Quasi‐maximum likelihood estimation of a censored equation system with a copula approach: meat consumption by U.S. individuals
提出一种基于Copula的删失方程组估计方法，使用拟极大似然估计器替代传统多元正态误差假设，解决高维删失系统中多重概率积分的计算难题，应用于美国个人肉类消费数据得到与现有方法不同的实证结果。
Abstract A copula approach to censored system estimation is proposed. The quasi‐maximum likelihood estimator departs from the multivariate normal error distribution predominantly used in existing estimators and resolves the computational difficulty with multiple probability integrals in high‐dimensional censored systems. An application to individual meat consumption demonstrates that the procedure produces very different empirical estimates from existing Gaussian full‐information and quasi‐maximum likelihood estimates.