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Sargan's Instrumental Variables Estimation and the Generalized Method of Moments

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  • Arellano, Manuel

Abstract

This article surveys J. D. Sargan's work on instrumental variables (IV) estimation and its connections with the generalized method of moments (GMM). First the modeling context in which Sargan motivated IV estimation is presented. Then the theory of IV estimation as developed by Sargan is discussed. His approach to efficiency, his minimax estimator, tests of overidentification and underidentification, and his later work on the finite-sample properties of IV estimators are reviewed. Next, his approach to modeling IV equations with serial correlation is discussed and compared with the GMM approach. Finally, Sargan's results for nonlinear-in-parameters IV models are described.

Suggested Citation

  • Arellano, Manuel, 2002. "Sargan's Instrumental Variables Estimation and the Generalized Method of Moments," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(4), pages 450-459, October.
  • Handle: RePEc:bes:jnlbes:v:20:y:2002:i:4:p:450-59
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    Cited by:

    1. Hansen, Lars Peter, 2013. "Uncertainty Outside and Inside Economic Models," Nobel Prize in Economics documents 2013-7, Nobel Prize Committee.
    2. Peñaranda, Francisco & Sentana, Enrique, 2012. "Spanning tests in return and stochastic discount factor mean–variance frontiers: A unifying approach," Journal of Econometrics, Elsevier, vol. 170(2), pages 303-324.
    3. Saona, Paolo, 2016. "Intra- and extra-bank determinants of Latin American Banks' profitability," International Review of Economics & Finance, Elsevier, vol. 45(C), pages 197-214.
    4. Brissimis, Sophocles N. & Bechlioulis, Alexandros P., 2017. "The link between consumption and leisure under Cobb-Douglas preferences:Some new evidence," MPRA Paper 80877, University Library of Munich, Germany.
    5. Joshua D. Angrist, 2004. "Treatment effect heterogeneity in theory and practice," Economic Journal, Royal Economic Society, vol. 114(494), pages 52-83, March.
    6. Hunter, John & Wu, Feng, 2014. "Multifactor consumption based asset pricing models using the US stock market as a reference: Evidence from a panel of developed economies," Economic Modelling, Elsevier, vol. 36(C), pages 557-565.
    7. Imbens, Guido W., 2014. "Instrumental Variables: An Econometrician's Perspective," IZA Discussion Papers 8048, Institute for the Study of Labor (IZA).
    8. Juan Mora-Sanguinetti, 2012. "Is judicial inefficacy increasing the weight of the house property market in Spain? Evidence at the local level," SERIEs: Journal of the Spanish Economic Association, Springer;Spanish Economic Association, vol. 3(3), pages 339-365, September.
    9. Arellano, Manuel, 2016. "Modelling optimal instrumental variables for dynamic panel data models," Research in Economics, Elsevier, vol. 70(2), pages 238-261.
    10. Jan F. Kiviet & Qu Feng, 2014. "Efficiency Gains by Modifying GMM Estimation in Linear Models under Heteroskedasticity," UvA-Econometrics Working Papers 14-06, Universiteit van Amsterdam, Dept. of Econometrics.
    11. Andreas Kyriacou & Oriol Roca sagalés, 2009. "Fiscal descentralization and the quality of government: evidence from panel data," Hacienda Pública Española, IEF, vol. 189(2), pages 131-155, June.
    12. repec:spr:rvmgts:v:12:y:2018:i:1:d:10.1007_s11846-016-0213-0 is not listed on IDEAS

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