pwartest | R Documentation |

Test of serial correlation for (the idiosyncratic component of) the errors in fixed–effects panel models.

```
pwartest(x, ...)
## S3 method for class 'formula'
pwartest(x, data, ...)
## S3 method for class 'panelmodel'
pwartest(x, ...)
```

`x` |
an object of class |

`...` |
further arguments to be passed on to |

`data` |
a |

As \insertCiteWOOL:10;textualplm, Sec. 10.5.4 observes, under
the null of no serial correlation in the errors, the residuals of a
FE model must be negatively serially correlated, with
`cor(\hat{u}_{it}, \hat{u}_{is})=-1/(T-1)`

for each
`t,s`

. He suggests basing a test for this null hypothesis on a
pooled regression of FE residuals on their first lag:
```
\hat{u}_{i,t} = \alpha + \delta \hat{u}_{i,t-1} +
\eta_{i,t}
```

. Rejecting the restriction `\delta = -1/(T-1)`

makes us conclude against the original null of no serial
correlation.

`pwartest`

estimates the `within`

model and retrieves residuals,
then estimates an AR(1) `pooling`

model on them. The test statistic
is obtained by applying a F test to the latter model to test the
above restriction on `\delta`

, setting the covariance matrix to
`vcovHC`

with the option `method="arellano"`

to control for serial
correlation.

Unlike the `pbgtest()`

and `pdwtest()`

, this test does
not rely on large–T asymptotics and has therefore good properties in
“short” panels. Furthermore, it is robust to general heteroskedasticity.

An object of class `"htest"`

.

Giovanni Millo

WOOL:02plm

\insertRefWOOL:10plm

`pwfdtest()`

, `pdwtest()`

, `pbgtest()`

, `pbltest()`

,
`pbsytest()`

.

```
data("EmplUK", package = "plm")
pwartest(log(emp) ~ log(wage) + log(capital), data = EmplUK)
# pass argument 'type' to vcovHC used in test
pwartest(log(emp) ~ log(wage) + log(capital), data = EmplUK, type = "HC3")
```

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