When you have data that is both Cross-Sectional (many stores) and Time-Series (many days), standard regression fails because of 'fixed effects' and 'autocorrelation'. Dynamic Panels handle this complexity.
"What is the universal impact of a price change across all 500 stores?"
"How does past growth predict future growth across brands?"
"Controlling for store-specific quirks, what works?"
It uses 'Instrumental Variables' (lags) to fix the endogeneity bias that comes from measuring the same entities over time.
The Problem
Confusing store location quality with ad quality.
What It Reveals
The true ad effect controlling for store baseline.
Decision Enabled
Standardize best practices across the network.
The engine for Enterprise/Portfolio Views, allowing us to draw global conclusions from thousands of local entities.
A regression output robust to Fixed Effects, showing the "True Beta" of marketing across the entire portfolio.