pdynmc version 0.9.11

Update of version 0.9.10 that adds three estimation functions for the lag parameter of AR(1) panel data models. Additionally, the update allows for user-specified dummy matrix in estimation function. For this purpose, the internal helper function corSparse which was adopted from package ‘qlcMatrix’ in a previous function update was adjusted. Additionally, the argument checks of the estimation function were updated and an option to collapse the moment conditions was added.






pdynmc version 0.9.10

Update of version 0.9.9 that generalizes functionality of functions for exploratory analysis of panel data. The function corSparse from package ‘qlcMatrix’ was added as internal helper function, as the aforementioned package was scheduled to be moved from CRAN to the archive by 2023-11-29. Additionally, bug fixes are provided for the estimation function and the documentation of the package is adjusted according to the new CRAN recommendation.




pdynmc version 0.9.9

Update of version 0.9.8 which adds new function for visualization of evolution of empirical density of a variable of interest over longitudinal dimension of a panel dataset. Additionally, typos in description of cigDemand dataset are adjusted and further information is added to summary of `pdynmc’ objects.


functions for exploratory analysis of panel data added

pdynmc version 0.9.8

Update of version 0.9.7 which adds functionality for excluding the lagged dependent variable from the right-hand-side of the equation. Additionally, the update adds the published version of the article as vignette, ensures correct rendering of the package documentation (thanks to Kevin Tappe), and corrects minor bugs in the estimation function (thanks to Github user Dazhwu).


pdynmc version 0.9.7

Update of version 0.9.6 which updates the estimation function, the functions for visualizing the panel data structure, and adds two datasets to the package. The functionality for deriving instruments and estimating parameters: Covariates for which no parameters are estimated, but from which instruments are derived and covariates for which parameters for which parameters are estimated, but from which no instruments are derived.





pdynmc version 0.9.6

Minor update of version 0.9.5 which adds doubly corrected standard errors. Also, commits and suggestions of github user tappek are added. Additionally, the compatibility of the estimation function with further input data structures is improved and a bug in the estimation function when multiple instruments from non-lagged dependent endogenous covariates are derived is corrected.





pdynmc version 0.9.5

Minor update of version 0.9.4 which adds further functionality and argument checks to estimation function. Additionally, the computation underlying non-robust two-step standard errors is adjusted (option accessible by changing argument “std.err” from its default to “std.err = unadjusted”) and the functions for deriving instruments from further exogenous covariates were adjusted to comply with data requirements.


pdynmc version 0.9.4

Minor update of version 0.9.3 in which package DESCRIPTION, CITATION, and documentation is adjusted and two further package vignettes are added.

new vignettes

pdynmc version 0.9.3

Minor update of version 0.9.2 that fixes minor bugs in estimation function and helper functions for setting up instrument and weighting matrix; additionally, coefficient path plots are added to the plot method and existing plot methods are adjusted.



pdynmc version 0.9.2

Minor update of version 0.9.1 that adds additional functionality for setting up the instrument matrix and adjusts the instrument count displayed by the summary function.



pdynmc version 0.9.1

Minor update of version 0.9.0 that fixes a bug in the estimation function, adjusts matrix calculations to achieve minor speed improvements, and robustifies general linear hypothesis testing functionality.



pdynmc version 0.9.0

Update of version 0.8.0 that includes visualizations for fitted model objects (coefficient-range plots for two-step and iterated estimation and plots of fitted values vs. residuals) and panel data structure

functions for exploratory analysis of panel data added

generic functions added

methods added