Recreation of the famous marketing paper by Guadagni and Little (1983) in Python

This git includes:

1. Dataset Recreation.py: A script to create from scratch a purchase history dataset of N consumers over T time periods for K options. All the parameters in the script can be changed to generate a different dataset. As in the original paper, the consumers are heterogenous in their loyalty to the brand and to the different sizes offered. The script outputs four files: * GuadagniLittle1983.csv, which contains the data to estimate * TrueBetas.csv, which contains the true parameters used to generate the data. * BrandShares.png, which plots the evolution of market shares for the brands over time. * SizeShares.png, which plots the evolution of market shares for the sizes over time.
2. Mixed Logit Estimation.py: A script to estimate the parameters used to generate the data. As in the original paper, the script constrains the utility of the first option to be 1, and estimates (K-1) brand intercepts and J utility components for the attributes, which are common to all brands.