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On estimating contemporaneous quarterly regional GDP

Author

Listed:
  • Bernardí Cabrer-Borrás

    (Departamento de Análisis Económico, Universidad de Valencia, Spain)

  • Jose Manuel Pavía-Miralles

    (Departamento Economía Aplicada, Universidad de Valencia, Spain)

Abstract

Subnational regional jurisdictions rarely have at their disposal a reasonable array of timely statistics to monitor their economic condition. In light of this, we develop a procedure that simultaneously estimates a quarterly time series for all regions of a country based upon quarterly national and annual regional data. While other such techniques exist, we suggest a temporal error structure that eliminates possible spurious jumps. Using our approach, regional analysts should now be able to distribute national growth among regions as soon as quarterly national figures are released. In a Spanish application, we detail some practicalities of the process and show that our proposal produces better estimates than the uniregional methods often used. Copyright © 2007 John Wiley & Sons. Ltd.

Suggested Citation

  • Bernardí Cabrer-Borrás & Jose Manuel Pavía-Miralles, 2007. "On estimating contemporaneous quarterly regional GDP," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 26(3), pages 155-170.
  • Handle: RePEc:jof:jforec:v:26:y:2007:i:3:p:155-170
    DOI: 10.1002/for.1018
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    References listed on IDEAS

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    1. Dickey, David A & Fuller, Wayne A, 1981. "Likelihood Ratio Statistics for Autoregressive Time Series with a Unit Root," Econometrica, Econometric Society, vol. 49(4), pages 1057-1072, June.
    2. 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 169-173, April.
    3. Milton Friedman, 1962. "Introduction to "The Interpolation of Time Series by Related Series"," NBER Chapters,in: The Interpolation of Time Series by Related Series, pages 1-3 National Bureau of Economic Research, Inc.
    4. Milton Friedman, 1962. "The Interpolation of Time Series by Related Series," NBER Books, National Bureau of Economic Research, Inc, number frie62-1.
    5. 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 169-173, April.
    6. Rossi, Nicola, 1982. "A Note on the Estimation of Disaggregate Time Series When the Aggregate Is Known," The Review of Economics and Statistics, MIT Press, vol. 64(4), pages 695-696, November.
    7. V. Guerrero & J. Martínez, 1995. "A recursive ARIMA-based procedure for disaggregating a time series variable using concurrent data," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 4(2), pages 359-376, December.
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