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IVREG2: Stata module for extended instrumental variables/2SLS and GMM estimation

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Author Info
Christopher F Baum () (Boston College)
Mark E Schaffer () (Heriot-Watt University)
Steven Stillman () (Motu Economic and Public Policy Research)

Additional information is available for the following registered author(s):

Abstract

ivreg2 provides extensions to Stata's official ivreg and newey. ivreg2 supports the same command syntax as official ivreg and supports (almost) all of its options. The main extensions: two-step feasible GMM estimation; continuously updated GMM estimation (CUE); LIML and k-class estimation; automatic output of the Hansen-Sargan or Anderson-Rubin statistic for overidentifying restrictions; C statistic test of exogeneity of subsets of instruments (orthog() option); kernel-based autocorrelation-consistent (AC) and heteroskedastic and autocorrelation-consistent (HAC) estimation, with user-specified choice of kernel; Cragg's "heteroskedastic OLS" (HOLS) estimator; default reporting of large-sample statistics (z and chi-squared rather than t and F); small option to report small-sample statistics; first-stage regression reported with F-test of excluded instruments and R-squared with included instruments "partialled-out"; enhanced Kleibergen-Paap and Cragg-Donald tests for weak instruments, redundancy of instruments, significance of endogenous regressors. ivreg2 can also be used for ordinary least squares (OLS) estimation using the same command syntax as Stata's official regress and newey. This is version 2.2.08 of ivreg2, updated from that published in Stata Journal, 5(4), requiring Stata 9.2 or better. Stata 8 users may use ivreg28 (q.v.) Stata 7 users may use the Stata Journal version of ivreg2, accessible via net search ivreg2.

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Publisher Info
Software component provided by Boston College Department of Economics in its series Statistical Software Components with number S425401.

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Programming language: Stata
Requires: Stata version 9.2
Date of creation: 02 Apr 2002
Date of revision: 04 May 2008
Handle: RePEc:boc:bocode:s425401

Note: This module may be installed from within Stata by typing "ssc install ivreg2". Windows users should not attempt to download these files with a web browser.
Contact details of provider:
Postal: Boston College, 140 Commonwealth Avenue, Chestnut Hill MA 02467 USA
Phone: 617-552-3670
Fax: +1-617-552-2308
Email:
Web page: http://fmwww.bc.edu/EC/
More information through EDIRC

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Web: http://repec.org/docs/ssc.php

For technical questions regarding this item, or to correct its listing, contact: (Christopher F Baum).

Related research
Keywords: instrumental variables Sargan test robust estimation orthogonality GMM Hansen's J heteroskedastic OLS HAC bandwidth k-class estimator LIML

Cited by:
(explanations, Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.)

  1. Natalia Trofimenko, 2005. "Learning by Exporting: Does It Matter Where One Learns?," Kiel Working Papers 1262, Kiel Institute for the World Economy. [Downloadable!]
  2. Kleck, Gary & Kovandzic, Tomislav & Schaffer, Mark E, 2005. "Gun Prevalence, Homicide Rates and Causality: A GMM Approach to Endogeneity Bias," CEPR Discussion Papers 5357, C.E.P.R. Discussion Papers. [Downloadable!] (restricted)
Statistics
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This page was last updated on 2008-5-9.

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