I derive simple, flexible strategies for difference-in-differences settings where the nature of the response variable may warrant a nonlinear model. In addition to covering the case of common treatment timing, I allow for staggered interventions, with and without covariates. Under an index...

The recursive prediction and filtering formulas of the Kalman filter are difficult to implement in nonlinear state space models. For Gaussian linear state space models, or for models with qualitative state variables, the recursive formulas of the filter require the updating of a finite number of...

This paper introduces a factor-augmented forecasting regression model in the presence of threshold effects. We consider least squares estimation of the regression parameters, and establish asymptotic theories for estimators of both slope coefficients and the threshold parameter. Prediction...