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Overcoming Measurement Error Problems in the use of Survey Data on Expectations


  • Kalvinder Shields
  • Kevin Lee


Survey data frequently requires conversion from qualitative responses to quantitative series. A commonly cited criticism of the use of the survey data is that the conversion procedures incorporate measurement errors which render the series unusable. In this paper, we provide a novel contribution to the literature by paying attention to the nature of, and the treatment of, the measurement error that arises when such a conversion takes place. Such an error is frequently ignored or assumed to be orthogonal to known information. The contributions of this paper are three-fold. Firstly, simulation experiments show that the conversion error is systematic in it's relation to known information and show that need for the adequate treatment of conversion errors is essential. Secondly, this paper formally shows that the procedure proposed by Lee (1994), which employs a relatively weak assumption, is extremely successful in circumventing the problems. Finally, in contrast to previous findings, these results provide strong support for the view that expectations are formed rationally in the case of Australian total manufacturing output

Suggested Citation

  • Kalvinder Shields & Kevin Lee, 2004. "Overcoming Measurement Error Problems in the use of Survey Data on Expectations," Econometric Society 2004 Australasian Meetings 107, Econometric Society.
  • Handle: RePEc:ecm:ausm04:107

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    References listed on IDEAS

    1. Ruiz, Esther & Pascual, Lorenzo, 2002. " Bootstrapping Financial Time Series," Journal of Economic Surveys, Wiley Blackwell, vol. 16(3), pages 271-300, July.
    2. Wright, Jonathan H, 2000. "Alternative Variance-Ratio Tests Using Ranks and Signs," Journal of Business & Economic Statistics, American Statistical Association, vol. 18(1), pages 1-9, January.
    3. Pan, Ming-Shiun & Chan, Kam C. & C.W. Fok, Robert, 1997. "Do currency futures prices follow random walks?," Journal of Empirical Finance, Elsevier, vol. 4(1), pages 1-15, January.
    4. Whang, Yoon-Jae & Kim, Jinho, 2003. "A multiple variance ratio test using subsampling," Economics Letters, Elsevier, vol. 79(2), pages 225-230, May.
    5. Richardson, Matthew & Smith, Tom, 1991. "Tests of Financial Models in the Presence of Overlapping Observations," Review of Financial Studies, Society for Financial Studies, vol. 4(2), pages 227-254.
    6. Yilmaz, Kamil, 2003. "Martingale Property of Exchange Rates and Central Bank Interventions," Journal of Business & Economic Statistics, American Statistical Association, vol. 21(3), pages 383-395, July.
    7. Hyun-Jung Ryoo & Graham Smith, 2002. "Korean stock prices under price limits: variance ratio tests of random walks," Applied Financial Economics, Taylor & Francis Journals, vol. 12(8), pages 545-553.
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    Cited by:

    1. Wilbert Van der Klaauw & Wändi Bruine de Bruin & Giorgio Topa & Simon M. Potter & Michael F. Bryan, 2008. "Rethinking the measurement of household inflation expectations: preliminary findings," Staff Reports 359, Federal Reserve Bank of New York.
    2. Barnett, Alina & Groen, Jan J J & Mumtaz, Haroon, 2010. "Time-varying inflation expectations and economic fluctuations in the United Kingdom: a structural VAR analysis," Bank of England working papers 392, Bank of England.

    More about this item


    Measurement Error; Survey-based Expectations; Rationality; Conversion Procedures;

    JEL classification:

    • C42 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Survey Methods
    • D84 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Expectations; Speculations


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