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

Doug J. Chung (), Byungyeon Kim () and Byoung Park
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Doug J. Chung: Harvard Business School, Harvard University, Boston, Massachusetts 02163
Byungyeon Kim: Harvard Business School, Harvard University, Boston, Massachusetts 02163

Management Science, 2019, vol. 65, issue 11, 5197-5218

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.

Keywords: Nerlove–Arrow framework; stock-of-goodwill; dynamic panel data; serial correlation; instrumental variables; sales effectiveness; detailing; pharmaceutical industry (search for similar items in EconPapers)
Date: 2019
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Citations: View citations in EconPapers (5)

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Persistent link: https://EconPapers.repec.org/RePEc:inm:ormnsc:v:65:y:2019:i:11:p:5197-5218

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