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Ill-conditioned problems, Fisher information, and weak instruments

Ill-conditioned problems, Fisher information, and weak instruments
Ill-conditioned problems, Fisher information, and weak instruments
The existence of a uniformly consistent estimator for a particular parameter is well-known to depend on the uniform continuity of the functional that defines the parameter in terms of the model. Recently, Potscher (Econometrica, 70, pp 1035 - 1065) showed that estimator risk may be bounded below by a term that depends on the oscillation (osc) of the functional, thus making the connection between continuity and risk quite explicit. However, osc has no direct statistical interpretation. In this paper we slightly modify the definition of osc so that it reflects a (generalized) derivative (der) of the functional. We show that der can be directly related to the familiar statistical concepts of Fisher information and identification, and also to the condition numbers that are used to measure ‘distance from an ill-posed problem’ in other branches of applied mathematics. We begin the analysis assuming a fully parametric setting, but then generalize to the nonparametric case, where the inverse of the Fisher information matrix is replaced by the covariance matrix of the efficient influence function. The results are applied to a number of examples, including the structural equation model, spectral density estimation, and estimation of variance and precision.
CWP04/05
IFS
Forchini, Giovanni
e5ed4ef7-02d1-491d-8105-c9e36baa2ad6
Hillier, Grant
3423bd61-c35f-497e-87a3-6a5fca73a2a1
Forchini, Giovanni
e5ed4ef7-02d1-491d-8105-c9e36baa2ad6
Hillier, Grant
3423bd61-c35f-497e-87a3-6a5fca73a2a1

Forchini, Giovanni and Hillier, Grant (2005) Ill-conditioned problems, Fisher information, and weak instruments (CeMMAP Working Papers, CWP04/05) London, GB. IFS

Record type: Monograph (Working Paper)

Abstract

The existence of a uniformly consistent estimator for a particular parameter is well-known to depend on the uniform continuity of the functional that defines the parameter in terms of the model. Recently, Potscher (Econometrica, 70, pp 1035 - 1065) showed that estimator risk may be bounded below by a term that depends on the oscillation (osc) of the functional, thus making the connection between continuity and risk quite explicit. However, osc has no direct statistical interpretation. In this paper we slightly modify the definition of osc so that it reflects a (generalized) derivative (der) of the functional. We show that der can be directly related to the familiar statistical concepts of Fisher information and identification, and also to the condition numbers that are used to measure ‘distance from an ill-posed problem’ in other branches of applied mathematics. We begin the analysis assuming a fully parametric setting, but then generalize to the nonparametric case, where the inverse of the Fisher information matrix is replaced by the covariance matrix of the efficient influence function. The results are applied to a number of examples, including the structural equation model, spectral density estimation, and estimation of variance and precision.

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Published date: 2005

Identifiers

Local EPrints ID: 80159
URI: http://eprints.soton.ac.uk/id/eprint/80159
PURE UUID: e726c4ce-62a3-421e-8840-6e5ea302120d
ORCID for Grant Hillier: ORCID iD orcid.org/0000-0003-3261-5766

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Date deposited: 24 Mar 2010
Last modified: 20 Dec 2023 02:33

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Contributors

Author: Giovanni Forchini
Author: Grant Hillier ORCID iD

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