tsls: Two-Stage Least Squares Estimation (TSLS)

In hdm: High-Dimensional Metrics

Description

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

Usage

tsls(x, ...)

## Default S3 method:
tsls(x, d, y, z, intercept = TRUE, homoscedastic = TRUE,
  ...)

## S3 method for class 'formula'
tsls(formula, data, intercept = TRUE,
  homoscedastic = TRUE, ...)

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.

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

hdm documentation built on May 1, 2019, 7:56 p.m.