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Nowcasting and predicting data revisions using panel survey data

Author

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  • Troy D. Matheson

    (Reserve Bank of New Zealand, Wellington, New Zealand)

  • James Mitchell

    (National Institute of Economic and Social Research (NIESR), London, UK)

  • Brian Silverstone

    (University of Waikato, Hamilton, New Zealand)

Abstract

The qualitative responses that firms give to business survey questions regarding changes in their own output provide a real-time signal of official output changes. The most commonly used method to produce an aggregate quantitative indicator from business survey responses-the net balance or diffusion index-has changed little in 40 years. This paper investigates whether an improved real-time signal of official output data changes can be derived from a recently advanced method on the aggregation of survey data from panel responses. We find, in a New Zealand application, that exploiting the panel dimension to qualitative survey data gives a better in-sample signal about official data than traditional methods. Out-of-sample, it is less clear that it matters how survey data are quantified, with simpler and more parsimonious methods hard to improve. It is clear, nevertheless, that survey data, exploited in some form, help to explain revisions to official data. Copyright © 2009 John Wiley & Sons, Ltd.

Suggested Citation

  • Troy D. Matheson & James Mitchell & Brian Silverstone, 2010. "Nowcasting and predicting data revisions using panel survey data," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 29(3), pages 313-330.
    • Handle: RePEc:jof:jforec:v:29:y:2010:i:3:p:313-330
    DOI: 10.1002/for.1127
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    References listed on IDEAS

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    1. Smith, Jeremy & McAleer, Michael, 1995. "Alternative Procedures for Converting Qualitative Response Data to Quantitative Expectations: An Application to Australian Manufacturing," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 10(2), pages 165-185, April-Jun.
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    10. Dr Martin Weale & Dr. James Mitchell, 2006. "A Bayesian Indicator of Manufacturing Output from Qualitative Business Panel Survey Data," National Institute of Economic and Social Research (NIESR) Discussion Papers 261, National Institute of Economic and Social Research.
    11. Dr Martin Weale & Dr. James Mitchell, 2006. "A Bayesian Indicator of Manufacturing Output from Qualitative Business Panel Survey Data," National Institute of Economic and Social Research (NIESR) Discussion Papers 261, National Institute of Economic and Social Research.
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    Cited by:

    1. Lui, Silvia & Mitchell, James & Weale, Martin, 2011. "The utility of expectational data: Firm-level evidence using matched qualitative-quantitative UK surveys," International Journal of Forecasting, Elsevier, vol. 27(4), pages 1128-1146, October.
    2. Fornaro, Paolo, 2016. "Predicting Finnish economic activity using firm-level data," International Journal of Forecasting, Elsevier, vol. 32(1), pages 10-19.
    3. Lui, Silvia & Mitchell, James & Weale, Martin, 2011. "The utility of expectational data: Firm-level evidence using matched qualitative-quantitative UK surveys," International Journal of Forecasting, Elsevier, vol. 27(4), pages 1128-1146, October.
    4. Sayag, Doron & Ben-hur, Dano & Pfeffermann, Danny, 2022. "Reducing revisions in hedonic house price indices by the use of nowcasts," International Journal of Forecasting, Elsevier, vol. 38(1), pages 253-266.
    5. Paolo Fornaro & Henri Luomaranta, 2020. "Nowcasting Finnish real economic activity: a machine learning approach," Empirical Economics, Springer, vol. 58(1), pages 55-71, January.
    6. Boysen-Hogrefe, Jens & Neuwirth, Stefan, 2012. "The impact of seasonal and price adjustments on the predictability of German GDP revisions," Kiel Working Papers 1753, Kiel Institute for the World Economy (IfW Kiel).
    7. Guizzardi, Andrea & Stacchini, Annalisa, 2015. "Real-time forecasting regional tourism with business sentiment surveys," Tourism Management, Elsevier, vol. 47(C), pages 213-223.
    8. Chrystalleni Aristidou & Kevin Lee & Kalvinder Shields, 2015. "Real-Time Data should be used in Forecasting Output Growth and Recessionary Events in the US," Discussion Papers 2015/13, University of Nottingham, Centre for Finance, Credit and Macroeconomics (CFCM).
    9. Martinsen, Kjetil & Ravazzolo, Francesco & Wulfsberg, Fredrik, 2014. "Forecasting macroeconomic variables using disaggregate survey data," International Journal of Forecasting, Elsevier, vol. 30(1), pages 65-77.

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