Instrumental-Variables Regression by '2SLS', '2SM', or '2SMM', with Diagnostics

Instrumental variable estimation for linear models by two-stage least-squares (2SLS) regression or by robust-regression via M-estimation (2SM) or MM-estimation (2SMM). The main ivreg() model-fitting function is designed to provide a workflow as similar as possible to standard lm() regression. A wide range of methods is provided for fitted ivreg model objects, including extensive functionality for computing and graphing regression diagnostics in addition to other standard model tools.

Two-Stage Least-Squares Regression with Diagnostics

An implementation of instrumental variables regression using two-stage least-squares (2SLS) estimation, based on the ivreg() function previously in the AER package. In addition to standard regression functionality (parameter estimation, inference, predictions, etc.) the package provides various regression diagnostics, including hat values, deletion diagnostics such as studentized residuals and Cook’s distances; graphical diagnostics such as component-plus-residual plots and added-variable plots; and effect plots with partial residuals.

Instrumental variables regression:

library("ivreg")
ivreg(Q ~ P + D | D + F + A, data = Kmenta)

Via two-stage least squares (2SLS):

With diagnostics: