IDEAS home Printed from https://ideas.repec.org/a/cii/cepiie/2020-q1-161-14.html

Constrained Poisson pseudo maximum likelihood estimation of structural gravity models

Author

Listed:
  • Michael Pfaffermayr

Abstract

This paper reconsiders the estimation of structural gravity models. It introduces a constrained, projection-based Poisson pseudo maximum likelihood estimation procedure (constrained PPML) that exploits the equilibrium conditions introduced by Anderson and Van Wincoop (2003) for estimation and inference. The constrained PPML estimator avoids the estimation of the large number of exporter and importer fixed effects, and provides more reliable inference than the unconstrained PPML estimator. Moreover, based on the delta method the paper drives confidence intervals of counterfactual changes. Monte Carlo simulations yield encouraging results on the performance of the constrained PPML estimator.

Suggested Citation

  • Michael Pfaffermayr, 2020. "Constrained Poisson pseudo maximum likelihood estimation of structural gravity models," International Economics, CEPII research center, issue 161, pages 188-198.
    • Handle: RePEc:cii:cepiie:2020-q1-161-14
    as

    Download full text from publisher

    File URL: https://www.sciencedirect.com/science/article/pii/S2110701719301842
    Download Restriction: no
    ---><---

    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. Harald Oberhofer & Zhenyi Wang, 2025. "Everything You Always Wanted to Know About EU Membership Trade Effects But Were Afraid to Ask," CESifo Working Paper Series 11823, CESifo.
    2. Alessio Baldassarre & Danilo Carullo & Paolo Caro & Elisa Fusco & Pasquale Giacobbe & Carlo Orecchia, 2025. "A New Approach to Measure Italian Regional Trade Flows with Administrative Micro Firm-Level Data," Italian Economic Journal: A Continuation of Rivista Italiana degli Economisti and Giornale degli Economisti, Springer;Società Italiana degli Economisti (Italian Economic Association), vol. 11(1), pages 65-101, March.
    3. Michael Pfaffermayr, 2020. "Trade creation and trade diversion of economic integration agreements revisited: a constrained panel pseudo-maximum likelihood approach," Review of World Economics (Weltwirtschaftliches Archiv), Springer;Institut für Weltwirtschaft (Kiel Institute for the World Economy), vol. 156(4), pages 985-1024, November.
    4. Harald Oberhofer & Michael Pfaffermayr, 2021. "Estimating the trade and welfare effects of Brexit: A panel data structural gravity model," Canadian Journal of Economics/Revue canadienne d'économique, John Wiley & Sons, vol. 54(1), pages 338-375, February.
    5. Harald Oberhofer & Michael Pfaffermayr & Richard Sellner, 2021. "Revisiting time as a trade barrier: Evidence from a panel structural gravity model," Review of International Economics, Wiley Blackwell, vol. 29(5), pages 1382-1417, November.
    6. Pfaffermayr, Michael, 2021. "Confidence intervals for the trade cost parameters of cross-section gravity models," Economics Letters, Elsevier, vol. 201(C).
    7. Julia Spornberger, 2022. "EU integration and structural gravity: A comprehensive quantification of the border effect on trade," Review of International Economics, Wiley Blackwell, vol. 30(4), pages 915-938, September.
    8. Harald Oberhofer & Michael Pfaffermayr & Yvonne Wolfmayr, 2021. "Die Auswirkungen des Brexit auf Österreichs Wirtschaft," WIFO Studies, WIFO, number 66782.
    9. Yoto V. Yotov, 2024. "The evolution of structural gravity: The workhorse model of trade," Contemporary Economic Policy, Western Economic Association International, vol. 42(4), pages 578-603, October.

    More about this item

    Keywords

    ;
    ;

    JEL classification:

    • F10 - International Economics - - Trade - - - General
    • F15 - International Economics - - Trade - - - Economic Integration
    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C50 - Mathematical and Quantitative Methods - - Econometric Modeling - - - 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:cii:cepiie:2020-q1-161-14. 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: the person in charge (email available below). General contact details of provider: https://edirc.repec.org/data/cepiifr.html .

    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.