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A Nonparametric Evaluation of the Optimality of German Export and Import Growth Forecasts under Flexible Loss

Department of Economics, Helmut Schmidt University, Holstenhofweg 85, 22043 Hamburg, Germany
Economies 2019, 7(3), 93; https://doi.org/10.3390/economies7030093
Received: 28 June 2019 / Revised: 4 September 2019 / Accepted: 5 September 2019 / Published: 9 September 2019
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. View Full-Text
Keywords: trade forecasts; German economic research institutes; forecast optimality; flexible loss; random forests trade forecasts; German economic research institutes; forecast optimality; flexible loss; random forests
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Behrens, C. A Nonparametric Evaluation of the Optimality of German Export and Import Growth Forecasts under Flexible Loss. Economies 2019, 7, 93.

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