In this paper, we evaluate macroeconomic forecasts for Austria and analyze the effects of external assumptions on forecast errors. We consider the growth rates of real GDP and the demand components as well as the inflation rate and the unemployment rate. The analyses are based on univariate measures like RMSE and Theil's inequality coefficient and also on the Mahalanobis distance, a multivariate measure that takes the variances of and the correlations between the variables into account. We compare forecasts generated by the two leading Austrian economic research institutes, the Institute for Advanced Studies (IHS) and the Austrian Institute of Economic Research (WIFO), and additionally consider the forecasts produced by the European Commission. The results indicate that there are no systematic differences between the forecasts of the two Austrian institutes, neither for the traditional measures nor for the Mahalanobis distance. Generally, forecasts become more accurate with a decreasing forecast horizon, as expected; they are unbiased for forecast horizons of less than a year considering traditional measures and for the shortest forecast horizon considering the Mahalanobis distance. Finally, we find that mistakes in external assumptions, in particular regarding EU GDP and the oil price, translate into forecast errors for GDP and inflation.

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Technical research projects often target innovative high-value products. These products may serve dynamic and fast-growing markets. However, while the general demand for such products may be very high and a lot of technical research is carried out in developing the respective processes, only very few new technologies and products are commercially realized and placed on the market. In order to widen the market focus toward a more comprehensive understanding of technical development, this study presents a mix of methods, including production cost analysis, business-to-business survey, and market impact assessment. When it comes to exploring a new technology that produces bioactive substances from wood, this article shows how the previously mentioned methods can be adapted, applied, and integrated for its successful commercialization.

Fibre-reinforced composites are an important field of composite research and are used in an enormous range of applications from special high-tech applications such as aeronautics to consumer goods such as sporting goods. The objective of this study is to assess the monetary value of fibres to be used for reinforcement in composites by the relation of price and certain fibre properties. To model this, relationship data from different types of technical fibres were used. An economic approach is used to identify the determinants of fibre value. In total, four regression models were calculated. The models give an impression of the impact of the explanatory variables. This work shows that the evaluation of the economic value of a reinforcement fibre by technical properties is feasible.