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Testing bias in professional forecasts

delete2021-01-28
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P
Philip Hans Franses *
DOI:10.1002/for.2765delete
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摘要

摘要

En 中文
Professional forecasters can rely on econometric models, on their personal expertise or on both. To accommodate for adjustments to model forecasts, this paper proposes to use two stage least squares (TSLS) (and not ordinary least squares [OLS]) for the familiar Mincer-Zarnowitz regression when examining bias in professional forecasts, where the instrumental variable is the consensus forecast. An illustration for 15 professional forecasters with their quotes for real gross domestic product (GDP) growth, inflation and unemployment for the United States documents the usefulness of this new estimation method. It also shows that TSLS suggests less bias than OLS does.
Keyword:
bias
forecast evaluation
Mincer-Zarnowitz regression
OLS
TSLS
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期刊

Journal of Forecasting 封面图
Journal of Forecasting
IF:
2.7
论文数:
2.3K
被引数:
3.0K

机构

E
Erasmus University Rotterdam
学者数:
4.6W
论文数: 4.0W
被引数: 2.4W
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