IDEAS home Printed from https://ideas.repec.org/a/kap/iaecre/v5y1999i3p339-34910.1007-bf02296416.html
   My bibliography  Save this article

EstimatingJ (>1) quarterly time series in fulfilling annual and quarterly constraints

Author

Listed:
  • Bernardí Cabred
  • Jose Pavía

Abstract

This paper addresses the problem of joint disaggregating a group of time series when their temporal aggregation values and their contemporaneous aggregation are known and when a number of related series in the desired frequency are available. The focus is on temporal distribution of annual series. This problem was treated before by other authors but they did not solve the problem of spurious steps which usually emerge in this framework. Proposed here is the simplest hypothesis congruent with reality that solves this difficulty. An algorithm is proposed to use these hypotheses in empirical works. Copyright International Atlantic Economic Society 1999

Suggested Citation

  • Bernardí Cabred & Jose Pavía, 1999. "EstimatingJ (>1) quarterly time series in fulfilling annual and quarterly constraints," International Advances in Economic Research, Springer;International Atlantic Economic Society, vol. 5(3), pages 339-349, August.
  • Handle: RePEc:kap:iaecre:v:5:y:1999:i:3:p:339-349:10.1007/bf02296416
    DOI: 10.1007/BF02296416
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1007/BF02296416
    Download Restriction: Access to full text is restricted to subscribers.

    File URL: https://libkey.io/10.1007/BF02296416?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    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. J. H. C. Lisman & J. Sandee, 1964. "Derivation of Quarterly Figures from Annual Data," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 13(2), pages 87-90, June.
    5. Milton Friedman, 1962. "The Interpolation of Time Series by Related Series," NBER Books, National Bureau of Economic Research, Inc, number frie62-1.
    6. 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 372-375, November.
    7. 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.
    8. 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.
    9. J. C. G. Boot & W. Feibes & J. H. C. Lisman, 1967. "Further Methods of Derivation of Quarterly Figures from Annual Data," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 16(1), pages 65-75, March.
    10. 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 471-476, August.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. 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.
    2. Wolfgang Polasek & Richard Sellner, 2008. "Spatial Chow-Lin Methods: Bayesian And Ml Forecast Comparisons," Working Paper series 38_08, Rimini Centre for Economic Analysis.
    3. Kahouli, Sondès, 2011. "Re-examining uranium supply and demand: New insights," Energy Policy, Elsevier, vol. 39(1), pages 358-376, January.
    4. Enrique M. Quilis, 2018. "Temporal disaggregation of economic time series: The view from the trenches," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 72(4), pages 447-470, November.
    5. José Manuel Pavía, 2000. "Desagregación conjunta de series anuales: perturbaciones AR(1) multivariante," Investigaciones Economicas, Fundación SEPI, vol. 24(3), pages 727-737, September.
    6. Huang, Yu-Lieh, 2012. "Measuring business cycles: A temporal disaggregation model with regime switching," Economic Modelling, Elsevier, vol. 29(2), pages 283-290.
    7. Mateusz Pipień & Sylwia Roszkowska, 2015. "Szacunki kwartalnego PKB w polskich województwach," Gospodarka Narodowa. The Polish Journal of Economics, Warsaw School of Economics, issue 5, pages 145-169.
    8. Ledenyov, Dimitri O. & Ledenyov, Viktor O., 2013. "On the Stratonovich – Kalman - Bucy filtering algorithm application for accurate characterization of financial time series with use of state-space model by central banks," MPRA Paper 50235, University Library of Munich, Germany.
    9. Abdullah Tahir & Jameel Ahmed & Waqas Ahmed, 2018. "Robust Quarterization of GDP and Determination of Business Cycle Dates for IGC Partner Countries," SBP Working Paper Series 97, State Bank of Pakistan, Research Department.
    10. Ledenyov, Dimitri O. & Ledenyov, Viktor O., 2015. "Wave function method to forecast foreign currencies exchange rates at ultra high frequency electronic trading in foreign currencies exchange markets," MPRA Paper 67470, University Library of Munich, Germany.
    11. Angelini, Elena & Henry, Jerome & Marcellino, Massimiliano, 2006. "Interpolation and backdating with a large information set," Journal of Economic Dynamics and Control, Elsevier, vol. 30(12), pages 2693-2724, December.
    12. José Manuel Pavía & Bernardí Cabrer, 2008. "On Distributing Quarterly National Growth among Regions," Environment and Planning A, , vol. 40(10), pages 2453-2468, October.
    13. Arby, Muhammad Farooq, 2008. "Some Issues in the National Income Accounts of Pakistan (Rebasing, Quarterly and Provincial Accounts and Growth Accounting)," MPRA Paper 32048, University Library of Munich, Germany.
    14. Jonathan Eaton & Samuel Kortum & Brent Neiman & John Romalis, 2016. "Trade and the Global Recession," American Economic Review, American Economic Association, vol. 106(11), pages 3401-3438, November.
    15. Massimo Gerli & Giovanni Marini, 2006. "Spatial and Temporal Time Series Conversion: A Consistent Estimator of the Error Variance-Covariance Matrix," Journal of Business Cycle Measurement and Analysis, OECD Publishing, Centre for International Research on Economic Tendency Surveys, vol. 2005(3), pages 373-405.
    16. Tommaso Proietti, 2011. "Multivariate temporal disaggregation with cross-sectional constraints," Journal of Applied Statistics, Taylor & Francis Journals, vol. 38(7), pages 1455-1466, June.
    17. Rashid, Abdul & Jehan, Zanaib, 2013. "Derivation of Quarterly GDP, Investment Spending, and Government Expenditure Figures from Annual Data: The Case of Pakistan," MPRA Paper 46937, University Library of Munich, Germany.
    18. Imad A. Moosa & Kelly Burns, 2013. "Interpolating flow and stock variables in a continuous-time dynamic framework," Applied Economics Letters, Taylor & Francis Journals, vol. 20(7), pages 621-625, May.
    19. Jérôme TRINH, 2019. "Temporal disaggregation of short time series with structural breaks: Estimating quarterly data from yearly emerging economies data," Working Papers 2019-11, Center for Research in Economics and Statistics.
    20. Marcus Scheiblecker & Sandra Steindl & Michael Wüger, 2007. "Quarterly National Accounts Inventory of Austria. Description of Applied Methods and Data Sources," WIFO Studies, WIFO, number 37249.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:kap:iaecre:v:5:y:1999:i:3:p:339-349:10.1007/bf02296416. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.