IDEAS home Printed from https://ideas.repec.org/a/eee/ecolet/v44y1994i3p221-228.html

Periodic properties of interpolated time series

Author

Listed:
  • Dezhbakhsh, Hashem
  • Levy, Daniel

Abstract

Although linearly interpolated series are often used in economics, little has been done to examine the effects of interpolation on time series properties and on statistical inference. We show that linear interpolation of a trend stationary series superimposes a 'periodic' structure on the moments of the series. Using conventional time series methods to make inference about the interpolated series may therefore be invalid. Also, the interpolated series may exhibit more shock persistence than the original trend stationary series.
(This abstract was borrowed from another version of this item.)

Suggested Citation

  • Dezhbakhsh, Hashem & Levy, Daniel, 1994. "Periodic properties of interpolated time series," Economics Letters, Elsevier, vol. 44(3), pages 221-228.
    • Handle: RePEc:eee:ecolet:v:44:y:1994:i:3:p:221-228
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/0165-1765(93)00378-2
    Download Restriction: Full text for ScienceDirect subscribers only
    ---><---

    As the access to this document is restricted, you may want to look for a different version below or

    for a different version of it.

    Other versions of this item:

    Citations

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


    Cited by:

    1. Franses, Philip Hans, 2013. "Data revisions and periodic properties of macroeconomic data," Economics Letters, Elsevier, vol. 120(2), pages 139-141.
    2. Olivier Darné & Amélie Charles, 2012. "A note on the uncertain trend in US real GNP: Evidence from robust unit root tests," Economics Bulletin, AccessEcon, vol. 32(3), pages 2399-2406.
    3. Daniel Levy, 2000. "Investment-Saving Comovement and Capital Mobility: Evidence from Century Long U.S. Time Series," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 3(1), pages 100-137, January.
    4. Young, Andrew T. & Higgins, Matthew J. & Levy, Daniel, 2013. "Heterogeneous Convergence," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 120(2), pages 238-241.
    5. Karger, Ezra & Wray, Anthony, 2024. "The Black–white lifetime earnings gap," Explorations in Economic History, Elsevier, vol. 94(C).
    6. Daniel Levy & Haiwei Chen, 1994. "Estimates Of The Aggregate Quarterly Capital Stock For The Post‐War U.S. Economy," Review of Income and Wealth, International Association for Research in Income and Wealth, vol. 40(3), pages 317-349, September.
    7. Dezhbakhsh, Hashem & Levy, Daniel, 2022. "Interpolation and shock persistence of prewar U.S. macroeconomic time series: A reconsideration," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 213.
    8. Matthew Higgins & Daniel Levy & Andrew T. Young, 2003. "Growth and Convergence across the US: Evidence from County-Level Data," Working Papers 2003-03, Bar-Ilan University, Department of Economics.
    9. Matthew J. Higgins & Donald J. Lacombe & Briana S. Stenard & Andrew T. Young, 2021. "Evaluating the effects of Small Business Administration lending on growth," Small Business Economics, Springer, vol. 57(1), pages 23-45, June.
    10. Michael Ehrmann, 2000. "Comparing monetary policy transmission across European countries," Review of World Economics (Weltwirtschaftliches Archiv), Springer;Institut für Weltwirtschaft (Kiel Institute for the World Economy), vol. 136(1), pages 58-83, March.
    11. Giuseppe Orlando & Giovanna Zimatore, 2021. "Recurrence Quantification Analysis of Business Cycles," Dynamic Modeling and Econometrics in Economics and Finance, in: Giuseppe Orlando & Alexander N. Pisarchik & Ruedi Stoop (ed.), Nonlinearities in Economics, chapter 0, pages 269-282, Springer.

    More about this item

    JEL classification:

    • C10 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - 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:eee:ecolet:v:44:y:1994:i:3:p:221-228. 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.

    We have no bibliographic 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.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/ecolet .

    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.