Pricing

Compare multiple product elasticity estimates obtained from separate individual models vs. a single hierarchical model.

Synthesize a time series dataset that can be used for modeling both price and cross elasticity of demand, and for optimizing product portfolios.

Apply refutation tests based on negative controlled and sensitivity analysis to test the validity and robustness of our causal estimate

Estimate Price Elasticity by building bayesian linear model with Bayesian Workflow.

Estimate Price Elasticity using DoubleML, coding from scratch. Analyse and compare against OLS on accuracy of causal estimate and predictions.

Replicate the Double ML framework to examine regularization bias and its impact on causal estimate errors, specifically in measuring price elasticity.

Synthesize a time series dataset that can be used for modeling price elasticity of demand.