力矩(物理)
生产(经济)
代表(政治)
估计员
矩母函数
功能(生物学)
概率分布
概率密度函数
数学优化
样品(材料)
分布(数学)
计算机科学
计量经济学
数学
应用数学
统计
经济
政治学
政治
法学
化学
色谱法
经典力学
宏观经济学
数学分析
进化生物学
物理
生物
标识
DOI:10.1080/07350015.1983.10509339
摘要
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.
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