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Weak Identification with Bounds in a Class of Minimum Distance Models

Gregory Fletcher Cox

arXiv 21 Dec 2020 · Econometrics

arXiv:2012.11222 · PDF · Extracted main text

Abstract

When parameters are weakly identified, bounds on the parameters may provide a valuable source of information. Existing weak identification estimation and inference results are unable to combine weak identification with bounds. Within a class of minimum distance models, this paper proposes identification-robust inference that incorporates information from bounds when parameters are weakly identified. This paper demonstrates the value of the bounds and identification-robust inference in a simple latent factor model and a simple GARCH model. This paper also demonstrates the identification-robust inference in an empirical application, a factor model for parental investments in children.

Citation extraction

49
references
122
in-text mentions
49
distinct cited
4
self-citations
20,538
main-text words

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Most heavily cited references

The works this paper leans on most, across its whole bibliography — not restricted to papers in our corpus. Ranked by composite intensity, which combines how often a work is mentioned, how many sections mention it, and how much of that falls in the main text rather than the appendix.

ReferenceIntensityMentionsSectionsMain text
1Cox, G (2024) Weak identification in low-dimensional factor models with one or two factors self1.000155100%
2Stock, J. and Wright, J (2000) GMM with weak identification1.00093100%
3Kleibergen, F (2005) Testing parameters in GMM without assuming that they are identified1.00063100%
4Han, S. and McCloskey, A (2019) Estimation and inference with a (nearly) singular Jacobian1.00053100%
5Andrews, D (1999) Estimation when a parameter is on a boundary0.92843100%
6Attanasio, O., Cattan, S., Fitzsimons, E., Meghir, C., and Rubio-Cod… (2020) Estimating the production function for human capital: Results from a randomized controlled trial in Colombia0.87472100%
7Andrews, D. and Guggenberger, P (2019) Identification- and singularity-robust inference for moment condition models0.87452100%
8Bugni, F., Canay, I., and Shi, X (2017) Inference for subvectors and other functions of partially identified parameters in moment inequality models0.81142100%
9Kaido, H., Molinari, F., and Stoye, J (2019) Confidence intervals for projections of partially identified parameters0.81142100%
10Andrews, D (2001) Testing when a parameter is on the boundary of the maintained hypothesis0.73732100%

Showing the top 10 of 49 scored citations.

Cited by, within the corpus

arXiv econ.EM papers that cite this one, ranked by how heavily they lean on it.

Citing paperIntensityMentionsSections
1Weak Identification in Low-Dimensional Factor Models with One or Two Factors1.00074
2A Generalized Argmax Theorem with Applications0.87452
3Almost Sure Uniqueness of a Global Minimum Without Convexity0.64441
4Allowing for weak identification when testing GARCH-X type models0.40511
5Robust Inference when Nuisance Parameters may be Partially Identified with Applications to Synthetic Controls0.40511
6Testing Inequalities Linear in Nuisance Parameters0.40511