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This paper analyzes the dynamic behavior of day-ahead spot prices in the German electricity spot market due to positive structural shocks in wind and solar power. It uses a dynamic structural vector autoregressive model to estimate the related structural impulse response functions. The estimates suggest that wind power shocks have a more prolonged negative effect on spot prices than solar power shocks. Significant autocorrelations of wind power for larger lags indicate these results. The total negative merit order effect of a solar power shock is larger when using a reasonable model specification. One reason might be that solar power shocks coincide with demand peaks. However, results regarding the relation of the effects of wind and solar should be dealt with carefully because these results do not hold for all specifications. Past static estimates show differences in the total average negative merit order effects. These estimates might be overstated if wind and solar power dynamics are transferred to the merit order effects.

In a power system featuring a large share of intermittent renewable energy sources (RES) and inflexible thermal generators, efficiency gains on generation costs could be achieved by curtailing the production of RES. However, as RES feature very low variable production costs, over-curtailment can be costly. In this article, we use a stylised analytical model to assess this trade-off. We show that while curtailing RES when their variability is high and the system flexibility is low can reduce generation costs, the different stakeholders (consumers, dispatchable generators, RES) will not necessarily benefit from such measures. As a consequence, generators will opt for a sub-optimal level of curtailment, and this level of curtailment should rather be set by the TSO. Either incentive to provide the TSO with accurate forecasts of RES availability, or alternatively centralised forecasting by the TSO, should then be put into place to solve the resulting problem of asymmetry of information.

This paper (CPB/PBL) uses the computable general equilibrium model WorldScan to analyse interactions between EU’s air pollution and climate change policies. Covering the entire world and seven EU countries, WorldScan simulates economic growth in a neo-classical recursive dynamic framework, including emissions and abatement of greenhouse gases (CO 2 , N2O and CH4) and air pollutants (SO2, NOx, NH3 and PM2.5). Abatement includes the possibility of using end-of-pipe control options that remove pollutants without affecting the emissionproducing activity itself. This paper analyses several variants of EU’s air pollution policies for the year 2020. Air pollution policy will depend on end-of-pipe controls for not more than 50%, thus also at least 50% of the required emission reduction will come from changes in the use of energy through efficiency improvements, fuel switching and other structural changes in the economy. Greenhouse gas emissions thereby decrease, which renders climate change policies less costly. Our results show that carbon prices will fall, but not more than 33%, although they could drop to zero when the EU agrees on a more stringent air pollution policy.

Economic thought on climate policy as an instance of environmental regulation is strongly influenced by the principle of a uniform carbon price. Economists acknowledge that this principle breaks down in a “second-best” world with other distortions, such as taxes and market power in domestic and international markets. However, systematic analysis of this point in the economic climate policy literature is scarce. In the present paper, a computable general equilibrium (CGE) set-up is chosen in order to examine what pattern of differentiated carbon prices emerges as optimal in a second-best world. The CGE model WorldScan, which is considered to be representative of the class of models routinely used for numerical climate policy analysis, produces three main results: First, the optimal pattern of carbon prices is highly differentiated, ranging from almost prohibitive taxes to high subsidies (with a range of more than 1700 euros per ton of CO 2 ). Second, the welfare gain from switching from a uniform price to optimally differentiated prices is enormous, equivalent to a 27% emission reduction for free. Third, the most important drivers of carbon price differentiation are market power in export markets as well as taxes on consumption, intermediate inputs and domestic output. This shows that carbon price differentiation cannot be dismissed as a policy option lightly. However, before translating these findings into concrete policy advice, the relevant features of modelling pre-existing distortions in CGE models need close revision.

