How Reliable is Duality Theory in Empirical Work?
通过蒙特卡洛模拟生成类似美国农业的数据，检验对偶理论在估计生产参数时的可靠性，发现弹性估计偏差很大，平均偏差达90%。
Abstract The Neoclassical theory of production establishes a dual relationship between the profit value function of a competitive firm and its underlying production technology. This relationship, commonly referred to as duality theory, has been widely used in empirical work to estimate production parameters such as elasticities and returns to scale. We generate a pseudo‐dataset by Monte Carlo simulations, which, starting from known production parameters, yield a dataset with the main characteristics of U.S. agriculture in terms of unobserved firm heterogeneity, decisions under uncertainty, unexpected production and price shocks, endogenous prices, output and input aggregation, measurement error in variables, and omitted variables. Production parameters are not precisely recovered when performing econometric estimation based on the duality approach, and the elasticity estimates are inaccurate. Deviations of own‐ and cross‐price elasticities from initial median values, given our parameter calibration, range between 6% and 690%, with an average of 90%. Also, own‐price elasticities are as imprecisely recovered as cross‐price elasticities. Sensitivity analysis shows that results still hold for different sources and levels of noise, and sample size used in estimation.