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plm (version 2.4-1)

Linear Models for Panel Data

Description

A set of estimators and tests for panel data econometrics, as described in Baltagi (2013), Econometric Analysis of Panel Data, ISBN-13:978-1-118-67232-7, Hsiao (2014), Analysis of Panel Data , and Croissant and Millo (2018), Panel Data Econometrics with R, ISBN-13:978-1-118-94918-4.

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Version

Install

install.packages('plm')

Monthly Downloads

37,995

Version

2.4-1

License

GPL (>= 2)

Homepage

https://cran.r-project.org/package=plm

Maintainer

Yves Croissant

Last Published

March 2nd, 2021

Functions in plm (2.4-1)

Crime in North Carolina

Grunfeld's Investment Data

Wages and Hours Worked

Purchasing Power Parity and other parity relationships

Hedonic Prices of Census Tracts in the Boston Area

Employment and Wages in the United Kingdom

Production of Rice in Indonesia

Wages and Education of Young Males

US States Production

The Penn World Table, v. 5

Cigarette Consumption

Employment and Wages in Spain

lag, lead, and diff for panel data

Check if an object is a pseries

Panel Data of Individual Wages

Cross--sectional correlation matrix

Estimation of the error components

Common Correlated Effects estimators

model.frame.pdata.frame

model.frame and model.matrix for panel data

Arellano--Bond Test of Serial Correlation

Extract the Fixed Effects

Chamberlain estimator and test for fixed effects

Tests of cross-section dependence for panel models

Angrist and Newey's version of Chamberlain test for fixed effects

Gasoline Consumption

Extract Total Number of Observations Used in Estimated Panelmodel

Check for the presence of an intercept in a formula or in a fitted model

Check for the Dimensions of the Panel

Hausman--Taylor Estimator for Panel Data

Extract the indexes of panel data

data.frame for panel data

Deprecated functions of plm

Panel estimators for limited dependent variables

Functions to detect linear dependence

Wald-style Chi-square Test and F Test

Hausman Test for Panel Models

Variable Coefficients Models for Panel Data

Breusch--Godfrey Test for Panel Models

make.pconsecutive

Make data consecutive (and, optionally, also balanced)

is.pconsecutive

Check if time periods are consecutive

Check if data are balanced

Make data balanced

Cross-sectionally Augmented IPS Test for Unit Roots in Panel Models

Wooldridge Test for AR(1) Errors in FE Panel Models

punbalancedness

Measures for Unbalancedness of Panel Data

Baltagi and Li Serial Dependence Test For Random Effects Models

within_intercept

Overall Intercept for Within Models Along its Standard Error

Wooldridge first--difference--based test for AR(1) errors in levels or first--differenced panel models

Durbin--Watson Test for Panel Models

plm package: linear models for panel data

F Test for Individual and/or Time Effects

General FGLS Estimators

Generalized Method of Moments (GMM) Estimation for Panel Data

Modified BNF--Durbin--Watson Test and Baltagi--Wu's LBI Test for Panel Models

Bera, Sosa-Escudero and Yoon Locally--Robust Lagrange Multiplier Tests for Panel Models and Joint Test by Baltagi and Li

Panel Data Estimators

Mean Groups (MG), Demeaned MG and CCE MG estimators

Test of Poolability

Lagrange FF Multiplier Tests for Panel Models

pmodel.response

A function to extract the model.response

Newey and West (1987) Robust Covariance Matrix Estimator

Extract the Random Effects

Panel Granger (Non-)Causality Test (Dumitrescu/Hurlin (2012))

Option to Switch On/Off Fast Data Transformations

summary.plm.list

Summary for plm objects

Generic Lego building block for Robust Covariance Matrix Estimators

Hansen--Sargan Test of Overidentifying Restrictions

Robust Covariance Matrix Estimators

Driscoll and Kraay (1998) Robust Covariance Matrix Estimator

Double-Clustering Robust Covariance Matrix Estimator

Beck and Katz Robust Covariance Matrix Estimators

re-export_functions

Functions exported from other packages

R squared and adjusted R squared for panel models

Check for Cross-Sectional and Time Variation

Unit root tests for panel data

Wooldridge's Test for Unobserved Effects in Panel Models