The Timing of National Greenhouse Gas Emission Reductions in the Presence of Other Environmental Policies

This paper shows in an empirical context that substantial cost reductions can be achieved in the implementation of Dutch national climate policy by (i) targeting the policy at the stock of greenhouse gases, thus allowing polluters flexibility in their timing of emission reductions; and (ii) integrating climate policy with other policies, thereby optimising the restructuring of the economy needed to achieve environmental policy targets. A dynamic applied general equilibrium model with bottom-up information on abatement techniques is used to show that the optimal timing of GHG emission reductions tends to follow the timing for the other environmental themes with an additional emphasis on emission reductions in the later periods. The optimal mix of technical measures and economic restructuring as source of emission reductions is affected by the strictness of environmental policy targets for all themes and hence can only be derived from an integrated analysis of these policies.Economic growth, Applied general equilibrium model, Climate change, Environmental policy

A vintage model of technology diffusion: The effects of returns to disversity and learning by using

The diffusion of new technologies is a lengthy process and many firms continue to invest in relatively old technologies. This paper develops a vintage model of technology adoption and diffusion that aims at explaining these two phenomena. Our explanation for these phenomena emphasises the relevance of complementarity between different vintages (or, alternatively, returns to diversity) and learning-by- using. The model is characterised by simultaneous investments in vintages of different quality and endogenously determined scrapping of old technologies. We show that the stronger the complementarity between different vintages and the stronger the learning-by-using, the longer it takes before firms scrap (seemingly) inferior technologies

Economic analysis of batteries: Impact on security of electricity supply and renewable energy expansion in Germany

Increasing amounts of fluctuating renewable energy lead to decreasing electricity prices and impair security of electricity supply. Consequently, sustainable and economically feasible solutions need to be found to ensure both ongoing renewable energy expansion and stable electricity supply. We examine the impact of batteries on security of the electricity supply and achieving renewable energy expansion. For this purpose we develop an electricity market model that enables the simulation of batteries both as an economic-driven investment option and as a government subsidized option. We present six policy scenarios in which batteries are utilized as an option that is subsidized by the government to secure electricity supply and engender renewable energy expansion. Our simulations, based on empirical data, indicate that, in a free market, battery investments are not profitable for private investors. On the other hand, these six policy scenarios show that by subsidizing investments in batteries governments could ensure a secure electricity supply as well as ongoing renewable energy expansion. A comparison to similar policy scenarios that do not adopt batteries indicates that the total sum of gove

Economics of renewable energy expansion and security of supply: A dynamic simulation of the German electricity market

We explore the impact of renewable energy under free market conditions on the security of energy supply using data for the German electricity market. We design a fundamental electricity market model, where renewable energy capacity is not driven by expansion goals, but is dynamically modeled as an economically-driven investment option. Furthermore, we analyze the economics of five policy scenarios designed to secure both electricity supply and renewable energy expansion. Our analysis demonstrates that renewable energy expansion leads to conventional power plant shut-downs (due to economic losses) and, as a result, to energy shortages. We find that the application of a fixed feed-in tariff mechanism for renewable energy (i.e. a fixed payment for the provided energy) is an appropriate instrument to simultaneously achieve renewable energy expansion and uninterrupted energy supply. However, when internalizing the external costs of electricity generation, the scenario of a free market for renewable energy together with subsidies for conventional power plants becomes the most cost efficient option

An optimal mix of conventional power systems in the presence of renewable energy: A new design for the German electricity market

In this paper we develop a new market design for the German electricity market. Our new market design simultaneously ensures security of energy supply and ongoing expansion of renewable energy (RE). The methodological approach applied considers the special challenges resulting from the intermittent nature of RE ‒ we simulate developments in the German electricity market between 2015 and 2034 and differentiate across various power plant technologies according to their ability to flexibly react to changes in the residual load. In theory, a composition of power plants that is optimally adapted to residual load always leads to the most cost efficient supply of electricity. However, our empirical analysis demonstrates that this does not necessarily lead to an improved market environment, both in terms of power plant profitability as well as uninterrupted power supply

Active learning and optimal climate policy

This paper develops a climate-economy model with uncertainty, irreversibility, and active learning. Whereas previous papers assume learning from one observation per period, or experiment with control variables to gain additional information, this paper considers active learning from investment in monitoring, specifically in improved observations of the global mean temperature. We find that the decision maker invests a significant amount of money in climate research, far more than the current level, in order to increase the rate of learning about climate change. This helps the decision maker make improved decisions. The level of uncertainty decreases more rapidly in the active learning model than in the passive learning model with only temperature observations. As the uncertainty about climate change is smaller, active learning reduces the optimal carbon tax. The greater the risk, the larger is the effect of learning. The method proposed here is applicable to any dynamic control problem where the quality of monitoring is a choice variable, for instance, the precision at which we observe GDP, unemployment, or the quality of education