Description Usage Arguments Details Value Note Author(s) References Examples
The Hausman–Taylor estimator is an instrumental variable estimator without external instruments (function deprecated).
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 |
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
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 | ## 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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