Module Reference

Models for Panel Data

PanelOLS(dependent, exog, *[, weights, …])

One- and two-way fixed effects estimator for panel data

RandomEffects(dependent, exog, *[, weights])

One-way Random Effects model for panel data

BetweenOLS(dependent, exog, *[, weights])

Between estimator for panel data

FirstDifferenceOLS(dependent, exog, *[, weights])

First difference model for panel data

PooledOLS(dependent, exog, *[, weights])

Pooled coefficient estimator for panel data

FamaMacBeth(dependent, exog, *[, weights])

Pooled coefficient estimator for panel data

Estimation Results

FamaMacBethResults(res)

Results container for Fama MacBeth panel data models

PanelResults(res)

Results container for panel data models that do not include effects

PanelEffectsResults(res)

Results container for panel data models that include effects

RandomEffectsResults(res)

Results container for random effect panel data models

PanelModelComparison(results, *[, precision])

Comparison of multiple models

Panel Model Covariance Estimators

HomoskedasticCovariance(y, x, params, …[, …])

Homoskedastic covariance estimation

HeteroskedasticCovariance(y, x, params, …)

Covariance estimation using White estimator

ClusteredCovariance(y, x, params, …[, …])

One-way (Rogers) or two-way clustered covariance estimation

DriscollKraay(y, x, params, entity_ids, …)

Driscoll-Kraay heteroskedasticity-autocorrelation robust covariance estimation

ACCovariance(y, x, params, entity_ids, …)

Autocorrelation robust covariance estimation

FamaMacBethCovariance(y, x, params, …[, …])

HAC estimator for Fama-MacBeth estimator

Panel Data Structures

PanelData(x[, var_name, convert_dummies, …])

Abstraction to handle alternative formats for panel data

Helper Functions

generate_panel_data(nentity, ntime, nexog, …)

Parameters