The Role of the Management Sciences in Research on Personalization
Management Science
Measuring Brand Value in an Equilibrium Framework
Marketing Science
Quantifying the Economic Value of Warranties in the U.S. Server Market
Marketing Science
The Sound of Silence: Observational Learning in the U.S. Kidney Market
Marketing Science
Structural Estimation of the Effect of Out-of-Stocks
Management Science
Deriving the Pricing Power of Product Features by Mining Consumer Reviews
Management Science
Online and Offline Demand and Price Elasticities: Evidence from the Air Travel Industry
Information Systems Research
Rational Herding in Microloan Markets
Management Science
Handling Endogenous Regressors by Joint Estimation Using Copulas
Marketing Science
Change of Scale and Forecasting with the Control-Function Method in Logit Models
Transportation Science
Advertising Effects in Presidential Elections
Marketing Science
The Dynamic Advertising Effect of Collegiate Athletics
Marketing Science
| Hi-index | 0.01 |
Applications of random utility models to scanner data have been widely presented in marketing for the last 20 years. One particular problem with these applications is that they have ignored possible correlations between the independent variables in the deterministic component of utility (price, promotion, etc.) and the stochastic component or error term. In fact, marketing-mix variables, such as price, not only affect brand purchasing probabilities but are themselves endogenously set by marketing managers. This work tests whether these endogeneity problems are important enough to warrant consideration when estimating random utility models with scanner panel data. Our results show that not accounting for endogeneity may result in a substantial bias in the parameter estimates.