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Modeling the Dynamics of EU Economic Sentiment Indicators: An Interaction-Based Approach

Author

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  • Thomas Lux

    (Department of Economics - CAU - Christian-Albrechts-Universität zu Kiel = Christian-Albrechts University of Kiel = Université Christian-Albrechts de Kiel, Kiel Institute for the World Economy - Kiel Institute for the World Economy)

  • Jaba Ghonghadze

    (Department of Economics - CAU - Christian-Albrechts-Universität zu Kiel = Christian-Albrechts University of Kiel = Université Christian-Albrechts de Kiel)

Abstract

This paper estimates a simple univariate model of expectation or opinion formation in continuous time adapting a 'canonical' stochastic model of collective opinion dynamics (Weidlich and Haag, 1983; Lux, 1995, 2007). This framework is applied to a selected data set of survey-based expectations from the rich EU business and consumer survey database for twelve European countries. The model parameters are estimated through maximum likelihood and numerical solution of the transient probability density functions for the resulting stochastic process. The model's performance is assessed with respect to its out-of-sample forecasting capacity relative to univariate time series models of the ARMA(p,q) and ARFIMA(p,d,q) varieties. These tests speak for a slight superiority of the canonical opinion dynamics model over the alternatives in the majority of cases.

Suggested Citation

  • Thomas Lux & Jaba Ghonghadze, 2011. "Modeling the Dynamics of EU Economic Sentiment Indicators: An Interaction-Based Approach," Post-Print hal-00711445, HAL.
    • Handle: RePEc:hal:journl:hal-00711445
    DOI: 10.1080/00036846.2011.570716
    Note: View the original document on HAL open archive server: https://hal.science/hal-00711445
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    References listed on IDEAS

