| Autor: |
Christoph Behrens |
| Jazyk: |
angličtina |
| Rok vydání: |
2019 |
| Předmět: |
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| Zdroj: |
Economies, Vol 7, Iss 3, p 93 (2019) |
| Druh dokumentu: |
article |
| ISSN: |
2227-7099 |
| DOI: |
10.3390/economies7030093 |
| Popis: |
This study contributes to research on the nonparametric evaluation of German trade forecasts. To this end, I compute random classification and regression forests to analyze the optimality of annual German export and import growth forecasts from 1970 to 2017. A forecast is considered as optimal if a set of predictors, which models the information set of a forecaster at the time of forecast formation, has no explanatory power for the corresponding (sign of the) forecast error. I analyze trade forecasts of four major German economic research institutes, a collaboration of German economic research institutes, and one international forecaster. For trade forecasts with a horizon of half-a-year, I cannot reject forecast optimality for all but one forecaster. In the case of a forecast horizon of one year, forecast optimality is rejected in more cases if the underlying loss function is assumed to be quadratic. Allowing for a flexible loss function results in more favorable assessment of forecast optimality. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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