Varying Coefficients in Logistic Regression with Applications to Marketing Research

In the marketing research world today, companies have access to massive amounts of data regarding the purchase behavior of consumers. Researchers study this data to understand how outside factors, such as demographics and marketing tools, affect the probability that a given consumer will make a purchase. Through the use of panel data, we tackle these questions and propose a logistic regression model in which coefficients can vary based on a consumer's purchase history. We also introduce a two-step procedure for model selection that uses a group LASSO penalty to decide which are informative and which variables need varying coefficients in the model