IDEAS home Printed from https://ideas.repec.org/a/jof/jforec/v20y2001i6p441-49.html
   My bibliography  Save this article

Creating High-Frequency National Accounts with State-Space Modelling: A Monte Carlo Experiment

Author

Listed:
  • Liu, H
  • Hall, Stephen G

Abstract

This paper assesses a new technique for producing high-frequency data from lower frequency measurements subject to the full set of identities within the data all holding. The technique is assessed through a set of Monte Carlo experiments. The example used here is gross domestic product (GDP) which is observed at quarterly intervals in the United States and it is a flow economic variable rather than a stock. The problem of constructing an unobserved monthly GDP variable can be handled using state space modelling. The solution of the problem lies in finding a suitable state space representation. A Monte Carlo experiment is conducted to illustrate this concept and to identify which variant of the model gives the best monthly estimates. The results demonstrate that the more simple models do almost as well as more complex ones and hence there may be little gain in return for the extra work of using a complex model. Copyright © 2001 by John Wiley & Sons, Ltd.

Suggested Citation

  • Liu, H & Hall, Stephen G, 2001. "Creating High-Frequency National Accounts with State-Space Modelling: A Monte Carlo Experiment," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 20(6), pages 441-449, September.
  • Handle: RePEc:jof:jforec:v:20:y:2001:i:6:p:441-49
    as

    Download full text from publisher

    To our knowledge, this item is not available for download. To find whether it is available, there are three options:
    1. Check below whether another version of this item is available online.
    2. Check on the provider's web page whether it is in fact available.
    3. Perform a search for a similarly titled item that would be available.

