2009
DOI: 10.1111/j.1468-0084.2008.00542.x
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A Note on the Theme of Too Many Instruments*

Abstract: The difference and system generalized method of moments (GMM) estimators are growing in popularity. As implemented in popular software, the estimators easily generate instruments that are numerous and, in system GMM, potentially suspect. A large instrument collection overfits endogenous variables even as it weakens the Hansen test of the instruments' joint validity. This paper reviews the evidence on the effects of instrument proliferation, and describes and simulates simple ways to control it. It illustrates … Show more

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Cited by 4,052 publications
(2,288 citation statements)
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References 37 publications
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“…For example, Windmeijer (2005) observes that when instrument counts are lowered mean bias of parameters are lowered as well. In a similar vein, Roodman (2009a) notes that increases in the instrument count can lead to overestimation of parameters. Moreover, León-González and Montolio (2015) find that models which involve nearer lags as instruments have larger posterior probability.…”
Section: Sensitivity Analysis Of the Resultsmentioning
confidence: 99%
“…For example, Windmeijer (2005) observes that when instrument counts are lowered mean bias of parameters are lowered as well. In a similar vein, Roodman (2009a) notes that increases in the instrument count can lead to overestimation of parameters. Moreover, León-González and Montolio (2015) find that models which involve nearer lags as instruments have larger posterior probability.…”
Section: Sensitivity Analysis Of the Resultsmentioning
confidence: 99%
“…AR(1) is also a test for the presence of first order serial autocorrelation and in this case presence of serial autocorrelation is strongly rejected. The Hansen test for instrument validity is within the required range (0.10 -0.25) as stated by Roodman (2009a and2009b). Also the number of instruments are reasonably less than the number of countries in the panel (Elbahnasawy and Ellis (2016)).…”
Section: Sensitivity Testmentioning
confidence: 88%
“…In this regard a highly significant p-value of the AR(1) and a small p-value of the Hansen test are desirable since they respectively signify the absence of first order serial correlation and validity of instruments. According to Roodman (2009a and2009b) a Hansen p-value above 0.10 but not greater than 0.25 is a good benchmark for validity of instruments. He warned that a p-value close to 0.25 and above should be viewed with great concern since it shows the weakening of system GMM model due to instrument proliferation.…”
Section: Methodology and Datamentioning
confidence: 99%
“…When the instruments count is high they may fail to expunge their endogenous components, biasing coefficient estimates toward those from non-instrumenting estimators, as discussed by (Roodman 2009a(Roodman , 2009b. With the limitation of lags we overcome this problem, e.g., we will keep the number of instruments lower than the number of countries.…”
Section: Data Econometric Specification and Summary Statisticsmentioning
confidence: 99%