4. By reviewing the existing literature and reporting the views of experts, we identify research gaps and priorities for improving the integrated assessment of climate engineering. Results point to differentiated roles of CDR and SRM as complementary strategies to the traditional ones, as well as diverse challenges for an adequate representation in integrated assessment models. We identify potential synergies for model development which can help better represent mitigation and adaptation challenges, as well as climate engineering.

The climate targets defined under the Paris agreement of limiting global temperature increase below 1.5 or 2°C require massive deployment of low-carbon options in the energy mix, which is currently dominated by fossil fuels. Scenarios suggest that Carbon Capture and Storage (CCS) might play a central role in this transformation, but CCS deployment is stagnating and doubts remain about its techno-economic feasibility. In this article, we carry out a throughout assessment of the role of CCS electricity for a variety of temperature targets, from 1.5 to above 4°C, with particular attention to the lower end of this range. We collect the latest data on CCS economic and technological future prospects to accurately represent several types of CCS plants in the WITCH energy-economy model, We capture uncertainties by means of extensive sensitivity analysis in parameters regarding plants technical aspects, as well as costs and technological progress. Our research suggests that stringent temperature scenarios constrain fossil fuel CCS based deployment, which is maximum for medium policy targets. On the other hand, Biomass CCS, along with renewables, increases with the temperature stringency. Moreover, the relative importance of cost and performance parameters change with the climate target. Cost uncertainty matters in less stringent policy cases, whereas performance matters for lower temperature targets.

Carbon dioxide removal (CDR) is a potentially important climate strategy for attaining low climate stabilization objectives. However, climate analysis has indicated a possible weakening of the ocean carbon sinks -the largest in the world- in relation to CDR deployment. Here, we provide an economic appraisal to assess the sensitivity of CDR and conventional abatement to CO2 outgassing from the oceans. We develop a theoretical framework to study the impact of the ocean-to-atmosphere transfer on the optimal mitigation strategies under different regimes that control the relationship between CO2 outgassing and the amount of CDR. We show that the optimal levels of emissions and CDR are correlated to the effectiveness of CDR expressed as a linear function of atmospheric concentrations. We incorporate this effect into an integrated assessment model of climate and economy (DICE model) and confirm the theoretical findings with numerical simulations. Further, we perform a sensitivity analysis to find the range of optimal abatement and CDR actions under different values of the CDR effectiveness coefficient.

We investigate the role of social interaction in technology adoption by conducting a field experiment in neighborhoods of Bamako. We invited women to attend a training/marketing session, where information on a more efficient cooking stove was provided and the chance to purchase the product at market price was offered. We randomly provided an information nudge on a peer’s willingness to buy an improved cookstove. We find that women purchase and use the product more when they receive information on a peer who purchased (or previously owned) the product, particularly if she is viewed as respected. In general, we find positive direct and spillover effects of attending the session. We also investigate whether social interaction plays a role in technology diffusion. We find that women who participated in the session, but did not buy during the intervention, are more likely to adopt the product when more women living around them own it. We investigate the mechanisms and provide evidence supporting imitation effects, rather than social learning or constraint interaction.

The mismatch between actions to combat climate change, which are based on voluntary national initiatives of limited effort, and the recognition of the importance of global warming is growing. Climate engineering via solar radiation management has been proposed as a possible complement to traditional climate policies. However, climate engineering entails specific risks, including its governance. Free driving, the possibility of unilateral climate engineering to the detriment of other nations, has been recently proposed as a potentially powerful additional externality to the traditional free riding one (Weitzman, 2015). This paper provides the first quantitative evaluation of the risks of free driving. Our results indicate that in a strategic setting there is significant over-provision (by almost an order of magnitude) of climate engineering above what is socially optimal, resulting in a sub-optimal global climate. Regions with high climate change impacts, most notably India and developing Asia, deploy climate engineering at the expenses of other regions.

Southeast Asia is at a time one of the most vulnerable region to the impacts of a changing climate, with millions of its inhabitants still trapped in extreme poverty without access to energy and employed in climate-sensitive sectors, and, potentially, one of the world’s biggest contributors to global warming in the future. Fortunately, major Southeast Asian countries are also implementing policies to improve their energy and carbon efficiency and are discussing if and how to extend these further. The present study aims to assess the implications for energy consumption, energy intensity and carbon intensity in the Southeast Asia region of a set of short-term and long-term de-carbonization policies characterized by different degrees of ambition and international cooperation. The analysis applies two energy-climate-economic models. The first, the fully dynamic Integrated Assessment model WITCH, is more aggregated in the sectoral and country representation, but provides a detailed technological description of the energy sector. The second, the ICES Computable General Equilibrium model, offers a richer sectoral breakdown of the economy and of international trade patterns, but is less refined in the representation of technology. The joint application of these two complementary models allows the capture of distinct and key aspects of low- carbon development paths in Southeast Asia.

