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“Panel Data Econometrics with R”

Panel data models

  • Panel standard errors : A simple approach for panel data is to fit the pooling (or independence) model (e.g., via lm() or glm()) and only correct the standard errors. Different types of clustered, panel, and panel-corrected standard errors are available in sandwich (incorporating prior work from multiwayvcov), clusterSEspcseclubSandwichplm, and geepack, respectively. The latter two require estimation of the pooling/independence models via plm() and geeglm() from the respective packages (which also provide other types of models, see below).
  • Linear panel models plm, providing a wide range of within, between, and random-effect methods (among others) along with corrected standard errors, tests, etc. Another implementation of several of these models is in Paneldata. Various dynamic panel models are available in plm and dynamic panel models with fixed effects in OrthoPanelsfeisr provides fixed effects individual slope (FEIS) models. Within-between(or “hybrid”) panel models are available in panelr, including multilevel, GEE, and Bayesian estimation of these models. Panel vector autoregressions are implemented inpanelvar.
  • Generalized estimation equations and GLMs : GEE models for panel data (or longitudinal data in statistical jargon) are in geepack. The pglm package provides estimation of GLM-like models for panel data.
  • Mixed effects models : Linear and nonlinear models for panel data (and more general multi-level data) are available in lme4 and nlme.
  • Instrumental variables ivfixed and ivpanel, see also above.
  • Heterogeneous time trends phtt offers the possibility of analyzing panel data with large dimensions n and T and can be considered when the unobserved heterogeneity effects are time-varying.
  • Miscellaneous : Multiple group fixed effects are in lfe. Autocorrelation and heteroscedasticity correction in are available in wahc and panelAR. PANIC Tests of nonstationarity are in PANICr. Threshold regression and unit root tests are in pdR. The panel data approach method for program evaluation is available in pampe.