How Do Sales Efforts Pay Off? Dynamic Panel Data Analysis in the Nerlove–Arrow Framework
研究了销售代表对不同类型医生的拜访带来的短期和长期价值，发现长期效果对专科医生更明显，短期边际效果对全科医生更高，并改进了动态面板数据方法中的矩条件问题。
This paper evaluates the short- and long-term value of sales representatives’ detailing visits to different types of physicians. By understanding the dynamic effect of sales calls across heterogeneous physicians, we provide guidance on the design of optimal call patterns for route sales. The findings reveal that the long-term persistence effect of detailing is more pronounced for specialist physicians, whereas the contemporaneous marginal effect is higher for generalists. The paper also provides a key methodological insight to the marketing and economics literature. In the Nerlove–Arrow framework, moment conditions that are typically used in conventional dynamic panel data methods become vulnerable to serial correlation in the error structure. We discuss the associated biases and present a robust set of moment conditions for both lagged dependent and predetermined explanatory variables. Furthermore, we show that conventional tests to detect serial correlation have weak power, resulting in the misuse of moment conditions that leads to incorrect inference. Theoretical illustrations and Monte Carlo simulations are provided for validation. This paper was accepted by Matthew Shum, marketing