Review of Economic Studies Vol. 50 No. 1 1983

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

Denis Conniffe

Economic and Social Research Institute

Abstract

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.

DOI

10.2307/2296958

Volume

50

Issue

1

Pages

111

Sources

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