Scaling Factors in Estimation of Time-Nonseparable Utility Functions
发现GMM估计中缩放因子选择不当会导致虚假估计，建议选择使缩放后边际效用大致恒定的因子，并用模拟数据和实际消费与资产收益数据验证。
In GMM estimations, when data exhibit exponential trends, scaling factors are often used to restore stationarity in Euler equation residuals. The present paper demonstrates that finite-sample estimates are sensitive to the scaling factors, and seemingly plausible scaling factors may produce spurious estimates. It suggests that scaling factors be chosen so that the scaled marginal utility is roughly constant. The discussion is conducted through estimation of a representative agent's time-nonseparable utility function, using first artificial data and then aggregate consumption and asset returns. © 1997 by the President and Fellows of Harvard College and the Massachusetts Institute of Technology