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lfe

summary.felm

Summarize felm model fits

Description

summary method for class "felm".

Usage

## S3 method for class 'felm'
summary(
  object,
  ...,
  robust = !is.null(object$clustervar) || getOption("lfe.robust"),
  lhs = NULL
)

Arguments

`object`	an object of class `"felm"`, a result of a call to `felm`.
`...`	further arguments passed to or from other methods.
`robust`	logical. Use robust standard errors. See notes.
`lhs`	character. If multiple left hand sides, specify the name of the one to obtain a summary for.

Value

The function summary.felm returns an object of class "summary.felm". It is quite similar to en "summary.lm" object, but not entirely compatible.

The "summary.felm" object is a list containing the following fields:

`residuals`	a numerical vector. The residuals of the full system, with dummies.
`p`	an integer. The total number of coefficients, including those projected out.
`Pp`	an integer. The number of coefficients, excluding those projected out.
`coefficients`	a Pp x 4 matrix with columns for the estimated coefficients, their standard errors, t-statistic and corresponding (two-sided) p-value.
`rse`	residual standard error.
`r2`	R^2, the fraction of variance explained by the model.
`r2adj`	Adjusted R^2.
`fstat`	F-statistic.
`pval`	P-values.
`P.fstat`	Projected F-statistic. The result of a call to `waldtest`
`fe`	list of factors. A list of the terms in the second part of the model.
`lhs.`	character. If `object` is the result of an estimation with multiple left hand sides, the actual argument `lhs` will be copied to this field.
`iv1fstat`	F-statistic for excluded instruments in 1. step IV, see `felm`.
`iv1pval`	P-value for `iv1fstat`.

Note

The standard errors are adjusted for the reduced degrees of freedom coming from the dummies which are implicitly present. They are also small-sample corrected.

If the robust parameter is FALSE, the returned object will contain ordinary standard errors. If the robust parameter is TRUE, clustered standard errors are reported if a cluster was specified in the call to felm; if not, heteroskedastic robust standard errors are reported.

Several F-statistics reported. The P.fstat is for the projected system. I.e. a joint test on whether all the Pp coefficients in coefficients are zero. Then there are fstat and pval which is a test on all the coefficients including the ones projected out, except for an intercept. This statistic assumes i.i.d. errors and is not reliable for robust or clustered data.

For a 1st stage IV-regression, an F-statistic against the model with excluded instruments is also computed.