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Nowcasting and predicting data revisions in real time using qualitative panel survey data

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Author Info
Troy Matheson
James Mitchell
Brian Silverstone (Reserve Bank of New Zealand)

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Abstract

The qualitative responses that firms give to business survey questions regarding changes in their own output provide a real-time signal of official output changes. The most commonly-used method to produce an aggregate quantitative indicator from business survey responses - the net balance, or diffusion index - has changed little in 40 years. It focuses on the proportion of survey respondents replying "up", "the same" or "down". This paper investigates whether an improved real-time signal of official output data changes can be derived from a recently advanced method on the aggregation of survey data from panel responses. It also considers the ability of survey data to anticipate revisions to official output data. We find, in a New Zealand application, that exploiting the panel dimension to qualitative survey data gives a better in-sample signal about official data than traditional methods. This is achieved by giving a higher weight to firms whose answers have a close link to official data than to those whose experiences correspond only weakly or not at all. Out-of-sample, it is less clear it matters how survey data are quantified with simpler and more parsimonious methods hard to improve. It is clear, nevertheless, that survey data, exploited in some form, help to explain revisions to official data.

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File URL: http://www.rbnz.govt.nz/research/discusspapers/dp07_02.pdf
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Publisher Info
Paper provided by Reserve Bank of New Zealand in its series Reserve Bank of New Zealand Discussion Paper Series with number DP2007/02.

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Length: 25 p.
Date of creation: Feb 2007
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Handle: RePEc:nzb:nzbdps:2007/02

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Find related papers by JEL classification:
C35 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Discrete Regression and Qualitative Choice Models
C42 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Survey Methods
C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Other Model Applications
C80 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - General

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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.:
  1. Ciaran Driver & Giovanni Urga, 2004. "Transforming Qualitative Survey Data: Performance Comparisons for the UK," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 66(1), pages 71-89, 02. [Downloadable!] (restricted)
  2. Carlson, John A & Parkin, J Michael, 1975. "Inflation Expectations," Economica, London School of Economics and Political Science, vol. 42(166), pages 123-38, May. [Downloadable!] (restricted)
  3. Faust, Jon & Rogers, John H & Wright, Jonathan H, 2005. "News and Noise in G-7 GDP Announcements," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 37(3), pages 403-19, June.
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  4. Cath Sleeman, 2006. "Analysis of revisions to quarterly GDP - a real-time database," Reserve Bank of New Zealand Bulletin, Reserve Bank of New Zealand, vol. 69, pages 44p., March. [Downloadable!]
  5. Michela Nardo, 2003. "The Quantification of Qualitative Survey Data: A Critical Assessment," Journal of Economic Surveys, Blackwell Publishing, vol. 17(5), pages 645-668, December. [Downloadable!] (restricted)
  6. McAleer, M. & Smith, J., 1990. "Alternative Procedures for Converting Qualitative Response Data to Quantitative Expectations: An Application to Australian Manufacturing," Papers 219, Australian National University - Department of Economics.
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  7. Tom Stark, 2002. "A summary of the conference on real-time data analysis," Business Review, Federal Reserve Bank of Philadelphia, issue Q 1, pages 5-11. [Downloadable!]
  8. 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. [Downloadable!] (restricted)
  9. James Mitchell & Richard J. Smith & Martin R. Weale, 2002. "Aggregate versus Disaggregate Survey-Based Indicators of Economic Activity," NIESR Discussion Papers 194, National Institute of Economic and Social Research. [Downloadable!]
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This page was last updated on 2008-7-16.


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