For the first time, we apply the wavelet coherence methodology on biofuels (ethanol and biodiesel) and a wide range of related commodities (gasoline, diesel, crude oil, corn, wheat, soybeans, sugarcane and rapeseed oil). This way, we are able to investigate dynamics of correlations in time and across scales (frequencies) with a model-free approach. We show that correlations indeed vary in time and across frequencies. We find two highly correlated pairs which are strongly connected at low frequencies - ethanol with corn and biodiesel with German diesel - during almost the whole analyzed period (2003-2011). Structure of correlations remarkably changes during the food crisis - higher frequencies become important for both mentioned pairs. This implies that during stable periods, ethanol is correlated with corn and biodiesel is correlated with German diesel mainly at low frequencies so that they follow a common long-term trend. However, in the crisis periods, ethanol (biodiesel) is lead by corn (German diesel) even at high frequencies (low scales), which implies that the biofuels prices react more rapidly to the changes in their producing factors., 16 pages, 5 figures

We develop a model of competition in the solar panel industry. Solar firms manufacture panels that are differentiated both vertically and horizontally, and compete by setting quantities. The equilibrium of the model is consistent with a set of stylized facts that we document, including variation in prices, markups and market shares across firms. We calibrate the model using a new dataset data on prices, costs and shipments of leading solar companies, as well as solar sales in four leading markets. The calibrated model is applied to evaluate the impact of a decline in the price of polysilicon, a key raw material used in the manufacture of solar panels, on the equilibrium price of solar panels.

Understanding fossil fuel supply behaviour is crucial for interpreting carbon leakage and assessing the potential effectiveness of border measures in climate policy. In most computable general equilibrium models, this fossil fuel supply is derived from a constant elasticity of substitution production function, in which a natural resource is treated as a fixed factor. We show that this leads to endogenously decreasing supply elasticities and sharply increasing marginal leakage rates for large coalitions that have ambitious emissions targets, particularly when fuel exporters participate in the coalition. We propose an alternative production function that has a constant elasticity of fuel supply, which results in more stable leakage rates and a different share of trade-related leakage. The role of this model variation for the assessment of border measures in climate policy turns out to be limited. In those cases where the model versions differ most (i.e. large coalition, ambitious targets), border measures have a small effect anyway.

This paper examines the roles of futures prices of crude oil, gasoline, ethanol, corn, soybeans and sugar in the energy-grain nexus. It also investigates the own- and cross-market impacts for the lagged grain trading volume and the open interest in the energy and grain markets. According to the results, the conventional view, for which the impacts are from oil to gasoline to ethanol to grains in the energy-grain nexus, does not hold well in the long run because the oil price is influenced by gasoline, soybeans and oil. Moreover, gasoline is preceded by only the oil price, and ethanol is not foreshadowed by any of the prices. However, in the short run, a two-way feedback in both directions exists in all markets. The grain trading volume effect across oil and gasoline is more pronounced in the short-run than in the long-run, satisfying both the overconfidence/disposition and the new information hypotheses across markets. The results for the ethanol open interest show that money flows out of this market in both the short- and long-run, but no results suggest across market inflows or outflows to the other grain markets.

In the past years biofuels have received increased attention since they were believed to contribute to rural development, energy security and to fight global warming. It became clear, though, that bioenergy cannot be evaluated independently of the rest of the economy and that national and international feedback effects are important. Computable general equilibrium (CGE) models have been widely employed in order to study the effects of international climate policies. The main characteristic of these models is their encompassing scope: Global models cover the whole world economy disaggregated into regions and countries as well as diverse sectors of economic activity. Such a modelling framework unveils direct and indirect feedback effects of certain policies or shocks across sectors and countries. CGE models are thus well suited for the study of bioenergy/biofuel policies. One can currently find various approaches in the literature of incorporating bioenergy into a CGE framework. This paper gives an overview of existing approaches, critically assesses their respective power and discusses the advantages of CGE models compared to partial equilibrium models. Grouping different approaches into categories and highlighting their advantages and disadvantages is important for giving a structure to this rather recent and rapidly growing research area and to provide a guidepost for future work.

This paper estimates a dynamic model of interfuel substitution for Swedish heating plants. We use the cost share linear logit model developed by Considine and Mount [Considine, T.J., Mount, T.D., 1984. The use of linear logit models for dynamic input demand systems. Review of Economics and Statistics 66, 434–443]. All estimated own-price elasticities are negative and all cross-price elasticities are positive. The estimated dynamic adjustment rate parameter is small, however, increasing with the size of the plant and time, indicating fast adjustments in the fuel mix when changing relative fuel prices. The estimated model is used to illustrate the effects of two different policy changes.