pht function

Hausman--Taylor Estimator for Panel Data

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,
  ...
)

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,

Returns

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.

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.

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.

Examples

## 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)

References

\insertCite AMEM:MACU:86plm

\insertCite BALT:13plm

\insertCite BREU:MIZO:SCHM:89plm

\insertCite HAUS:TAYL:81plm

Author(s)

Yves Croissant