A double-copula stochastic frontier model with dependent error components and correction for sample selection

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• 作者：Songsak Sriboonchitta^a ; Jianxu Liu^a ; ^{liujianxu1984@163.com} ; Aree Wiboonpongse^b ; Thierry Denoeux^c
• 关键词：Stochastic frontier model ; Copula representation ; Dependence ; Families of copula ; Sample selection ; Technical efficiency
• 刊名：International Journal of Approximate Reasoning
• 出版年：2017
• 出版时间：January 2017
• 年：2017
• 卷：80
• 期：Complete
• 页码：174-184
• 全文大小：593 K
• 卷排序：80

文摘

We propose a stochastic frontier model with self-selection, based on two copulas. The model is estimated using maximum simulated likelihood. Several copula families are considered; the best model is selected using AIC. The model was applied to cross-sectional rice production data. Our model provides more reliable estimates of technical efficiency scores.