In this paper the Bry and Boschan (1971) procedure is modified such that it can be applied to quarterly data in order to recalculate the maximum duration of business cycles. In this way it can be shown that the maximum duration of business cycles constitutes 42 quarters in the United States of America and 49 quarters in the United Kingdom. The large difference to the maximum duration of Burns and Mitchell (1946) makes clear that caution is advisable with the application of the filters by Baxter and King (1999) and Christiano and Fitzgerald (2003). If one chooses the maximum duration too low (high), the amplitude of the medium-term business cycles is underestimated (overestimated) and the variability of the growth rate of the long-term trend is overestimated (underestimated).

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Using a battery on a household level has become easier after the launch of Tesla's Powerwall. Storing electricity during daytime's PV overproduction or charging the battery during night with an attractive tariff is the most prominent applications. This paper explores the economic impact of the usage of residential battery storage combined with solar photovoltaics (PV) based on real load data from Northern California, USA. A data-driven, deterministic model to benchmark electricity cost savings for single households is presented and the financial viability of such systems is scrutinized for California. Our results indicate that under current capacity and price points, battery systems have limited financial viability and have a payback period exceeding 20 years in most cases. We deepen our analysis and compare the results of our deterministic model to that of a stochastic model to demonstrate that for an hourly time resolution the deterministic model provides an adequate benchmark for estimating cost (within 3%) savings with a short (1/60th) computation time.

Upon discussion of price setting on electricity wholesale markets, many refer to the so-called merit order model. Conventional wisdom holds that during most hours of the year, coal-or natural gas-fired power plants set the price on European markets. In this context, this paper analyses price setting on European power markets. We use a fundamental electricity market model of interconnected bidding zones to determine hourly price-setting technologies for the year 2020. We find a price-setting pattern that is more complex and nuanced than the conventional wisdom suggests: across all researched countries, coal-and natural gas-fired power plants set the price for only 40 per cent of all hours. Other power generation technologies such as wind, biomass, hydro and nuclear power plants as well as lignite-fired plants set the price during the rest of the year. On some markets, the price setting is characterised by a high level of interconnectivity and thus foreign influence-as illustrated by the example of the Netherlands. During some 75 per cent of hours, foreign power plants set the price on the Dutch market, whilst price setting in other more isolated markets is barely affected by foreign markets. Hence, applying the price setting analysis to the proposed Dutch carbon price floor, we show that different carbon prices have little effect on the technological structure of the price-setting units. In this respect, the impacts of the unilateral initiative are limited. There are, however, considerable changes to be observed in wholesale power prices, import/export balances as well as production volumes and subsequent CO2 outputs of lignite-, coal-and gas-fired power plants.