tsls: Two-Stage Least Squares Estimation (TSLS)

Description

The function does Two-Stage Least Squares Estimation (TSLS).

Usage

tsls(x, ...)
# S3 method for default
tsls(x, d, y, z, intercept = TRUE, homoscedastic = TRUE, ...)
# S3 method for formula
tsls(formula, data, intercept = TRUE, homoscedastic = TRUE, ...)

Value

The function returns a list with the following elements

coefficients: coefficients
vcov: variance-covariance matrix
residuals: outcome minus predicted values
call: function call
samplesize: sample size
se: standard error

Arguments

x: exogenous variables
...: further arguments (only for consistent defintion of methods)
d: endogenous variables
y: outcome variable
z: instruments
intercept: logical, if intercept should be included
homoscedastic: logical, if homoscedastic (TRUE, default) or heteroscedastic erros (FALSE) should be calculated.
formula: An object of class Formula of the form " y ~ x + d | x + z" with y the outcome variable, d endogenous variable, z instrumental variables, and x exogenous variables.
data: An optional data frame, list or environment (or object coercible by as.data.frame to a data frame) containing the variables in the model. If not found in data, the variables are taken from environment(formula), typically the environment from which tsls is called.

Details

The function computes tsls estimate (coefficients) and variance-covariance-matrix assuming homoskedasticity for outcome variable y where d are endogenous variables in structural equation, x are exogensous variables in structural equation and z are instruments. It returns an object of class tsls for which the methods print and summary are provided.