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Forecasting manufacturing output growth using firm-level survey data

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  • Dr Martin Weale

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  • Dr. James Mitchell

    ()

Abstract

Traditionally forecasts of macroeconomic aggregates are extracted from prospective qualitative survey data by relating official data on the aggregate to both the proportion of survey respondents who are "optimists" and the proportion who are "pessimists". But there is no reason to focus on these proportions to the exclusion of other possible means of aggregating and quantifying the underlying panel of respondent or firm-level survey responses. Accordingly in this paper we show how the panel of firm-level responses underlying these proportions can be exploited to derive forecasts of (aggregate) manufacturing output growth that do not lose information that may be contained in the pattern of individual responses. An application using firm-level prospective survey data from the Confederation of British Industry shows that the forecasts of manufacturing output growth derived using these "disaggregate" methods mark an improvement over the so-called "aggregate" methods based on use of the proportions data alone.

Suggested Citation

  • Dr Martin Weale & Dr. James Mitchell, 2005. "Forecasting manufacturing output growth using firm-level survey data," National Institute of Economic and Social Research (NIESR) Discussion Papers 251, National Institute of Economic and Social Research.
  • Handle: RePEc:nsr:niesrd:776
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    References listed on IDEAS

    as
    1. Entorf, Horst, 1993. "Constructing leading indicators from non-balanced sectoral business survey series," International Journal of Forecasting, Elsevier, vol. 9(2), pages 211-225, August.
    2. 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.
    3. 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, February.
    4. William A. Branch, 2004. "The Theory of Rationally Heterogeneous Expectations: Evidence from Survey Data on Inflation Expectations," Economic Journal, Royal Economic Society, vol. 114(497), pages 592-621, July.
    5. Smith, Richard J & Blundell, Richard W, 1986. "An Exogeneity Test for a Simultaneous Equation Tobit Model with an Application to Labor Supply," Econometrica, Econometric Society, vol. 54(3), pages 679-685, May.
    6. McIntosh, James & Schiantarelli, Fabio & Low, William, 1989. "A Qualitative Response Analysis of UK Firms' Employment and Output Decisions," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 4(3), pages 251-264, July-Sept.
    7. François Bouton & Hélène Erkel-Rousse, 2002. "Conjonctures sectorielles et prévision à court terme de l'activité : l'apport de l'enquête de conjoncture dans les services," Économie et Statistique, Programme National Persée, vol. 359(1), pages 35-68.
    8. Ashley, Richard, 2003. "Statistically significant forecasting improvements: how much out-of-sample data is likely necessary?," International Journal of Forecasting, Elsevier, vol. 19(2), pages 229-239.
    9. Stéphane Grégoir & Fabrice Lenglart, 1998. "Measuring the Probability of a Business Cycle Turning Point by Using a Multivariate Qualitative Hidden Markov Model," Working Papers 98-48, Center for Research in Economics and Statistics.
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    Citations

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    Cited by:

    1. Maurizio Bovi, 2005. "Consumers Sentiment and Cognitive Macroeconometrics Paradoxes and Explanations," Macroeconomics 0512002, University Library of Munich, Germany.
    2. Lahiri, Kajal & Zhao, Yongchen, 2015. "Quantifying survey expectations: A critical review and generalization of the Carlson–Parkin method," International Journal of Forecasting, Elsevier, vol. 31(1), pages 51-62.
    3. 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.
    4. James Mitchell & Richard J. Smith & Martin R. Weale, 2013. "Efficient Aggregation Of Panel Qualitative Survey Data," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 28(4), pages 580-603, June.
    5. repec:spr:soinre:v:135:y:2018:i:1:d:10.1007_s11205-016-1490-3 is not listed on IDEAS
    6. Oscar Claveria & Enric Monte & Salvador Torra, 2017. "Let the data do the talking: Empirical modelling of survey-based expectations by means of genetic programming," IREA Working Papers 201711, University of Barcelona, Research Institute of Applied Economics, revised May 2017.
    7. 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.
    8. Troy D. Matheson & James Mitchell & Brian Silverstone, 2010. "Nowcasting and predicting data revisions using panel survey data," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 29(3), pages 313-330.
    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, April.
    10. Dr Martin Weale & Dr. James Mitchell, 2006. "A Bayesian Indicator of Manufacturing Output from Qualitative Business Panel Survey Data," National Institute of Economic and Social Research (NIESR) Discussion Papers 261, National Institute of Economic and Social Research.
    11. Troy Matheson & James Mitchell & Brian Silverstone, 2007. "Nowcasting and predicting data revisions in real time using qualitative panel survey data," Reserve Bank of New Zealand Discussion Paper Series DP2007/02, Reserve Bank of New Zealand.
    12. 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.
    13. 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.
    14. repec:eee:touman:v:47:y:2015:i:c:p:213-223 is not listed on IDEAS
    15. David Bywaters & Gareth Thomas, 2008. "Output Expectations and Forecasting of UK Manufacturing," Atlantic Economic Journal, Springer;International Atlantic Economic Society, vol. 36(2), pages 125-137, June.
    16. François Hild, 2006. "Un nouvel indicateur synthétique prenant en compte la dynamique des réponses individuelles à l'enquête Industrie," Économie et Statistique, Programme National Persée, vol. 395(1), pages 65-89.
    17. Olivier Biau & Hélène Erkel-Rousse & Nicolas Ferrari, 2006. "Réponses individuelles aux enquêtes de conjoncture et prévision de la production manufacturière," Économie et Statistique, Programme National Persée, vol. 395(1), pages 91-116.
    18. Kajal Lahiri & Yongchen Zhao, 2013. "Quantifying Heterogeneous Survey Expectations: The Carlson-Parkin Method Revisited," Discussion Papers 13-08, University at Albany, SUNY, Department of Economics.

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