scholarly journals Confidence sets for dynamic poverty indexes

2021 ◽  
pp. 1-20
Author(s):  
Guglielmo D'Amico ◽  
Riccardo De Blasis
Keyword(s):  
Confidence Sets ◽  
Poverty Indexes

scholarly journals Confidence sets for optimal factor levels of a response surface

Biometrics ◽  
2016 ◽  
Vol 72 (4) ◽  
pp. 1285-1293 ◽  
Author(s):  
Fang Wan ◽  
Wei Liu ◽  
Frank Bretz ◽  
Yang Han
Keyword(s):  
Response Surface ◽  
Confidence Sets

Improved confidence estimators for Fieller's confidence sets

1998 ◽  
Vol 26 (2) ◽  
pp. 299-310 ◽  
Author(s):  
C. Andy Tsao ◽  
J. T. Gene Hwang
Keyword(s):  
Confidence Sets

scholarly journals Invariant Confidence Sets with Smallest Expected Measure

1982 ◽  
Vol 10 (4) ◽  
pp. 1283-1294 ◽  
Author(s):  
Peter M. Hooper
Keyword(s):  
Confidence Sets

Determining risk model confidence sets

2017 ◽  
Vol 22 ◽  
pp. 169-174
Author(s):  
Mark Cummins ◽  
Michael Dowling ◽  
Francesco Esposito
Keyword(s):  
Risk Model ◽  
Confidence Sets ◽  
Model Confidence

scholarly journals ASYMPTOTIC SIZE OF KLEIBERGEN’S LM AND CONDITIONAL LR TESTS FOR MOMENT CONDITION MODELS

2016 ◽  
Vol 33 (5) ◽  
pp. 1046-1080 ◽  
Author(s):  
Donald W.K. Andrews ◽  
Patrik Guggenberger
Keyword(s):  
Moment Condition ◽  
Rank Statistic ◽  
Confidence Sets ◽  
Null Distributions ◽  
Asymptotic Size ◽  
Instrumental Variable Regression ◽  
Lm Test ◽  
Endogenous Variables ◽  
Influential Paper ◽  
Special Case

An influential paper by Kleibergen (2005, Econometrica 73, 1103–1123) introduces Lagrange multiplier (LM) and conditional likelihood ratio-like (CLR) tests for nonlinear moment condition models. These procedures aim to have good size performance even when the parameters are unidentified or poorly identified. However, the asymptotic size and similarity (in a uniform sense) of these procedures have not been determined in the literature. This paper does so.This paper shows that the LM test has correct asymptotic size and is asymptotically similar for a suitably chosen parameter space of null distributions. It shows that the CLR tests also have these properties when the dimension p of the unknown parameter θ equals 1. When p ≥ 2, however, the asymptotic size properties are found to depend on how the conditioning statistic, upon which the CLR tests depend, is weighted. Two weighting methods have been suggested in the literature. The paper shows that the CLR tests are guaranteed to have correct asymptotic size when p ≥ 2 when the weighting is based on an estimator of the variance of the sample moments, i.e., moment-variance weighting, combined with the Robin and Smith (2000, Econometric Theory 16, 151–175) rank statistic. The paper also determines a formula for the asymptotic size of the CLR test when the weighting is based on an estimator of the variance of the sample Jacobian. However, the results of the paper do not guarantee correct asymptotic size when p ≥ 2 with the Jacobian-variance weighting, combined with the Robin and Smith (2000, Econometric Theory 16, 151–175) rank statistic, because two key sample quantities are not necessarily asymptotically independent under some identification scenarios.Analogous results for confidence sets are provided. Even for the special case of a linear instrumental variable regression model with two or more right-hand side endogenous variables, the results of the paper are new to the literature.

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