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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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    References listed on IDEAS

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    1. repec:spr:soinre:v:133:y:2017:i:2:d:10.1007_s11205-016-1376-4 is not listed on IDEAS
    2. Rangan Gupta & John W. Muteba Mwamba & Mark E. Wohar, 2016. "The Role of Partisan Conflict in Forecasting the U.S. Equity Premium: A Nonparametric Approach," Working Papers 201686, University of Pretoria, Department of Economics.
    3. 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.
    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.

    More about this item

    Keywords

    Forecasting; Consumer confidence; Non-parametric methods; Non linear methods;

    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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