Folklore Theorems, Implicit Maps, and Indirect Inference

The delta method and continuous mapping theorem are among the most extensively used tools in asymptotic derivations in econometrics. Extensions of these methods are provided for sequences of functions that are commonly encountered in applications and where the usual methods sometimes fail. Important...

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Main Author: Peter C. B. PHILLIPS
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Language:English
Published: Institutional Knowledge at Singapore Management University 2012
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Online Access:https://ink.library.smu.edu.sg/soe_research/1826
https://ink.library.smu.edu.sg/context/soe_research/article/2825/viewcontent/FolkloreTheoremsImplicitMapsIndirectInference_2010_pp.pdf
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spelling sg-smu-ink.soe_research-28252017-08-06T00:54:04Z Folklore Theorems, Implicit Maps, and Indirect Inference Peter C. B. PHILLIPS, The delta method and continuous mapping theorem are among the most extensively used tools in asymptotic derivations in econometrics. Extensions of these methods are provided for sequences of functions that are commonly encountered in applications and where the usual methods sometimes fail. Important examples of failure arise in the use of simulation-based estimation methods such as indirect inference. The paper explores the application of these methods to the indirect inference estimator (IIE) in first order autoregressive estimation. The IIE uses a binding function that is sample size dependent. Its limit theory relies on a sequence-based delta method in the stationary case and a sequence-based implicit continuous mapping theorem in unit root and local to unity cases. The new limit theory shows that the IIE achieves much more than (partial) bias correction. It changes the limit theory of the maximum likelihood estimator (MLE) when the autoregressive coefficient is in the locality of unity, reducing the bias and the variance of the MLE without affecting the limit theory of the MLE in the stationary case. Thus, in spite of the fact that the IIE is a continuously differentiable function of the MLE, the limit distribution of the IIE is not simply a scale multiple of the MLE, but depends implicitly on the full binding function mapping. The unit root case therefore represents an important example of the failure of the delta method and shows the need for an implicit mapping extension of the continuous mapping theorem. 2012-01-01T08:00:00Z text application/pdf https://ink.library.smu.edu.sg/soe_research/1826 info:doi/10.3982/ECTA9350 https://ink.library.smu.edu.sg/context/soe_research/article/2825/viewcontent/FolkloreTheoremsImplicitMapsIndirectInference_2010_pp.pdf http://creativecommons.org/licenses/by-nc-nd/4.0/ Research Collection School Of Economics eng Institutional Knowledge at Singapore Management University Binding function Delta method Exact bias Implicit continuous maps Indirect inference Maximum likelihood Econometrics
institution Singapore Management University
building SMU Libraries
continent Asia
country Singapore
Singapore
content_provider SMU Libraries
collection InK@SMU
language English
topic Binding function
Delta method
Exact bias
Implicit continuous maps
Indirect inference
Maximum likelihood
Econometrics
spellingShingle Binding function
Delta method
Exact bias
Implicit continuous maps
Indirect inference
Maximum likelihood
Econometrics
Peter C. B. PHILLIPS,
Folklore Theorems, Implicit Maps, and Indirect Inference
description The delta method and continuous mapping theorem are among the most extensively used tools in asymptotic derivations in econometrics. Extensions of these methods are provided for sequences of functions that are commonly encountered in applications and where the usual methods sometimes fail. Important examples of failure arise in the use of simulation-based estimation methods such as indirect inference. The paper explores the application of these methods to the indirect inference estimator (IIE) in first order autoregressive estimation. The IIE uses a binding function that is sample size dependent. Its limit theory relies on a sequence-based delta method in the stationary case and a sequence-based implicit continuous mapping theorem in unit root and local to unity cases. The new limit theory shows that the IIE achieves much more than (partial) bias correction. It changes the limit theory of the maximum likelihood estimator (MLE) when the autoregressive coefficient is in the locality of unity, reducing the bias and the variance of the MLE without affecting the limit theory of the MLE in the stationary case. Thus, in spite of the fact that the IIE is a continuously differentiable function of the MLE, the limit distribution of the IIE is not simply a scale multiple of the MLE, but depends implicitly on the full binding function mapping. The unit root case therefore represents an important example of the failure of the delta method and shows the need for an implicit mapping extension of the continuous mapping theorem.
format text
author Peter C. B. PHILLIPS,
author_facet Peter C. B. PHILLIPS,
author_sort Peter C. B. PHILLIPS,
title Folklore Theorems, Implicit Maps, and Indirect Inference
title_short Folklore Theorems, Implicit Maps, and Indirect Inference
title_full Folklore Theorems, Implicit Maps, and Indirect Inference
title_fullStr Folklore Theorems, Implicit Maps, and Indirect Inference
title_full_unstemmed Folklore Theorems, Implicit Maps, and Indirect Inference
title_sort folklore theorems, implicit maps, and indirect inference
publisher Institutional Knowledge at Singapore Management University
publishDate 2012
url https://ink.library.smu.edu.sg/soe_research/1826
https://ink.library.smu.edu.sg/context/soe_research/article/2825/viewcontent/FolkloreTheoremsImplicitMapsIndirectInference_2010_pp.pdf
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