Empirical evidence of least squares in the Random Coefficients Regression Model
DOI:
https://doi.org/10.21754/tecnia.v11i1.527Keywords:
Random Coefficients, Generalized Least Squares; Bias , Consistency, EfficiencyAbstract
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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