IDEAS home Printed from https://ideas.repec.org/
MyIDEAS: Log in (now much improved!) to save this article

Quantifying survey expectations: A critical review and generalization of the Carlson–Parkin method

Listed author(s):
  • Lahiri, Kajal
  • Zhao, Yongchen

This paper provides a critical review of the popular Carlson–Parkin (CP) quantification method using household-level data from the University of Michigan’s Survey of Consumers. We find strong evidence against the threshold constancy, symmetry, homogeneity, and overall unbiasedness assumptions of the CP method. To address these violations, we generalize the CP method using a hierarchical ordered probit (HOPIT) model. By comparing the quantified inflation expectations with quantitative expectations obtained from the same set of households directly, we show that the generalized model performs better than the CP method. In particular, when the CP unbiasedness assumption is replaced by a time-varying calibration, the resulting quantified series is found to track the quantitative benchmark well, over diverse time periods.

If you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.

File URL: http://www.sciencedirect.com/science/article/pii/S0169207014000995
Download Restriction: Full text for ScienceDirect subscribers only

As the access to this document is restricted, you may want to look for a different version under "Related research" (further below) or search for a different version of it.

Article provided by Elsevier in its journal International Journal of Forecasting.

Volume (Year): 31 (2015)
Issue (Month): 1 ()
Pages: 51-62

as
in new window

Handle: RePEc:eee:intfor:v:31:y:2015:i:1:p:51-62
DOI: 10.1016/j.ijforecast.2014.06.003
Contact details of provider: Web page: http://www.elsevier.com/locate/ijforecast

References listed on IDEAS
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:

as
in new window


  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. Lui, Silvia & Mitchell, James & Weale, Martin, 2011. "The utility of expectational data: Firm-level evidence using matched qualitative-quantitative UK surveys," International Journal of Forecasting, Elsevier, vol. 27(4), pages 1128-1146, October.
  3. 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.
  4. Magnus Forsells & Geoff Kenny, 2004. "Survey Expectations, Rationality and the Dynamics of Euro Area Inflation," Journal of Business Cycle Measurement and Analysis, OECD Publishing, Centre for International Research on Economic Tendency Surveys, vol. 2004(1), pages 13-41.
  5. Smith, Jeremy & McAleer, Michael, 1995. "Alternative Procedures for Converting Qualitative Response Data to Quantitative Expectations: An Application to Australian Manufacturing," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 10(2), pages 165-185, April-Jun.
  6. Pesaran, M. Hashem & Weale, Martin, 2006. "Survey Expectations," Handbook of Economic Forecasting, Elsevier.
  7. N. Gregory Mankiw & Ricardo Reis, 2002. "Sticky Information versus Sticky Prices: A Proposal to Replace the New Keynesian Phillips Curve," The Quarterly Journal of Economics, Oxford University Press, vol. 117(4), pages 1295-1328.
  8. Ang, Andrew & Bekaert, Geert & Wei, Min, 2007. "Do macro variables, asset markets, or surveys forecast inflation better?," Journal of Monetary Economics, Elsevier, vol. 54(4), pages 1163-1212, May.
  9. Silvia Lui & James Mitchell & Martin Weale, 2011. "Qualitative business surveys: signal or noise?," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 174(2), pages 327-348, 04.
  10. 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.
  11. 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.
  12. Rolf Scheufele, 2011. "Are Qualitative Inflation Expectations Useful to Predict Inflation?," OECD Journal: Journal of Business Cycle Measurement and Analysis, OECD Publishing, Centre for International Research on Economic Tendency Surveys, vol. 2011(1), pages 29-53.
  13. Souleles, Nicholas S, 2004. "Expectations, Heterogeneous Forecast Errors, and Consumption: Micro Evidence from the Michigan Consumer Sentiment Surveys," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 36(1), pages 39-72, February.
  14. James Mitchell & Richard J. Smith & Martin R. Weale, 2005. "Forecasting Manufacturing Output Growth Using Firm-Level Survey Data," Manchester School, University of Manchester, vol. 73(4), pages 479-499, 07.
  15. Christian M. Dahl & Lin Xia, 2004. "Quantification of Qualitative Survey Data and Test of Consistent Expectations: A New Likelihood Approach," Journal of Business Cycle Measurement and Analysis, OECD Publishing, Centre for International Research on Economic Tendency Surveys, vol. 2004(1), pages 71-92.
  16. Kajal Lahiri & Xuguang Sheng, 2010. "Measuring forecast uncertainty by disagreement: The missing link," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 25(4), pages 514-538.
  17. William H. Greene & David A. Hensher, 2010. "Ordered Choices and Heterogeneity in Attribute Processing," Journal of Transport Economics and Policy, University of Bath, vol. 44(3), pages 331-364, September.
  18. 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.
  19. Kanoh, Satoru & Li, Zhi Dong, 1990. "A Method of Exploring the Mechanism of Inflationary Expectations Based on Qualitative Survey Data," Journal of Business & Economic Statistics, American Statistical Association, vol. 8(4), pages 395-403, October.
  20. Batchelor, Roy A & Orr, Adrian B, 1988. "Inflation Expectations Revisited," Economica, London School of Economics and Political Science, vol. 55(219), pages 317-331, August.
  21. Richard Curtin, 2007. "Consumer Sentiment Surveys: Worldwide Review and Assessment," Journal of Business Cycle Measurement and Analysis, OECD Publishing, Centre for International Research on Economic Tendency Surveys, vol. 2007(1), pages 7-42.
  22. Carlson, John A & Parkin, J Michael, 1975. "Inflation Expectations," Economica, London School of Economics and Political Science, vol. 42(166), pages 123-138, May.
  23. 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.
  24. 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.
  25. Fishe, Raymond P H & Idson, Todd L, 1990. "Information-Induced Heteroscedasticity in Price Expectations Data," The Review of Economics and Statistics, MIT Press, vol. 72(2), pages 304-312, May.
  26. Batchelor, R A, 1986. "Quantitative v. Qualitative Measures of Inflation Expectations," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 48(2), pages 99-120, May.
Full references (including those not matched with items on IDEAS)

This item is not listed on Wikipedia, on a reading list or among the top items on IDEAS.

When requesting a correction, please mention this item's handle: RePEc:eee:intfor:v:31:y:2015:i:1:p:51-62. See general information about how to correct material in RePEc.

For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Dana Niculescu)

If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

If references are entirely missing, you can add them using this form.

If the full references list an item that is present in RePEc, but the system did not link to it, you can help with this form.

If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your profile, as there may be some citations waiting for confirmation.

Please note that corrections may take a couple of weeks to filter through the various RePEc services.

This information is provided to you by IDEAS at the Research Division of the Federal Reserve Bank of St. Louis using RePEc data.