plm (version 1.6-5)

pht: Hausman--Taylor Estimator for Panel Data

Description

The Hausman--Taylor estimator is an instrumental variable estimator without external instruments.

Usage

pht(formula, data, subset, na.action, model = c("ht", "am", "bmc"), index = NULL, ...)
"summary"(object, ...)
"print"(x, digits = max(3, getOption("digits") - 2), width = getOption("width"), subset = NULL, ...)

Arguments

formula

a symbolic description for the model to be estimated,

object,x

an object of class "plm",

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,

digits

digits,

width

the maximum length of the lines in the print output,

...

further arguments.

Value

An object of class c("pht", "plm", "panelmodel").A "pht" object contains the same elements as plm, 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.

References

Amemiya, T. and MaCurdy, T.E. (1986) Instrumental--variable estimation of an error components model, Econometrica, 54(4), pp. 869--880.

Baltagi, Badi H. (2013) Econometric Analysis of Panel Data, 5th ed., John Wiley and Sons.

Breusch, T.S., Mizon, G.E. and Schmidt, P. (1989) Efficient estimation using panel data, Econometrica, 57(3), pp. 695--700. Hausman, J.A. and Taylor W.E. (1981) Panel data and unobservable individual effects, Econometrica, 49(6), pp. 1377--1398.

Examples

# replicates Baltagi (2005, 2013), table 7.4
data("Wages", package = "plm")
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)