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Addressing endogeneity in aggregate logit models with time-varying parameters for optimal retail-pricing

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  • Guhl, Daniel

Abstract

It is well known that price endogeneity is a severe problem in demand models for market-level data (e.g., aggregate logit models) because it leads to biased estimates and therefore incorrect managerial implications. If the price parameter varies over time, as is usually the case, the relevance of the issue increases because standard methods to correct endogeneity biases (e.g., generalized method of moments) fail. This paper presents a control function approach as a remedy. A comprehensive simulation study demonstrates this method’s suitability, such that addressing endogeneity with the control function approach is the best choice. Moreover, addressing the endogeneity problem incorrectly may be even more harmful than simply ignoring it. To further illustrate the control function approach, we analyze the demand for canned tuna using aggregate retailer-level data. Here, all utility parameters vary over time and price endogeneity is indeed an issue. Effectively addressing price endogeneity correct has positive economic consequences: a normative model analysis reveals that implementing the control function approach yields a 3 % increase in retailer profits.

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  • Guhl, Daniel, 2019. "Addressing endogeneity in aggregate logit models with time-varying parameters for optimal retail-pricing," European Journal of Operational Research, Elsevier, vol. 277(2), pages 684-698.
    • Handle: RePEc:eee:ejores:v:277:y:2019:i:2:p:684-698
    DOI: 10.1016/j.ejor.2019.02.058
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    as
    1. Jean‐Pierre Dubé & Jeremy T. Fox & Che‐Lin Su, 2012. "Improving the Numerical Performance of Static and Dynamic Aggregate Discrete Choice Random Coefficients Demand Estimation," Econometrica, Econometric Society, vol. 80(5), pages 2231-2267, September.
    2. Kamel Jedidi & Carl F. Mela & Sunil Gupta, 1999. "Managing Advertising and Promotion for Long-Run Profitability," Marketing Science, INFORMS, vol. 18(1), pages 1-22.
    3. Yunmi Kim & Chang‐Jin Kim, 2011. "Dealing with endogeneity in a time‐varying parameter model: joint estimation and two‐step estimation procedures," Econometrics Journal, Royal Economic Society, vol. 14(3), pages 487-497, October.
    4. S. Sriram & Pradeep K. Chintagunta & Ramya Neelamegham, 2006. "Effects of Brand Preference, Product Attributes, and Marketing Mix Variables in Technology Product Markets," Marketing Science, INFORMS, vol. 25(5), pages 440-456, September.
    5. Vincent Nijs & Kanishka Misra & Eric T. Anderson & Karsten Hansen & Lakshman Krishnamurthi, 2010. "Channel Pass-Through of Trade Promotions," Marketing Science, INFORMS, vol. 29(2), pages 250-267, 03-04.
    6. Chang-Jin, Kim, 2010. "Dealing with Endogeneity in Regression Models with Dynamic Coefficients," Foundations and Trends(R) in Econometrics, now publishers, vol. 3(3), pages 165-266, June.
    7. Jiang, Renna & Manchanda, Puneet & Rossi, Peter E., 2009. "Bayesian analysis of random coefficient logit models using aggregate data," Journal of Econometrics, Elsevier, vol. 149(2), pages 136-148, April.
    8. Casado, Esteban & Ferrer, Juan-Carlos, 2013. "Consumer price sensitivity in the retail industry: Latitude of acceptance with heterogeneous demand," European Journal of Operational Research, Elsevier, vol. 228(2), pages 418-426.
    9. Keane, Michael P, 1997. "Modeling Heterogeneity and State Dependence in Consumer Choice Behavior," Journal of Business & Economic Statistics, American Statistical Association, vol. 15(3), pages 310-327, July.
    10. Kalouptsidis, N. & Psaraki, V., 2010. "Approximations of choice probabilities in mixed logit models," European Journal of Operational Research, Elsevier, vol. 200(2), pages 529-535, January.
    11. Heckman, James J, 1978. "Dummy Endogenous Variables in a Simultaneous Equation System," Econometrica, Econometric Society, vol. 46(4), pages 931-959, July.
    12. Ackerberg, Daniel & Lanier Benkard, C. & Berry, Steven & Pakes, Ariel, 2007. "Econometric Tools for Analyzing Market Outcomes," Handbook of Econometrics, in: J.J. Heckman & E.E. Leamer (ed.), Handbook of Econometrics, edition 1, volume 6, chapter 63, Elsevier.
