Green parties have enjoyed tremendous electoral success over the last decades. Yet, little is known about what they do when leading governments. We examine how Green governments influence macroeconomic, education, and environmental outcomes. Our empirical strategy exploits that the Fukushima nuclear disaster in Japan gave rise to an unanticipated change in government in the German state Baden-Wuerttemberg in 2011. The incumbent rightwing government was replaced by a leftwing government led by the Green party. We use the synthetic control method to select control states against which Baden-Wuerttemberg's outcomes can be compared. The results do not suggest that the Green government influenced macroeconomic outcomes. The Green government implemented education policies that caused comprehensive schools to become larger. We find no evidence that the Green government influenced CO2 emissions or increased energy usage from renewable energies overall. An intriguing result is that the share of wind power usage decreased relative to the estimated counterfactual. Intra-ecological conflicts are likely to have prevented the Green government from implementing drastic changes in environmental policies.

In this study we consider the pricing of energy derivatives when the evolution of spot prices is modeled with a normal tempered stable driven Ornstein-Uhlenbeck process. Such processes are the generalization of normal inverse Gaussian processes that are widely used in energy finance applications. We first specify their statistical properties calculating their characteristic function in closed form. This result is instrumental for the derivation of non-arbitrage conditions such that the spot dynamics is consistent with the forward curve without relying on numerical approximations or on numerical integration. Moreover, we conceive an efficient algorithm for the exact generation of the trajectories which gives the possibility to implement Monte Carlo simulations without approximations or bias. We illustrate the applicability of the theoretical findings and the simulation algorithms in the context of the pricing of different contracts, namely, strips of daily call options, Asian options with European style and swing options. Finally, we present an extension to future markets.

Demand response (DR) programs have gained much attention during the last three decades to optimize the decisions of the electricity market participants considering the demand-side management (DSM). It can potentially enhance system reliability and manages price volatility by modifying the amount or time of electricity consumption. This paper proposes a novel game-theoretical model accounting for the relationship between retailers (leaders) and consumers (followers) in a dynamic price environment where both players optimize their respective economic goals under uncertainty. The model is solved under two frameworks. First by considering retailer's market power and second by accounting for an equilibrium setting based on a Cournot game. These are formulated in terms of a mathematical program with equilibrium constraints (MPEC) and with a mixed-integer linear program (MILP), respectively. In particular, the retailers' market power model is first formulated as a bi-level optimization problem, and the MPEC is subsequently derived by replacing the consumers' problem (lower level) with its Karush-Kuhn-Tucker (KKT) optimality conditions. In contrast, the Cournot equilibrium model is solved as a MILP by concatenating the retailer's and consumers' KKT optimality conditions. The solution sets, the practical approaches for solutions, the required techniques to test and compare the performance of the model are undertaken with realistic data. Numerical simulations confirm the applicability and effectiveness of the proposed model to explore the interactions of markets power and DR programs. The results confirm that consumers are better off in an equilibrium framework while the retailer increases its expected profit when the market power is considered. However, we show how these results are highly affected by the levels of of consumers' flexibility.