Open AccessAitken’s Generalized Least Square Method for Estimating Parameter of Demand Function of Animal Protein In Indonesia
Author(s) -
Fitria Virgantari,
Hagni Wijayanti,
Sonny Koeshendrajana
Publication year - 2019
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1245/1/012045
Subject(s) - homoscedasticity , estimator , mathematics , statistics , ordinary least squares , function (biology) , heteroscedasticity , econometrics , biology , evolutionary biology
Ordinary least square (OLS) method is the most popular and commonly technique used to estimate numerical values of parameters of selected regression models. This was due to its unbiasedness property. However, when elements of dependent variable have unequal variances and/or correlated each other, there is no guarantee that the OLS estimator will show the most efficient within the class of linear unbiased estimators. For conditions generally encountered, GLS method is proposed an estimation procedure which yields coefficient estimators at least asymptotically more efficient than single equation OLS estimator. This method is derived by Aitken and it’s named Aitken GLS. This paper reported a study of application of Aitken’s GLS method for estimating parameter of demand function of animal protein in Indonesia of which have a system equation. This system of equation causes violation of the assumptions of homoscedasticity and independency of estimated parameters. Secondary data obtained from the Central Bureau of Statistics 2016 in 34 provinces in Indonesia was used in this study. Animal food was grouped in terms of fish, meat, eggs and milk. Results showed that error of those three equations were correlated. It suggests that GLS method should be used. Normality and homogenity assumptions were not violated. The determination coefficient was 99%, indicating that the method was very good.