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New proposals for the quantification of qualitative survey data

Author

Listed:
  • Tommaso Proietti

    (Universita di Roma “Tor Vergata”)

  • Cecilia Frale

    (Universita di Roma “Tor Vergata”)

Abstract

In this paper we deal with several issues related to the quantification of business surveys. In particular, we propose and compare new ways of scoring the ordinal responses concerning the qualitative assessment of the state of the economy, such as the spectral envelope and cumulative logit unobserved components models, and investigate the nature of seasonality in the series. We conclude with an evaluation of the type of business cycle fluctuations that is captured by the qualitative surveys.

Suggested Citation

  • Tommaso Proietti & Cecilia Frale, 2007. "New proposals for the quantification of qualitative survey data," CEIS Research Paper 98, Tor Vergata University, CEIS.
    • Handle: RePEc:rtv:ceisrp:98
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    File URL: https://ceistorvergata.it/RePEc/rpaper/No-98.pdf
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    References listed on IDEAS

    as
    1. James Mitchell & Richard J. Smith & Martin R. Weale, 2002. "Quantification of Qualitative Firm-Level Survey Data," Economic Journal, Royal Economic Society, vol. 112(478), pages 117-135, March.
    2. Busetti, Fabio & Harvey, Andrew, 2003. "Seasonality Tests," Journal of Business & Economic Statistics, American Statistical Association, vol. 21(3), pages 420-436, July.
    3. Michael Artis & Massimiliano Marcellino & Tommaso Proietti, 2004. "Dating Business Cycles: A Methodological Contribution with an Application to the Euro Area," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 66(4), pages 537-565, September.
    4. Canova, Fabio & Hansen, Bruce E, 1995. "Are Seasonal Patterns Constant over Time? A Test for Seasonal Stability," Journal of Business & Economic Statistics, American Statistical Association, vol. 13(3), pages 237-252, July.
    5. Carlson, John A & Parkin, J Michael, 1975. "Inflation Expectations," Economica, London School of Economics and Political Science, vol. 42(166), pages 123-138, May.
    Full references (including those not matched with items on IDEAS)

    Citations

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    Cited by:

    1. Marco Cacciotti & Cecilia Frale & Serena Teobaldo, 2013. "A new methodology for a quarterly measure of the Output Gap," Working Papers LuissLab 13103, Dipartimento di Economia e Finanza, LUISS Guido Carli.
    2. Marco Cacciotti & Cecilia Frale & Serena Teobaldo, 2013. "A new methodology for a quarterly measure of the output gap," Working Papers 6, Department of the Treasury, Ministry of the Economy and of Finance.
    3. Cecilia Frale & Massimiliano Marcellino & Gian Luigi Mazzi & Tommaso Proietti, 2010. "Survey data as coincident or leading indicators," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 29(1-2), pages 109-131.
    4. Giancarlo Bruno, 2014. "Consumer confidence and consumption forecast: a non-parametric approach," Empirica, Springer;Austrian Institute for Economic Research;Austrian Economic Association, vol. 41(1), pages 37-52, February.
    5. Cecilia Frale, "undated". "Do Surveys Help in Macroeconomic Variables Disaggregation and Estimation?," Working Papers wp2008-2, Department of the Treasury, Ministry of the Economy and of Finance.
    6. Inna Lola, 2020. "A Multidimensional Classification for the Information Technology Market," Economic Studies journal, Bulgarian Academy of Sciences - Economic Research Institute, issue 4, pages 70-88.
    7. Cecilia Frale & Massimiliano Marcellino & Gian Luigi Mazzi & Tommaso Proietti, 2008. "A Monthly Indicator of the Euro Area GDP," Economics Working Papers ECO2008/32, European University Institute.
    8. Das, Abhiman & Lahiri, Kajal & Zhao, Yongchen, 2019. "Inflation expectations in India: Learning from household tendency surveys," International Journal of Forecasting, Elsevier, vol. 35(3), pages 980-993.
    9. Luciana Crosilla & Marco Malgarini, 2011. "Behavioural models for manufacturing firms: analysing survey data," ECONOMIA E POLITICA INDUSTRIALE, FrancoAngeli Editore, vol. 2011(4), pages 139-163.
    10. Bruno, Giancarlo, 2009. "Non-linear relation between industrial production and business surveys data," MPRA Paper 42337, University Library of Munich, Germany.
    11. G. Bruno & L. Crosilla & P. Margani, 2019. "Inspecting the Relationship Between Business Confidence and Industrial Production: Evidence on Italian Survey Data," Journal of Business Cycle Research, Springer;Centre for International Research on Economic Tendency Surveys (CIRET), vol. 15(1), pages 1-24, April.
    12. Vermeulen, Philip, 2014. "An evaluation of business survey indices for short-term forecasting: Balance method versus Carlson–Parkin method," International Journal of Forecasting, Elsevier, vol. 30(4), pages 882-897.

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    More about this item

    Keywords

    Spectral envelope; Seasonality; Deviation cycles; Cumulative Logit Model.;
    All these keywords.

    JEL classification:

    • H1 - Public Economics - - Structure and Scope of Government
    • L5 - Industrial Organization - - Regulation and Industrial Policy
    • L1 - Industrial Organization - - Market Structure, Firm Strategy, and Market Performance

    NEP fields

    This paper has been announced in the following NEP Reports:

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