Lorem ipsum
Lorem ipsum dolor sit amet, consectetur adipisicing elit, sed do eiusmod tempor incididunt ut labore et dolore magna aliqua. Ut enim ad minim veniam, quis nostrud exercitation ullamco laboris nisi ut aliquip ex ea commodo consequat. Duis aute irure dolor in reprehenderit in voluptate velit esse cillum dolore eu fugiat nulla pariatur. Excepteur sint occaecat cupidatat non proident, sunt in culpa qui officia deserunt mollit anim id est laborum.
The Effects of Shock Uncertainty and Learning on New Keynesian DSGE Model Dynamics
With Stefano Eusepi and Neville Francis
- We present a new Keynesian dynamic stochastic general equilibrium (DSGE) model with the rigidities of sticky prices, habit
persistence, investment adjustment costs and wage adjustment costs. We
introduce uncertainty and learning into this model by assuming that agents cannot observe
the underlying trend and level components of investment-specific and neutral
technology shocks. Instead agents must rely on Kalman filter learning
techniques to produce and update forecasts of these underlying components.
We use impulse response function matching estimation techniques to
investigate how learning affects the fit and dynamic behavior of the model. We find that including signal-extraction learning greatly enhances the standard theoretical model's ability to match the data. We also find that learning frictions dominate the standard rigidities of habit persistence and investment-adjustment costs.
