IDEAS home Printed from https://ideas.repec.org/p/bea/papers/0077.html
   My bibliography  Save this paper

An Empirical Comparison of Methods for Temporal Distribution and Interpolation at the National Accounts

Author

Listed:
  • Baoline Chen

    (Bureau of Economic Analysis)

Abstract

This study evaluates five mathematical and five statistical methods for temporal disaggregation in an attempt to select the most suitable method(s) for routine compilation of sub-annual estimates through temporal distribution and interpolation in the national accounts at BEA. The evaluation is conducted using 60 series of annual data from the National Economic Accounts, and the final sub-annual estimates are evaluated according to specific criteria to ensure high quality final estimates that are in compliance with operational policy at the national accounts. The study covers the cases of temporal disaggregation when 1) both annual and sub-annual information is available; 2) only annual data are available; 3) sub-annual estimates have both temporal and contemporaneous constraints; and 4) annual data contain negative values. The estimation results show that the modified Denton proportional first difference method outperforms the other methods, though the Casey-Trager growth preservation model is a close competitor in certain cases. Lagrange polynomial interpolation procedure is inferior to all other methods.

Suggested Citation

  • Baoline Chen, 2007. "An Empirical Comparison of Methods for Temporal Distribution and Interpolation at the National Accounts," BEA Papers 0077, Bureau of Economic Analysis.
  • Handle: RePEc:bea:papers:0077
    as

    Download full text from publisher

    File URL: https://www.bea.gov/papers/pdf/chen_temp_aggregation_wp.pdf
    Download Restriction: no

    References listed on IDEAS

    as
    1. 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.
    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. David Aadland, 2000. "Distribution and interpolation using transformed data," Journal of Applied Statistics, Taylor & Francis Journals, vol. 27(2), pages 141-156.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Temurshoev, Umed, 2012. "Entropy-based benchmarking methods," GGDC Research Memorandum GD-122, Groningen Growth and Development Centre, University of Groningen.
    2. Vega-Lacorte, Juliana E. & Watkins-Fassler, Karen., 2013. "Crédito al consumo en Argentina durante periodos normales y de crisis económicas," Panorama Económico, Escuela Superior de Economía, Instituto Politécnico Nacional, vol. 0(16), pages 51-76, primer se.
    3. Pillay, Sagaren & de Beer, Joe, 2016. "Alignment of the Quarterly Financial Statistics to the Annual Financial Statistics data," MPRA Paper 82130, University Library of Munich, Germany.
    4. Matthias Uhl, 2014. "State Fiscal Policies and Regional Economic Activity," MAGKS Papers on Economics 201446, Philipps-Universität Marburg, Faculty of Business Administration and Economics, Department of Economics (Volkswirtschaftliche Abteilung).
    5. Mateusz Pipień & Sylwia Roszkowska, 2015. "Szacunki kwartalnego PKB w polskich województwach," Gospodarka Narodowa, Warsaw School of Economics, issue 5, pages 145-169.
    6. K. Azim Ozdemir, 2015. "Interest Rate Surprises and Transmission Mechanism in Turkey: Evidence from Impulse Response Analysis," Working Papers 1504, Research and Monetary Policy Department, Central Bank of the Republic of Turkey.
    7. Travaglini, Guido, 2010. "Supervised Principal Components and Factor Instrumental Variables. An Application to Violent CrimeTrends in the US, 1982-2005," MPRA Paper 22077, University Library of Munich, Germany.
    8. Klaus Abberger & Michael Graff & Boriss Siliverstovs & Jan-Egbert Sturm, 2014. "The KOF Economic Barometer, Version 2014," KOF Working papers 14-353, KOF Swiss Economic Institute, ETH Zurich.
    9. Ricci L. Reber & Sarah J. Pack, 2014. "Methods of Temporal Disaggregation for Estimating Output of the Insurance Industry," BEA Working Papers 0115, Bureau of Economic Analysis.

    More about this item

    JEL classification:

    • E60 - Macroeconomics and Monetary Economics - - Macroeconomic Policy, Macroeconomic Aspects of Public Finance, and General Outlook - - - General

    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:bea:papers:0077. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Bryn Whitmire). General contact details of provider: http://edirc.repec.org/data/beagvus.html .

    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 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.

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

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.