The Exact Distribution of LIML: I
It is shown that the exact finite sample distribution of the limited information maximum likelihood (LIML) estimator in a general and leading single equation case is multivariate Cauchy. When the LIML estimator utilizes a known error covariance matrix (LIMLK) it is proved that the same Cauchy distribution still applies. The corresponding result for the instrumental variable (IV) estimator is a form of multivariate t density where the degrees of freedom depend on the number of instruments.
|Date of creation:||Dec 1982|
|Date of revision:|
|Publication status:||Published in International Economic Review (February 1984), 25(1): 249-261|
|Note:||Extended version of CFDP 626. CFP 589.|
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- Naoto Kunitomo, 1981. "On A Third Order Optimum Property of The LIML Estimator When the Sample Size is Large," Discussion Papers 502, Northwestern University, Center for Mathematical Studies in Economics and Management Science.
- Kelejian, Harry H, 1974. "Random Parameters in a Simultaneous Equation Framework: Identification and Estimation," Econometrica, Econometric Society, vol. 42(3), pages 517-27, May.
- Mariano, Roberto S, 1977. "Finite Sample Properties of Instrumental Variable Estimators of Structural Coefficients," Econometrica, Econometric Society, vol. 45(2), pages 487-96, March.
- P. C. B. Phillips, 1980. "Finite Sample Theory and the Distributions of Alternative Estimators of the Marginal Propensity to Consume," Review of Economic Studies, Oxford University Press, vol. 47(1), pages 183-224.
- Fuller, Wayne A, 1977. "Some Properties of a Modification of the Limited Information Estimator," Econometrica, Econometric Society, vol. 45(4), pages 939-53, May.
- Wegge, Leon L, 1971. "The Finite Sampling Distribution of Least Squares Estimators with Stochastic Regressors," Econometrica, Econometric Society, vol. 39(2), pages 241-51, March.
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