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Consumer confidence and consumption forecast: a non-parametric approach

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  • Bruno, Giancarlo

Abstract

The consumer confidence index is a highly observed indicator among short-term analysts and news reporters and it is generally considered to convey some useful information about the short-term evolution of consumer expenditure. Notwithstanding this, its usefulness in forecasting aggregate consumption is sometimes questioned in empirical studies. Overall, the conclusions seem to be that the extensive press coverage about this indicator is somewhat undue. Nevertheless, from time to time, attention revamps on consumer confidence, especially when turns of the business cycle are expected and/or abrupt changes in this indicator occur. Some authors argue that in such events consumer confidence is a more relevant variable in predicting consumption. This fact can be a signal that a linear functional form is inadequate to explain the relationship between these two variables. Nevertheless, the choice of a suitable non-linear model is not straightforward. Here I propose that a non-parametric model can be a possible choice, in order to explore the usefulness of confidence in forecasting consumption, without making too restrictive assumptions about the functional form to use.

Suggested Citation

  • Bruno, Giancarlo, 2012. "Consumer confidence and consumption forecast: a non-parametric approach," MPRA Paper 41312, University Library of Munich, Germany.
  • Handle: RePEc:pra:mprapa:41312
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    Cited by:

    1. Oscar Claveria & Enric Monte & Salvador Torra, 2019. "Empirical modelling of survey-based expectations for the design of economic indicators in five European regions," Empirica, Springer;Austrian Institute for Economic Research;Austrian Economic Association, vol. 46(2), pages 205-227, May.
    2. Gabe Jacob de Bondt & Arne Gieseck & Zivile Zekaite, 2020. "Thick modelling income and wealth effects: a forecast application to euro area private consumption," Empirical Economics, Springer, vol. 58(1), pages 257-286, January.
    3. Gupta, Rangan & Mwamba, John W. Muteba & Wohar, Mark E., 2018. "The role of partisan conflict in forecasting the U.S. equity premium: A nonparametric approach," Finance Research Letters, Elsevier, vol. 25(C), pages 131-136.
    4. Stephen Bruestle & W. Mark Crain, 2015. "A mean-variance approach to forecasting with the consumer confidence index," Applied Economics, Taylor & Francis Journals, vol. 47(23), pages 2430-2444, May.
    5. Aneta Maria Kłopocka, 2017. "Does Consumer Confidence Forecast Household Saving and Borrowing Behavior? Evidence for Poland," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 133(2), pages 693-717, September.
    6. Aneta M. Klopocka & Rumiana Gorska, 2021. "Forecasting Household Saving Rate with Consumer Confidence Indicator and its Components: Panel Data Analysis of 14 European Countries," European Research Studies Journal, European Research Studies Journal, vol. 0(3), pages 874-898.
    7. Oscar Claveria & Enric Monte & Salvador Torra, 2018. "“Tracking economic growth by evolving expectations via genetic programming: A two-step approach”," AQR Working Papers 201801, University of Barcelona, Regional Quantitative Analysis Group, revised Jan 2018.
    8. Oscar Claveria & Enric Monte & Salvador Torra, 2019. "Evolutionary Computation for Macroeconomic Forecasting," Computational Economics, Springer;Society for Computational Economics, vol. 53(2), pages 833-849, February.
    9. Rojo Suárez, Javier & Alonso Conde, Ana Belén & Ferrero Pozo, Ricardo, 2020. "European equity markets: Who is the truly representative investor?," The Quarterly Review of Economics and Finance, Elsevier, vol. 75(C), pages 325-346.
    10. Marina Matosec & Zdenka Obuljen Zoricic, 2019. "Identifying the Interdependence between Consumer Confidence and Macroeconomic Developments in Croatia," Interdisciplinary Description of Complex Systems - scientific journal, Croatian Interdisciplinary Society Provider Homepage: http://indecs.eu, vol. 17(2-B), pages 345-354.

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    More about this item

    Keywords

    Forecasting; Consumer confidence; Non-parametric methods; Non linear methods;
    All these keywords.

    JEL classification:

    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • E21 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment - - - Consumption; Saving; Wealth

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