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Quantification of Expectations. Are They Useful for Forecasting Inflation?

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  • O Claveria
  • E Pons
  • J Surinach

Abstract

Business tendency surveys are commonly used to provide estimations of a wide range of macroeconomic variables before the publication of official data. The qualitative nature of data on the direction of change has often led to quantifying survey results making use of official data, introducing a measurement error due to incorrect assumptions. Through Monte Carlo simulations it is possible to isolate the measurement error introduced by incorrect assumptions when quantifying survey results. By means of a simulation experiment we check the effect on the measurement error of respondents diverging from "rationality". We also analyse the predictive performance of different quantification methods for fourteen EU countries and the euro area. We find that allowing for asymmetric and stochastic response thresholds (indifference interval) produces a lower measurement error and more accurate forecasts.

Suggested Citation

  • O Claveria & E Pons & J Surinach, 2006. "Quantification of Expectations. Are They Useful for Forecasting Inflation?," Economic Issues Journal Articles, Economic Issues, vol. 11(2), pages 19-38, September.
    • Handle: RePEc:eis:articl:206claveria
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    1. Dasgupta, Susmita & Lahiri, Kajal, 1992. "A Comparative Study of Alternative Methods of Quantifying Qualitative Survey Responses Using NAPM Data," Journal of Business & Economic Statistics, American Statistical Association, vol. 10(4), pages 391-400, October.
    2. Michel De Vroey & Pierre Malgrange, 2016. "Macroeconomics," Chapters, in: Gilbert Faccarello & Heinz D. Kurz (ed.), Handbook on the History of Economic Analysis Volume III, chapter 27, pages 372-390, Edward Elgar Publishing.
    3. Jan Marc Berk, 1999. "Measuring inflation expectations: a survey data approach," Applied Economics, Taylor & Francis Journals, vol. 31(11), pages 1467-1480.
    4. Balcombe, Kelvin, 1996. "The Carlson-Parkin method applied to NZ price expectations using QSBO survey data," Economics Letters, Elsevier, vol. 51(1), pages 51-57, April.
    5. Diebold, Francis X & Mariano, Roberto S, 2002. "Comparing Predictive Accuracy," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(1), pages 134-144, January.
    6. Lee, Kevin C, 1994. "Formation of Price and Cost Inflation Expectations in British Manufacturing Industries: A Multi-Sectoral Analysis," Economic Journal, Royal Economic Society, vol. 104(423), pages 372-385, March.
    7. Common, Michael S, 1985. "Testing for Rational Expectations with Qualitative Survey Data," The Manchester School of Economic & Social Studies, University of Manchester, vol. 53(2), pages 138-148, June.
    8. Mitchell, James, 2002. "The use of non-normal distributions in quantifying qualitative survey data on expectations," Economics Letters, Elsevier, vol. 76(1), pages 101-107, June.
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    Cited by:

    1. Werner Hölzl & Gerhard Schwarz, 2014. "Der WIFO-Konjunkturtest: Methodik und Prognoseeigenschaften," WIFO Monatsberichte (monthly reports), WIFO, vol. 87(12), pages 835-850, December.
    2. Oscar Claveria & Salvador Torra, 2013. "“Forecasting Business surveys indicators: neural networks vs. time series models”," AQR Working Papers 201312, University of Barcelona, Regional Quantitative Analysis Group, revised Nov 2013.
    3. Oscar Claveria & Enric Monte & Salvador Torra, 2015. "“Self-organizing map analysis of agents' expectations. Different patterns of anticipation of the 2008 financial crisis”," IREA Working Papers 201511, University of Barcelona, Research Institute of Applied Economics, revised Mar 2015.
    4. Juan G Brida & Bibiana Lanzilotta & Lucia I Rosich, 2021. "On the empirical relations between producers expectations and economic growth," Economics Bulletin, AccessEcon, vol. 41(3), pages 1970-1982.
    5. Oscar Claveria, 2021. "Forecasting with Business and Consumer Survey Data," Forecasting, MDPI, vol. 3(1), pages 1-22, February.
    6. Petar Soric & Mateo Zokalj & Marija Logarusic, 2020. "Economic determinants of Croatian consumer confidence: real estate prices vs. macroeconomy," Interdisciplinary Description of Complex Systems - scientific journal, Croatian Interdisciplinary Society Provider Homepage: http://indecs.eu, vol. 18(2B), pages 240-257.
    7. 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.
    8. Oscar Claveria & Enric Monte & Salvador Torra, 2017. "A new approach for the quantification of qualitative measures of economic expectations," Quality & Quantity: International Journal of Methodology, Springer, vol. 51(6), pages 2685-2706, November.
    9. Santiago Pinto & Pierre-Daniel G. Sarte & Robert Sharp, 2015. "Learning About Consumer Uncertainty from Qualitative Surveys: As Uncertain As Ever," Working Paper 15-9, Federal Reserve Bank of Richmond.
    10. Oscar Claveria & Enric Monte & Salvador Torra, 2017. "“Let the data do the talking: Empirical modelling of survey-based expectations by means of genetic programming”," AQR Working Papers 201706, University of Barcelona, Regional Quantitative Analysis Group, revised May 2017.

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