Abstract or Introduction
This seminar paper aims to briefly introduce selected modelfree methods which can be used both to evaluate specific forecast series and to compare pairwise competing series of forecasts. Problems arising from parameter estimation uncertainty and nested forecast generating models are illuminated curtly. The model-free methods will be applied to three series of annual german economic forecasts from 1970 - 2015 provided by the joint forecast and the Council of Economic Advisors.
It turns out that the forecast accuracy matches the chronology of the forecasts within the annual forecast semester. Moreover, a simple Monte Carlo study aims to illustrate graphically empirical size and empirical power of the tests for pairwise comparison depending on certain properties of the underlying forecast error sequences.
- Quote paper
- Frank Undorf (Author), 2016, Forecast Evaluation Methods, Munich, GRIN Verlag, https://www.grin.com/document/441425