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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:

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Version

Install

install.packages('ivreg')

Monthly Downloads

9,736

Version

0.6-2

License

GPL (>= 2)

Maintainer

Achim Zeileis

Last Published

March 17th, 2023

Functions in ivreg (0.6-2)

Kmenta

Partly Artificial Data on the U.S. Economy
influence.ivreg

Deletion and Other Diagnostic Methods for "ivreg" Objects
coef.ivreg

Methods for "ivreg" Objects
ivreg

Instrumental-Variable Regression by 2SLS, 2SM, or 2SMM Estimation
SchoolingReturns

U.S. Returns to Schooling Data
ivreg.fit

Fitting Instrumental-Variable Regressions by 2SLS, 2SM, or 2SMM Estimation
CigaretteDemand

U.S. Cigarette Demand Data