Автор |
Lien, Donald |
Автор |
Rearden, David |
Дата выпуска |
1992 |
dc.description |
In this note, we consider the problem of estimating regression coefficients when there are missing observations of some explanatory variables. Following Dagenais (1973), Gourieroux and Monfort (1981), and Conniffe (1983a, 1983b), we assume auxiliary relationships exist among explanatory varibles. Several estimatprs and their interrelationships are discussed. We begin with the model of Gourieroux and Monfort (1981) |
Формат |
application.pdf |
Издатель |
Marcel Dekker, Inc. |
Копирайт |
Copyright Taylor and Francis Group, LLC |
Название |
A note on estimating regression coefficients with missing data |
Тип |
research-article |
DOI |
10.1080/07474939208800224 |
Electronic ISSN |
1532-4168 |
Print ISSN |
0747-4938 |
Журнал |
Econometric Reviews |
Том |
11 |
Первая страница |
119 |
Последняя страница |
122 |
Аффилиация |
Lien, Donald; Department of Economics, University of Kansas |
Аффилиация |
Rearden, David; Department of Economics, Cleveland State University |
Выпуск |
1 |
Библиографическая ссылка |
Afifi, A. A. and Elashoff, R. M. 1967. Missing observations in multivariate statistics 11. Point estimation in simple linear regression. Journal of the American Statistical Association, 62: 10–29. |
Библиографическая ссылка |
Conniffe, D. 1978. Substituting Means for Missing Observations in Regression. The Economic and Social Review, 9: 329–334. |
Библиографическая ссылка |
Conniffe, D. 1983a. Comments on the weighted regression approach to missing values. The Economic and Social Review, 14: 259–272. |
Библиографическая ссылка |
Conniffe, D. 1983b. Small-sample properties of estimators of regression coefficients given a common pattern of missing data. Review of Economic Studies, 50: 111–120. |
Библиографическая ссылка |
Dagenais, M. G. 1973. The use of incomplete observations in multiple regression analysis. Journal of Econometrics, 1: 317–328. |
Библиографическая ссылка |
Gourieroux, C. and Monfort, A. 1981. On the problem of missing data in linear models. Review of Economic Studies, 48: 579–586. |