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This paper assesses the economic impacts of linking the EU emissions trading scheme (ETS) to emerging schemes beyond Europe in the presence of a post-Kyoto agreement in 2020. Numerical simulations with a multi-country equilibrium model of the global carbon market show that linking the European ETS induces only minor economic benefits. As trading is restricted to energy-intensive companies that are assigned high initial emissions, the major compliance burden is carried by the non-trading industries excluded from the linked ETS. In the presence of parallel government trading under a post-Kyoto Protocol, the burden of the excluded sectors can be substantially alleviated by international permit trade at the country level. However, the parallel carbon markets of linked ETS companies and post-Kyoto governments are still separated here. From an efficiency perspective, the most desirable future climate policy regime is thus represented by a joint trading system facilitating international emissions trading between ETS companies and post-Kyoto governments. While the Clean Development Mechanism is not able to attenuate the inefficiencies within linked ETS, in a parallel or joint trading regime the economy-wide access to project-based abatement options in developing countries induces large additional cost-savings.

Abstract According to some definitions, an energy transition refers to the time that elapses between the introduction of a new primary energy source, or prime mover, and its rise to claiming a substantial share of the overall energy market. According to one academic view, energy transitions take an incredibly long time to occur. Another view argues the opposite. It suggests that there have been many transitions at varying scales that have occurred quite quickly—that is, between a few years and a decade or so, or within a single generation. This chapter holds that both sides are partly right, and partly wrong. After presenting evidence in support of either thesis, it elucidates four lessons for energy analysts and policymakers.

We present a novel data set of subnational economic output, Gross Regional Product (GRP), for more than 1500 regions in 77 countries that allows us to empirically estimate historic climate impacts at different time scales. Employing annual panel models, long-difference regressions and cross-sectional regressions, we identify effects on productivity levels and productivity growth. We do not find evidence for permanent growth rate impacts but we find robust evidence that temperature affects productivity levels considerably. An increase in global mean surface temperature by about 3.5°C until the end of the century would reduce global output by 7–14% in 2100, with even higher damages in tropical and poor regions. Updating the DICE damage function with our estimates suggests that the social cost of carbon from temperature-induced productivity losses is on the order of 73–142$/tCO2 in 2020, rising to 92–181$/tCO2 in 2030. These numbers exclude non-market damages and damages from extreme weather events or sea-level rise. © 2020 The Authors

This paper shows how sustainable consumption patterns can spread within a population via processes of social learning even though a strong individual learning bias may favor environmentally harmful products. We present a model depicting how the biased transmission of different behaviors via individual and social learning influences agents' consumption behavior. The underlying learning biases can be traced back to evolved cognitive dispositions. Challenging the vision of a permanent transition toward sustainability, we argue that "green" consumption patterns are not self-reinforcing and cannot be locked in permanently.

The German feed-in support of electricity generation from renewable energy sources has led to high growth rates of the supported technologies. Critics state that the costs for consumers are too high. An important aspect to be considered in the discussion is the price effect created by renewable electricity generation. This paper seeks to analyse the impact of privileged renewable electricity generation on the electricity market in Germany. The central aspect to be analysed is the impact of renewable electricity generation on spot market prices. The results generated by an agent-based simulation platform indicate that the financial volume of the price reduction is considerable. In the short run, this gives rise to a distributional effect which creates savings for the demand side by reducing generator profits. In the case of the year 2006, the volume of the merit-order effect exceeds the volume of the net support payments for renewable electricity generation which have to be paid by consumers.

Abstract This paper examines household energy use and appliance ownership in Ireland. Logit regression analyses on a large micro-dataset reveal how household characteristics can help explain the ownership of energy using appliances. Using OLS regression models, we explore the factors affecting residential energy demand conditional on appliance ownership. Results suggest that the methods of space and water heating employed by a household are even more important than electrical appliances in explaining domestic energy usage. However, the stock of appliances must be included in such models so that results will not be biased. The methods employed in this paper can be easily adopted for studies of household energy use in other countries where household expenditure survey data are available.

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