In this comprehensive empirical study we critically evaluate the use of forecast averaging in the context of electricity prices. We apply seven averaging and one selection scheme and perform a backtesting analysis on day-ahead electricity prices in three major European and US markets. Our...

Even after Fukushima, the nuclear debate is strong in many countries, with the discussion of its economics being a significant part of it. However, most of the estimates are based on a levelized-cost methodology, which presents several shortcomings, particularly when applied to liberalized...

Using recursive estimation and rolling windows over extended sample periods we examine the time-varying relationship between spot and short-term forward prices in the Pennsylvania–New Jersey–Maryland (PJM) wholesale electricity market. We examine theoretical models of forward risk premia in...

Heating and cooling degree days are in common use in conditional demand models, billing analysis, and large-scale energy forecasts. The implications of either choosing an ex-ante base temperature, or scanning over the base temperatures, as suggested in Fels (1986) and recommended by some...

An important issue in fitting stochastic models to electricity spot prices is the estimation of a component to deal with trends and seasonality in the data. Unfortunately, estimation routines for the long-term and short-term seasonal pattern are usually quite sensitive to extreme observations,...

We use high frequency real time spot prices and day-ahead forward prices from the Pennsylvania–New Jersey–Maryland wholesale electricity market to calculate, describe, and forecast spot price volatility. We introduce the concept of forward realized volatility calculated from day-ahead...

Stochastic process models of commodity prices are important inputs in energy investment evaluation and planning problems. In this paper, we focus on modeling and forecasting the long-term price level, since it is the dominant factor in many such applications. To provide a foundation for our...

This paper develops an econometric forecasting system of energy demand coupled with engineering–economic models of energy supply. The framework is used to quantify the energy and environmental impacts of renewable and natural gas based electricity power generation in California, considering...

The European energy policy is substantially driven by the target to reduce the CO2-emissions significantly and to mitigate climate change. Nevertheless European power generation is still widely based on fossil fuels. The carbon capture and storage technology (CCS) could be part of an approach to...

We propose using Realized GARCH-type models to estimate the daily price volatility in the EPEX power markets. The model specifications extract the volatility-related information from realized measures, which improves the in-sample fit of the data. More importantly, evidence on the out-of-sample...