Essays on the Macroeconomics of Incomplete Information

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Doctor of Philosophy (PhD)
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Economics
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Imperfect common knowledge
forecasting the forecasts of others
rational inattention
Bayesian econometrics
persistent real effects of nominal shocks
monetary policy and beliefs.
Econometrics
Macroeconomics
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Abstract

In the first chapter, I develop and estimate a dynamic general equilibrium model with imperfectly informed firms in the sense of Woodford (2002). The model has two aggregate shocks: a monetary policy shock and a technology shock. Firms observe idiosyncratic noisy signals about these shocks and face strategic complementarities in price setting. In this environment, agents' "forecasting the forecasts of others" can produce realistic dynamics of model variables, with associated highly persistent real effects of monetary shocks and delayed effects of such shocks on inflation. The paper provides a full Bayesian analysis of the model, revealing that it can capture the persistent propagation of monetary shocks only by predicting that firms acquire less information about monetary policy than about technology. To further investigate this finding, I augment the model to allow firms to optimally choose how much information to acquire about the two shocks, subject to an information-processing constraint à la Sims (2003). This constraint sets the rate at which firms can substitute pieces of information about the two shocks. I find that, in the estimated model, firms' marginal value of the information about monetary policy shocks is much higher than that about technology shocks. I argue that this finding admits two alternative interpretations. First, firms acquire implausibly too little information about the monetary shock in the estimated model. Second, the rate of substitution implied by the information-processing constraint is inconsistent with the data. In the third chapter, I develop a model where firms have incomplete and dispersed information to study how monetary policy affects agents' beliefs. I estimate the model through Bayesian methods and find that dispersed information has two main implications for monetary policy. First, it reduces the real effects of money. Second, it raises the output loss associated with a monetary policy of disinflation.

Advisor
Frank Schorfheide
Francis X. Diebold
Date of degree
2010-05-17
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