Testing the Stochastic Structure of Production: A Flexible Moment-Based Approach
指出传统生产函数对产出概率分布施加了不可检验的限制，提出基于产出矩的灵活随机技术表示，并开发大样本估计量，用牛奶生产数据验证了前三阶矩显著且传统模型的交叉矩约束被拒绝。
Conventional production function specifications are shown to impose restrictions on the probability distribution of output that cannot be tested with the conventional models. These restrictions have important implications for firm behavior under uncertainty. A flexible representation of a firm's stochastic technology is developed based on the moments of the probability distribution of output. These moments are a unique representation of the technology and are functions of inputs. Large-sample estimators are developed for a linear moment model that is sufficiently flexible to test the restrictions implied by conventional production function specifications. The flexible moment-based approach is applied to milk production data. The first three moments of output are statistically significant functions of inputs. The cross-moment restrictions implied by conventional models are rejected.