    References listed on IDEAS

    as
    1. Henriksson, Roy D & Merton, Robert C, 1981. "On Market Timing and Investment Performance. II. Statistical Procedures for Evaluating Forecasting Skills," The Journal of Business, University of Chicago Press, vol. 54(4), pages 513-533, October.
    2. John Y. Campbell, 1995. "Some Lessons from the Yield Curve," Journal of Economic Perspectives, American Economic Association, vol. 9(3), pages 129-152, Summer.
    3. Wallace, Myles S & Warner, John T, 1996. "Do Excess Holding-Period Returns Depend on the Composition of Outstanding Federal Debt?," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 28(1), pages 132-139, February.
    4. Franco Modigliani & Richard Sutch, 1967. "Debt Management and the Term Structure of Interest Rates: An Empirical Analysis of Recent Experience," Journal of Political Economy, University of Chicago Press, vol. 75, pages 569-569.
    5. Campbell, John Y., 1987. "Stock returns and the term structure," Journal of Financial Economics, Elsevier, vol. 18(2), pages 373-399, June.
    6. Friedman, Benjamin M, 1979. "Substitution and Expectation Effects on Long-Term Borrowing Behavior and Long-Term Interest Rates," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 11(2), pages 131-150, May.
    7. Robert J. Shiller & John Y. Campbell & Kermit L. Schoenholtz, 1983. "Forward Rates and Future Policy: Interpreting the Term Structure of Interest Rates," Brookings Papers on Economic Activity, Economic Studies Program, The Brookings Institution, vol. 14(1), pages 173-224.
    8. Hall, Anthony D & Anderson, Heather M & Granger, Clive W J, 1992. "A Cointegration Analysis of Treasury Bill Yields," The Review of Economics and Statistics, MIT Press, vol. 74(1), pages 116-126, February.
    9. Friedman, Benjamin M & Kuttner, Kenneth N, 1992. "Time-Varying Risk Perceptions and the Pricing of Risky Assets," Oxford Economic Papers, Oxford University Press, vol. 44(4), pages 566-598, October.
    10. Hardouvelis, Gikas A., 1994. "The term structure spread and future changes in long and short rates in the G7 countries: Is there a puzzle?," Journal of Monetary Economics, Elsevier, vol. 33(2), pages 255-283, April.
    11. Jones, David S. & Vance Roley, V., 1983. "Rational expectations and the expectations model of the term structure : A test using weekly data," Journal of Monetary Economics, Elsevier, vol. 12(3), pages 453-465, September.
    12. Hamilton, James D., 1988. "Rational-expectations econometric analysis of changes in regime : An investigation of the term structure of interest rates," Journal of Economic Dynamics and Control, Elsevier, vol. 12(2-3), pages 385-423.
    13. V. Vance Roley, 1982. "The Effect of Federal Debt-Management Policy on Corporate Bond and Equity Yields," The Quarterly Journal of Economics, Oxford University Press, vol. 97(4), pages 645-668.
    14. Evans, Martin D. D. & Lewis, Karen K., 1994. "Do stationary risk premia explain it all?: Evidence from the term structure," Journal of Monetary Economics, Elsevier, vol. 33(2), pages 285-318, April.
    15. Granger, Clive W. J. & King, Maxwell L. & White, Halbert, 1995. "Comments on testing economic theories and the use of model selection criteria," Journal of Econometrics, Elsevier, vol. 67(1), pages 173-187, May.
    16. Swanson, Norman R & White, Halbert, 1995. "A Model-Selection Approach to Assessing the Information in the Term Structure Using Linear Models and Artificial Neural Networks," Journal of Business & Economic Statistics, American Statistical Association, vol. 13(3), pages 265-275, July.
    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. Mariano, Roberto S. & Ozmucur, Suleyman, 2015. "High-Mixed-Frequency Dynamic Latent Factor Forecasting Models for GDP in the Philippines/Modelos de factores dinámicos latentes con datos mixtos de alta frecuencia aplicados a la predicción del PIB en," Estudios de Economía Aplicada, Estudios de Economía Aplicada, vol. 33, pages 451-462, Mayo.
    2. Aruoba, S. BoraÄŸan & Diebold, Francis X. & Scotti, Chiara, 2009. "Real-Time Measurement of Business Conditions," Journal of Business & Economic Statistics, American Statistical Association, vol. 27(4), pages 417-427.
    3. Pedregal, Diego J. & Pérez, Javier J., 2010. "Should quarterly government finance statistics be used for fiscal surveillance in Europe?," International Journal of Forecasting, Elsevier, vol. 26(4), pages 794-807, October.
    4. Issler, João Victor & Notini, Hilton Hostalacio, 2016. "Estimating Brazilian Monthly GDP: a State-Space Approach," Revista Brasileira de Economia - RBE, FGV/EPGE - Escola Brasileira de Economia e Finanças, Getulio Vargas Foundation (Brazil), vol. 70(1), March.
    5. Nikolaus Hautsch & Fuyu Yang, 2014. "Bayesian Stochastic Search for the Best Predictors: Nowcasting GDP Growth," University of East Anglia Applied and Financial Economics Working Paper Series 056, School of Economics, University of East Anglia, Norwich, UK..
    6. S. Boragan Aruoba & Francis X. Diebold & Chiara Scotti, 2007. "Real-Time Measurement of Business Conditions, Second Version," PIER Working Paper Archive 08-011, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania, revised 04 Apr 2008.
    7. Namwon Hyung & Clive W.J. Granger, 2008. "Linking series generated at different frequencies This work is part of a PhD dissertation presented at the University of California, San Diego (1999)," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 27(2), pages 95-108.
    8. Roberto S. Mariano & Yasutomo Murasawa, 2004. "Constructing a Coincident Index of Business Cycles without Assuming a One-factor Model," Working Papers 22-2004, Singapore Management University, School of Economics, revised Oct 2004.
    9. Pedregal, D.J. & Dejuán, O. & Gómez, N. & Tobarra, M.A., 2009. "Modelling demand for crude oil products in Spain," Energy Policy, Elsevier, vol. 37(11), pages 4417-4427, November.
    10. Martin D. D. Evans, 2005. "Where Are We Now? Real-Time Estimates of the Macroeconomy," International Journal of Central Banking, International Journal of Central Banking, vol. 1(2), September.
    11. Castilla, Adolfo, 2015. "Proyecto LINK y Econometría de Alta Frecuencia: Las últimas aportaciones econométricas de Lawrence R. Klein /LINK Project and High Frequency Econometrics: Recent Econometric Contributions of Lawrence ," Estudios de Economía Aplicada, Estudios de Economía Aplicada, vol. 33, pages 421-450, Mayo.
    12. Byeongchan Seong & Sung K. Ahn & Peter Zadrozny, 2007. "Cointegration Analysis with Mixed-Frequency Data," CESifo Working Paper Series 1939, CESifo Group Munich.
    13. Diego J. Pedregal & Javier J. Pérez & Antonio Sánchez Fuentes, 2014. "A Tookit to strengthen Government," Hacienda Pública Española, IEF, vol. 211(4), pages 117-146, December.

    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:jof:jforec:v:20:y:2001:i:6:p:441-49. 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: (Wiley-Blackwell Digital Licensing) or (Christopher F. Baum). General contact details of provider: http://www3.interscience.wiley.com/cgi-bin/jhome/2966 .

    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.

    We have no references for this item. You can help adding them by using 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.