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Title: On Least Squares Estimation When the Dependent Variable is Grouped
Authors: Stewart, Mark B.
Issue Date: 1-Nov-1982
Citation: Review of Economic Studies, pp. 737-753, November 1982
Series/Report no.: Working Papers (Princeton University. Industrial Relations Section) ; 159
Abstract: This paper examines the problem of estimating the parameters of an underlying linear model using data in which the dependent variable is only observed to fall in a certain interval on a continuous scale, its actual value remaining unobserved. A Least Squares algorithm for attaining the Maximum Likelihood estimator is described, the asymptotic bias of the OLS estimator derived for the normal regressors case and a "moment" estimator presented. A "two-step estimator" based on combining the two approaches is proposed and found to perform well in both an economic illustration and simulation experiments.
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