How Do Sales Efforts Pay Off? Dynamic Panel Data Analysis in the Nerlove–Arrow Framework

Abstract

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.

Shadow Economy and Environmental Pollution in West African Countries: The Role of Institutions

“…This is not a surprise because in the context of GMM regression, AR(1) may be expected. However, AR(1) is usually ignored in this context because it is not the decision criteria (Doug et al, 2019). The diagnostic decision is based on AR(2) test on the residuals.…”