On Testing Equal Conditional Predictive Ability Under Measurement Error
نویسندگان
چکیده
Loss functions are widely used to compare several competing forecasts. However, forecast comparisons often based on mismeasured proxy variables for the true target. We introduce concept of exact robustness measurement error loss and fully characterize this class as Bregman class. Hence, only conditional mean forecasts can be evaluated exactly robustly. For such robust functions, differences average unaffected by use and, thus, inference predictive ability carried out usual. Moreover, we show that more precise proxies give tests higher power in discriminating between Simulations illustrate different behavior nonrobust functions. An empirical application U.S. GDP growth rates demonstrates nonrobustness quantile It also shows it is easier discriminate issued at horizons if a better used.
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ژورنال
عنوان ژورنال: Journal of Business & Economic Statistics
سال: 2022
ISSN: ['1537-2707', '0735-0015']
DOI: https://doi.org/10.1080/07350015.2021.2021923