Skip to main content

Endogeneity and Exogeneity in Sales Response Functions

  • Conference paper
  • First Online:
Challenges at the Interface of Data Analysis, Computer Science, and Optimization

Abstract

Endogeneity and exogeneity are topics that are mainly discussed in macroeconomics. We show that sales response functions (SRF) are exposed to the same problem if we assume that the control variables in a SRF reflect behavioral reactions of the supply side. The supply side actions are covering a flexible marketing component which could interact with the sales responses if sales managers decide to react fast according to new market situations. A recent article of Kao et al. (Evaluating the effectiveness of marketing expenditures, Working Paper, Ohio State University, Fisher College of Business, 2005) suggested to use a class of production functions under constraints to estimate the sales responses that are subject to marketing strategies. In this paper we demonstrate this approach with a simple SRF(1) model that contains one endogenous variable. Such models can be extended by further exogenous variables leading to SRF-X models. The new modeling approach leads to a multivariate equation system and will be demonstrated using data from a pharma-marketing survey in German regions.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 84.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 109.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  • Baier D, Polasek W (2010) Marketing and regional sales: Evaluation of expenditure strategies by spatial sales response functions. In: Bock HH, Gaul W, Schader M, Bodendorf F, Bryant PG, Critchley F, Diday E, Ihm P, Meulmann J, Nishisato S, Ohsumi N, Opitz O, Radermacher FJ, Wille R, Locarek-Junge H, Weihs C (eds) Classification as a tool for research, studies in classification, data analysis, and knowledge organization. Springer Berlin Heidelberg, pp 673–681

    Google Scholar 

  • Chib S, Greenberg E (1995) Understanding the Metropolis-Hastings algorithm. Am Stat 49:327–335

    Google Scholar 

  • Kao LJ, Chiu CC, Gilbride T, Otter T, Allenby GM (2005) Evaluating the effectiveness of marketing expenditures. Working Paper, Ohio State University, Fisher College of Business

    Google Scholar 

  • Newton MA, Raftery AE (1994) Approximate Bayesian inference with the weighted likelihood bootstrap (with discussion). J Royal Stat Soc B 56:3–48

    MathSciNet  MATH  Google Scholar 

  • Polasek W (2010) Sales response functions (SRF) with stochastic derivative constraints. Working Paper, Institute of Advanced Studies, Wien

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Wolfgang Polasek .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2012 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Polasek, W. (2012). Endogeneity and Exogeneity in Sales Response Functions. In: Gaul, W., Geyer-Schulz, A., Schmidt-Thieme, L., Kunze, J. (eds) Challenges at the Interface of Data Analysis, Computer Science, and Optimization. Studies in Classification, Data Analysis, and Knowledge Organization. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-24466-7_52

Download citation

Publish with us

Policies and ethics