131 research outputs found
A comparison of four computer-based telephone interviewing methods: Getting answers to sensitive questions
Investment Incentives Under Emission Trading: An Experimental Study
This paper presents the results of an experimental investigation on incentives to adopt advanced abatement technology under emissions trading. Our experimental design mimics an industry with small asymmetric polluting firms regulated by different schemes of tradable permits. We consider three allocation/auction policies: auctioning off (costly) permits through an ascending clock auction, grandfathering permits with re-allocation through a single-unit double auction, and grandfathering with re-allocation through an ascending clock auction. Our results confirm both dynamic and static theoretical equivalence of auctioning and grandfathering. We nevertheless find that although the market institution used to reallocate permits does not impact the dynamic efficiency from investment, it affects the static efficiency from permit trading
Small Sample Properties of the Wilcoxon Signed Rank Test with Discontinuous and Dependent Observations
Optimizing the procedure of grain nutrient predictions in barley via hyperspectral imaging
Hyperspectral imaging enables researchers and plant breeders to analyze various traits of interest like nutritional value in high throughput. In order to achieve this, the optimal design of a reliable calibration model, linking the measured spectra with the investigated traits, is necessary. In the present study we investigated the impact of different regression models, calibration set sizes and calibration set compositions on prediction performance. For this purpose, we analyzed concentrations of six globally relevant grain nutrients of the wild barley population HEB-YIELD as case study. The data comprised 1,593 plots, grown in 2015 and 2016 at the locations Dundee and Halle, which have been entirely analyzed through traditional laboratory methods and hyperspectral imaging. The results indicated that a linear regression model based on partial least squares outperformed neural networks in this particular data modelling task. There existed a positive relationship between the number of samples in a calibration model and prediction performance, with a local optimum at a calibration set size of ~40% of the total data. The inclusion of samples from several years and locations could clearly improve the predictions of the investigated nutrient traits at small calibration set sizes. It should be stated that the expansion of calibration models with additional samples is only useful as long as they are able to increase trait variability. Models obtained in a certain environment were only to a limited extent transferable to other environments. They should therefore be successively upgraded with new calibration data to enable a reliable prediction of the desired traits. The presented results will assist the design and conceptualization of future hyperspectral imaging projects in order to achieve reliable predictions. It will in general help to establish practical applications of hyperspectral imaging systems, for instance in plant breeding concepts
Do short-term laboratory experiments provide valid descriptions of long-term economic interactions? A study of Cournot markets
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