This paper presents an econometric model to value latent information underlying corporate events. This model computes the market's inference of the value of latent information from the probability of an event, conditional on firm-specific, preevent information. It provides a convenient framework for testing significance of preevent information variables, such as accounting attributes and lagged stock return. Simulations show that this model, when applied to both event and preevent period data, can decrease the incidence of bias in event studies. If restricted to only event period data, this model reduces to a truncated regression and does not perform as well as standard procedures.
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