The market for voluntary carbon offsets has grown steadily in the last decade, yet it remains a very small niche. Most emissions from business travel are still not offset. This paper exploits a unique dataset examining the decision to purchase carbon offsets at two academic conferences in environmental and ecological economics. We find that having the conference expenses covered by one's institution increases the likelihood of offsetting, but practical and ethical reservations as well as personal characteristics and preferences also play an important role. We draw lessons from the effect of objections on the use of offsets and discuss the implications for practitioners and policy-makers. Based on our findings, we conclude that ecological and environmental economists should be more involved in the design and use of carbon offsets.

We study the impact of loss-aversion and the threat of catastrophic damages, which we jointly call threshold concerns, on international environmental agreements. We aim to understand whether a threshold for dangerous climate change is as an effective coordination device for countries to overcome the global free-riding problem and abate sufficiently to avoid disaster. We focus on loss-averse countries negotiating either under the threat of either high environmental damages (loss domain), or low damages (gain domain). Under symmetry, that is when countries display identical degrees of threshold concern, we show that such beliefs have a positive effect on reducing the emission levels of both signatories to the treaty and non-signatories, leading to higher global welfare and weakly larger coalitions of signatories. We then introduce asymmetry, by allowing countries to differ in the degree of concern about the threat of disaster. We show that stable coalitions are mostly formed by the countries with higher threshold concern. When enough countries having no threshold concern could cause the coalition size to diminish, regardless of the other countries have strong or mild threshold concerns.

We empirically assess the distributional impacts and welfare effects of policies to incentivize renewable electricity production for the case of Italy. We use data from the Household Budget Survey between 2000 and 2010 to estimate a demand system in which energy goods' shares of expenditure are modelled using different empirical approaches. We show that the general Exact Affine Stone Index (EASI) demand system provides more robust estimates of price elasticities of each composite good than the commonly used Almost Ideal Demand System (AIDS). The estimated coefficients are used to perform a welfare analysis of the Italian renewable electricity production incentive policy. We show that different empirical approaches give rise to significantly different estimates of price elasticities and that methodological choices are the reasons for the very high elasticities of substitutions estimated using similar data by previous contributions. We find no evidence of regressivity of the incidence of the Italian renewable incentive scheme in the period under consideration. The renewable subsidies act as a middle-class tax, with the higher welfare losses experienced by households in the second to fourth quintiles of the expenditure distribution.

This paper describes the WITCH - World Induced Technical Change Hybrid - model in its structure, calibration, and the implementation of the SSP/RCP scenario implementation. The WITCH model is a regionally disaggregated hard-linked model based on a Ramsey type optimal growth model and a detailed bottom-up energy sector model. A particular focus of the model is the modeling or technical change and RnD investments and the analysis of cooperative and non-cooperative climate policies. Moreover, the WITCH 2016 version now includes land-use change modeling based on the GLOBIOM model, and air pollutants, as well as detailed modeling of the transport sector and the possibility for stochastic modeling. This version has been also used to implement the Shared Socioeconomic Pathways (SSPs) set of scenarios and RCP based climate policies to provide a new set of climate scenarios. In this paper, we describe in detail the mathematical formulation of the WITCH model, the solution method and calibration, as well as the implementation of the five SSP scenarios. This report therefore provides detailed information for interested users of the model, and for understanding the implementation of the different “worlds" of the SSP.

The provision of global public goods, such as climate change mitigation and managing fisheries to avoid overharvesting, requires the coordination of national contributions. The contributions are managed by elected governments who, in turn, are subject to public pressure on the matter. In an experimental setting, we randomly assign subjects into four teams, and ask them to elect a delegate by a secret vote. The elected delegates repeatedly play a one shot public goods game in which the aim is to avoid losses that can ensue if the sum of their contributions falls short of a threshold. Earnings are split evenly among the team members, including the delegate. We find that delegation causes a small reduction in the group contributions. Public pressure, in the form of teammates’ messages to their delegate, has a significant negative effect on contributions, even though the messages are designed to be payoff-inconsequential (i.e., cheap talk). The reason for the latter finding is that delegates tend to focus on the least ambitious suggestion. In other words, they focus on the lower of the two public good contributions preferred by their teammates. This finding is consistent with the prediction of our model, a modified version of regret theory.

Universal access to modern energy services, in terms of access to electricity and to modern cooking facilities, has been recognized as a fundamental challenge for development. Despite strong praise for action and the deployment of large-scale electrification programs and improved cookstove (ICS) distribution campaigns, few studies have shed light on the barriers to, the enablers of and the impacts of access to energy on development outcomes, using rigorous methodologies. This paper reviews this recent strand of research, trying to fill these gaps. We focus on the demand-side and household perspective. Our main outcomes of interest are electricity connection and ICS adoption for the analysis of barriers, time allocation, labour market outcomes and welfare for the impact analysis. We provide evidence of significant wellbeing impacts of electrification, and mixed evidence for cookstoves.

