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Animal Spirits and the Business Cycle: Empirical Evidence from Moment Matching

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  • Tae-Seok Jang
  • Stephen Sacht

Abstract

In this paper we empirically examine a hybrid New-Keynesian model with heterogeneous bounded rational agents who may adopt an optimistic or pessimistic attitude - so called animal spirits - towards future movements of the output and inflation gap. The model is estimated via the simulated method of moments using Euro Area data from 1975Q1 to 2009Q4. In addition, we compare its empirical performance to the standard model with rational expectations. Our empirical results show that the model-generated auto- and cross-covariances of the output gap, the inflation gap and the nominal interest gap can provide a good approximation of the empirical second moments. The result is mainly driven by a high degree of persistence in the output and inflation gap due to the impact of animal spirits on economic activity. Furthermore, over the whole time interval the agents had expected moderate deviations of the future output gap from its steady state value.
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  • 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.
  • Handle: RePEc:bla:metroe:v:67:y:2016:i:1:p:76-113
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    Cited by:

    1. Kukacka, Jiri & Jang, Tae-Seok & Sacht, Stephen, 2018. "On the estimation of behavioral macroeconomic models via simulated maximum likelihood," Economics Working Papers 2018-11, Christian-Albrechts-University of Kiel, Department of Economics.
    2. Jump, Robert Calvert & Levine, Paul, 2019. "Behavioural New Keynesian models," Journal of Macroeconomics, Elsevier, vol. 59(C), pages 59-77.
    3. Liang, Hanchao & Yang, Chunpeng & Cai, Chuangqun, 2017. "Beauty contest, bounded rationality, and sentiment pricing dynamics," Economic Modelling, Elsevier, vol. 60(C), pages 71-80.
    4. repec:spr:jbuscr:v:13:y:2017:i:2:d:10.1007_s41549-017-0020-y is not listed on IDEAS
    5. 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.
    6. Jang, Tae-Seok & Sacht, Stephen, 2018. "Forecast heuristics, consumer expectations, and new-Keynesian macroeconomics: A horse race," Economics Working Papers 2018-09, Christian-Albrechts-University of Kiel, Department of Economics.
    7. Jang, Tae-Seok & Sacht, Stephen, 2017. "Modeling consumer confidence and its role for expectation formation: A horse race," Economics Working Papers 2017-04, Christian-Albrechts-University of Kiel, Department of Economics.
    8. Jang, Tae-Seok & Sacht, Stephen, 2018. "Macroeconomic dynamics under bounded rationality: On the impact of consumers' forecast heuristics," Economics Working Papers 2018-10, Christian-Albrechts-University of Kiel, Department of Economics.
    9. Liang, Hanchao & Yang, Chunpeng & Zhang, Rengui & Cai, Chuangqun, 2017. "Bounded rationality, anchoring-and-adjustment sentiment, and asset pricing," The North American Journal of Economics and Finance, Elsevier, vol. 40(C), pages 85-102.

    More about this item

    JEL classification:

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

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