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Small-Sample Properties of Estimators of Regression Coefficients Given a Common Pattern of Missing Data

Denis Conniffe
Review of Economic Studies 1983 50(1), 111 open access
For a commonly occurring pattern of missing data, estimators of regression coefficients are derived by a non-likelihood method. The small-sample properties are investigated for the case of normality assumptions. The estimators are shown to be unbiased, exact small-sample variance formulae are derived, comparisons are made with ordinary least-squares estimators and it is demonstrated that the estimators can be more efficient than maximum-likelihood estimators in small samples.

Testing the Assumptions of Seemingly Unrelated Regressions

Denis Conniffe
The Review of Economics and Statistics 1982 64(1), 172
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