    13. Hausman, Jerry, 2015. "Specification tests in econometrics," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 38(2), pages 112-134.
    14. Harikesh Nair & Jean-Pierre Dubé & Pradeep Chintagunta, 2005. "Accounting for Primary and Secondary Demand Effects with Aggregate Data," Marketing Science, INFORMS, vol. 24(3), pages 444-460, November.
    15. Leeflang, Peter S.H. & Bijmolt, Tammo H.A. & van Doorn, Jenny & Hanssens, Dominique M. & van Heerde, Harald J. & Verhoef, Peter C. & Wieringa, Jaap E., 2009. "Creating lift versus building the base: Current trends in marketing dynamics," International Journal of Research in Marketing, Elsevier, vol. 26(1), pages 13-20.
    16. David Besanko & Sachin Gupta & Dipak Jain, 1998. "Logit Demand Estimation Under Competitive Pricing Behavior: An Equilibrium Framework," Management Science, INFORMS, vol. 44(11-Part-1), pages 1533-1547, November.
    17. Hruschka, Harald, 2010. "Considering endogeneity for optimal catalog allocation in direct marketing," European Journal of Operational Research, Elsevier, vol. 206(1), pages 239-247, October.
    18. Pradeep Chintagunta & Jean-Pierre Dubé & Vishal Singh, 2003. "Balancing Profitability and Customer Welfare in a Supermarket Chain," Quantitative Marketing and Economics (QME), Springer, vol. 1(1), pages 111-147, March.
    19. Reiss, Peter C. & Wolak, Frank A., 2007. "Structural Econometric Modeling: Rationales and Examples from Industrial Organization," Handbook of Econometrics, in: J.J. Heckman & E.E. Leamer (ed.), Handbook of Econometrics, edition 1, volume 6, chapter 64, Elsevier.
    20. Steven T. Berry, 1994. "Estimating Discrete-Choice Models of Product Differentiation," RAND Journal of Economics, The RAND Corporation, vol. 25(2), pages 242-262, Summer.
    21. W. Ross Morrow & Steven J. Skerlos, 2011. "Fixed-Point Approaches to Computing Bertrand-Nash Equilibrium Prices Under Mixed-Logit Demand," Operations Research, INFORMS, vol. 59(2), pages 328-345, April.
    22. Peter M. Guadagni & John D. C. Little, 1983. "A Logit Model of Brand Choice Calibrated on Scanner Data," Marketing Science, INFORMS, vol. 2(3), pages 203-238.
    23. Anett Weber & Winfried J. Steiner & Stefan Lang, 2017. "A comparison of semiparametric and heterogeneous store sales models for optimal category pricing," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 39(2), pages 403-445, March.
    24. Pennings, Clint L.P. & van Dalen, Jan, 2017. "Integrated hierarchical forecasting," European Journal of Operational Research, Elsevier, vol. 263(2), pages 412-418.
    25. Sha Yang & Yuxin Chen & Greg Allenby, 2003. "Reply to Comments on “Bayesian Analysis of Simultaneous Demand and Supply”," Quantitative Marketing and Economics (QME), Springer, vol. 1(3), pages 299-304, September.
    26. Kim, Byung-Do & Blattberg, Robert C & Rossi, Peter E, 1995. "Modeling the Distribution of Price Sensitivity and Implications for Optimal Retail Pricing," Journal of Business & Economic Statistics, American Statistical Association, vol. 13(3), pages 291-303, July.
    27. Steven M. Shugan, 2002. "In Search of Data: An Editorial," Marketing Science, INFORMS, vol. 21(4), pages 369-377.
    28. A. Gürhan Kök & Marshall L. Fisher, 2007. "Demand Estimation and Assortment Optimization Under Substitution: Methodology and Application," Operations Research, INFORMS, vol. 55(6), pages 1001-1021, December.
    29. Peter E. Rossi, 2014. "Invited Paper —Even the Rich Can Make Themselves Poor: A Critical Examination of IV Methods in Marketing Applications," Marketing Science, INFORMS, vol. 33(5), pages 655-672, September.
    30. Kevin YC Chung & Timothy P. Derdenger & Kannan Srinivasan, 2013. "Economic Value of Celebrity Endorsements: Tiger Woods' Impact on Sales of Nike Golf Balls," Marketing Science, INFORMS, vol. 32(2), pages 271-293, March.
