EU Consumer Confidence and the New Modesty Hypothesis

Abstract

Voices have been raised that the link between economic sentiment and hard macroeconomic data has considerably weakened over time, bringing agents’ macroeconomic assessments of normal growth to a more modest, new normal level. We empirically test this hypothesis by linking consumer confidence to consumption growth for all individual EU member states, as well as for the EU and the euro area. Applying a battery of nonlinear econometric techniques, we find that normal consumption growth rates (as assessed by consumers) have recorded a long-term decline in about half of countries (dominantly old EU member states), while all other economies either contradict such a hypothesis or exhibit intermittent intervals of increasing and decreasing normal growth. Our calculations reveal that normal consumption growth rates are highly positively related to macroeconomic volatility, reflecting the postulates of psychophysics. In that sense, the new modesty hypothesis can to some extent be attributed to the Great Moderation era, which has diminished consumers’ perceptive reactions to macroeconomic stimuli.

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Fig. 1

Source: authors’ calculation

Fig. 2

Source: authors’ calculation

Fig. 3

Source: authors’ calculation

Notes

  1. 1.

    The original contribution of Lucas (1973) focuses on firms' capability of separating aggregate from relative price changes.

  2. 2.

    An alternative explanation for the detected decoupling of hard and soft data (at least for the case of business confidence) is the sample selection bias. Namely, each time a firm ceases to be operating, it is replaced in the business survey sample by another firm, according to criteria such as size, regional affiliation or type of activity. In that sense, one might infer that the usual survey sampling procedures are interfered by Darwinian economic selection. The stated downward trend in what is perceived as the normal state of the economy might be simply the result of the fact that these new firms in the survey panel have considerably lower economic aspirations. However, Bruno et al. (2019) disapprove of this hypothesis based on their analysis of micro data from the Italian industrial sector business survey.

  3. 3.

    Final consumption expenditure of households and non-profit organizations serving households (NPISH) at constant prices (Eurostat code: P31_S14_S15).

  4. 4.

    \( \overline{CCI} \) is obtained as the average value of CCI during the full estimation period.

  5. 5.

    A compromise between adequate sample size (accuracy) and securing enough degrees of freedom had to be made. We found that insisting on a larger rolling window length would disable us from including the 2008 recession period in the analysis for some of the countries (Bulgaria, Cyprus, Latvia, Lithuania, Luxembourg, Malta, Poland, and Romania) due to data availability, so we fixed the window size to 30 observations accordingly.

  6. 6.

    Throughout the paper, the assessed countries are grouped into new and old EU member states to enable easier comparison of the obtained results. Namely, old member states tend to have a much longer time span of available data. CZ, HU, and SI are also grouped into the old member states for the same reason.

  7. 7.

    It should be noted that Slovakia is not considered in any of the model specifications in the paper due to data unavailability.

  8. 8.

    Equation (3) models time-varying coefficients using a random walk model. We also tried to conceptualize Eq. (3) as an AR(1) process, but this caused severe convergence issues and the resulting models were unable to meet conventional error term assumptions.

  9. 9.

    We consider 2008 Q2 as the starting point of the crisis for the euro area, according to the OECD based Recession Indicators (https://fred.stlouisfed.org/series/EUROREC). We opted for not assessing different recession dates for each individual country because the obtained standard deviations and average rolling window estimates of normal growth would not be comparable in that case. Although some of the EU economies have officially entered a recession several quarters after 2008 Q2, this date point has generally triggered extreme economic uncertainty (and a consequential rise of macroeconomic volatility) across the EU, which makes it adequate for the sake of our analysis.

  10. 10.

    It should be noted that the total number of breaks in Table 1 is 57 (22 up and 35 down breaks). The total number of breaks for the two exchange rates variables is smaller because there is no data for the EU aggregate for those variables. It should also be noted that we impose break dates obtained for the normal consumption growth rates to the 10 assessed macro variables. This does not necessarily imply that an e.g. up break detected in time t in the normal growth rates is also accompanied by an analogous up break in the assessed macroeconomic variable. The latter variable may potentially be characterized by a down break in the same period. This is the reason why the number of up and down breaks is not equal for all 10 analyzed variables.

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Acknowledgements

This work has been fully supported by the Croatian Science Foundation under the Project No. 4189.

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Sorić, P., Čižmešija, M. & Matošec, M. EU Consumer Confidence and the New Modesty Hypothesis. Soc Indic Res (2020). https://doi.org/10.1007/s11205-020-02449-x

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Keywords

  • Consumer surveys
  • Time-varying parameter model
  • Structural break
  • Great Moderation

JEL Classification

  • C14
  • D12
  • E71