IDEAS home Printed from https://ideas.repec.org/p/nzb/nzbdps/2009-12.html
   My bibliography  Save this paper

A quarterly Post-World War II Real GDP Series for New Zealand

Author

Abstract

There are no official quarterly real GDP estimates for New Zealand, for the period prior to 1977. We report the development of a seasonally adjusted series for a period of more than 60 years from mid-1947, and evaluate statistical properties. The series were developed by linking quarterly observations from two recent official series to temporally disaggregated observations for an earlier time period. Annual real GDP series are disaggregated, using the information from two quarterly diffusion indexes, developed by Haywood and Campbell (1976). Three econometric models are used: the Chow and Lin (1971) model that disaggregates the level of GDP; and the Fern´andez (1981) and Litterman (1983) models that disaggregate changes in GDP. Our preferred quarterly series is based on results generated from the Chow-Lin model. We assess movements in the new series against qualitative findings from New Zealand’s post-WWII economic history.

Suggested Citation

  • John McDermott & Viv B. Hall, "undated". "A quarterly Post-World War II Real GDP Series for New Zealand," Reserve Bank of New Zealand Discussion Paper Series DP2009/12, Reserve Bank of New Zealand.
  • Handle: RePEc:nzb:nzbdps:2009/12
    as

    Download full text from publisher

    File URL: http://www.rbnz.govt.nz/-/media/ReserveBank/Files/Publications/Discussion%20papers/2009/dp09-12.pdf
    Download Restriction: no

    Other versions of this item:

    References listed on IDEAS

    as
    1. Stock, James H. & Watson, Mark W., 1999. "Business cycle fluctuations in us macroeconomic time series," Handbook of Macroeconomics,in: J. B. Taylor & M. Woodford (ed.), Handbook of Macroeconomics, edition 1, volume 1, chapter 1, pages 3-64 Elsevier.
    2. Hansen, Bruce E., 2000. "Testing for structural change in conditional models," Journal of Econometrics, Elsevier, vol. 97(1), pages 93-115, July.
    3. Andrews, Donald W K & Ploberger, Werner, 1994. "Optimal Tests When a Nuisance Parameter Is Present Only under the Alternative," Econometrica, Econometric Society, vol. 62(6), pages 1383-1414, November.
    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, July.
    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. 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.
    7. Andrews, Donald W K, 1993. "Tests for Parameter Instability and Structural Change with Unknown Change Point," Econometrica, Econometric Society, vol. 61(4), pages 821-856, July.
    8. 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.
    9. 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.
    10. Hall, Viv B. & McDermott, C. John, 2009. "The New Zealand Business Cycle," Econometric Theory, Cambridge University Press, vol. 25(04), pages 1050-1069, August.
    11. Hawke, G R, 1975. "Income Estimation from Monetary Data: Further Explorations," Review of Income and Wealth, International Association for Research in Income and Wealth, vol. 21(3), pages 301-307, September.
    12. Silver, J Lew, 1986. "Two Results Useful for Implementing Litterman's Procedure for Interpolating a Time Series [A Random Walk, Markov Model for the Distribution of Time Series]," Journal of Business & Economic Statistics, American Statistical Association, vol. 4(1), pages 129-130, January.
    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. Vosen, Simeon & Schmidt, Torsten, 2012. "A monthly consumption indicator for Germany based on Internet search query data," EconStor Open Access Articles, ZBW - German National Library of Economics, pages 683-687.

    More about this item

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C82 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Methodology for Collecting, Estimating, and Organizing Macroeconomic Data; Data Access
    • E01 - Macroeconomics and Monetary Economics - - General - - - Measurement and Data on National Income and Product Accounts and Wealth; Environmental Accounts
    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles

    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:nzb:nzbdps:2009/12. 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: (Reserve Bank of New Zealand Knowledge Centre). General contact details of provider: http://edirc.repec.org/data/rbngvnz.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.