    as
    1. Lux, Thomas, 2009. "Rational forecasts or social opinion dynamics? Identification of interaction effects in a business climate survey," Journal of Economic Behavior & Organization, Elsevier, vol. 72(2), pages 638-655, November.
    2. Zullow, Harold M., 1991. "Pessimistic rumination in popular songs and newsmagazines predict economic recession via decreased consumer optimism and spending," Journal of Economic Psychology, Elsevier, vol. 12(3), pages 501-526, September.
    3. William A. Branch, 2004. "The Theory of Rationally Heterogeneous Expectations: Evidence from Survey Data on Inflation Expectations," Economic Journal, Royal Economic Society, vol. 114(497), pages 592-621, July.
    4. James Mitchell & Stephen G. Hall, 2005. "Evaluating, Comparing and Combining Density Forecasts Using the KLIC with an Application to the Bank of England and NIESR ‘Fan’ Charts of Inflation," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 67(s1), pages 995-1033, December.
    5. Reiner Franke, 2008. "A Microfounded Herding Model and Its Estimation On German Survey Expectations," European Journal of Economics and Economic Policies: Intervention, Edward Elgar Publishing, vol. 5(2), pages 301-328.
    6. William A. Brock & Steven N. Durlauf, 2001. "Discrete Choice with Social Interactions," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 68(2), pages 235-260.
    7. Sarah Gelper & Aurelie Lemmens & Christophe Croux, 2007. "Consumer sentiment and consumer spending: decomposing the Granger causal relationship in the time domain," Applied Economics, Taylor & Francis Journals, vol. 39(1), pages 1-11.
    8. Lux, Thomas, 1997. "Time variation of second moments from a noise trader/infection model," Journal of Economic Dynamics and Control, Elsevier, vol. 22(1), pages 1-38, November.
    9. Marco Malgarini & Patrizia Margani, 2007. "Psychology, consumer sentiment and household expenditures," Applied Economics, Taylor & Francis Journals, vol. 39(13), pages 1719-1729.
    10. Christopher D. Carroll, 2003. "Macroeconomic Expectations of Households and Professional Forecasters," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 118(1), pages 269-298.
    11. Lux, Thomas & Kaizoji, Taisei, 2007. "Forecasting volatility and volume in the Tokyo Stock Market: Long memory, fractality and regime switching," Journal of Economic Dynamics and Control, Elsevier, vol. 31(6), pages 1808-1843, June.
    12. Karl Taylor & Robert McNabb, 2007. "Business Cycles and the Role of Confidence: Evidence for Europe," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 69(2), pages 185-208, April.
    13. Michela Nardo, 2003. "The Quantification of Qualitative Survey Data: A Critical Assessment," Journal of Economic Surveys, Wiley Blackwell, vol. 17(5), pages 645-668, December.
    14. Dr. James Mitchell, 2005. "Evaluating, comparing and combining density forecasts using the KLIC with an application to the Bank of England and NIESR ÔfanÕ charts of inflation," National Institute of Economic and Social Research (NIESR) Discussion Papers 253, National Institute of Economic and Social Research.
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    16. Alfarano, Simone & Lux, Thomas, 2007. "A Noise Trader Model As A Generator Of Apparent Financial Power Laws And Long Memory," Macroeconomic Dynamics, Cambridge University Press, vol. 11(S1), pages 80-101, November.
    17. Lemmens, A. & Croux, C. & Dekimpe, M.G., 2005. "On the Predictive Content of Production Surveys : a Pan-European Study," Other publications TiSEM adab9f0e-7dfd-4dc4-bd92-b, Tilburg University, School of Economics and Management.
    18. Charles Delorme & David Kamerschen & Lisa Ford Voeks, 2001. "Consumer confidence and rational expectations in the United States compared with the United Kingdom," Applied Economics, Taylor & Francis Journals, vol. 33(7), pages 863-869.
    19. Thomas Lux, 2009. "Rational Forecasts or Social Opinion Dynamics? Identification of Interaction Effects in a Business Climate Survey," Post-Print hal-00720175, HAL.
    20. Dr. James Mitchell, 2005. "Evaluating, comparing and combining density forecasts using the KLIC with an application to the Bank of England and NIESR ÔfanÕ charts of inflation," National Institute of Economic and Social Research (NIESR) Discussion Papers 253, National Institute of Economic and Social Research.
    21. Stan Hurn & J.Jeisman & K.A. Lindsay, 2006. "Teaching an old dog new tricks: Improved estimation of the parameters of SDEs by numerical solution of the Fokker-Planck equation," Stan Hurn Discussion Papers 2006-01, School of Economics and Finance, Queensland University of Technology.
    22. Michel De Vroey & Pierre Malgrange, 2016. "Macroeconomics," Chapters, in: Gilbert Faccarello & Heinz D. Kurz (ed.), Handbook on the History of Economic Analysis Volume III, chapter 27, pages 372-390, Edward Elgar Publishing.
    23. Lux, Thomas, 1995. "Herd Behaviour, Bubbles and Crashes," Economic Journal, Royal Economic Society, vol. 105(431), pages 881-896, July.
    24. John A. Cotsomitis & Andy C. C. Kwan, 2006. "Can Consumer Confidence Forecast Household Spending? Evidence from the European COmmission Business and Consumer Surveys," Southern Economic Journal, John Wiley & Sons, vol. 72(3), pages 597-610, January.
    25. Gelper, S. & Lemmens, A. & Croux, C., 2007. "Consumer sentiment and consumer spending : Decomposing the granger causal relationship in the time domain," Other publications TiSEM 55ac7230-2985-41f1-a42c-7, Tilburg University, School of Economics and Management.
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    1. Sudeshna Ghosh, 2021. "Consumer Confidence and Consumer Spending in Brazil: A Nonlinear Autoregressive Distributed Lag Model Analysis," Arthaniti: Journal of Economic Theory and Practice, , vol. 20(1), pages 53-85, June.
    2. Andrzej Cieslik & Mahdi Ghodsi, 2021. "Economic sentiment indicators and foreign direct investment: Empirical evidence from European Union countries," International Economics, CEPII research center, issue 168, pages 56-75.
    3. Nicolas, Maxime L.D., 2022. "Estimating a model of herding behavior on social networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 604(C).

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