pht | R Documentation |

The Hausman–Taylor estimator is an instrumental variable estimator without external instruments (function deprecated).

```
pht(
formula,
data,
subset,
na.action,
model = c("ht", "am", "bms"),
index = NULL,
...
)
## S3 method for class 'pht'
summary(object, ...)
## S3 method for class 'summary.pht'
print(
x,
digits = max(3, getOption("digits") - 2),
width = getOption("width"),
subset = NULL,
...
)
```

`formula` |
a symbolic description for the model to be estimated, |

`data` |
a |

`subset` |
see |

`na.action` |
see |

`model` |
one of |

`index` |
the indexes, |

`...` |
further arguments. |

`object, x` |
an object of class |

`digits` |
digits, |

`width` |
the maximum length of the lines in the print output, |

`pht`

estimates panels models using the Hausman–Taylor estimator,
Amemiya–MaCurdy estimator, or Breusch–Mizon–Schmidt estimator, depending
on the argument `model`

. The model is specified as a two–part formula,
the second part containing the exogenous variables.

An object of class `c("pht", "plm", "panelmodel")`

.

A `"pht"`

object contains the same elements as `plm`

object, with a further argument called `varlist`

which
describes the typology of the variables. It has `summary`

and
`print.summary`

methods.

The function `pht`

is deprecated. Please use function `plm`

to estimate Taylor–Hausman models like this with a three-part
formula as shown in the example:

`plm(<formula>, random.method = "ht", model = "random", inst.method = "baltagi")`

. The Amemiya–MaCurdy estimator and the
Breusch–Mizon–Schmidt estimator is computed likewise with
`plm`

.

Yves Croissant

AMEM:MACU:86plm

\insertCiteBALT:13plm

\insertCiteBREU:MIZO:SCHM:89plm

\insertCiteHAUS:TAYL:81plm

```
## replicates Baltagi (2005, 2013), table 7.4; Baltagi (2021), table 7.5
## preferred way with plm()
data("Wages", package = "plm")
ht <- plm(lwage ~ wks + south + smsa + married + exp + I(exp ^ 2) +
bluecol + ind + union + sex + black + ed |
bluecol + south + smsa + ind + sex + black |
wks + married + union + exp + I(exp ^ 2),
data = Wages, index = 595,
random.method = "ht", model = "random", inst.method = "baltagi")
summary(ht)
am <- plm(lwage ~ wks + south + smsa + married + exp + I(exp ^ 2) +
bluecol + ind + union + sex + black + ed |
bluecol + south + smsa + ind + sex + black |
wks + married + union + exp + I(exp ^ 2),
data = Wages, index = 595,
random.method = "ht", model = "random", inst.method = "am")
summary(am)
## deprecated way with pht() for HT
#ht <- pht(lwage ~ wks + south + smsa + married + exp + I(exp^2) +
# bluecol + ind + union + sex + black + ed |
# sex + black + bluecol + south + smsa + ind,
# data = Wages, model = "ht", index = 595)
#summary(ht)
# deprecated way with pht() for AM
#am <- pht(lwage ~ wks + south + smsa + married + exp + I(exp^2) +
# bluecol + ind + union + sex + black + ed |
# sex + black + bluecol + south + smsa + ind,
# data = Wages, model = "am", index = 595)
#summary(am)
```

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