linearmodels.panel.model.PooledOLS

class PooledOLS(dependent, exog, *, weights=None)

Pooled coefficient estimator for panel data

Parameters

dependentarray_like

Dependent (left-hand-side) variable (time by entity)

exogarray_like

Exogenous or right-hand-side variables (variable by time by entity).

weightsarray_like, optional

Weights to use in estimation. Assumes residual variance is proportional to inverse of weight to that the residual time the weight should be homoskedastic.

Notes

The model is given by

\[y_{it}=\beta^{\prime}x_{it}+\epsilon_{it}\]

Methods

fit(self, \*, cov_type, debiased, …)	Estimate model parameters
from_formula(formula, data, numpy.ndarray, …)	Create a model from a formula
predict(self, params, …)	Predict values for additional data
reformat_clusters(self, clusters, …)	Reformat cluster variables

Properties

formula	Formula used to construct the model
has_constant	Flag indicating the model a constant or implicit constant
not_null	Locations of non-missing observations