Governments worldwide have agreed that international climate policy should aim to limit the increase of global mean temperature to less than 2oC with respect to pre-industrial levels. The purpose of this paper is to analyse the emission reductions and related energy system changes in various countries in pathways consistent with the 2oC target. We synthesize and provide an overview of the national and regional information contained in different scenarios from various global models published over the last few years, as well as yet unpublished scenarios submitted by modelling teams participating in the MILES project (Modelling and Informing Low-Emission Strategies). We find that emissions in the mitigation scenarios are significantly reduced in all regions compared to the baseline without climate policies. The regional cumulative CO2 emissions show on average a 76% reduction between the baseline and 450 scenario. The 450 scenarios show a reduction of primary energy demand in all countries of roughly 30-40% compared to the baseline. In the baseline scenario, the contribution of low-carbon energy technology remains around 15%, i.e. similar as today. In the mitigation scenario, these numbers are scaled up rapidly towards 2050. Looking at air quality, sulphur dioxide and black carbon emissions are strongly reduced as a co-benefit of greenhouse gas emission reductions, in both developing and developed countries. However, black carbon emissions increase in countries that strongly rely on bioenergy to reach mitigation targets. Concerning energy security, energy importing countries generally experience a decrease in net-energy imports in mitigation scenarios compared to the baseline development, while energy exporters experience a loss of energy export revenues.

This paper aims at improving the application of the learning curve, a popular tool used for forecasting future costs of renewable technologies in integrated assessment models (IAMs). First, we formally discuss under what assumptions the traditional (OLS) estimates of the learning curve can deliver meaningful predictions in IAMs. We argue that the most problematic of them is the absence of any effect of technology cost on its demand (reverse causality). Next, we show that this assumption can be relaxed by modifying the traditional econometric method used to estimate the learning curve. The new estimation approach presented in this paper is robust to the reverse causality problem but preserves the reduced form character of the learning curve. Finally, we provide new estimates of learning curves for wind turbines and PV technologies which are tailored for use in IAMs. Our results suggest that the learning rate should be revised downward for wind power, but possibly upward for solar PV.

We study the effect of leadership in an experimental threshold public ‘bad' game, where we manipulate both the relative returns of two investments (the more productive of which causes a negative externality) and the extent to which the gains from leadership diffuse to the group. The game tradeoffs mimic those faced by countries choosing to what degree and when to transition from incumbent polluting technologies to cleaner alternatives, with the overall commitment dictating whether they manage to avert dangerous environmental thresholds. Leading countries, by agreeing on a shared effort, may be pivotal in triggering emission reductions in non-signatories countries. In addition, the leaders' coalition might also work as innovation and technology adoption catalyzer, thus producing a public good (knowledge) that benefits all countries. In our game, players can choose to tie their hands to a cooperative strategy by signing up to a coalition of first movers. The game is setup such that as long as the leading group reaches a pivotal size, its early investment in the externality-free project may catalyze cooperation by non-signatories. We find that the likelihood of reaching the pivotal size is higher when the benefits of early cooperation are completely appropriated by the coalition members, less so when these benefits spillover to the non-signatories. On the other hand, spillovers have the potential to entice second movers into adopting the ‘clean' technology.

This paper applies the Directed Technical Change (DTC) framework to study improvements in the efficiency of energy use. We present a theoretical model which (1) shows that the demand for energy is shifted down by innovations in energy intensive sectors and (2) highlights the drivers of innovative activity in these sectors. We then estimate the model through an empirical analysis of patent and energy data. Our contribution is fivefold. First, our model shows that under very general assumptions information about energy expenditures, knowledge spillovers and the parameters governing the R&D process are sufficient to predict the R&D effort in efficiency improving technologies. Second, we pin down the conditions for a log-linear relation between energy expenditure and the R&D effort. Third, the calibration of the model provides clear evidence that the value of the energy market as well as international and inter-temporal spillovers play a significant role in determining the level of innovative activity. Fourth, we show that innovative activity in energy intensive sectors shifts down the (Marshallian) demand for energy. Finally, we show that due to the streamlined modelling framework we adopt, the point estimates from our regression can potentially be used to calibrate any model of DTC in the context of energy consumption.

Carbon budgets have emerged as a robust metric of warming, but little is known about the usefulness of regional carbon budgets as indicators of policy. This article explores the potential of regional carbon budgets to inform climate policy. Using the large database of scenarios from IPCC AR5 WGIII, we show that regional budgets are important metrics of the long term contribution to climate change and the effort required to mitigate it. However, their value appears to be more limited for informing short term courses of actions, and for predicting the economic consequences of emission reduction policies.

