feis: Fixed Effects Individual Slope Estimator

View source: R/feis.R

feisR Documentation

Fixed Effects Individual Slope Estimator

Description

Estimates fixed effects individual slope estimators by applying linear lm models to "detrended" data.

Usage

feis(
  formula,
  data,
  id,
  weights = NULL,
  robust = FALSE,
  intercept = FALSE,
  dropgroups = FALSE,
  tol = .Machine$double.eps,
  ...
)

## S3 method for class 'feis'
formula(x, lhs = NULL, rhs = NULL, ...)

## S3 method for class 'feis'
terms(x, lhs = NULL, rhs = NULL, ...)

## S3 method for class 'feis'
residuals(object, ...)

## S3 method for class 'feis'
df.residual(object, ...)

## S3 method for class 'feis'
coef(object, ...)

## S3 method for class 'feis'
sigma(object, ...)

## S3 method for class 'feis'
deviance(object, ...)

## S3 method for class 'feis'
nobs(object, ...)

## S3 method for class 'feis'
fitted(object, ...)

## S3 method for class 'feis'
hatvalues(model, ...)

Arguments

formula

a symbolic description for the model to be fitted (see Details).

data

a data.frame containing the specified variables.

id

the name of a unique group / person identifier (as string).

weights

an optional vector of weights to be used in the fitting process. See lm.

robust

logical. If TRUE estimates cluster robust standard errors (default is FALSE).

intercept

logical. If TRUE estimates the model with an intercept (default is FALSE).

dropgroups

logical. If TRUE groups without any within variance on a slope variable are dropped , if FALSE those variables are omitted for the respective groups only (default is FALSE).

tol

the tolerance for detecting linear dependencies in the residual maker transformation (see solve). The argument is forwarded to bsfeistest.

...

further arguments.

lhs, rhs

indexes of the left- and right-hand side for the methods formula and terms.

object, x, model

an object of class "feis".

Details

feis is a special function to estimate linear fixed effects models with individual-specific slopes. In contrast to conventional fixed effects models, data are not person "demeaned", but "detrended" by the predicted individual slope of each person \insertCiteBruderl.2015.387,Ruttenauer.2020,Wooldridge.2010.384feisr.

Estimation requires at least q+1 observations per unit, where q is the number of slope parameters (including a constant). feis automatically selects only those groups from the current data set which have at least q+1 observations. The function returns a warning if units with <q+1 observations are dropped.

The function requires a two-part formula, in which the second part indicates the slope parameter(s). If, for example, the model is y ~ x1 + x2, with the slope variables x3 and x4, the model can be estimated with:

  • formula = y ~ x1 + x2 | x3 + x4

To estimate a conventional fixed effects model without individual slopes, please use y ~ x1 + x2 | 1 to indicate that the slopes should only contain an individual-specific intercept.

If specified, feis estimates panel-robust standard errors. Panel-robust standard errors are robust to arbitrary forms of serial correlation within groups formed by id as well as heteroscedasticity across groups \insertCite@see @Wooldridge.2010.384, pp. 379-381feisr.

The model output can be exported using the texreg package.

Value

An object of class "feis", containing the following elements:

coefficients

the vector of coefficients.

vcov

the scaled (if specified, robust) variance-covariance matrix of the coefficients. See vcov.feis for unscaled vcov

.

residuals

the vector of residuals (computed from the "detrended" data).

df.residual

degrees of freedom of the residuals.

formula

an object of class "Formula" describing the model.

model

the original model frame as a data.frame containing the original variables used for estimation.

modelhat

a constructed model frame as a data.frame containing the predicted values from the first stage regression using the slope variable(s) as predictor(s).

modeltrans

a constructed model frame as a data.frame containing the "detrended" variables used for the final model estimation. Note that the weights are already used for detrending if specified.

response

the vector of the "detrended" response variable.

fitted.values

the vector of fitted values (computed from the "detrended" data).

id

a vector containing the unique person identifier.

weights

a vector containing weights used in fitting, or integer 1 if not speficied in call.

call

the matched call.

assign

assign attributes of the formula.

na.omit

(where relevant) a vector of the omitted observations. The only handling method of NAs is "omit".

contrasts

(only where relevant) the contrasts used.

arg

a list containing the used methods. Only "feis" and "individual" effects available.

slopevars

a character vector containing the names of the slope variables.

r2

R squared of the "detrended" model.

adj.r2

adjusted R squared of the "detrended" model.

vcov_arg

a character containing the method used to compute the variance-covariance matrix.

tol

the tolerance parameter (for use in bsfeistest).

References

\insertAllCited

See Also

summary.feis, plm, pvcm, pmg, feistest

Examples

data("mwp", package = "feisr")
feis.mod <- feis(lnw ~ marry + enrol + as.factor(yeargr) | exp + I(exp^2),
                 data = mwp, id = "id", robust = TRUE)
summary(feis.mod)


feisr documentation built on April 1, 2022, 5:06 p.m.