linearmodels.panel.model.FamaMacBeth.fit

FamaMacBeth.fit(cov_type='unadjusted', debiased=True, bandwidth=None, kernel=None)[source]

Estimate model parameters

Parameters:
cov_typestr

Name of covariance estimator (see notes). Default is “unadjusted”.

debiasedbool

Flag indicating whether to debiased the covariance estimator using a degree of freedom adjustment.

bandwidthfloat

The bandwidth to use when cov_type is “kernel”. If None, it is automatically computed.

kernelstr

The kernel to use. None chooses the default kernel.

Returns:
PanelResults

Estimation results

Notes

Two covariance estimators are supported:

  • “unadjusted”, “homoskedastic”, “robust”, “heteroskedastic” use the standard covariance estimator of the T parameter estimates.

  • “kernel” is a HAC estimator. Configurations options are:

Examples

>>> from linearmodels import FamaMacBeth
>>> mod = FamaMacBeth(y, x)
>>> res = mod.fit(cov_type="kernel", kernel="Parzen")
Return type:

FamaMacBethResults