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An Alternative to the Carlson-Parkin Method for the Quantification of Qualitative Inflation Expectations: Evidence from the Ifo World Economic Survey

Author

Listed:
  • Steffen Henzel
  • Timo Wollmershäuser

Abstract

This paper presents a new methodology for the quantification of qualitative survey data. Traditional conversion methods, such as the probability approach of Carlson and Parkin (1975) or the time-varying parameters model of Seitz (1988), require very restrictive assumptions concerning the expectations formation process of survey respondents. Above all, the unbiasedness of expectations, which is a necessary condition for rationality, is imposed. Our approach avoids these assumptions. The novelty lies in the way the boundaries inside of which survey respondents expect the variable under consideration to remain unchanged are determined. Instead of deriving these boundaries from the statistical properties of the reference time-series (which necessitates the unbiasedness assumption), we directly queried them from survey respondents by a special question in the Ifo World Economic Survey. The new methodology is then applied to expectations about the future development of inflation obtained from the Ifo World Economic Survey.

Suggested Citation

  • Steffen Henzel & Timo Wollmershäuser, 2005. "An Alternative to the Carlson-Parkin Method for the Quantification of Qualitative Inflation Expectations: Evidence from the Ifo World Economic Survey," ifo Working Paper Series 9, ifo Institute - Leibniz Institute for Economic Research at the University of Munich.
    • Handle: RePEc:ces:ifowps:_9
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    References listed on IDEAS

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    6. Michela Nardo, 2003. "The Quantification of Qualitative Survey Data: A Critical Assessment," Journal of Economic Surveys, Wiley Blackwell, vol. 17(5), pages 645-668, December.
    7. repec:bla:econom:v:55:y:1988:i:219:p:317-31 is not listed on IDEAS
    8. Forsells, Magnus & Kenny, Geoff, 2002. "The rationality of consumers' inflation expectations: survey-based evidence for the euro area," Working Paper Series 163, European Central Bank.
    9. repec:bla:econom:v:42:y:1975:i:166:p:123-38 is not listed on IDEAS
    10. Fishe, Raymond P. H. & Lahiri, Kajal, 1981. "On the estimation of inflationary expectations from qualitative responses," Journal of Econometrics, Elsevier, vol. 16(1), pages 89-102, May.
    Full references (including those not matched with items on IDEAS)

    Citations

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    Cited by:

    1. Evgenia Kudymowa & Johanna Garnitz & Klaus Wohlrabe, 2013. "Ifo World Economic Survey und die realwirtschaftliche Entwicklung in ausgewählten Ländern," ifo Schnelldienst, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 66(19), pages 23-30, October.
    2. 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.
    3. Christian Mueller & Aniela Wirz & Nora Sydow, 2007. "A Note on the Carlson-Parkin Method of Quantifying Qualitative Data," KOF Working papers 07-168, KOF Swiss Economic Institute, ETH Zurich.
    4. Klaus Abberger & Sascha Becker & Barbara Hofmann & Klaus Wohlrabe, 2007. "Mikrodaten im ifo Institut für Wirtschaftsforschung – Bestand, Verwendung und Zugang," AStA Wirtschafts- und Sozialstatistisches Archiv, Springer;Deutsche Statistische Gesellschaft - German Statistical Society, vol. 1(1), pages 27-42, June.
    5. Oscar Claveria & Enric Monte & Salvador Torra, 2018. "“Tracking economic growth by evolving expectations via genetic programming: A two-step approach”," AQR Working Papers 201801, University of Barcelona, Regional Quantitative Analysis Group, revised Jan 2018.
    6. 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.
    7. Teresita Bascos-Deveza, 2011. "Quantifying qualitative data from expectation surveys: how well do expectation surveys forecast inflation?," IFC Bulletins chapters, in: Bank for International Settlements (ed.), Proceedings of the IFC Conference on "Initiatives to address data gaps revealed by the financial crisis", Basel, 25-26 August 2010, volume 34, pages 128-137, Bank for International Settlements.
    8. 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.
    9. Tine Janžek & Petra Ziherl, 2013. "Overview of models and methods for measuring economic agent’s expectations," IFC Bulletins chapters, in: Bank for International Settlements (ed.), Proceedings of the Sixth IFC Conference on "Statistical issues and activities in a changing environment", Basel, 28-29 August 2012., volume 36, pages 172-179, Bank for International Settlements.
    10. Perevyshin, Yury (Перевышин, Юрий) & Rykalin, A.S. (Рыкалин, А.С.), 2018. "Modeling Inflation Expectations in the Russian Economy [Моделирование Инфляционных Ожиданий В Российской Экономике]," Working Papers 031816, Russian Presidential Academy of National Economy and Public Administration.
    11. Evgenia Kudymowa & Johanna Garnitz & Klaus Wohlrabe, 2014. "Ifo World Economic Survey and the Business Cycle in Selected Countries," CESifo Forum, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 14(04), pages 51-57, January.
    12. 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.
    13. Evgenia Kudymowa & Johanna Garnitz & Klaus Wohlrabe, 2014. "Ifo World Economic Survey and the Business Cycle in Selected Countries," CESifo Forum, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 14(4), pages 51-57, January.
    14. Wolfgang Nierhaus & Timo Wollmershäuser, 2016. "ifo Konjunkturumfragen und Konjunkturanalyse: Band II," ifo Forschungsberichte, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, number 72.

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    More about this item

    JEL classification:

    • C42 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Survey Methods
    • D84 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Expectations; Speculations
    • E31 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Price Level; Inflation; Deflation

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