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The use of incomplete observations in multiple regression analysis : A generalized least squares approach

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  • Dagenais, Marcel G.

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  • Dagenais, Marcel G., 1973. "The use of incomplete observations in multiple regression analysis : A generalized least squares approach," Journal of Econometrics, Elsevier, vol. 1(4), pages 317-328, December.
    • Handle: RePEc:eee:econom:v:1:y:1973:i:4:p:317-328
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    Cited by:

    1. Qian, Hang, 2012. "Essays on statistical inference with imperfectly observed data," ISU General Staff Papers 201201010800003618, Iowa State University, Department of Economics.
    2. Helen Jensen & Justo Manrique, 1998. "Demand for food commodities by income groups in Indonesia," Applied Economics, Taylor & Francis Journals, vol. 30(4), pages 491-501.
    3. Chris Muris, 2020. "Efficient GMM Estimation with Incomplete Data," The Review of Economics and Statistics, MIT Press, vol. 102(3), pages 518-530, July.
    4. Palm, Franz C & Nijman, Theo E, 1984. "Missing Observations in the Dynamic Regression Model," Econometrica, Econometric Society, vol. 52(6), pages 1415-1435, November.
    5. Theodore E. Nijman & Franz C. Palm, 1988. "Consistent Estimation of Regression Models with Incompletely Observed Exogenous Variables," Annals of Economics and Statistics, GENES, issue 12, pages 151-175.
    6. Denis Conniffe & Donal O'Neill, 2011. "Efficient Probit Estimation with Partially Missing Covariates," Advances in Econometrics, in: Missing Data Methods: Cross-sectional Methods and Applications, pages 209-245, Emerald Group Publishing Limited.
    7. Nijman, T.E. & Palm, F.C., 1987. "Consistent estimation of regression models with incompletely observed exogenous variables," Other publications TiSEM a1dbc0ec-23d6-4bb1-8a95-7, Tilburg University, School of Economics and Management.
    8. Maria Raikou & Alistair McGuire, 2012. "Estimating Costs for Economic Evaluation," Chapters, in: Andrew M. Jones (ed.), The Elgar Companion to Health Economics, Second Edition, chapter 43, Edward Elgar Publishing.
    9. Palm, F.C. & Nijman, Th., 1984. "Consistent estimation using proxy-variables in models with unobserved variables," Serie Research Memoranda 0012, VU University Amsterdam, Faculty of Economics, Business Administration and Econometrics.
    10. Palm, F. C. & Nijman, T. E., 1982. "Linear regression using both temporally aggregated and temporally disaggregated data," Journal of Econometrics, Elsevier, vol. 19(2-3), pages 333-343, August.
    11. Lee, Jonq-Ying, 1986. "Imputed Missing Incomes And Marginal Propensity To Consume Food," Western Journal of Agricultural Economics, Western Agricultural Economics Association, vol. 11(2), pages 1-8, December.
    12. H. Toutenburg & V.K. Srivastava & Shalabh & C. Heumann, 2005. "Estimation of Parameters in Multiple Regression with Missing Covariates Using a Modified First Order Regression Procedure," Annals of Economics and Finance, Society for AEF, vol. 6(2), pages 289-301, November.
    13. MoonJoong Tcha, 2005. "Australian Wool Exports and Exchange Rate Pass-Through: Asymmetric Responses and Market Share," Economics Discussion / Working Papers 05-31, The University of Western Australia, Department of Economics.
    14. Heien, Dale & Pompelli, Greg, 1988. "The Demand For Beef Products: Cross-Section Estimation Of Demographic And Economic Effects," Western Journal of Agricultural Economics, Western Agricultural Economics Association, vol. 13(1), pages 1-8, July.
    15. Denis Conniffe & Donal O’Neill, 2008. "An Efficient Estimator for Dealing with Missing Data on Explanatory Variables in a Probit Choice Model," Economics Department Working Paper Series n1960908.pdf, Department of Economics, National University of Ireland - Maynooth.
    16. Qian, Hang, 2010. "Linear regression using both temporally aggregated and temporally disaggregated data: Revisited," MPRA Paper 32686, University Library of Munich, Germany.
    17. Laitila, Thomas & Wang, Lisha, 2015. "A Two-Step Estimator for Missing Values in Probit Model Covariates," Working Papers 2015:3, Örebro University, School of Business.

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