Point Estimation in Multiplicative Models

In a multiplicative model it is usual to assume that the logarithm of the disturbance variable is normally distributed with unknown variance σ 2 and with a mean which is either zero or $-{\textstyle\frac{1}{2}}\sigma ^{2}$ according to the viewpoint taken of the object of the model. It is shown that...

Full description

Saved in:
Bibliographic Details
Published inEconometrica Vol. 44; no. 3; pp. 467 - 473
Main Authors Evans, I. G., Shaban, S. A.
Format Journal Article
LanguageEnglish
Published Menasha, Wis The Econometric Society 01.05.1976
George Banta Pub. Co. for the Econometric Society
Blackwell Publishing Ltd
Subjects
Cobb douglas production function
Dependent variables
Economic models
Estimators
Expected values
Least squares
Logarithms
Logical givens
Maximum likelihood estimation
Maximum likelihood estimators
Point estimators
Production functions
Regression analysis
Unbiased estimators
Variables
Online AccessGet full text

Cover

More Information
Summary:In a multiplicative model it is usual to assume that the logarithm of the disturbance variable is normally distributed with unknown variance σ 2 and with a mean which is either zero or $-{\textstyle\frac{1}{2}}\sigma ^{2}$ according to the viewpoint taken of the object of the model. It is shown that, for each of several estimation criteria, the two assumptions lead to precisely the same point estimators of the exponents of the explanatory variables in the model and of the conditional mean, median, and mode of the dependent variable for specified values of the explanatory variables. An improved form is also given of the estimator of the conditional mean proposed by Teekens and Koerts [8].
ISSN:0012-9682
1468-0262
DOI:10.2307/1913975