The Frontier of Estimator in Agriculture Economics: Application for Rice Products in 7 Top Countries in Asia

Abstract

Abstract The purpose to econometrically calculate the comparing estimators in parametric estimations is successfully done in this paper. The two powerful estimators such as the James-Stein estimation (JSE) and Maximum Likelihood estimation (MLE) were employed to solve the most efficiently parametric forecasting. Experimentally, the yearly time-series data of rice exporting products during 2006 to 2016 was collected and observed from 7 Asian countries, which are the major exporters in the world, such as Thailand, India, Pakistan, Vietnam, Myanmar, China, and Cambodia. Methodologically, the comparison between the two estimators was based on the linear regression to provide residual terms. Empirically, the results of the estimator comparison implied that the JSE can be substantially replaced the counterpart when doing in the multiple-factors estimation, and error terms estimated were compared for seeking the best estimator to predict trends of rice products. Consequently, it is sensible to introduce the J-S estimator can be one of interesting tools in the modern econometric researches.