# summary.felm

##### Summarize felm model fits

`summary`

method for class `"felm"`

.

##### Usage

```
# S3 method for felm
summary(object, ..., robust = !is.null(object$clustervar),
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:

a numerical vector. The residuals of the full system, with dummies.

an integer. The total number of coefficients, including those projected out.

an integer. The number of coefficients, excluding those projected out.

a Pp x 4 matrix with columns for the estimated coefficients, their standard errors, t-statistic and corresponding (two-sided) p-value.

residual standard error.

R^2, the fraction of variance explained by the model.

Adjusted R^2.

F-statistic.

P-values.

Projected F-statistic. The result of a
call to `waldtest`

list of factors. A list of the terms in the second part of the model.

character. If
`object`

is the result of an estimation with multiple left hand sides,
the actual argument `lhs`

will be copied to this field.

F-statistic for excluded instruments in 1. step IV, see
`felm`

.

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.

##### See Also

*Documentation reproduced from package lfe, version 2.8-2, License: Artistic-2.0*