A Numerical Comparison of Exact, Large-Sample and Small-Disturbance Appoximations of Properties of k-Class Estimators
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Publication:3893205
DOI10.2307/2526253zbMath0447.62109OpenAlexW1976738967MaRDI QIDQ3893205
No author found.
Publication date: 1980
Published in: International Economic Review (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.2307/2526253
mean squared errornumerical comparisonexact biaslarge-samplek- class estimatorssimultaneous linear stochastic equation modelsmall-disturbance approximations
Applications of statistics to economics (62P20) Probabilistic methods, stochastic differential equations (65C99)
Related Items (8)
Moments of the ratio of quadratic forms in non-normal variables with econometric examples ⋮ Adaptive k-class estimation in high-dimensional linear models ⋮ Moments of the function of non-normal random vector with applications to econometric estimators and test statistics1 ⋮ The sampling distribution of shrinkage estimators and their F-ratios in the regression model ⋮ Exact finite sample properties of double k-class estimators in simultaneous equations ⋮ Uses of entropy and divergence measures for evaluating econometric approximations and infer\-ence. ⋮ Confidence sets centered at James-Stein estimators. A surprise concerning the unknown-variance case ⋮ A note on the double \(k\)-class estimator in simultaneous equations.
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