    31. Jean-Pierre Dubé & Günter J. Hitsch & Peter E. Rossi & Maria Ana Vitorino, 2008. "Category Pricing with State-Dependent Utility," Marketing Science, INFORMS, vol. 27(3), pages 417-429, 05-06.
    32. Berry, Steven & Levinsohn, James & Pakes, Ariel, 1995. "Automobile Prices in Market Equilibrium," Econometrica, Econometric Society, vol. 63(4), pages 841-890, July.
    33. Sriram, S. & Kadiyali, Vrinda, 2009. "Empirical investigation of channel reactions to brand introductions," International Journal of Research in Marketing, Elsevier, vol. 26(4), pages 345-355.
    34. Sergio Meza & K. Sudhir, 2006. "Pass-through timing," Quantitative Marketing and Economics (QME), Springer, vol. 4(4), pages 351-382, December.
    35. Sungho Park & Sachin Gupta, 2012. "Handling Endogenous Regressors by Joint Estimation Using Copulas," Marketing Science, INFORMS, vol. 31(4), pages 567-586, July.
    36. Judith A. Chevalier & Anil K. Kashyap & Peter E. Rossi, 2003. "Why Don't Prices Rise During Periods of Peak Demand? Evidence from Scanner Data," American Economic Review, American Economic Association, vol. 93(1), pages 15-37, March.
    37. Sungho Park & Sachin Gupta, 2012. "Comparison of SML and GMM estimators for the random coefficient logit model using aggregate data," Empirical Economics, Springer, vol. 43(3), pages 1353-1372, December.
    38. Sha Yang & Yuxin Chen & Greg Allenby, 2003. "Bayesian Analysis of Simultaneous Demand and Supply," Quantitative Marketing and Economics (QME), Springer, vol. 1(3), pages 251-275, September.
    39. Tülin Erdem & Michael Keane & Baohong Sun, 2008. "The impact of advertising on consumer price sensitivity in experience goods markets," Quantitative Marketing and Economics (QME), Springer, vol. 6(2), pages 139-176, June.
    40. Kim, Chang-Jin, 2006. "Time-varying parameter models with endogenous regressors," Economics Letters, Elsevier, vol. 91(1), pages 21-26, April.
    41. Harald J. Heerde & Scott A. Neslin, 2008. "Sales Promotion Models," International Series in Operations Research & Management Science, in: Berend Wierenga (ed.), Handbook of Marketing Decision Models, chapter 0, pages 107-162, Springer.
    42. Mohamed Lachaab & Asim Ansari & Kamel Jedidi & Abdelwahed Trabelsi, 2006. "Modeling preference evolution in discrete choice models: A Bayesian state-space approach," Quantitative Marketing and Economics (QME), Springer, vol. 4(1), pages 57-81, March.
    43. Praveen K. Kopalle & Carl F. Mela & Lawrence Marsh, 1999. "The Dynamic Effect of Discounting on Sales: Empirical Analysis and Normative Pricing Implications," Marketing Science, INFORMS, vol. 18(3), pages 317-332.
    44. Pradeep Chintagunta & Jean-Pierre Dubé & Khim Yong Goh, 2005. "Beyond the Endogeneity Bias: The Effect of Unmeasured Brand Characteristics on Household-Level Brand Choice Models," Management Science, INFORMS, vol. 51(5), pages 832-849, May.
    45. Winer, Russell S, 1986. "A Reference Price Model of Brand Choice for Frequently Purchased Products," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 13(2), pages 250-256, September.
    46. Pradeep K. Chintagunta, 2001. "Endogeneity and Heterogeneity in a Probit Demand Model: Estimation Using Aggregate Data," Marketing Science, INFORMS, vol. 20(4), pages 442-456, December.
    47. Vincent R. Nijs & Shuba Srinivasan & Koen Pauwels, 2007. "Retail-Price Drivers and Retailer Profits," Marketing Science, INFORMS, vol. 26(4), pages 473-487, 07-08.
    48. Pagan, Adrian, 1984. "Econometric Issues in the Analysis of Regressions with Generated Regressors," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 25(1), pages 221-247, February.
    49. S. Sriram & Manohar U. Kalwani, 2007. "Optimal Advertising and Promotion Budgets in Dynamic Markets with Brand Equity as a Mediating Variable," Management Science, INFORMS, vol. 53(1), pages 46-60, January.
    50. J. Miguel Villas-Boas & Russell S. Winer, 1999. "Endogeneity in Brand Choice Models," Management Science, INFORMS, vol. 45(10), pages 1324-1338, October.
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