Forecasting Conditional Probabilities of Binary Outcomes under Misspecification

Forecasting Binary Outcomes∗

Binary events are involved in many economic decision problems. In recent years, considerable progress has been made in diverse disciplines in developing models for forecasting binary outcomes. We distinguish between two types of forecasts for binary events that are generally obtained as the output of regression models: probability forecasts and point forecasts. We summarize specification, estim...

Quantum Conditional Probabilities Are Not Probabilities of Quantum Conditional

Bayesian Inconsistency under Misspecification

This is a synopsis of the work underlying the author’s contributed plenary presentation at the Valencia 8 meeting on Bayesian Statistics, held in Benidorm, June 2006. We show that Bayesian inference can be inconsistent under misspecification. Specifically, we exhibit a distribution P ∗, a model M with P ∗ 6∈ M, and a prior Π on M such that the prior puts significant mass on P̃ , the best approxi...

Probabilities of Conditionals and Conditional Probabilities Ii

A dams's thesis about indicative conditionals is that their assertIlability goes by the conditional subjective probability of the consequent given the antecedent, in very much the same way that assertability normally goes by the subjective probability of truth.' The thesis is well established; the remaining question is how it may best be explained. The nicest explanation would be that the truth...

Misspecification and Heterogeneity in Binary Choice Models

We address function misspecification and model heterogeneity, two critical issues in empirical work. A nonparametric approach is proposed for single-index, binary-choice models when parametric models such as Probit and Logit are potentially misspecified. The new approach involves two steps: first, we estimate index coefficients using sliced inverse regression without knowing the conditional pro...