Analyse der Marktaussichten von Biogasanlagen

Without guaranteed compensation, granted by the German Renewable Energy Sources Act (Erneuerbare Energien Gesetz/EEG), biogas plants compete with all other plant types on the market for electrical energy. However, exchange-based electricity products do not currently permit an economically viable operation of biogas plants owing to their cost situation.     

Strategic Patenting in Biotechnology

Patents can be used by their owners in a variety of strategic ways in the market place that do not necessarily conform with the original idea of patents as a remedy against market failure. More patenting does not lead to more innovation in all cases. This article looks at the relevance of patents and their strategic uses in the biotechnology industry. The article considers the different motives for applying for patents and various strategies. Theoretical considerations are made based on empirical findings from a survey of the Swiss biotechnology industry carried out in 2003. The empirical data confirm that patents for biotechnological inventions are important as an incentive for investment in R&D and that patents are an efficient tool for protecting biotechnological inventions. Strategic patenting is not very common in Switzerland and there are no signs for an abusive level of strategic patenting.     

The process safety impact of distributed control systems

Experience has shown that a Distributed Control System (DCS) can provide enhanced process monitoring and control capabilities, as well as system self-diagnostics, that permit increased safety of process operations. However, this enhanced safety does not come about automatically with the installation of a DCS. The complexity and versatility of the DCS can introduce new failure scenarios leading to process upset and potential relization of process hazards. This paper reviews some novel considerations that should be taken into account when conducting process hazards reviews on facilities controlled by a DCS.     

Competitive moment matching of a New-Keynesian and an Old-Keynesian model

The paper considers two rival models referring to the new macroeconomic consensus: a standard three-equation model of the New-Keynesian variety versus dynamic adjustments of a business and an inflation climate in an ‘Old-Keynesian’ tradition. Over the two subperiods of the Great Inflation and Great Moderation, both of them are estimated by the method of simulated moments. An innovative feature is here that the moments do not only include the autocovariances up to eight lags of quarterly output, inflation and the interest rate, but optionally also a measure of the raggedness of the three variables. In short, the performance of the Old-Keynesian model is very satisfactory and similar to the New-Keynesian model, or even better. In particular, the Old-Keynesian model is better suited to match the new moments without deteriorating the original second moments too much.     

Buchbesprechung

Buchbesprechung

Buchbesprechung     

What you are is what you like—similarity biases in venture capitalists' evaluations of start-up teams

This paper extends recent research studying biases in venture capitalist's decision making. We contribute to this literature by analyzing biases arising from similarities between a venture capitalist and members of a venture team. We summarize the psychological foundations of such similarity effects and derive a set of hypotheses regarding the impact of similarity on the assessment of team quality. Using data from a conjoint experiment with 51 respondents, we find that venture capitalists tend to favor teams that are similar to themselves in type of training and professional experience. Our results have important implications for academics and practitioners alike.     

Modelling and forecasting liquidity supply using semiparametric factor dynamics

We model the dynamics of ask and bid curves in a limit order book market using a dynamic semiparametric factor model. The shape of the curves is captured by a factor structure which is estimated nonparametrically. Corresponding factor loadings are modelled jointly with best bid and best ask quotes using a vector error correction specification. Applying the framework to four stocks traded at the Australian Stock Exchange (ASX) in 2002, we show that the suggested model captures the spatial and temporal dependencies of the limit order book. We find spill-over effects between both sides of the market and provide evidence for short-term quote predictability. Relating the shape of the curves to variables reflecting the current state of the market, we show that the recent liquidity demand has the strongest impact. In an extensive forecasting analysis we show that the model is successful in forecasting the liquidity supply over various time horizons during a trading day. Moreover, it is shown that the model's forecasting power can be used to improve optimal order execution strategies.