Recent research in the field of network economics has shown how explicitly modelling the network structure of social and economic relations can provide significant theoretical insights, as well as account for previously unexplained empirical evidence. Despite their critical importance to many environmental problems, network structures and dynamics have been largely disregarded by the environmental economics literature. This paper aims to begin to fill this gap by analyzing how networks can provide new insights for both theory and practice, and identifying several avenues for future research. The paper addresses questions pertaining to a wide range of issues, including the adoption and diffusion of green technologies, access to and distribution of natural resources, common-pool resource management and governance, and the stability of international environmental coalitions.

Universal access to modern energy services, in terms of access to electricity and to modern cooking facilities, has been recognized as fundamental challenge for development and is likely to be included in the post-2015 Sustainable Development Goals. Despite a strong praise for action and several programs at both national and international level, very few impact evaluation studies try to shed light on the causal relationship between access to energy and development, by also allowing decision makers to rigorously assess cost-effectiveness and efficiency of policies and programs. This work attempts to review the literature on existing impact evaluation of access to electricity and modern cooking facilities. For access to electricity we consider as outcomes labour markets, time allocation, household welfare (consumption, income, schooling and health) and business. For access to improved cookstoves, we assess impacts on household welfare. The reviewed literature highlights a significant causal impact of electricity access on important metrics of wellbeing, but more mixed evidence regarding clean cookstove. Finally, we also review the barriers and drivers of access to modern energy services identified by most recent impact evaluation studies.

The potential of geoengineering as an alternative or complementary option to mitigation and adaptation has received increased interest in recent years. The scientific assessment of geoengineering is driven to a large extent by assumptions about its effectiveness, costs, and impacts, all of which are highly uncertain. This has led to a polarizing debate. This paper evaluates the role of Solar Radiation Management (SRM) on the optimal abatement path, focusing on the uncertainty about the effectiveness of SRM and the interaction with uncertain climate change response. Using standard economic models of dynamic decision theory under uncertainty, we show that abatement is decreasing in the probability of success of SRM, but that this relation is concave and thus that significant abatement reductions are optimal only if SRM is very likely to be effective. The results are confirmed even when considering positive correlation structures between the effectiveness of geoengineering and the magnitude of climate change. Using a stochastic version of an Integrated Assessment Model, the results are found to be robust for a wide range of parameters specification.

This paper uses an integrated assessment model to quantify the climate R&D investment strategy for a variety of scenarios fully consistent with 2°C. We estimate the total climate R&D investment needs in approximately 1 USD Trillion cumulatively in the period 2010-2030, and 1.6 USD Trillions in the period 2030-2050. Most of the R&D would be carried out in industrialized countries initially, but would be evenly split after 2030. We also assess a ‘climate R&D deal’ in which countries cooperate on innovation in the short term, and find that an R&D agreement slightly underperforms a climate policy based on the extension of the Copenhagen pledges till 2030. Both policies are inferior to full cooperation on mitigation starting in 2020. A global agreement on clean energy innovation beyond 2030 without sufficiently stringent GHG emissions reduction policies is found to be incompatible with 2°C.

Our purpose is to analyse the effectiveness and efficiency of a Partial Climate Agreement with open entry under a non-cooperative Nash-Equilibrium framework. We evaluate a partial agreement policy in which non-signatory countries can decide to join or to leave a coalition of the willing at any point in time. By means of a simple analytical model and of a numerical integrated assessment model, we assess different coalition structures, and different minimum admission requirements. Our results indicate that a Partial Climate Agreement with open entry can be effective, achieving climate stabilization between 2C and 3C depending on the composition of the coalition of the willing. The policy turns out to be also rather efficient, with only minor losses with respect to a full cooperation agreement. Finally, we quantify the optimal admission requirement in about 40-50% of cumulative abatement.

This paper examines the dynamics of energy investments and clean energy Research and Development (R&D) using a scenario-based modeling approach. Starting from the global scenarios proposed in the RoSE model ensemble experiment, we analyze the dynamics of investments under different assumptions regarding economic and population growth as well as availability of fossil fuel resources, in the absence of a climate policy. Our analysis indicates that economic growth and the speed of income convergence across countries matters for improvements in energy efficiency, both via dedicated R&D investments but mostly through capital-energy substitution. In contrast, fossil fuel prices, by changing the relative competitiveness of energy sources, create an economic opportunity for radical innovation in the energy sector. Indeed, our results suggest that fossil fuel availability is the key driver of investments in low carbon energy innovation. However, this innovation, by itself, is not sufficient to induce emission reductions compatible with climate stabilization objectives.

