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Based on the approach advanced by Elliott et al. (Rev. Ec. Studies. 72, 1197-1125), we found that the loss function of a sample of oil price forecasters is asymmetric in the forecast error. Our findings indicate that the loss oil price forecasters incurred when their forecasts exceeded the price...
Persistent link: https://www.econbiz.de/10010308142
We study the properties of generalized stochastic gradient (GSG) learning in forward-looking models. We examine how the conditions for stability of standard stochastic gradient (SG) learning both differ from and are related to E-stability, which governs stability under least squares learning. SG...
Persistent link: https://www.econbiz.de/10010261355
Estimating linear rational expectations models requires replacing the expectations of future, endogenous variables either with forecasts from a fully solved model, or with the instrumented actual values, or with forecast survey data. Extending the methods of McCallum (1976) and Gottfries and...
Persistent link: https://www.econbiz.de/10011940743
Based on annual data for growth and inflation forecasts for Germany covering the time span from 1970 to 2007 and up to 17 different forecasts per year, we test for a possible asymmetry of the forecasters' loss function and estimate the degree of asymmetry for each forecasting institution using...
Persistent link: https://www.econbiz.de/10010285849
The concept of cointegration (see e.g., Engle and Granger, 1987; Johansen, 1988) has extensively been used to model equilibrium relationships (see e.g., Johansen and Juselius, 1990; Ericsson, 1998). The links between economic and econometric concepts are now well understood and they have become part of...
Persistent link: https://www.econbiz.de/10010285865
Do financial market analysts use structural economic models when forecasting exchange rates? This is the leading question analysed in this apper. In contrast to other studies we use expectations instead of realised data. Therefore we analyse the implicit structural models forecasters have in...
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