On Least Squares Estimation when the Dependent Variable is Grouped

Mark Stewart

The Review of Economic Studies, 1983, vol. 50, issue 4, 737-753

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.

Date: 1983
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Working Paper: On Least Squares Estimation When the Dependent Variable is Grouped (1982)
Working Paper: On Least Squares Estimation when the Dependent Variable is Grouped (1982)
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Persistent link: https://EconPapers.repec.org/RePEc:oup:restud:v:50:y:1983:i:4:p:737-753.

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