Replication data for: Learning in a Medium-Scale DSGE Model with Expectations Based on Small Forecasting Models

Principal Investigator(s): View help for Principal Investigator(s) Sergey Slobodyan; Raf Wouters

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Project Citation:

Slobodyan, Sergey, and Wouters, Raf. Replication data for: Learning in a Medium-Scale DSGE Model with Expectations Based on Small Forecasting Models. Nashville, TN: American Economic Association [publisher], 2012. Ann Arbor, MI: Inter-university Consortium for Political and Social Research [distributor], 2019-10-12. https://doi.org/10.3886/E114246V1

Project Description

Summary: This paper evaluates the empirical performance of a medium-scale DSGE model with agents forming expectations using small forecasting models updated by the Kalman filter. The adaptive learning model fits the data better than the rational expectations (RE) model. Beliefs about the inflation persistence explain the observed decline in the mean and the volatility of inflation as well as Phillips curve flattening. Learning about inflation results in lower estimates for the persistence of the exogenous shocks that drive price and wage dynamics in the RE version of the model. Expectations based on small forecasting models are closely related to the survey evidence on inflation expectations. (JEL C53, D83, D84, E13, E17, E31)

Scope of Project

JEL Classification:
      C53 Forecasting Models; Simulation Methods
      D83 Search; Learning; Information and Knowledge; Communication; Belief; Unawareness
      D84 Expectations; Speculations
      E13 General Aggregative Models: Neoclassical
      E17 General Aggregative Models: Forecasting and Simulation: Models and Applications
      E31 Price Level; Inflation; Deflation

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Published Versions

V1 [2019-10-12]

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