Artikel

A nonparametric evaluation of the optimality of German export and import growth forecasts under flexible loss

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.

Language
Englisch

Bibliographic citation
Journal: Economies ; ISSN: 2227-7099 ; Volume: 7 ; Year: 2019 ; Issue: 3 ; Pages: 1-23 ; Basel: MDPI

Classification
Wirtschaft
Forecasting Models; Simulation Methods
Trade: Forecasting and Simulation
Macroeconomic Aspects of International Trade and Finance: Forecasting and Simulation: Models and Applications
Subject
flexible loss
forecast optimality
German economic research institutes
random forests
trade forecasts

Event
Geistige Schöpfung
(who)
Behrens, Christoph
Event
Veröffentlichung
(who)
MDPI
(where)
Basel
(when)
2019

DOI
doi:10.3390/economies7030093
Handle
Last update
10.03.2025, 11:44 AM CET

Data provider

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Object type

  • Artikel

Associated

  • Behrens, Christoph
  • MDPI

Time of origin

  • 2019

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