Abstract
Abstract In the estimation of econometric simultaneous equations models, hypothesized necessary conditions for the identifiability of a single equation usually specify the exclusion of a number of variables from the structural equation in question. If the pre-determined variables are completely exogenous, if the disturbances in the equations are jointly normally distributed, and if a moderately high degree of precision can be obtained in reduced-form estimation, then the exact finite sample distribution of the generalized classical linear identifiability test statistic can be closely approximated by Snedecor's F with appropriate degrees of freedom.
Keywords
IdentifiabilityMathematicsApplied mathematicsDegrees of freedom (physics and chemistry)Test statisticStatisticStatisticsSampling distributionSample (material)Statistical hypothesis testing
Affiliated Institutions
Related Publications
On Finite Sample Distributions of Generalized Classical Linear Identifiability Test Statistics
Abstract In the estimation of econometric simultaneous equations models, hypothesized necessary conditions for the identifiability of a single equation usually specify the exclu...
Consistent Partial Least Squares for Nonlinear Structural Equation Models
Partial Least Squares as applied to models with latent variables, measured indirectly by indicators, is well-known to be inconsistent. The linear compounds of indicators that PL...
Correcting a Significance Test for Clustering
A common mistake in analysis of cluster randomized trials is to ignore the effect of clustering and analyze the data as if each treatment group were a simple random sample. This...
An Introduction to Multivariate Statistical Analysis
Preface to the Third Edition.Preface to the Second Edition.Preface to the First Edition.1. Introduction.2. The Multivariate Normal Distribution.3. Estimation of the Mean Vector ...
Bootstrap Methods in Econometrics: Theory and Numerical Performance
The bootstrap is a method for estimating the distribution of an estimator or test statistic by resampling one's data. It amounts to treating the data as if they were the populat...
Publication Info
- Year
- 1960
- Type
- article
- Volume
- 55
- Issue
- 292
- Pages
- 650-650
- Citations
- 89
- Access
- Closed
External Links
Social Impact
Altmetric
PlumX Metrics
Social media, news, blog, policy document mentions
Citation Metrics
89
OpenAlex
Cite This
R. L. Basmann
(1960).
On Finite Sample Distributions of Generalized Classical Linear Identifiability Test Statistics.
Journal of the American Statistical Association
, 55
(292)
, 650-650.
https://doi.org/10.2307/2281588
Identifiers
- DOI
- 10.2307/2281588