Energy poverty alleviation has become an important political issue in the most recent years. Several initiatives and policies have been proposed to deal with poor access to modern sources of energy in many developing countries. Given the large number of people lacking basic energy services, an important question is whether providing universal access to modern energy could significantly increase CO2 emissions. This paper provides one of the few formal assessments of this problem by means of a simple but robust model of current and future energy consumption. The model allows mapping energy consumption globally for different classes of energy use, quantifying current and future imbalances in the distribution of energy consumption. Our results indicate that an energy poverty eradication policy to be met by 2030 would increase global final energy consumption by about 7% (or 19EJ). This is the same quantity of energy which would be added between now and 2030 by individuals with energy consumption above current European standards. The additional energy infrastructure needed to eradicate energy poverty would produce 16-131 GtCO2 over the 21st century and contribute at most 0.1C of additional warming.

The theory of international environmental agreements overwhelmingly assumes that governments engage as unitary agents. Each government makes choices based on benefits and costs that are simple national aggregates, and similarly on a single set of national-level motivations, together drawing a strong analogy with the behaviour of an individual or firm in other strategic contexts. In reality, however, various domestic special interests shape environmental policy, including how national governments cooperate on cross-border issues. Therefore in this paper we introduce to a classic model of international environmental cooperation the phenomenon of domestic political competition, whereby lobby groups seek to influence policy by offering to fund political campaigning. We use the model to establish some general conditions for the effects of lobbying on the stringency of policy and the size of coalitions cooperating to provide an environmental good. Using specific functional forms, we obtain a range of further results, including circumstances in which the omission of lobbying results in environmental protection being underestimated.

This paper looks at the interplay between human capital and innovation in the presence of climate and educational policies. Using recent empirical estimates, human capital and general purpose R&D are introduced in an integrated assessment model that has been extensively applied to study climate change mitigation. Our results suggest that climate policy stimulates general purpose as well as clean energy R&D but reduces the incentive to invest in human capital formation. Human capital increases the productivity of labour and the complementarity between labour and energy drives its pollution-using effect (direct effect). When human capital is an essential input in the production of generic and energy dedicated knowledge, the crowding out induced by climate policy is mitigated, thought not completely offset (indirect effect). The pollution-using implications of the direct effect prevail over the indirect contribution of human capital to the creation of new and cleaner knowledge. A policy mix that combines educational as well as climate objectives offsets the human capital crowding-out with a moderate, short-term consumption loss. Human capital is complement to all forms of innovation and an educational policy stimulates both energy and general purpose innovation. This result has important policy implications considering the growing concern that effective climate policy is conditional on solid economic development and therefore it needs to be supplemented by other policy targets.

This paper analyses the incentives to participate in and the stability of international climate coalitions. Using the integrated assessment model WITCH, the analysis of coalitions' profitability and stability is performed under alternative assumptions concerning the pure rate of time preference, the social welfare aggregator and the extent of climate damages. We focus on the profitability, stability, and potential stability of a number of coalitions which are potentially effective in reducing emissions. We find that only the grand coalition under a specific sets of assumptions finds it optimal to stabilise GHG concentration below 550 ppm CO2-eq. However, the grand coalition is found not to be stable, not even potentially stable even through an adequate set of transfers. However, there exist potentially stable coalitions, but of smaller size, which are also potentially environmentally effective. Depending on the assumptions made, they could achieve up to 600 ppm CO2-eq. More ambitious targets lead to the collapse of the coalition.

Global warming requires a response characterized by forward-looking management of atmospheric carbon and respect for ethical principles. Both safety and fairness must be pursued, and there are severe trade-offs as these are intertwined by the limited headroom for additional atmospheric CO2 emissions. This paper provides a simple numerical mapping at the aggregated level of developed vs. developing countries in which safety and fairness are formulated in terms of cumulative emissions and cumulative per capita emissions respectively. It becomes evident that safety and fairness cannot be achieved simultaneously for strict definitions of both. The paper further posits potential global trading in future cumulative emissions budgets in a world where financial transactions compensate for physical emissions: the safe vs. fair trade-off is less severe but remains formidable. Finally, we explore very large deployments of engineered carbon sinks and show that roughly 1000 GtCO2 of cumulative negative emissions over the century are required to have a significant effect, a remarkable scale of deployment. We also identify the unexplored issue of how such sinks might be treated in sub-global carbon accounting.

The aim of this paper is to provide an assessment of the potential for resource curse in the renewable energy sector. Taking a political economy approach, we analyze the link between public support schemes for renewable energy and the potential scope for rent seeking and corruption. The insights of a model of political influence by interest groups are tested empirically using a panel data of Italian provinces for the period 1990-2007. We find evidence that a curse exists in the case of wind energy, and specifically that: i) criminal association activity increased more in high-wind provinces and especially after the introduction of a more favourable public policy regime and, ii) the expansion of the wind energy sector has been driven by both the wind level and the quality of political institutions, through their effect on criminal association. The analysis points out that in the presence of poor institutions, efficient market-based policies can have an adverse impact. This has important normative implications especially for countries that are characterized by abundant renewable resources and weak institutions, and are thus more susceptible to the private exploitation of public incentives.

