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A mean-variance approach to forecasting with the consumer confidence index

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  • Stephen Bruestle
  • W. Mark Crain

Abstract

This article refines the way consumer confidence survey data are used in forecasting models. The refinement is easy to describe: it extends existing models by controlling for statistically significant changes in consumer confidence index values. The motivation behind this refinement is simply that not all changes in the confidence index are statistically significant, and mean index values alone provide a noisy signal. Using Michigan Index of Consumer Confidence from 1967 through 2013, we show that controlling for significant versus insignificant changes in the consumer confidence index materially enhances the explanatory power of household expenditure forecasting models.

Suggested Citation

  • 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.
    • Handle: RePEc:taf:applec:v:47:y:2015:i:23:p:2430-2444
    DOI: 10.1080/00036846.2015.1008763
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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. Sorić, Petar & Lolić, Ivana & Claveria, Oscar & Monte, Enric & Torra, Salvador, 2019. "Unemployment expectations: A socio-demographic analysis of the effect of news," Labour Economics, Elsevier, vol. 60(C), pages 64-74.
    3. Oscar Claveria & Enric Monte & Salvador Torra, 2018. "Tracking economic growth by evolving expectations via genetic programming: A two-step approach," Working Papers XREAP2018-4, Xarxa de Referència en Economia Aplicada (XREAP), revised Oct 2018.
    4. 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.
    5. Baghestani, Hamid, 2021. "Predicting growth in US durables spending using consumer durables-buying attitudes," Journal of Business Research, Elsevier, vol. 131(C), pages 327-336.
    6. 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.
    7. Oscar Claveria, 2021. "Forecasting with Business and Consumer Survey Data," Forecasting, MDPI, vol. 3(1), pages 1-22, February.

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