The function estimates a linear dynamic panel data model of the form
$$y_{i,t} = y_{i,t-1} \rho_1 + a_i + \varepsilon_{i,t}$$
where \(y_{i,t-1}\) is the lagged dependent variable, \(\rho_1\) is
the lag parameter, \(a_i\) is an unobserved individual specific effect,
and \(\varepsilon_{i,t}\) is an idiosyncratic remainder component. The
model structure accounts for unobserved individual specific heterogeneity
and dynamics. Note that more general lag structures and further covariates
are beyond the scope of the current implementation in pdynmc.
The nonlinear IV estimator employs an alternative formulation of the
nonlinear moment conditions of AhnSch1995;textualpdynmc.
More details on the implementation and the properties of the estimator
are provided in FriPuaSch2024;textualpdynmc.