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Logit analysis of the probability of meeting or exceeding forecasts and the incentives to avoid negative FEs.

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Figshare2015-12-02 更新2026-04-29 收录
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https://figshare.com/articles/dataset/_Logit_analysis_of_the_probability_of_meeting_or_exceeding_forecasts_and_the_incentives_to_avoid_negative_FEs_/827210
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The regression is run on the first and second subsamples. The coefficients and related t-statistics are estimated by using the following model:Prob(meet = 1) = F(α0+α1 AR+α2 FREQ+α3 Difficulty+α4 LMV+α5 MB+α6DA+α7Hightech+α8 Lag_loss+ε).*, **,***Significant at 0.1, 0.05 and 0.01 levels, respectively based on one-tailed tests for signed predictions, two-tailed tests otherwise.
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2015-12-02
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