This paper examines the role of pro-social behavior as a mechanism for the establishment and maintenance of cooperation in resource use under variable social and environmental conditions. By coupling resource stock dynamics with social dynamics concerning compliance to a social norm prescribing non-excessive resource extraction in a common pool resource (CPR), we show that when reputational considerations matter and a sufficient level of social stigma affects the violators of a norm, sustainable outcomes are achieved. We find large parameter regions where norm-observing and norm-violating types coexist, and analyze to what extent such coexistence depends on the environment.

This paper analyzes the economic and investment implications of a series of climate mitigation scenarios, characterized by different levels of ambition in terms of long term stabilization goals and the transition to attain them. In particular, the implications of fairly ambitious scenarios are investigated for the first time by means of the model WITCH. Although milder climate objectives can be achieved at moderate costs, our results show that stringent stabilization paths, compatible with the target of the European Union and the G8, might have important economic repercussions. The timing of mitigation action influences the cost of meeting a target as well the stringency of the targets we can aspire to. To contain costs it is crucial to rely on a wide mitigation portfolio. Strong reductions in energy consumption through enhanced energy efficiency and life style changes are needed to achieve stringent climate policies. The analysis carried out in the present paper contains several idealistic assumptions that could be violated in the real world where some technologies may not be fully available, technology transfers and diffusion are imperfect, some world regions may not accept to reduce their GHG emissions, trading might be limited to some sectors or to a fraction of the total abatement effort, etc. This would increase the challenge of climate protection and the costs of reducing GHG emissions.

Substantial evidence has accumulated in recent empirical works on the limited ability of the Nash equilibrium to rationalize observed behavior in many classes of games played by experimental subjects. This realization has led to several attempts aimed at finding tractable equilibrium concepts which perform better empirically; one such example is the impulse balance equilibrium (Selten, Chmura, 2008), which introduces a psychological reference point to which players compare the available payoff allocations. This paper is concerned with advancing two new, empirically sound, concepts: equity-driven impulse balance equilibrium (EIBE) and equity-driven quantal response equilibrium (EQRE): both introduce a distributive reference point to the corresponding established stationary concepts known as impulse balance equilibrium (IBE) and quantal response equilibrium (QRE). The explanatory power of the considered models leads to the following ranking, starting with the most successful in terms of fit to the experimental data: EQRE, IBE, EIBE, QRE and Nash equilibrium.

This paper uses WITCH, an integrated assessment model with a game-theoretic structure, to explore the prospects for, and the stability of broad coalitions to achieve ambitious climate change mitigation action. Only coalitions including all large emitting regions are found to be technically able to meet a concentration stabilisation target below 550 ppm CO2eq by 2100. Once the free-riding incentives of non-participants are taken into account, only a grand coalition including virtually all regions can be successful. This grand coalition is profitable as a whole, implying that all countries can gain from participation provided appropriate transfers are made across them. However, neither the grand coalition nor smaller but still environmentally significant coalitions appear to be stable. This is because the collective welfare surplus from cooperation is not found to be large enough for transfers to offset the free-riding incentives of all countries simultaneously. Some factors omitted from the analysis, which might improve coalition stability, include the co-benefits from mitigation action, the costless removal of fossil fuel subsidies, as well as alternative assumptions regarding countries' bargaining behaviour.

This paper uses the WITCH model, a computable general equilibrium model with endogenous technological change, to explore the impact of various climate policies on energy technology choices and the costs of stabilising greenhouse gas concentrations. Current and future expected carbon prices appear to have powerful effects on R&D spending and clean technology diffusion. Their impact on stabilisation costs depends on the nature of R&D: R&D targeted at incremental energy efficiency improvements has only limited effects, but R&D focused on the emergence of major new low-carbon technologies could lower costs drastically if successful - especially in the non-electricity sector, where such low-carbon options are scarce today. With emissions coming from multiple sources, keeping a wide range of options available matters for stabilisation costs more than improving specific technologies. Due to international knowledge spillovers, stabilisation costs could be further reduced through a complementary, global R&D policy. However, a strong price signal is always required.

This paper builds on the assumption that OECD countries are (or will soon be) taking actions to reduce their greenhouse gas emissions. These actions, however, will not be sufficient to control global warming, unless developing countries also get involved in the cooperative effort to reduce GHG emissions. This paper investigates the best short-term strategies that emerging economies can adopt in reacting to OECD countrie's mitigation effort, given the common long-term goal to prevent excessive warming without hampering economic growth. Results indicate that developing countries would incur substantial economic losses by following a myopic strategy that disregards climate in the short-run, and that their optimal investment behaviour is to anticipate the implementation of a climate policy by roughly 10 years. Investing in innovation ahead of time is also found to be advantageous. The degree of policy anticipation is shown to be important in determining the financial transfers of an international carbon market meant to provide incentives for the participation of developing countries. This is especially relevant for China, whose recent and foreseeable trends of investments in innovation are consistent with the adoption of domestic emission reduction obligations in 2030.

