ON THE USE OF SAMPLING WEIGHTS WHEN ESTIMATING REGRESSION-MODELS WITHSURVEY DATA

In this paper it is argued that when the population regression coeffic ient is of interest, the use of sampling weights can be desirable in r egression models with complex survey data. A two-step ML estimator is proposed as an alternative to OLS and weighted least squares. Specific ation tests are given. The ML estimator does well in simulations, incl uding several cases where it is based on a misspecified model. The spe cification tests are effective in selecting the best estimator. As an example, the methods are used to estimate the returns to education usi ng data from the Canadian Survey of Consumer Finances. (C) 1998 Elsevi er Science S.A. All rights reserved.