pht

0th

Percentile

Hausman--Taylor Estimator for Panel Data

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

Keywords
regression
Usage
pht(
  formula,
  data,
  subset,
  na.action,
  model = c("ht", "am", "bms"),
  index = NULL,
  ...
)

# S3 method for pht summary(object, ...)

# S3 method for summary.pht print( x, digits = max(3, getOption("digits") - 2), width = getOption("width"), subset = NULL, ... )

Arguments
formula

a symbolic description for the model to be estimated,

data

a data.frame,

subset

see lm() for "plm", a character or numeric vector indicating a subset of the table of coefficient to be printed for "print.summary.plm",

na.action

see lm(),

model

one of "ht" for Hausman--Taylor, "am" for Amemiya--MaCurdy and "bms" for Breusch--Mizon--Schmidt,

index

the indexes,

further arguments.

object, x

an object of class "plm",

digits

digits,

width

the maximum length of the lines in the print output,

Details

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.

Value

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.

Note

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.

References

AMEM:MACU:86plm

BALT:13plm

BREU:MIZO:SCHM:89plm

HAUS:TAYL:81plm

Aliases
  • pht
  • summary.pht
  • print.summary.pht
Examples
# NOT RUN {
## replicates Baltagi (2005, 2013), table 7.4
## 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)


# }
Documentation reproduced from package plm, version 2.2-5, License: GPL (>= 2)

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