lfe (version 1.0-418)

felm: Fitting linear models with multiple group fixed effects

Description

'felm' is used to fit linear models with multiple group fixed effects, similarly to lm. It uses the Method of Alternating projections to sweep out multiple group effects from the normal equations.

This function is intended for use with large datasets with multiple group effects of large cardinality. If dummy-encoding the group effects results in a manageable number of coefficients, you are probably better off by using lm or package lme4.

Usage

felm(model,fl,data)

Arguments

model

an object of class '"formula"' (or one that can be coerced to that class: a symbolic description of the model to be fitted. Similarly to 'lm'

fl

a list of factors defining the groups. The list must have unique names, see Examples section.

data

a data frame containing the variables of the model

Value

• felm return an object of class "lm.fe". The content of this is currently not documented, but there is a method print.lm.fe which may be used to display the content in a similar way as for lm.

See Also

getfe

Examples

## create covariates
x <- rnorm(100)
x2 <- rnorm(length(x))

## individual and firm
id <- factor(sample(10,length(x),replace=TRUE))
firm <- factor(sample(3,length(x),replace=TRUE))

## effects for them
id.eff <- rnorm(nlevels(id))
firm.eff <- rnorm(nlevels(firm))

## left hand side
y <- x + 0.5*x2 + id.eff[id] + firm.eff[firm] + rnorm(length(x))

## estimate and print result
est <- felm(y ~ x+x2,fl=list(id=id,firm=firm),data=data.frame(y,x,x2))
print(est)
print(getfe(est))