Artikel
Identification- and singularity-robust inference for moment condition models
This paper introduces a new identification- and singularity-robust conditional quasi-likelihood ratio (SR-CQLR) test and a new identification- and singularity-robust Anderson and Rubin (1949) (SR-AR) test for linear and nonlinear moment condition models. Both tests are very fast to compute. The paper shows that the tests have correct asymptotic size and are asymptotically similar (in a uniform sense) under very weak conditions. For example, in i.i.d. scenarios, all that is required is that the moment functions and their derivatives have 2 + Ú bounded moments for some Ú > 0. No conditions are placed on the expected Jacobian of the moment functions, on the eigenvalues of the variance matrix of the moment functions, or on the eigenvalues of the expected outer product of the (vectorized) orthogonalized sample Jacobian of the moment functions. The SR-CQLR test is shown to be asymptotically efficient in a GMM sense under strong and semi-strong identification (for all k Ï p, where k and p are the numbers of moment conditions and parameters, respectively). The SR-CQLR test reduces asymptotically to Moreira's CLR test when p = 1 in the homoskedastic linear IV model. The same is true for p Ï 2 in most, but not all, identification scenarios. We also introduce versions of the SR-CQLR and SR-AR tests for subvector hypotheses and show that they have correct asymptotic size under the assumption that the parameters not under test are strongly identified. The subvector SR-CQLR test is shown to be asymptotically efficient in a GMM sense under strong and semi-strong identification. Asymptotics conditional likelihood ratio test confidence set identification inference moment conditions robust singular variance subvector test test weak identification weak instruments C10 C12
- Language
-
Englisch
- Bibliographic citation
-
Journal: Quantitative Economics ; ISSN: 1759-7331 ; Volume: 10 ; Year: 2019 ; Issue: 4 ; Pages: 1703-1746 ; New Haven, CT: The Econometric Society
- Classification
-
Wirtschaft
Econometric and Statistical Methods and Methodology: General
Hypothesis Testing: General
- Subject
-
Asymptotics
conditional likelihood ratio test
confidence set
identification
inference
moment conditions
robust
singular variance
subvector test
test
weak identification
weak instruments
- Event
-
Geistige Schöpfung
- (who)
-
Andrews, Donald W. K.
Guggenberger, Patrik
- Event
-
Veröffentlichung
- (who)
-
The Econometric Society
- (where)
-
New Haven, CT
- (when)
-
2019
- DOI
-
doi:10.3982/QE1219
- Handle
- Last update
-
10.03.2025, 11:43 AM CET
Data provider
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. If you have any questions about the object, please contact the data provider.
Object type
- Artikel
Associated
- Andrews, Donald W. K.
- Guggenberger, Patrik
- The Econometric Society
Time of origin
- 2019
Other Objects (12)
Semiparametric Estimation and Inference Using Doubly Robust Moment Conditions
Robust inference in deconvolution
Inference using simulated neural moments
Robust inference with clustered data
Robust inference with clustered data
Averaging of moment condition estimators
Indirect inference: Which moments to match?
Robust Bayesian inference in proxy SVARs
Robust Inference in Risk Elicitation Tasks
Robust Bayesian inference in proxy SVARs
Robust inference with multi-way clustering
Thirty years of heteroskedasticity-robust inference
Semiparametric Estimation and Inference Using Doubly Robust Moment Conditions
Robust inference in deconvolution
Inference using simulated neural moments
Robust inference with clustered data
Robust inference with clustered data
Averaging of moment condition estimators
Indirect inference: Which moments to match?
Robust Bayesian inference in proxy SVARs
Robust Inference in Risk Elicitation Tasks
Robust Bayesian inference in proxy SVARs
Robust inference with multi-way clustering
Thirty years of heteroskedasticity-robust inference
Semiparametric Estimation and Inference Using Doubly Robust Moment Conditions
Robust inference in deconvolution
Inference using simulated neural moments
Robust inference with clustered data
Robust inference with clustered data
Averaging of moment condition estimators
Indirect inference: Which moments to match?
Robust Bayesian inference in proxy SVARs
Robust Inference in Risk Elicitation Tasks
Robust Bayesian inference in proxy SVARs
Robust inference with multi-way clustering