Estimating Monotone Concave Stochastic Production Frontiers
利用满足全局单调性和曲率性质的灵活成本函数，通过成本最小化的一阶条件来估计生产函数特征，并在蒙特卡洛实验和印度水稻种植实证中表现良好。
Recent research shows that the search for Bayesian estimation of concave production functions is a fruitful area of investigation. In this article, we use a flexible cost function that satisfies globally the monotonicity and curvature properties to estimate features of the production function. Specification of a globally monotone concave production function is a difficult task which is avoided here by using the first-order conditions for cost minimization from a globally monotone concave cost function. The problem of unavailable factor prices is bypassed by assuming structure for relative prices in the first-order conditions. The new technique is shown to perform well in a Monte Carlo experiment as well as in an empirical application to rice farming in India.