Response Function Estimation Using the Equity Estimator
比较了均衡估计量、岭估计量、普通最小二乘和主成分估计量在36种药品销售响应函数估计中的表现，发现均衡估计量在偏差、方差和表面有效性上优于其他方法，预测精度相近。
Multicollinearity often hampers the estimation of the “independent” effects of the marketing mix variables in sales response models. In a previous study, the authors recommended the use of the equity estimator for estimating linear models in the presence of multicollinearity. In this article, they evaluate the performance of equity, ridge, OLS, and principal components estimators in estimating response functions for 36 pharmaceutical products. Overall, equity outperforms the other three estimators on criteria such as estimated bias, variance, and face validity of the estimates. The four estimators have similar levels of predictive accuracy. The authors also present some managerial implications for resource allocation in the pharmaceutical industry.