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A Novel Approach to Measuring Consumer Confidence

Author

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  • de Bruijn, L.P.
  • Segers, R.
  • Franses, Ph.H.B.F.

Abstract

This paper puts forward a new data collection method to measure daily consumer confidence at the individual level. The data thus obtained allow to statistically analyze the dynamic correlation of such a consumer confidence indicator and to draw inference on transition rates. The latter is not possible for currently available monthly data collected by statistical agencies on the basis of repeated cross-sections. In an application to measuring Dutch consumer confidence, we show that the incremental information content in the novel indicator helps to better forecast consumption.

Suggested Citation

  • de Bruijn, L.P. & Segers, R. & Franses, Ph.H.B.F., 2014. "A Novel Approach to Measuring Consumer Confidence," Econometric Institute Research Papers EI 2014-30, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    • Handle: RePEc:ems:eureir:77640
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    References listed on IDEAS

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    1. Sydney C. Ludvigson, 2004. "Consumer Confidence and Consumer Spending," Journal of Economic Perspectives, American Economic Association, vol. 18(2), pages 29-50, Spring.
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    6. Deaton, Angus, 1985. "Panel data from time series of cross-sections," Journal of Econometrics, Elsevier, vol. 30(1-2), pages 109-126.
    7. Jeff Dominitz & Charles F. Manski, 2004. "How Should We Measure Consumer Confidence?," Journal of Economic Perspectives, American Economic Association, vol. 18(2), pages 51-66, Spring.
    8. Rene Segers & Philip Hans Franses, 2014. "Panel design effects on response rates and response quality," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 68(1), pages 1-24, February.
    9. Cameron,A. Colin & Trivedi,Pravin K., 2005. "Microeconometrics," Cambridge Books, Cambridge University Press, number 9780521848053.
    10. Diebold, Francis X & Mariano, Roberto S, 2002. "Comparing Predictive Accuracy," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(1), pages 134-144, January.
    11. Franses,Philip Hans & Paap,Richard, 2010. "Quantitative Models in Marketing Research," Cambridge Books, Cambridge University Press, number 9780521143653.
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    3. Chi-Wei Su & Xian-Li Meng & Ran Tao & Muhammad Umar, 2023. "Chinese consumer confidence: A catalyst for the outbound tourism expenditure?," Tourism Economics, , vol. 29(3), pages 696-717, May.

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    JEL classification:

    • C33 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Models with Panel Data; Spatio-temporal Models
    • C42 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Survey Methods
    • C81 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Methodology for Collecting, Estimating, and Organizing Microeconomic Data; Data Access
    • E20 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment - - - General (includes Measurement and Data)

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