# pooltest: Test of Poolability In plm: Linear Models for Panel Data

## Description

A Chow test for the poolability of the data.

## Usage

 ```1 2 3 4 5``` ```pooltest(x, ...) ## S3 method for class 'plm' pooltest(x, z, ...) ## S3 method for class 'formula' pooltest(x, data, ...) ```

## Arguments

 `x` an object of class `"plm"` for the plm method; an object of class `"formula"` for the formula interface, `z` an object of class `"pvcm"` obtained with `model="within"`, `data` a `data.frame`, `...` further arguments passed to plm.

## Details

`pooltest` is a F test of stability (or Chow test) for the coefficients of a panel model. For argument `x`, the estimated `plm` object should be a `"pooling"` model or a `"within"` model (the default); intercepts are assumed to be identical in the first case and different in the second case.

## Value

An object of class `"htest"`.

Yves Croissant

## Examples

 ``` 1 2 3 4 5 6 7 8 9 10``` ```data("Gasoline", package = "plm") form <- lgaspcar ~ lincomep + lrpmg + lcarpcap gasw <- plm(form, data = Gasoline, model = "within") gasp <- plm(form, data = Gasoline, model = "pooling") gasnp <- pvcm(form, data = Gasoline, model = "within") pooltest(gasw, gasnp) pooltest(gasp, gasnp) pooltest(form, data = Gasoline, effect = "individual", model = "within") pooltest(form, data = Gasoline, effect = "individual", model = "pooling") ```

### Example output

```Loading required package: Formula

F statistic

data:  form
F = 27.335, df1 = 51, df2 = 270, p-value < 2.2e-16
alternative hypothesis: unstability

F statistic

data:  form
F = 129.32, df1 = 68, df2 = 270, p-value < 2.2e-16
alternative hypothesis: unstability

F statistic

data:  form
F = 27.335, df1 = 51, df2 = 270, p-value < 2.2e-16
alternative hypothesis: unstability

F statistic

data:  form
F = 129.32, df1 = 68, df2 = 270, p-value < 2.2e-16
alternative hypothesis: unstability
```

plm documentation built on March 18, 2018, 1:10 p.m.