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Identification of Animal Spirits in a Bounded Rationality Model: An Application to the Euro Area

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  • Jang, Tae-Seok
  • Sacht, Stephen
Abstract
In this paper, we empirically examine a heterogenous bounded rationality version of a hybrid New-Keynesian model. The model is estimated via the simulated method of moments using Euro Area data from 1975Q1 to 2009Q4. It is generally assumed that agents' beliefs display waves of optimism and pessimism - so called animal spirits - on future movements in the output and inflation gap. Our main empirical findings show that a bounded rationality model with cognitive limitation provides fits for auto- and cross-covariances of the data which are slightly better than or equal to a model where rational expectations are assumed. This implies that the bounded rationality model provides some structural insights on the expectation formation process at the macro-level for the Euro Area. First, over the whole time interval the agents had expected moderate deviations of the future output gap from its steady state value with low uncertainty. Second, we find strong evidence for an autoregressive expectation formation process regarding the inflation gap. Both observations explain a high degree of persistence in the output gap and the inflation gap.

Suggested Citation

  • Jang, Tae-Seok & Sacht, Stephen, 2012. "Identification of Animal Spirits in a Bounded Rationality Model: An Application to the Euro Area," MPRA Paper 37399, University Library of Munich, Germany.
    • Handle: RePEc:pra:mprapa:37399
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    Cited by:

    1. Cars Hommes & Robert Calvert Jump & Paul Levine, 2017. "Internal rationalityuyuyuy, heterogeneity and complexity in the New Keynesian model," Working Papers 20171706, Department of Accounting, Economics and Finance, Bristol Business School, University of the West of England, Bristol.
    2. De Grauwe, Paul & Macchiarelli, Corrado, 2015. "Animal spirits and credit cycles," Journal of Economic Dynamics and Control, Elsevier, vol. 59(C), pages 95-117.
    3. Tae-Seok Jang & Stephen Sacht, 2016. "Animal Spirits and the Business Cycle: Empirical Evidence from Moment Matching," Metroeconomica, Wiley Blackwell, vol. 67(1), pages 76-113, February.
    4. Özge Dilaver & Robert Calvert Jump & Paul Levine, 2018. "Agent‐Based Macroeconomics And Dynamic Stochastic General Equilibrium Models: Where Do We Go From Here?," Journal of Economic Surveys, Wiley Blackwell, vol. 32(4), pages 1134-1159, September.
    5. Fabio Milani, 2012. "The Modeling of Expectations in Empirical DSGE Models: A Survey," Advances in Econometrics, in: DSGE Models in Macroeconomics: Estimation, Evaluation, and New Developments, pages 3-38, Emerald Group Publishing Limited.
    6. Zhijian Wang & Bin Xu, 2014. "Cycling in stochastic general equilibrium," Papers 1410.8432, arXiv.org.
    7. Markus Demary, 2017. "Yield curve responses to market sentiments and monetary policy," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 12(2), pages 309-344, July.
    8. Jang, Tae-Seok, 2012. "Structural estimation of the New-Keynesian Model: a formal test of backward- and forward-looking expectations," MPRA Paper 40278, University Library of Munich, Germany.
    9. Jang, Tae-Seok, 2012. "Structural estimation of the New-Keynesian model: A formal test of backward- and forward-looking behavior," Economics Working Papers 2012-07, Christian-Albrechts-University of Kiel, Department of Economics.
    10. Jang, Tae-Seok, 2012. "Structural estimation of the New-Keynesian Model: a formal test of backward- and forward-looking expectations," MPRA Paper 39669, University Library of Munich, Germany.

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    More about this item

    Keywords

    Animal Spirits; Bounded Rationality; Euro Area; New-Keynesian Model; Simulated Method of Moments;
    All these keywords.

    JEL classification:

    • E12 - Macroeconomics and Monetary Economics - - General Aggregative Models - - - Keynes; Keynesian; Post-Keynesian; Modern Monetary Theory
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles
    • D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness

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