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Set Identified Linear Models

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  • Christian Bontemps
  • Thierry Magnac
  • Eric Maurin

Abstract

We analyze the identification and estimation of parameters β satisfying the incomplete linear moment restrictions E(z T (x β−y)) = E(z Tu(z)) where z is a set of instruments and u(z) an unknown bounded scalar function. We first provide empirically relevant examples of such a set-up. Second, we show that these conditions set identify β where the identified set B is bounded and convex. We provide a sharp characterization of the identified set not only when the number of moment conditions is equal to the number of parameters of interest but also in the case in which the number of conditions is strictly larger than the number of parameters. We derive a necessary and sufficient condition of the validity of supernumerary restrictions which generalizes the familiar Sargan condition. Third, we provide new results on the asymptotics of analog estimates constructed from the identification results. When B is a strictly convex set, we also construct a test of the null hypothesis, β 0 ε B, whose size is asymptotically correct and which relies on the minimization of the support function of the set B − { β 0 }. Results of some Monte Carlo experiments are presented.

(This abstract was borrowed from another version of this item.)

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Bibliographic Info

Article provided by Econometric Society in its journal Econometrica.

Volume (Year): 80 (2012)
Issue (Month): 3 (05)
Pages: 1129-1155

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Handle: RePEc:ecm:emetrp:v:80:y:2012:i:3:p:1129-1155

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References

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Citations

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Cited by:
  1. Donald W.K. Andrews & Xiaoxia Shi, 2010. "Inference Based on Conditional Moment Inequalities," Cowles Foundation Discussion Papers 1761, Cowles Foundation for Research in Economics, Yale University.
  2. Hoshino, Tadao, 2013. "Partial identification in binary response models with nonignorable nonresponses," Economics Letters, Elsevier, vol. 121(1), pages 74-78.
  3. David Pacini, 2012. "Least Square Linear Prediction with Two-Sample Data," Bristol Economics Discussion Papers 12/631, Department of Economics, University of Bristol, UK.
  4. Magnac, Thierry, 2014. "Identification partielle: méthodes et conséquences pour les applications empiriques," IDEI Working Papers 814, Institut d'Économie Industrielle (IDEI), Toulouse.
  5. Laura Coroneo & Valentina Corradi & Paulo Santos Monteiro, 2013. "Testing for optimal monetary policy via moment inequalities," Discussion Papers 13/07, Department of Economics, University of York.
  6. Donald W.K. Andrews & Panle Jia, 2008. "Inference for Parameters Defined by Moment Inequalities: A Recommended Moment Selection Procedure," Cowles Foundation Discussion Papers 1676R, Cowles Foundation for Research in Economics, Yale University, revised Aug 2011.
  7. Daniel Cerquera & François Laisney & Hannes Ullrich, 2012. "Considerations on partially identified regression models," Working Papers of BETA 2012-07, Bureau d'Economie Théorique et Appliquée, UDS, Strasbourg.
  8. Arun Chandrasekhar & Victor Chernozhukov & Francesca Molinari & Paul Schrimpf, 2012. "Inference for best linear approximations to set identified functions," CeMMAP working papers CWP43/12, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
  9. Aviv Nevo & Adam M. Rosen, 2012. "Identification With Imperfect Instruments," The Review of Economics and Statistics, MIT Press, vol. 94(3), pages 659-671, August.
  10. Melanie Arntz & Simon Lo & Ralf Wilke, 2014. "Bounds analysis of competing risks: a non-parametric evaluation of the effect of unemployment benefits on migration," Empirical Economics, Springer, vol. 46(1), pages 199-228, February.
  11. Adam Rosen, 2006. "Confidence sets for partially identified parameters that satisfy a finite number of moment inequalities," CeMMAP working papers CWP25/06, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
  12. Liao, Yuan & Simoni, Anna, 2012. "Semi-parametric Bayesian Partially Identified Models based on Support Function," MPRA Paper 43262, University Library of Munich, Germany.

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