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Do Surveys Help in Macroeconomic Variables Disaggregation and Estimation?

  • Cecilia Frale
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    This paper explores the potential of Business Survey data for the estimation and disaggregation of macroeconomic variables at higher frequency. We propose a multivariate approach which is an extension of the Stock and Watson (1991) dynamic factor model, considering more than one common factor and low-frequency cycles. The multivariate model is cast in State Space Form and the temporal aggregation constraint is converted into a problem of missing values. An application in real time for the value added of the Industry sector in the Euro area is presented.

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    File URL: http://www.dt.tesoro.it/modules/documenti_it/analisi_progammazione/working_papers/n.-2-2008---Surveys--role-in-macroeconomic-variables-disaggregation-and-estimation.pdf
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    Paper provided by Department of the Treasury, Ministry of the Economy and of Finance in its series Working Papers with number wp2008-2.

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    Length: 31
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    Handle: RePEc:itt:wpaper:wp2008-2
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    1. M. Hashem Pesaran & Martin Weale, 2005. "Survey Expectations," IEPR Working Papers 05.30, Institute of Economic Policy Research (IEPR).
    2. Cecilia Frale & Massimiliano Marcellino & Gian Luigi Mazzi & Tommaso Proietti, 2008. "A Monthly Indicator of the Euro Area GDP," Economics Working Papers ECO2008/32, European University Institute.
    3. Raffaella Giacomini & Halbert White, 2003. "Tests of Conditional Predictive Ability," Econometrics 0308001, EconWPA.
    4. Filippo Moauro & Giovanni Savio, 2005. "Temporal disaggregation using multivariate structural time series models," Econometrics Journal, Royal Economic Society, vol. 8(2), pages 214-234, 07.
    5. Roberto S. Mariano & Yasutomo Murasawa, 2003. "A new coincident index of business cycles based on monthly and quarterly series," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 18(4), pages 427-443.
    6. Tommaso Proietti & Filippo Moauro, 2006. "Dynamic factor analysis with non-linear temporal aggregation constraints," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 55(2), pages 281-300.
    7. Tommaso Proietti & Cecilia Frale, 2011. "New proposals for the quantification of qualitative survey data," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 30(4), pages 393-408, July.
    8. Mario Forni & Filippo Altissimo & Riccardo Cristadoro & Marco Lippi & Giovanni Veronese., 2008. "New Eurocoin: Tracking Economic Growth in Real Time," Center for Economic Research (RECent) 020, University of Modena and Reggio E., Dept. of Economics "Marco Biagi".
    9. Litterman, Robert B, 1983. "A Random Walk, Markov Model for the Distribution of Time Series," Journal of Business & Economic Statistics, American Statistical Association, vol. 1(2), pages 169-73, April.
    10. Tommaso Proietti, 2006. "Temporal disaggregation by state space methods: Dynamic regression methods revisited," Econometrics Journal, Royal Economic Society, vol. 9(3), pages 357-372, November.
    11. Boivin, Jean & Ng, Serena, 2006. "Are more data always better for factor analysis?," Journal of Econometrics, Elsevier, vol. 132(1), pages 169-194, May.
    12. Tommaso Proietti, 2004. "On the Estimation of Nonlinearly Aggregated Mixed Models," Econometrics 0411012, EconWPA.
    13. Chow, Gregory C & Lin, An-loh, 1971. "Best Linear Unbiased Interpolation, Distribution, and Extrapolation of Time Series by Related Series," The Review of Economics and Statistics, MIT Press, vol. 53(4), pages 372-75, November.
    14. Andrew Harvey & Chia-Hui Chung, 2000. "Estimating the underlying change in unemployment in the UK," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 163(3), pages 303-309.
    15. Fernandez, Roque B, 1981. "A Methodological Note on the Estimation of Time Series," The Review of Economics and Statistics, MIT Press, vol. 63(3), pages 471-76, August.
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