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Qualitative business surveys: signal or noise?

Author

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  • Silvia Lui
  • James Mitchell
  • Martin Weale

Abstract

This papers identifies the information content at the firm-level of qualitative business survey data by first examining the consistency between these data and the quantitative data provided by the same respondents to the UK's ONS in official surveys. Since the qualitative data are published ahead of the quantitative data the paper then assesses the ability of the qualitative data to predict (or nowcast) the firm-level quantitative data.
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Suggested Citation

  • Silvia Lui & James Mitchell & Martin Weale, 2011. "Qualitative business surveys: signal or noise?," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 174(2), pages 327-348, April.
    • Handle: RePEc:bla:jorssa:v:174:y:2011:i:2:p:327-348
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    Cited by:

    1. Kedai Cheng & Derek S. Young, 2023. "An Approach for Specifying Trimming and Winsorization Cutoffs," Journal of Agricultural, Biological and Environmental Statistics, Springer;The International Biometric Society;American Statistical Association, vol. 28(2), pages 299-323, June.
    2. Driver, Ciaran & Muñoz-Bugarin, Jair, 2019. "Financial constraints on investment: Effects of firm size and the financial crisis," Research in International Business and Finance, Elsevier, vol. 47(C), pages 441-457.
    3. Bachmann, Rüdiger & Elstner, Steffen, 2015. "Firm optimism and pessimism," European Economic Review, Elsevier, vol. 79(C), pages 297-325.
    4. Lahiri, Kajal & Zhao, Yongchen, 2015. "Quantifying survey expectations: A critical review and generalization of the Carlson–Parkin method," International Journal of Forecasting, Elsevier, vol. 31(1), pages 51-62.
    5. 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.
    6. Michele Caivano & Andrew Harvey, 2014. "Time-series models with an EGB2 conditional distribution," Journal of Time Series Analysis, Wiley Blackwell, vol. 35(6), pages 558-571, November.
    7. Oscar Claveria & Enric Monte & Salvador Torra, 2018. "A Data-Driven Approach to Construct Survey-Based Indicators by Means of Evolutionary Algorithms," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 135(1), pages 1-14, January.
    8. Oscar Claveria & Enric Monte & Salvador Torra, 2017. "Let the data do the talking: Empirical modelling of survey-based expectations by means of genetic programming," IREA Working Papers 201711, University of Barcelona, Research Institute of Applied Economics, revised May 2017.
    9. Ciaran Driver, 2019. "Trade liberalization and South African manufacturing: Looking back with data," WIDER Working Paper Series wp-2019-30, World Institute for Development Economic Research (UNU-WIDER).
    10. Mazzi Gian Luigi & Mitchell James & Carausu Florabela, 2021. "Measuring and Communicating the Uncertainty in Official Economic Statistics," Journal of Official Statistics, Sciendo, vol. 37(2), pages 289-316, June.
    11. 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.
    12. Kaufmann, Daniel & Scheufele, Rolf, 2017. "Business tendency surveys and macroeconomic fluctuations," International Journal of Forecasting, Elsevier, vol. 33(4), pages 878-893.
    13. Raïsa Basselier & David Antonio Liedo & Geert Langenus, 2018. "Nowcasting Real Economic Activity in the Euro Area: Assessing the Impact of Qualitative Surveys," Journal of Business Cycle Research, Springer;Centre for International Research on Economic Tendency Surveys (CIRET), vol. 14(1), pages 1-46, April.
    14. Breitung, Jörg & Schmeling, Maik, 2013. "Quantifying survey expectations: What’s wrong with the probability approach?," International Journal of Forecasting, Elsevier, vol. 29(1), pages 142-154.
    15. Corder, Matthew & Weale, Martin, 2011. "Banking crises and recessions: what can leading indicators tell us?," Discussion Papers 33, Monetary Policy Committee Unit, Bank of England.
    16. Frohm, Erik, 2020. "Price-setting and economic slack: Evidence from firm-level survey data," Journal of Macroeconomics, Elsevier, vol. 65(C).
    17. Guizzardi, Andrea & Stacchini, Annalisa, 2015. "Real-time forecasting regional tourism with business sentiment surveys," Tourism Management, Elsevier, vol. 47(C), pages 213-223.
    18. Alexandros Botsis & Christoph Görtz & Plutarchos Sakellaris, 2020. "Quantifying Qualitative Survey Data: New Insights on the (Ir)Rationality of Firms' Forecasts," CESifo Working Paper Series 8148, CESifo.
    19. 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.
    20. Boneva, Lena & CLoyne, James & Weale, Martin & Wieladek, Tomasz, 2016. "Firms’ expectations and price-setting: evidence from micro data," Discussion Papers 48, Monetary Policy Committee Unit, Bank of England.
    21. Alex Botsis & Kevin Lee, 2022. "Nowcasting Using Firm-Level Survey Data; Tracking UK Output Fluctuations and Recessionary Events," Economic Statistics Centre of Excellence (ESCoE) Technical Reports ESCOE-TR-20, Economic Statistics Centre of Excellence (ESCoE).
    22. Luboš Marek & Stanislava Hronová & Richard Hindls, 2019. "Možnosti odhadů krátkodobých makroekonomických agregátů na základě výsledků konjunkturních průzkumů [Possibilities of Estimations of Short-term Macroeconomic Aggregates Based on Business Survey Res," Politická ekonomie, Prague University of Economics and Business, vol. 2019(4), pages 347-370.
    23. Kajal Lahiri & Yongchen Zhao, 2013. "Quantifying Heterogeneous Survey Expectations: The Carlson-Parkin Method Revisited," Discussion Papers 13-08, University at Albany, SUNY, Department of Economics.

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