# feis: Fixed Effects Individual Slope Estimator In feisr: Estimating Fixed Effects Individual Slope Models

 feis R 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 `NA`s 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

`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.