This paper investigates the nonlinearity in the effects of news shocks about technological innovations. In a maximally flexible logistic smooth transition vector autoregressive model, state-dependent effects of news shocks are identified based on medium-run restrictions. We propose a novel...

We extend the event study methodology into a richer and more dynamic environment by including time-varying parameters. Under the Bayesian framework, useful to update relevant information in a sequential learning mechanism, we use the Kalman filter to consider time dependent parameters, and we...