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Forecast Combination, Non-linear Dynamics, and the Macroeconomy

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  • Christopher Gibbs

    () (School of Economics, UNSW Business School, UNSW)

Abstract

This paper introduces the concept of a Forecast Combination Equilibrium to model boundedly rational agents who combine a menu of different forecasts using insights from the forecasting literature to mimic the behavior of actual forecasters. The equilibrium concept is consistent with rational expectations under certain conditions, while also permitting multiple, distinct, self-fulfilling equilibria, many of which are stable under least squares learning. The equilibrium concept is applied to a simple Lucas-type monetary model where agents engage in constant gain learning. The combination of multiple equilibria and learning is sufficient to replicate some key features of inflation data, such as time-varying volatility and periodic bouts of high inflation or deflation in a model that experiences only i.i.d. random shocks.

Suggested Citation

  • Christopher Gibbs, 2015. "Forecast Combination, Non-linear Dynamics, and the Macroeconomy," Discussion Papers 2015-05, School of Economics, The University of New South Wales.
  • Handle: RePEc:swe:wpaper:2015-05
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    File URL: http://research.economics.unsw.edu.au/RePEc/papers/2015-05.pdf
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    References listed on IDEAS

    as
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    Citations

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    Cited by:

    1. Gibbs, Christopher G. & Kulish, Mariano, 2017. "Disinflations in a model of imperfectly anchored expectations," European Economic Review, Elsevier, vol. 100(C), pages 157-174.
    2. Honkapohja, Seppo & Kaushik, Mitra, 2018. "Price level targeting with evolving credibility," Research Discussion Papers 5/2018, Bank of Finland.
    3. Duncan, Roberto & Martinez-Garcia, Enrique, 2018. "New Perspectives on Forecasting Inflation in Emerging Market Economies: An Empirical Assessment," Globalization and Monetary Policy Institute Working Paper 338, Federal Reserve Bank of Dallas.

    More about this item

    Keywords

    Forecast Combination; Adaptive Learning; Expectations; Dynamic Predictor Selection; Inflation; Forecast Combination Puzzle;

    JEL classification:

    • E17 - Macroeconomics and Monetary Economics - - General Aggregative Models - - - Forecasting and Simulation: Models and Applications
    • E31 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Price Level; Inflation; Deflation
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods

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