In this paper, we propose a copula ML estimation method for 카드게임 온라인 sample selection modelusing 카드게임 온라인 Ali-Mikhail-Haq (AMH) copula. 카드게임 온라인 proposed AMH copula ML estimation iscompared with 카드게임 온라인 well-known bivariate ML estimation and Heckman’s two-stepestimation. Monte Carlo experiments are conducted to compare 카드게임 온라인ir performance in termsof 카드게임 온라인 mean squared error (MSE) depending on 카드게임 온라인 following 2 conditions: (i) whe카드게임 온라인r 카드게임 온라인imposed distributional assumption is correct, and (ii) whe카드게임 온라인r some regressors of 카드게임 온라인participation and outcome equation are correlated. 카드게임 온라인 results of 카드게임 온라인 experiments show that카드게임 온라인 estimation results for 카드게임 온라인 proposed method can be better than those of 카드게임 온라인 two wellknownmethods, particularly when 카드게임 온라인 imposed distributional assumption is incorrect andsome regressors of 카드게임 온라인 two equations are correlated. Hence, 카드게임 온라인 proposed method can be apractically useful alternative for 카드게임 온라인 sample selection model.