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Easier said than done: the divergence between soft and hard data

Author

Listed:
  • Antonio M. Conti

    (Bank of Italy)

  • Concetta Rondinelli

    (Bank of Italy)

Abstract

Between the first half of 2013 and the summer of 2014, survey data pointed to a gradual recovery of economic activity, while the hard data continued to show persistent weakness. After providing statistical evidence to support the hypothesis that, during the sovereign debt crisis, the relationship between soft and hard variables for the Italian economy has weakened, the paper evaluates some possible explanations for this gap. The micro data for the quarterly survey conducted by the Bank of Italy � Il Sole 24 Ore on growth and inflation expectations tend to rule out the hypothesis that the gap between the qualitative and quantitative indicators comes from selection effects due to the progressive exclusion from the sample of economically distressed firms. Furthermore, the prolonged recession seems to have modified firms� expectations, leading to a downward revision of production plans and the setting of a �new normal� situation. Therefore, firms may still have expressed favorable expectations for the economic outlook in spite of cyclically slack activity.

Suggested Citation

  • Antonio M. Conti & Concetta Rondinelli, 2015. "Easier said than done: the divergence between soft and hard data," Questioni di Economia e Finanza (Occasional Papers) 258, Bank of Italy, Economic Research and International Relations Area.
    • Handle: RePEc:bdi:opques:qef_258_15
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    File URL: https://www.bancaditalia.it/pubblicazioni/qef/2015-0258/QEF_258.pdf
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    References listed on IDEAS

    as
    1. Valentina Aprigliano, 2011. "The relationship between the PMI and the Italian index of industrial production and the impact of the latest economic crisis," Temi di discussione (Economic working papers) 820, Bank of Italy, Economic Research and International Relations Area.
    2. Sylvain Leduc & Keith Sill, 2013. "Expectations and Economic Fluctuations: An Analysis Using Survey Data," The Review of Economics and Statistics, MIT Press, vol. 95(4), pages 1352-1367, October.
    3. Barsky, Robert B. & Sims, Eric R., 2011. "News shocks and business cycles," Journal of Monetary Economics, Elsevier, vol. 58(3), pages 273-289.
    4. Paul Beaudry & Franck Portier, 2006. "Stock Prices, News, and Economic Fluctuations," American Economic Review, American Economic Association, vol. 96(4), pages 1293-1307, September.
    5. Mario Forni & Luca Gambetti & Marco Lippi & Luca Sala, 2017. "Noisy News in Business Cycles," American Economic Journal: Macroeconomics, American Economic Association, vol. 9(4), pages 122-152, October.
    6. Robert B. Barsky & Eric R. Sims, 2012. "Information, Animal Spirits, and the Meaning of Innovations in Consumer Confidence," American Economic Review, American Economic Association, vol. 102(4), pages 1343-1377, June.
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    Cited by:

    1. Maria Rita Ippoliti & Fabiana Sartor & Luigi Martone, 2021. "Trade surveys: qualitative and quantitative indicators," RIEDS - Rivista Italiana di Economia, Demografia e Statistica - The Italian Journal of Economic, Demographic and Statistical Studies, SIEDS Societa' Italiana di Economia Demografia e Statistica, vol. 75(4), pages 75-85, October-D.
    2. 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.

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    More about this item

    Keywords

    survey data; confidence; industrial production; new normal;
    All these keywords.

    JEL classification:

    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles
    • C40 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - General
    • C80 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - General

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