WITCH is an energy-economy-climate model developed by the climate change group at FEEM. The model has been extensively used in the past 3 years for the economic analysis of climate change policies. WITCH is a hybrid top-down economic model with a representation of the energy sector of medium complexity. Two distinguishing features of the WITCH model are the representation of endogenous technological change and the game-theoretic set-up. Technological change is driven by innovation and diffusion processes, both of which feature international spillovers. World countries are grouped in 12 regions which interact with each other in a setting of strategic interdependence. This paper describes the updating of the base year data to 2005 and some new features: the inclusion of non-CO2 greenhouse gases and abatement options, the new specification of low carbon technologies and the inclusion of reducing emissions from deforestation and degradation.

In this paper we analyze the relative importance and mutual behavior of two competing base-load electricity generation options that each are capable of contributing significantly to the abatement of global CO2 emissions: nuclear energy and coal-based power production complemented with CO2 capture and storage (CCS). We also investigate how, in scenarios from an integrated assessment model that simulates the economics of a climate-constrained world, the prospects for nuclear energy would change if exogenous limitations on the spread of nuclear technology were relaxed. Using the climate change economics model WITCH we find that until 2050 the resulting growth rates of nuclear electricity generation capacity become comparable to historical rates observed during the 1980s. Given that nuclear energy continues to face serious challenges and contention, we inspect how extensive the improvements of coal-based power equipped with CCS technology would need to be if our model is to significantly scale down the construction of new nuclear power plants.

This paper analyses the cost implications for climate policy in developed countries if developing countries are unwilling to adopt measures to reduce their own GHG emissions. First, we assume that a 450 CO2 (550 CO2e) ppmv stabilisation target is to be achieved and that Non Annex1 (NA1) countries decide to delay their GHG emission reductions by 30 years. What would be the cost difference between this scenario and a case in which both developed and developing countries start reducing their emissions at the same time? Then, we look at a scenario in which the timing of developing countries' participation is uncertain and again we compute the costs of climate policy in developed and developing countries. We find that delayed participation of NA1 countries has a negative impact on climate policy costs. Economic inefficiencies can be as large as 10-25 TlnUSD. However, this additional cost wanes when developing countries are allowed to trade emission reductions from their baseline emission paths during the 30-year delay period. Thus, irrespective of whether NA1 countries are immediately assigned an emission reduction target or not, they should nonetheless be included in a global carbon market. Technology deployment is also affected by the timing of developing countries' mitigation measures. Delayed NA1-country participation in a climate agreement would scale down the deployment of coal with CCS throughout the century. On the other hand, innovation in the form of energy R&D investments would be positively affected, since it would become crucial in developed countries. Finally, uncertainty about the timing of NA1-country participation does not modify the optimal abatement strategy for developed countries and does not alter policy costs as long as a global carbon market is in place. - Delayed action ; climate policy ; stabilisation costs ; uncertain participation

Despite the growing concern about actual on-going climate change, there is little consensus about the scale and timing of actions needed to stabilise the concentrations of greenhouse gases. Many countries are unwilling to implement effective mitigation strategies, at least in the short-term, and no agreement on an ambitious global stabilisation target has yet been reached. It is thus likely that some, if not all countries, will delay the adoption of effective climate policies. This delay will affect the cost of future policy measures that will be required to abate an even larger amount of emissions. What additional economic cost of mitigation measures will this delay imply? At the same time, the uncertainty surrounding the global stabilisation target to be achieved crucially affects short-term investment and policy decisions. What will this uncertainty cost? Is there a hedging strategy that decision makers can adopt to cope with delayed action and uncertain targets? This paper addresses these questions by quantifying the economic implications of delayed mitigation action, and by computing the optimal abatement strategy in the presence of uncertainty about a global stabilisation target (which will be agreed upon in future climate negotiations). Results point to short-term inaction as the key determinant for the economic costs of ambitious climate policies. They also indicate that there is an effective hedging strategy that could minimise the cost of climate policy under uncertainty, and that a short-term moderate climate policy would be a good strategy to reduce the costs of delayed action and to cope with uncertainty about the outcome of future climate negotiations. By contrast, an insufficient short-term effort significantly increases the costs of compliance in the long-term.

This paper investigates the relative economic and environmental outcomes of price versus quantity mechanisms to control GHG emissions when abatement costs are uncertain. In particular, we evaluate the impacts on policy costs, CO2 emissions and energy R&D for a stringent mitigation target of 550 ppmv CO2 equivalent (i.e. 450 for CO2 only) concentrations. The analysis is performed in an optimal growth framework via Monte Carlo simulations of the integrated assessment model WITCH (World Induced Technical Change Hybrid). Results indicate that the price instrument stochastically dominates the quantity instrument when a stringent stabilization policy is in place.

