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Réponses individuelles aux enquêtes de conjoncture et prévision de la production manufacturière

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  • Olivier Biau
  • Hélène Erkel-Rousse
  • Nicolas Ferrari

Abstract

[spa] Respuestas individuales a las encuestas de coyuntura y previsión de la producción manufacturera. Hemos comparado los resultados de saldos de opinión y los indicadores propuestos por Mitchell, Smith y Weale para la previsión a un trimestre de la tasa de crecimiento de la producción manufacturera. Las fuentes utilizadas son la encuesta sobre la situación y las perspectivas en la industria y las cuentas trimestrales publicadas por el Insee. Los indicadores se refi eren a las cuestiones relativas a la producción pasada y prevista de las unidades de producción encuestadas. [ger] Individuelle Antworten auf die Konjunkturerhebungen und Vorausschätzung der Produktion im verarbeitenden Gewerbe. Wir vergleichen die Performance der Meinungssalden und der Indikatoren, die Mitchell, Smith und Weale zur vierteljährlichen Vorausschätzung des Produktionszuwachses im verarbeitenden Gewerbe vorgeschlagen haben. Als Quellen dienen die Erhebung über die Konjunktur und die Perspektiven der Industrie und die vom INSEE veröffentlichten vierteljährlichen Volkswirtschaftlichen Gesamtrechnungen. [fre] Nous comparons les performances de soldes d'opinion et d'indicateurs proposés par Mitchell, Smith et Weale pour la prévision à un trimestre du taux de croissance de la production manufacturière. Les sources utilisées sont l'enquête sur la situation et les perspectives dans l'industrie et les comptes trimestriels publiés par l'Insee. Les indicateurs se réfèrent aux questions portant sur les productions passée et prévue des unités de production enquêtées. Contrairement aux soldes d'opinion, les indicateurs de Mitchell, Smith et Weale ont comme particularité de tenir compte de l'hétérogénéité des comportements de réponse des entrepreneurs à l'enquête de conjoncture. Les réponses des entrepreneurs qui sont les plus en phase avec le taux de croissance de la production manufacturière sont celles qui contribuent le plus à la variabilité de ces indicateurs. Il s'agit de vérifier si cette propriété se traduit par une capacité prédictive supérieure à celle d'indicateurs plus classiques, comme le solde d'opinion. Les applications de Mitchell, Smith et Weale sur des données britanniques et allemandes le suggèrent, mais pas leurs applications sur des données suédoises et portugaises. Dans cette étude effectuée sur des données françaises, les performances prédictives des indicateurs de Mitchell, Smith et Weale s'avèrent inférieures ou, au mieux, équivalentes à celles des soldes d'opinion, selon les modèles utilisés. Ce résultat paraît robuste en raison de la grande taille du panel de données françaises et de la méthode d'évaluation des indicateurs qui est retenue, les qualités prédictives de ces derniers étant testées en dehors de leur période d'estimation. [eng] Individual Responses to Business Tendency Surveys and the Forecasting of Manufacturing Production. We compare the performances of balances of opinion to those of indicators introduced by Mitchell, Smith and Weale for the one-quarter forecasting of the manufacturing production growth rate. The sources used are the Business Tendency Survey in industry and the quarterly accounts published by INSEE. The indicators relate to answers given by the production units questioned about their past and expected production Unlike the balances of opinion, the indicators proposed by Mitchell, Smith and Weale take into account the heterogeneity of the response behaviours of the entrepre- neurs taking part in the Business Tendency Survey. The responses of entrepreneurs which are the most tightly linked to the overall fl uctuations of manufactured production contribute to the variability of these indicators to a larger extent than the responses of the other surveyed. Does this specifi c feature of these indicators enable the latter to perform better in short-term forecasting than more classic indicators, such as the balance of opinion? The application of Mitchell, Smith and Weale to British and German data seems to suggest that this is the case, but their application to Swedish and Portuguese data suggests not. In our study carried out using French data, the predictive performances of the Mitchell, Smith and Weale indicators turn out to be inferior or, at best, equivalent to those of the balances of opinion, depending on the models used. This result seems robust due to both the large size of the French panel and the evaluation method used, the predictive qualities of the indicators being tested outside of their estimation period.

