IDEAS home Printed from https://ideas.repec.org/a/cup/etheor/v19y2003i03p457-480_19.html
   My bibliography  Save this article

J. Denis Sargan And The Origins Of Lse Econometric Methodology

Author

Listed:
  • Hendry, David F.

Abstract

I review the part played by John Denis Sargan in the formation of the “LSE approach” to dynamic econometric modeling. Despite his unassuming demeanor and his location at LSE—which had earlier dismissed a substantive role for econometric evidence—Sargan nevertheless radically altered the econometric approach of a generation, establishing a powerful approach to empirical modeling of economic time series. His main contributions to econometric methodology, and the subsequent research, are discussed as a complement to the other papers in this memorial volume.Financial support from the U.K. Economic and Social Research Council under grant L138251009 is gratefully acknowledged. I am indebted to Alok Bhargava, Julia Campos, Meghnad Desai, Neil Ericsson, Toni Espasa, Grayham Mizon, Peter Phillips, Timo Teräsvirta, and Ken Wallis for helpful comments and to Peter Phillips for the invitation to contribute this paper to Econometric Theory.

Suggested Citation

  • Hendry, David F., 2003. "J. Denis Sargan And The Origins Of Lse Econometric Methodology," Econometric Theory, Cambridge University Press, vol. 19(3), pages 457-480, June.
    • Handle: RePEc:cup:etheor:v:19:y:2003:i:03:p:457-480_19
    as

    Download full text from publisher

    File URL: https://www.cambridge.org/core/product/identifier/S0266466603193061/type/journal_article
    File Function: link to article abstract page
    Download Restriction: no
    ---><---

    Citations

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


    Cited by:

    1. Anya McGuirk & Aris Spanos, 2009. "Revisiting Error‐Autocorrelation Correction: Common Factor Restrictions and Granger Non‐Causality," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 71(2), pages 273-294, April.
    2. Duo Qin, 2010. "Modelling of the Inflation-Unemployment Tradeoff from the Perspective of the History of Econometrics," Working Papers 661, Queen Mary University of London, School of Economics and Finance.
    3. Aris Spanos, 2018. "Mis†Specification Testing In Retrospect," Journal of Economic Surveys, Wiley Blackwell, vol. 32(2), pages 541-577, April.
    4. Bauwens, Luc & Sucarrat, Genaro, 2010. "General-to-specific modelling of exchange rate volatility: A forecast evaluation," International Journal of Forecasting, Elsevier, vol. 26(4), pages 885-907, October.
    5. Qin, Duo, 2015. "Resurgence of the endogeneity-backed instrumental variable methods," Economics - The Open-Access, Open-Assessment E-Journal (2007-2020), Kiel Institute for the World Economy (IfW Kiel), vol. 9, pages 1-35.
    6. James Reade & Genaro Sucarrat, 2016. "General-to-Specific (GETS) Modelling And Indicator Saturation With The R Package Gets," Economics Series Working Papers 794, University of Oxford, Department of Economics.
    7. David F. Hendry, 2024. "A Brief History of General‐to‐specific Modelling," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 86(1), pages 1-20, February.
    8. Castle, Jennifer L. & Hendry, David F., 2009. "The long-run determinants of UK wages, 1860-2004," Journal of Macroeconomics, Elsevier, vol. 31(1), pages 5-28, March.
    9. Phillips, Peter C.B., 2003. "Vision And Influence In Econometrics: John Denis Sargan," Econometric Theory, Cambridge University Press, vol. 19(3), pages 495-511, June.
    10. Genaro Sucarrat, 2010. "Econometric reduction theory and philosophy," Journal of Economic Methodology, Taylor & Francis Journals, vol. 17(1), pages 53-75.
    11. Rahmanov, Ramiz, 2014. "A Historical Sketch of Macroeconometrics," MPRA Paper 56869, University Library of Munich, Germany.
    12. Spanos, Aris, 2008. "The 'Pre-Eminence of Theory' versus the 'General-to-Specific' Cointegrated VAR Perspectives in Macro-Econometric Modeling," Economics Discussion Papers 2008-25, Kiel Institute for the World Economy (IfW Kiel).
    13. Hoang‐Phuong Do & Aris Spanos, 2024. "Revisiting the Phillips Curve: The Empirical Relationship Yet to be Validated," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 86(4), pages 761-793, August.
    14. David F. Hendry, 2020. "A Short History of Macro-econometric Modelling," Economics Papers 2020-W01, Economics Group, Nuffield College, University of Oxford.
    15. Duo Qin & Yanqun Zhang, 2013. "A History of Polyvalent Structural Parameters: the Case of Instrument Variable Estimators," Working Papers 183, Department of Economics, SOAS University of London, UK.
    16. David F. Hendry & Peter C.B. Phillips, 2017. "John Denis Sargan at the London School of Economics," Cowles Foundation Discussion Papers 2082, Cowles Foundation for Research in Economics, Yale University.
    17. Jennifer L. Castle & David F. Hendry, 2024. "What a Puzzle! Unravelling Why UK Phillips Curves were Unstable," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 86(4), pages 743-760, August.
    18. Dalano DaSouza & Mahalia Jackman, 2024. "Estimating the Impact of Education on Growth in a Small Data-Poor Country: the Case of Saint Vincent and the Grenadines," Journal of the Knowledge Economy, Springer;Portland International Center for Management of Engineering and Technology (PICMET), vol. 15(3), pages 13449-13469, September.
    19. Qin, Duo, 2014. "Resurgence of instrument variable estimation and fallacy of endogeneity," Economics Discussion Papers 2014-42, Kiel Institute for the World Economy (IfW Kiel).

    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:cup:etheor:v:19:y:2003:i:03:p:457-480_19. 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: Kirk Stebbing (email available below). General contact details of provider: https://www.cambridge.org/ect .

    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.