Synapse
⌘+K
Synapse
PulseExploreClubsResearchersJournals
Instagram
HomeClubsExplore
December 1, 1960Journal of the American Statistical Association

On Finite Sample Distributions of Generalized Classical Linear Identifiability Test Statistics

View Full Paper
Ask AI
Bookmark
Share

Authors

RBR. L. BasmannUniversity of North Texas

Discussion

Loading...

Member takes

Implication

Randomized trial examines finite sample distributions of identifiability test statistics in econometric models, indicating optimal estimation conditions.

Key Points

  • The aim is to explore conditions under which the finite sample distribution of identifiability test statistics can be approximated.
  • Analyzed conditions for identifiability in econometric simultaneous equations models.
  • Evaluated the role of exclusion restrictions and exogenous variables.
  • Utilized Snedecor's F distribution for approximation under certain assumptions.
  • Identifiability test statistic distribution is closely approximated by Snedecor's F under specific conditions.
  • Results hold when excluded variables are exogenous and disturbances are jointly normally distributed.

Cite This Study

R. L. Basmann (1960) studied this question.

synapsesocial.com/papers/6a10e42d8102eb4b66eea07fhttps://doi.org/10.2307/2281588
View Full Paper
Ask AI
Bookmark
Share

Also Consider

Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context:

  1. 1Estimation of the Parameters of a Single Equation in a Complete System of Stochastic Equations1949 · 1,606 citations
  2. 2Finite‐Sample Identification‐Robust Inference for Nonlinear DSGE Models2025 · 2 citations
  3. 3Database for Identifiability Properties of Linear Compartmental Models2026
  4. 4A simple specification test for models with many conditional moment inequalities2024 · 2 citations
  5. 5Overidentification in Shift-Share Designs2024