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Macroeconomic Models with Incomplete Information and Endogenous Signals

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  • Jonathan J Adams

    (Department of Economics, University of Florida)

Abstract

This paper characterizes a general class of macroeconomic models with incomplete information, when the information process includes endogenous variables. I derive conditions for existence and uniqueness of equilibrium, which apply even when the model contains endogenous state variables, and I introduce an algorithm to solve the general model. As an application I consider a business cycle model with capital where firms must make inferences about aggregate shocks through the movements of endogenous prices. In this model, the central bank's policy rule determines the real effects of nominal shocks, by controlling how informative prices are about the aggregate state. The optimal policy targets acyclical inflation, which makes money neutral. Finally, I demonstrate an advantage of models with endogenous information: the noisy signals are driven by fundamental shocks, rather than ad hoc noise, so data can discipline the information structure. Accordingly, I calibrate the model using US industry-level panel data.

Suggested Citation

  • Jonathan J Adams, 2019. "Macroeconomic Models with Incomplete Information and Endogenous Signals," Working Papers 001004, University of Florida, Department of Economics.
  • Handle: RePEc:ufl:wpaper:001004
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    References listed on IDEAS

    as
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    More about this item

    JEL classification:

    • D84 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Expectations; Speculations
    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles
    • C62 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Existence and Stability Conditions of Equilibrium
    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques

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