Estimation of Regression Models with Equi-correlated Responses when some Observations on the Response Variable are Missing

The present article deals with the problem of estimation of
parameters in a linear regression model when some data on response
variable is missing and the responses are equicorrelated. The
ordinary least squares and optimal homogeneous predictors are
employed to find the imputed values of missing observations. Their
efficiency properties are analyzed using the small disturbances
asymptotic theory. The estimation of regression coefficients using
these imputed values is also considered and a comparison of
estimators is presented.