This paper provides a quantitative comparison of the main architectures for an agreement on climate policy. Possible successors to the Kyoto protocol are assessed according to four criteria: economic efficiency; environmental effectiveness; distributional implications; and their political acceptability which is measured in terms of feasibility and enforceability. The ultimate aim is to derive useful information for designing a future agreement on climate change control.

It is widely recognized that technological change has the potential to reduce GHG emissions without compromising economic growth; hence, any better understanding of the process of technological innovation is likely to increase our knowledge of mitigation possibilities and costs. This paper explores how international knowledge flows affect the dynamics of the domestic R&D sector and the main economic and environmental variables. The analysis is performed using WITCH, a dynamic regional model of the world economy, in which energy technical change is endogenous. The focus is on disembodied energy R&D international spillovers. The knowledge pool from which regions draw foreign ideas differs between High Income and Low Income countries. Absorption capacity is also endogenous in the model. The basic questions are as follows. Do knowledge spillovers enhance energy technological innovation in different regions of the world? Does the speed of innovation increase? Or do free-riding incentives prevail and international spillovers crowd out domestic R&D efforts? What is the role of domestic absorption capacity and of policies designed to enhance it? Do greenhouse gas stabilization costs drop in the presence of international technological spillovers? The new specification of the WITCH model presented in this paper enables us to answer these questions. Our analysis shows that international knowledge spillovers tend to increase free-riding incentives and decrease the investments in energy R&D. The strongest cuts in energy R&D investments are recorded among High Income countries, where international knowledge flows crowd out domestic R&D efforts. The overall domestic pool of knowledge, and thus total net GHG stabilization costs, remain largely unaffected. International spillovers, however, are also an important policy channel. We therefore analyze the implication of a policy mix in which climate policy is combined with a technology policy designed to enhance absorption capacity in developing countries. Significant positive impacts on the costs of stabilising GHG concentrations are singled out. Finally, a sensitivity analysis shows that High Income countries are more responsive than Low Income countries to changes in the parameters and thus suggests to focus additional empirical research efforts on the former.

This paper investigates the potential contribution of forestry management in meeting a CO2 stabilization policy of 550 ppmv by 2100. In order to assess the optimal response of the carbon market to forest sequestration we couple two global models. An energy-economy-climate model for the study of climate policies is linked with a detailed forestry model through an iterative procedure to provide the optimal abatement strategy. Results show that forestry is a determinant abatement option and could lead to significantly lower policy costs if included. Linking forestry management to the carbon market has the potential to delay the policy burden, and is expected to reduce the price of carbon of 40% by 2050. Biological sequestration will mostly come from avoided deforestation in tropical forests rich countries. The inclusion of this mitigation option is demonstrated to crowd out some of the traditional abatement in the energy sector and to lessen induced technological change in clean technologies.

The stabilisation of GHG atmospheric concentrations at levels expected to prevent dangerous climate change has become an important, global, long-term objective. It is therefore crucial to identify a cost-effective way to achieve this objective. In this paper we use WITCH, a hybrid climate-energy-economy model, to obtain a quantitative assessment of some cost-effective strategies that stabilise CO2 concentrations at 550 or 450 ppm. In particular, this paper analyses the energy investment and R&D policies that optimally achieve these two GHG stabilisation targets (i.e. the future optimal energy mix consistent with the stabilisation of GHG atmospheric concentrations at 550 and 450 ppm). Given that the model accounts for interdependencies and spillovers across 12 regions of the world, optimal strategies are the outcome of a dynamic game through which inefficiency costs induced by global strategic interactions can be assessed. Therefore, our results are somehow different from previous analyses of GHG stabilisation policies, where a central planner or a single global economy are usually assumed. In particular, the effects of free-riding incentives in reducing emissions and in investing in R&D are taken into account. Technical change being endogenous in WITCH, this paper also provides an assessment of the implications of technological evolution in the energy sector of different stabilisation scenarios. Finally, this paper quantifies the net costs of stabilising GHG concentrations at different levels, for different allocations of permits and for different technological scenarios. In each case, the optimal long-term investment strategies for all available energy technologies are determined. The case of an unknown backstop energy technology is also analysed.

This paper analyses optimal investments in innovation when dealing with a stringent climate target and with the uncertain effectiveness of R&D. The innovation needed to achieve the deep cut in emissions is modelled by a backstop carbon-free technology whose cost depends on R&D investments. To better represent the process of technological progress, we assume that R&D effectiveness is uncertain. By means of a simple analytical model, we show how accounting for the uncertainty that characterizes technological advancement yields higher investments in innovation and lower policy costs. We then confirm the results via a numerical analysis performed with a stochastic version of WITCH, an energy-economy-climate model. The results stress the importance of a correct specification of the technological change process in economy-climate models.