Replication data for: Estimating Models with Dispersed Information

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Project Citation:

Melosi, Leonardo. Replication data for: Estimating Models with Dispersed Information. Nashville, TN: American Economic Association [publisher], 2014. Ann Arbor, MI: Inter-university Consortium for Political and Social Research [distributor], 2019-10-12. https://doi.org/10.3886/E114288V1

Project Description

Summary: We conduct likelihood evaluation of a DSGE model in which firms have imperfect common knowledge. Imperfect common knowledge is found to be more successful than price stickiness á la Calvo to account for the highly persistent effects of nominal shocks on output and inflation. Our likelihood analysis suggests that firms pay little attention to aggregate nominal conditions. This paper shows that such allocation of attention is plausible because it is optimal for firms with a reasonably small size of information frictions and a size of idiosyncratic uncertainty that is in line with the micro evidence on price changes.

Scope of Project

JEL Classification:
      C51 Model Construction and Estimation
      D83 Search; Learning; Information and Knowledge; Communication; Belief; Unawareness
      E13 General Aggregative Models: Neoclassical
      E23 Macroeconomics: Production
      E31 Price Level; Inflation; Deflation

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Published Versions

V1 [2019-10-12]

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