The Exact Finite-Sample Distribution of the Limited-Information Maximum Likelihood Estimator in the Case of Two Included Endogenous Variables
This article is concerned with the exact finite-sample distribution of the limited-information maximum likelihood estimator when the structural equation being estimated contains two endogenous variables and is identifiable in a complete system of linear stochastic equations. The density function der...
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Institutional Knowledge at Singapore Management University
1972
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sg-smu-ink.soe_research-11542010-09-23T05:48:03Z The Exact Finite-Sample Distribution of the Limited-Information Maximum Likelihood Estimator in the Case of Two Included Endogenous Variables Mariano, Roberto S. Sawa, Takamitsu This article is concerned with the exact finite-sample distribution of the limited-information maximum likelihood estimator when the structural equation being estimated contains two endogenous variables and is identifiable in a complete system of linear stochastic equations. The density function derived, which is represented as a doubly infinite series of a complicated form, reveals the important fact that For arbitrary values of the parameters in the model, the LIML estimator does not possess moments of order greater than or equal to one. 1972-01-01T08:00:00Z text https://ink.library.smu.edu.sg/soe_research/155 info:doi/10.1080/01621459.1972.10481219 Research Collection School Of Economics eng Institutional Knowledge at Singapore Management University Econometrics |
| institution |
Singapore Management University |
| building |
SMU Libraries |
| continent |
Asia |
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Singapore Singapore |
| content_provider |
SMU Libraries |
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InK@SMU |
| language |
English |
| topic |
Econometrics |
| spellingShingle |
Econometrics Mariano, Roberto S. Sawa, Takamitsu The Exact Finite-Sample Distribution of the Limited-Information Maximum Likelihood Estimator in the Case of Two Included Endogenous Variables |
| description |
This article is concerned with the exact finite-sample distribution of the limited-information maximum likelihood estimator when the structural equation being estimated contains two endogenous variables and is identifiable in a complete system of linear stochastic equations. The density function derived, which is represented as a doubly infinite series of a complicated form, reveals the important fact that For arbitrary values of the parameters in the model, the LIML estimator does not possess moments of order greater than or equal to one. |
| format |
text |
| author |
Mariano, Roberto S. Sawa, Takamitsu |
| author_facet |
Mariano, Roberto S. Sawa, Takamitsu |
| author_sort |
Mariano, Roberto S. |
| title |
The Exact Finite-Sample Distribution of the Limited-Information Maximum Likelihood Estimator in the Case of Two Included Endogenous Variables |
| title_short |
The Exact Finite-Sample Distribution of the Limited-Information Maximum Likelihood Estimator in the Case of Two Included Endogenous Variables |
| title_full |
The Exact Finite-Sample Distribution of the Limited-Information Maximum Likelihood Estimator in the Case of Two Included Endogenous Variables |
| title_fullStr |
The Exact Finite-Sample Distribution of the Limited-Information Maximum Likelihood Estimator in the Case of Two Included Endogenous Variables |
| title_full_unstemmed |
The Exact Finite-Sample Distribution of the Limited-Information Maximum Likelihood Estimator in the Case of Two Included Endogenous Variables |
| title_sort |
exact finite-sample distribution of the limited-information maximum likelihood estimator in the case of two included endogenous variables |
| publisher |
Institutional Knowledge at Singapore Management University |
| publishDate |
1972 |
| url |
https://ink.library.smu.edu.sg/soe_research/155 |
| _version_ |
1770569042037309440 |