IDEAS home Printed from https://ideas.repec.org/a/ier/iecrev/v50y2009i2p627-675.html
   My bibliography  Save this article

Simulated Maximum Likelihood Estimation Based On First-Order Conditions

Author

Listed:
  • Michael P. Keane

Abstract

I describe a strategy for structural estimation that uses simulated maximum likelihood (SML) to estimate the structural parameters appearing in a model's first-order conditions (FOCs). Generalized method of moments (GMM) is often the preferred method for estimation of FOCs, as it avoids distributional assumptions on stochastic terms, "provided" all structural errors enter the FOCs additively, giving a single composite additive error. But SML has advantages over GMM in models where multiple structural errors enter the FOCs nonadditively. I develop new simulation algorithms required to implement SML based on FOCs, and I illustrate the method using a model of U.S. multinational corporations. Copyright © (2009) by the Economics Department of the University of Pennsylvania and the Osaka University Institute of Social and Economic Research Association.

Suggested Citation

  • Michael P. Keane, 2009. "Simulated Maximum Likelihood Estimation Based On First-Order Conditions," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 50(2), pages 627-675, May.
    • Handle: RePEc:ier:iecrev:v:50:y:2009:i:2:p:627-675
    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.

    Citations

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


    Cited by:

    1. Ledic, Marko, 2012. "Estimating Labor Supply at the Extensive Margin in the presence of Sample Selection Bias," MPRA Paper 55745, University Library of Munich, Germany.
    2. repec:hal:journl:hal-04665916 is not listed on IDEAS
    3. CARPENTIER, Alain & GOHIN, Alexandre & SCKOKAI, Paolo & THOMAS, Alban, 2015. "Economic modelling of agricultural production: past advances and new challenges," Review of Agricultural and Environmental Studies - Revue d'Etudes en Agriculture et Environnement (RAEStud), Institut National de la Recherche Agronomique (INRA), vol. 96(1), March.
    4. Koutchad, P. & Carpentier, A. & Femenia, F., 2018. "Dealing with corner solutions in multi-crop micro-econometric models: an endogenous regime approach with regime fixed costs," 2018 Conference, July 28-August 2, 2018, Vancouver, British Columbia 277530, International Association of Agricultural Economists.
    5. Michael P. Keane, 2011. "Labor Supply and Taxes: A Survey," Journal of Economic Literature, American Economic Association, vol. 49(4), pages 961-1075, December.
    6. Koutchadé, Philippe & Carpentier, Alain & Féménia, Fabienne, 2015. "Empirical modelling of production decisions of heterogeneous farmers with mixed models," 2015 AAEA & WAEA Joint Annual Meeting, July 26-28, San Francisco, California 205098, Agricultural and Applied Economics Association.
    7. Koutchade, Philippe & Carpentier, Alain & Femenia, Fabienne, 2015. "Accounting for unobserved heterogeneity in micro-econometric agricultural production models: a random parameter approach," 2015 Conference, August 9-14, 2015, Milan, Italy 212015, International Association of Agricultural Economists.
    8. Koutchade, Philippe & Carpentier, Alain & Féménia, Fabienne, 2015. "Empirical modeling of production decisions of heterogeneous farmers with random parameter models," Working Papers 210097, Institut National de la recherche Agronomique (INRA), Departement Sciences Sociales, Agriculture et Alimentation, Espace et Environnement (SAE2).
    9. Hall, George & Rust, John, 2021. "Estimation of endogenously sampled time series: The case of commodity price speculation in the steel market," Journal of Econometrics, Elsevier, vol. 222(1), pages 219-243.
    10. Obafèmi P. Koutchadé & Alain Carpentier & Fabienne Femenia, 2021. "Modeling Corners, Kinks, and Jumps in Crop Acreage Choices: Impacts of the EU Support to Protein Crops," American Journal of Agricultural Economics, John Wiley & Sons, vol. 103(4), pages 1502-1524, August.

    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:ier:iecrev:v:50:y:2009:i:2:p:627-675. 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: Wiley-Blackwell Digital Licensing or the person in charge (email available below). General contact details of provider: https://edirc.repec.org/data/deupaus.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.