Suggested Citation

  • 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.
  • Handle: RePEc:prs:ecstat:estat_0336-1454_2006_num_395_1_7133
    DOI: 10.3406/estat.2006.7133
    Note: DOI:10.3406/estat.2006.7133
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    References listed on IDEAS

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    1. 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.
    2. 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.
    3. Pilar Bengoechea & Gabriel Pérez Quirós, 2004. "A useful tool to identify recessions in the euro area," European Economy - Economic Papers 2008 - 2015 215, Directorate General Economic and Financial Affairs (DG ECFIN), European Commission.
    4. Hamilton, James D., 1990. "Analysis of time series subject to changes in regime," Journal of Econometrics, Elsevier, vol. 45(1-2), pages 39-70.
    5. Stéphane Gregoir & Fabrice Lenglart, 1998. "Un nouvel indicateur pour saisir les retournements de conjoncture," Économie et Statistique, Programme National Persée, vol. 314(1), pages 39-60.
    6. Jan Marc Berk, 1999. "Measuring inflation expectations: a survey data approach," Applied Economics, Taylor & Francis Journals, vol. 31(11), pages 1467-1480.
    7. 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.
    8. Diebold, Francis X & Mariano, Roberto S, 2002. "Comparing Predictive Accuracy," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(1), pages 134-144, January.
    9. Thomas J. Sargent & Christopher A. Sims, 1977. "Business cycle modeling without pretending to have too much a priori economic theory," Working Papers 55, Federal Reserve Bank of Minneapolis.
    10. 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, July.
    11. 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.
    12. repec:adr:anecst:y:1999:i:54:p:05 is not listed on IDEAS
    13. Carlson, John A & Parkin, J Michael, 1975. "Inflation Expectations," Economica, London School of Economics and Political Science, vol. 42(166), pages 123-138, May.
    14. Lee, Kevin C, 1994. "Formation of Price and Cost Inflation Expectations in British Manufacturing Industries: A Multi-Sectoral Analysis," Economic Journal, Royal Economic Society, vol. 104(423), pages 372-385, March.
    15. 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.
    16. 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.
    17. Lahiri, Kajal & Teigland, Christie & Zaporowski, Mark, 1988. "Interest Rates and the Subjective Probability Distribution of Inflation Forecasts," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 20(2), pages 233-248, May.
    18. Forni, Mario, et al, 2001. "Coincident and Leading Indicators for the Euro Area," Economic Journal, Royal Economic Society, vol. 111(471), pages 62-85, May.
    19. Hamilton, James D, 1989. "A New Approach to the Economic Analysis of Nonstationary Time Series and the Business Cycle," Econometrica, Econometric Society, vol. 57(2), pages 357-384, March.
    20. Fabrice Lenglart & Fabien Toutlemonde, 2002. "Mieux appréhender le climat conjoncturel de la zone euro," Économie et Statistique, Programme National Persée, vol. 359(1), pages 69-81.
    21. 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.
    22. 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.
    23. Catherine Doz & Fabrice Lenglart, 1999. "Analyse factorielle dynamique : test du nombre de facteurs, estimation et application à l'enquête de conjoncture dans l'industrie," Annals of Economics and Statistics, GENES, issue 54, pages 91-127.
    24. Batchelor, R. A., 1981. "Aggregate expectations under the stable laws," Journal of Econometrics, Elsevier, vol. 16(2), pages 199-210, June.
    25. 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.
    26. 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.
    27. Kaiser, Ulrich & Spitz, Alexandra, 2000. "Quantification of qualitative data using ordered probit models with an application to a business survey in the German service sector," ZEW Discussion Papers 00-58, ZEW - Leibniz Centre for European Economic Research.
    28. Harvey, David & Leybourne, Stephen & Newbold, Paul, 1997. "Testing the equality of prediction mean squared errors," International Journal of Forecasting, Elsevier, vol. 13(2), pages 281-291, June.
    29. 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.
    30. Ray Barrell, 1999. "Employment Security and European Labour Demand: A Panel Study Across 16 Industries," National Institute of Economic and Social Research (NIESR) Discussion Papers 148, National Institute of Economic and Social Research.
    31. 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.
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