Linear dynamic panel data modeling based on linear and
nonlinear moment conditions as proposed by
Holtz-Eakin, Newey, and Rosen (1988) <doi:10.2307/1913103>,
Ahn and Schmidt (1995) <doi:10.1016/0304-4076(94)01641-C>,
and Arellano and Bover (1995) <doi:10.1016/0304-4076(94)01642-D>.
Estimation of the model parameters relies on the Generalized
Method of Moments (GMM), numerical optimization (when nonlinear
moment conditions are employed) and the computation of closed
form solutions (when estimation is based on linear moment
conditions). One-step, two-step and iterated estimation is
available. of closed form solutions. For inference and specification
testing, Windmeijer (2005) <doi:10.1016/j.jeconom.2004.02.005>
and doubly corrected standard errors
(Hwang, Kang, Lee, 2021 <doi:10.1016/j.jeconom.2020.09.010>)
are available. Additionally, serial correlation tests, tests for
overidentification, and Wald tests are provided. Functions for
visualizing panel data structures and modeling results obtained
from GMM estimation are also available. The plot methods include
functions to plot unbalanced panel structure, coefficient ranges
and coefficient paths across GMM iterations (the latter is
implemented according to the plot shown in
Hansen and Lee, 2021 <doi:10.3982/ECTA16274>).

Linear dynamic panel data modeling based on linear and
nonlinear moment conditions as proposed by
Holtz-Eakin, Newey, and Rosen (1988) <doi:10.2307/1913103>,
Ahn and Schmidt (1995) <doi:10.1016/0304-4076(94)01641-C>,
and Arellano and Bover (1995) <doi:10.1016/0304-4076(94)01642-D>.
Estimation of the model parameters relies on the Generalized
Method of Moments (GMM), numerical optimization (when nonlinear
moment conditions are employed) and the computation of closed
form solutions (when estimation is based on linear moment
conditions). One-step, two-step and iterated estimation is
available. For inference and specification
testing, Windmeijer (2005) <doi:10.1016/j.jeconom.2004.02.005>
and doubly corrected standard errors
(Hwang, Kang, Lee, 2021 <doi:10.1016/j.jeconom.2020.09.010>)
are available. Additionally, serial correlation tests, tests for
overidentification, and Wald tests are provided. Functions for
visualizing panel data structures and modeling results obtained
from GMM estimation are also available. The plot methods include
functions to plot unbalanced panel structure, coefficient ranges
and coefficient paths across GMM iterations (the latter is
implemented according to the plot shown in
Hansen and Lee, 2021 <doi:10.3982/ECTA16274>).
For a more detailed description of the functionality, please
see Fritsch, Pua, Schnurbus (2021) <doi:10.32614/RJ-2021-035>.