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Forecasting Private Consumption by Consumer Surveys

Author

Listed:
  • Christian Dreger
  • Konstantin Arkadievich Kholodilin

Abstract

Survey-based indicators such as the consumer confidence are widely seen as leading indicators for economic activity, especially for the future path of private consumption. Although they receive high attention in the media, their forecasting power appears to be very limited. Therefore, this paper takes a fresh look on the survey data, which serve as a basis for the consumer confidence indicator (CCI) reported by the EU Commission for the euro area and individual member states. Different pooling methods are considered to exploit the information embedded in the consumer survey. Quantitative forecasts are based on Mixed Data Sampling (MIDAS) and bridge equations. While the CCI does not outperform an autoregressive benchmark for the majority of countries, the new indicators increase the forecasting performance. The gains over the CCI are striking for Italy and the entire euro area (20 percent). For Germany and France the gains seem to be lower, but are nevertheless substantial (10 to 15 percent). The best performing indicator should be built upon pre-selection methods, while data-driven aggregation methods should be preferred to determine the weights of the individual ingredients.
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Suggested Citation

  • Christian Dreger & Konstantin Arkadievich Kholodilin, 2013. "Forecasting Private Consumption by Consumer Surveys," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 32(1), pages 10-18, January.
  • Handle: RePEc:wly:jforec:v:32:y:2013:i:1:p:10-18
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    Cited by:

    1. Kamil Kladívko & Pär Österholm, 2024. "An Analysis of UK Households’ Directional Forecasts of Interest Rates," Journal of Business Cycle Research, Springer;Centre for International Research on Economic Tendency Surveys (CIRET), vol. 20(3), pages 423-442, November.
    2. Gustavo Adolfo HERNANDEZ DIAZ & Margarita MAR�N JARAMILLO, 2016. "Pronóstico del Consumo Privado: Usando datos de alta frecuencia para el pronóstico de variables de baja frecuencia," Archivos de Economía 14828, Departamento Nacional de Planeación.
    3. Duarte, Cláudia & Rodrigues, Paulo M.M. & Rua, António, 2017. "A mixed frequency approach to the forecasting of private consumption with ATM/POS data," International Journal of Forecasting, Elsevier, vol. 33(1), pages 61-75.
    4. Mirjana Čižmešija & Zrinka Lukač & Marina Matošec, 2025. "Gaining confidence in the revised consumer confidence indicator: nonlinear optimization approach," Empirical Economics, Springer, vol. 69(1), pages 517-547, July.
    5. Dimitrios Sideris & Georgia Pavlou, 2021. "Disaggregate income and wealth effects on private consumption in Greece," Working Papers 293, Bank of Greece.
    6. 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.
    7. Kladivko, Kamil & Österholm, Pär, 2020. "Can Households Predict where the Macroeconomy is Headed?," Working Papers 2020:11, Örebro University, School of Business.
    8. Antonello D Agostino & Caterina Mendicino & Caterina Mendicino, 2015. "Can consumer confidence provide independent information on consumption spending?," Working Papers 2, European Stability Mechanism.
    9. Willem Vanlaer & Samantha Bielen & Wim Marneffe, 2020. "Consumer Confidence and Household Saving Behaviors: A Cross-Country Empirical Analysis," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 147(2), pages 677-721, January.
    10. 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.
    11. repec:ers:journl:v:xxiv:y:2021:i:3:p:874-898 is not listed on IDEAS
    12. Paradiso, Antonio & Kumar, Saten & Margani, Patrizia, 2014. "Are Italian consumer confidence adjustments asymmetric? A macroeconomic and psychological motives approach," Journal of Economic Psychology, Elsevier, vol. 43(C), pages 48-63.
    13. Lindner, Axel & Heinisch, Katja, 2019. "Economic Sentiment in Europe: Disentangling Private Information from Public Knowledge," VfS Annual Conference 2019 (Leipzig): 30 Years after the Fall of the Berlin Wall - Democracy and Market Economy 203501, Verein für Socialpolitik / German Economic Association.
    14. Alina Stundziene & Vaida Pilinkiene & Jurgita Bruneckiene & Andrius Grybauskas & Mantas Lukauskas & Irena Pekarskiene, 2024. "Future directions in nowcasting economic activity: A systematic literature review," Journal of Economic Surveys, Wiley Blackwell, vol. 38(4), pages 1199-1233, September.
    15. de Bondt, Gabe & Gieseck, Arne & Herrero, Pablo & Zekaite, Zivile, 2019. "Disaggregate income and wealth effects in the largest euro area countries," Research Technical Papers 15/RT/19, Central Bank of Ireland.
    16. Bengt Assarsson & Pär Österholm, 2015. "Do Swedish Consumer Confidence Indicators Do What They Are Intended to Do?," Applied Economics Quarterly (formerly: Konjunkturpolitik), Duncker & Humblot GmbH, Berlin, vol. 61(4), pages 391-404.
    17. Cláudia Duarte, 2016. "A Mixed Frequency Approach to Forecast Private Consumption with ATM/POS Data," Working Papers w201601, Banco de Portugal, Economics and Research Department.
    18. Vincenzo Merella & Stephen E. Satchell, 2019. "Asset pricing with utility from external anticipation," Carlo Alberto Notebooks 589, Collegio Carlo Alberto.
    19. Luis A. Gil-Alana & Emmanuel Joel Aikins Abakah & Nieves Carmona-González & Aviral Kumar Tiwari, 2024. "Consumer sentiments across G7 and BRICS economies: Are they related?," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 48(2), pages 323-344, June.
    20. Oscar Claveria, 2021. "Forecasting with Business and Consumer Survey Data," Forecasting, MDPI, vol. 3(1), pages 1-22, February.
    21. Paradiso, Antonio & Rao, B. Bhaskara & Margani, Patrizia, 2011. "Time Series Estimates of the Italian Consumer Confidence Indicator," MPRA Paper 28395, University Library of Munich, Germany.
    22. 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 - Part ), pages 874-898.

    More about this item

    JEL classification:

    • E21 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment - - - Consumption; Saving; Wealth
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes

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