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Higher Order Properties of the Symmetricallr Normalized Instrumental Variable Estimator

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  • Rodrigo Alfaro

Abstract

This paper provides the second order bias for the Symmetrically Normalized Instrumental Variable Estimator (SNIV), using Edgeworth expansions for both the estimator and the minimum eigenvalue. SNIV was proposed by Alonso-Borrego and Arellano (1999) as an alternative for the Limited Information Maximum Likelihood Estimator (LIML), based solely on simulations. The paper shows that second order biases of SNIV and 2SLS are similar meanwhile LIML is second order unbiased. Previous results can be obtained in a specific design: small number of strong instruments, where biases of 2SLS, SNIV, and LIML are zero.

Suggested Citation

  • Rodrigo Alfaro, 2008. "Higher Order Properties of the Symmetricallr Normalized Instrumental Variable Estimator," Working Papers Central Bank of Chile 500, Central Bank of Chile.
  • Handle: RePEc:chb:bcchwp:500
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    References listed on IDEAS

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    1. Mariano, Roberto S, 1982. "Analytical Small-Sample Distribution Theory in Econometrics: The Simultaneous-Equations Case," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 23(3), pages 503-533, October.
    2. Phillips, Peter C B, 1985. "The Exact Distribution of LIML: II," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 26(1), pages 21-36, February.
    3. Ullah, Aman, 2004. "Finite Sample Econometrics," OUP Catalogue, Oxford University Press, number 9780198774488.
    4. Alonso-Borrego, Cesar & Arellano, Manuel, 1999. "Symmetrically Normalized Instrumental-Variable Estimation Using Panel Data," Journal of Business & Economic Statistics, American Statistical Association, vol. 17(1), pages 36-49, January.
    5. Hillier, Grant H, 1990. "On the Normalization of Structural Equations: Properties of Direct Estimators," Econometrica, Econometric Society, vol. 58(5), pages 1181-1194, September.
    6. Donald, Stephen G & Newey, Whitney K, 2001. "Choosing the Number of Instruments," Econometrica, Econometric Society, vol. 69(5), pages 1161-1191, September.
    7. Davidson, Russell & MacKinnon, James G., 1993. "Estimation and Inference in Econometrics," OUP Catalogue, Oxford University Press, number 9780195060119.
    8. Bekker, Paul A, 1994. "Alternative Approximations to the Distributions of Instrumental Variable Estimators," Econometrica, Econometric Society, vol. 62(3), pages 657-681, May.
    9. Douglas Staiger & James H. Stock, 1997. "Instrumental Variables Regression with Weak Instruments," Econometrica, Econometric Society, vol. 65(3), pages 557-586, May.
    10. Jinyong Hahn & Jerry Hausman & Guido Kuersteiner, 2004. "Estimation with weak instruments: Accuracy of higher-order bias and MSE approximations," Econometrics Journal, Royal Economic Society, vol. 7(1), pages 272-306, June.
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