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Many Instruments ∗
, 2009
"... This paper considers specification testing for instrumental variables estimation in the presence of many instruments. The test proposed is a modified version of the Sargan (1958, Econometrica 26(3): 393415) test of overidentifying restrictions. The test statistic asymptotically follows the standard ..."
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Cited by 2 (0 self)
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This paper considers specification testing for instrumental variables estimation in the presence of many instruments. The test proposed is a modified version of the Sargan (1958, Econometrica 26(3): 393415) test of overidentifying restrictions. The test statistic asymptotically follows
Regularized LIML for many instruments
, 2013
"... The use of many moment conditions improves the asymptotic e ¢ ciency of the instrumental variables estimators. However, in
nite samples, the inclusion of an excessive number of moments increases the bias. To solve this problem, we propose regularized versions of the limited information maximum li ..."
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The use of many moment conditions improves the asymptotic e ¢ ciency of the instrumental variables estimators. However, in
nite samples, the inclusion of an excessive number of moments increases the bias. To solve this problem, we propose regularized versions of the limited information maximum
A Note on the Theme of Too Many Instruments
"... The Difference and System generalized method of moments (GMM) estimators are growing in popularity, thanks in part to specialized software. But as implemented in these packages, the estimators easily generate results by default that are at once invalid yet appear valid in specification tests. The cu ..."
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Cited by 208 (2 self)
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. The culprit is their tendency to generate instruments that are a) numerous and, in System GMM, b) suspect. A large collection of instruments, even if individually valid, can be collectively invalid in finite samples because they overfit endogenous variables. They also weaken the Hansen test of overidentifying
tMany instruments
"... parameter based on the approximate MSE. A Monte Carlo study and two empirical applications illustrate the relevance of our estimators. ..."
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parameter based on the approximate MSE. A Monte Carlo study and two empirical applications illustrate the relevance of our estimators.
MINIMUM DISTANCE APPROACH TO INFERENCE WITH MANY INSTRUMENTS∗
, 2015
"... Minimum distance approach to inference with many instruments ..."
Instrumental Variable Estimation with Heteroskedasticity and Many Instruments ∗
, 2006
"... This paper gives a relatively simple, well behaved solution to the problem of many instruments in heteroskedastic data. Such settings are common in microeconometric applications where many instruments are used to improve efficiency and allowance for heteroskedasticity is generally important. The sol ..."
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Cited by 23 (2 self)
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This paper gives a relatively simple, well behaved solution to the problem of many instruments in heteroskedastic data. Such settings are common in microeconometric applications where many instruments are used to improve efficiency and allowance for heteroskedasticity is generally important
2006) Estimation with Many Instrumental Variables mimeo
"... Using many valid instrumental variables has the potential to improve efficiency but makes the usual inference procedures inaccurate. We give corrected standard errors, an extension of Bekker (1994) to nonnormal disturbances, that adjust for many instruments. We find that this adjustment is useful in ..."
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Cited by 48 (4 self)
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Using many valid instrumental variables has the potential to improve efficiency but makes the usual inference procedures inaccurate. We give corrected standard errors, an extension of Bekker (1994) to nonnormal disturbances, that adjust for many instruments. We find that this adjustment is useful
A Short Note on the Theme of Too Many Instruments
 Journal of Monetary Economics
, 2000
"... The “difference ” and “system ” generalized method of moments (GMM) estimators for dynamic panel models are growing steadily in popularity. The estimators are designed for panels with short time dimensions (T), and by default they generate instruments sets whose number grows quadratically in T. The ..."
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Cited by 68 (2 self)
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. The dangers associated with having many instruments relative to observations are documented in the applied literature. The instruments can overfit endogenous variables, failing to expunge their endogenous components and biasing coefficient estimates. Meanwhile they can vitiate the Hansen J test for joint
On the Asymptotic Optimality of the LIML Estimator with Possibly Many Instruments ∗
, 2007
"... We consider the estimation of the coefficients of a linear structural equation in a simultaneous equation system when there are many instrumental variables. We derive some asymptotic properties of the limited information maximum likelihood (LIML) estimator when the number of instruments is large; so ..."
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Cited by 10 (5 self)
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We consider the estimation of the coefficients of a linear structural equation in a simultaneous equation system when there are many instrumental variables. We derive some asymptotic properties of the limited information maximum likelihood (LIML) estimator when the number of instruments is large
An Optimal Modification of the LIML Estimation for Many Instruments and Persistent
, 2009
"... We consider the estimation of coefficients of a structural equation with many instrumental variables in a simultaneous equation system. It is mathematically equivalent to an estimating equation estimation or a reduced rank regression in the statistical linear models when the number of restrictions o ..."
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We consider the estimation of coefficients of a structural equation with many instrumental variables in a simultaneous equation system. It is mathematically equivalent to an estimating equation estimation or a reduced rank regression in the statistical linear models when the number of restrictions
Results 1  10
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