Empirical evidence of least squares in the Random Coefficients Regression Model

Authors

  • Luis Huamanchumo de la Cuba Facultad de Ingeniería Económica, Estadística y CCSS, Universidad de Ingeniería, Lima-Perú

DOI:

https://doi.org/10.21754/tecnia.v11i1.527

Keywords:

Random Coefficients, Generalized Least Squares; Bias , Consistency, Efficiency

Abstract

This article studies some properties in finite samples of several estimators of the Mean Response Coefficient in a Linear Regression Model of Random Coefficients.
For this purpose, it was necessary to design a sample experiment. Thus, evidence about Bias, Consistency and Efficiency was obtained from 15,120 estimates. According to this, not only the Two-Stage Generalized Least Squares (GLS) estimator produced the best results but also the Ordinary Least Squares (OLS) estimator by obtaining significant gains in Efficiency when it was estimated from a model without Error of Specification. It is necessary to expand this research by including the Maximum Likelihood estimator.

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References

[1] . Rao, C.R. Linear Statistical Models and Its Applications. New York: John Wiley & Sons. 1971.

[2] . Johnson, Richard Applied Multivariate Statistical Analysis. Third Edition. Prentice Hall International Inc. 1992.

[3] . Swamy, P. A. V. B. Statistical Inference in Random Coefficient Regression Models. Springer Verlag. 1971.

[4] . Hildreth, Clifford & Houck, James (junio, 1968) "Some Estimators for a Linear Model with Random Coefficients". Journal of the American Statistical Asociation, pp. 584-595.

[5] . Raj, Baldev (marzo, 1971) "Linear Regression with Random Coefficients: The Finite Sample and Convergence Properties". Journal of the American Statistical Association. Vol 70, No 349, pp. 127-137.

[6] . Haussman, Jerry y Taylor, William (marzo, 1979) "Attrition Bias in Experimental and Panel Data: The Gary Income Maintenance Experiment".

Econometrica. Vol No 2, pp. 455-472.

[7] . Marija J., Norousis. SPSS. Advanced Statistics 6+.1 SPSS Inc. 1994.

[8] . Huamanchumo de la Cuba, Luis "Eficiencia en Muestras Finitas en el Modelo de Parámetros Aleatorios de Hildreth & Houck: Un Experimento. Muestral". Tesis de Licenciatura. Escuela Profesional de Ingeniería Estadística. Universidad Nacional de Ingeniería, Octubre 2000.

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Published

2001-06-01

How to Cite

[1]
L. Huamanchumo de la Cuba, “Empirical evidence of least squares in the Random Coefficients Regression Model”, TEC, vol. 11, no. 1, Jun. 2001.

Issue

Vol. 11 No. 1 (2001)

Section

Articles

License

Copyright (c) 2001 TECNIA

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