Internal helpers for the Augmented Mean Group (AMG) estimator of Eberhardt & Teal (2010) and Bond & Eberhardt (2013). AMG accounts for cross-sectional dependence via a two-step procedure:
Fit a pooled first-difference regression of \(\Delta y_{it}\) on \(\Delta x_{it}\) augmented with \(T-1\) time dummies.
Extract the time-dummy coefficients as the Common Dynamic Process (CDP), a non-parametric proxy for unobserved common factors.
Cumulate the CDP within each unit (back to the level) and add it as an extra regressor in a unit-level OLS on levels.
Average the unit-level slopes (excluding the CDP) to obtain the AMG Mean Group estimate.
This implementation uses base R throughout and does not add any new package dependencies.