Nonparametric instrumental variable derivative estimation

The focus of this paper is the nonparametric estimation of the marginal effects (i.e. first partial derivatives) of an instrumental regression function π defined by conditional moment restrictions that stem from a structural econometric model [Formula omitted.] , and involve endogenous variables Y a...

Full description

Saved in:
Bibliographic Details
Published in:Journal of nonparametric statistics 2018-04, Vol.30 (2), p.368-391
Main Authors: Florens, J. P., Racine, J. S., Centorrino, S.
Format: Article
Language:English
Subjects:
Econometrics
Economic models
Ill posed problems
Inverse problems
Nonparametric statistics
Regularization
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
cited_by cdi_FETCH-LOGICAL-c281t-7d6d13852d27509714a6a3d6581d15e37fd3f57c9b4f3c95946a070a6031d6593
cites cdi_FETCH-LOGICAL-c281t-7d6d13852d27509714a6a3d6581d15e37fd3f57c9b4f3c95946a070a6031d6593
container_end_page 391
container_issue 2
container_start_page 368
container_title Journal of nonparametric statistics
container_volume 30
creator Florens, J. P.
Racine, J. S.
Centorrino, S.
description The focus of this paper is the nonparametric estimation of the marginal effects (i.e. first partial derivatives) of an instrumental regression function π defined by conditional moment restrictions that stem from a structural econometric model [Formula omitted.] , and involve endogenous variables Y and Z and instruments W. The derivative function [Formula omitted.] is the solution of an ill-posed inverse problem and we propose an estimation procedure based on Landweber-Fridman regularisation. We provide theoretical underpinnings of the proposed approach, examine finite-sample performance, and consider an illustrative application.
doi_str_mv 10.1080/10485252.2018.1428745
format article
fullrecord <record><control><sourceid>proquest_cross</sourceid><recordid>TN_cdi_proquest_journals_2030749458</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>2030749458</sourcerecordid><originalsourceid>FETCH-LOGICAL-c281t-7d6d13852d27509714a6a3d6581d15e37fd3f57c9b4f3c95946a070a6031d6593</originalsourceid><addsrcrecordid>eNo1kEtLxDAUhYMoOI7-BKHguvXePJpkKYMvGHSj65BpUujQl0lb8N-bMuPqnsXHPYePkHuEAkHBIwJXggpaUEBVIKdKcnFBNghU58AQL9fMVb5C1-QmxiMAspLBhuiPoR9tsJ2fQlNlTR-nMHe-n2ybLTY09tD6zPnQLHZqFp_5ODVdikN_S65q20Z_d75b8v3y_LV7y_efr--7p31eUYVTLl3pkKV9jkoBWiK3pWWuFAodCs9k7VgtZKUPvGaVFpqXFiTYMg1PlGZb8nD6O4bhZ0795jjMoU-VhgIDyTUXKlHiRFVhiDH42owhDQ2_BsGslsy_JbNaMmdL7A_PG1kh</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2030749458</pqid></control><display><type>article</type><title>Nonparametric instrumental variable derivative estimation</title><source>Taylor and Francis Science and Technology Collection</source><creator>Florens, J. P. ; Racine, J. S. ; Centorrino, S.</creator><creatorcontrib>Florens, J. P. ; Racine, J. S. ; Centorrino, S.</creatorcontrib><description>The focus of this paper is the nonparametric estimation of the marginal effects (i.e. first partial derivatives) of an instrumental regression function π defined by conditional moment restrictions that stem from a structural econometric model [Formula omitted.] , and involve endogenous variables Y and Z and instruments W. The derivative function [Formula omitted.] is the solution of an ill-posed inverse problem and we propose an estimation procedure based on Landweber-Fridman regularisation. We provide theoretical underpinnings of the proposed approach, examine finite-sample performance, and consider an illustrative application.</description><identifier>ISSN: 1048-5252</identifier><identifier>EISSN: 1029-0311</identifier><identifier>DOI: 10.1080/10485252.2018.1428745</identifier><language>eng</language><publisher>Abingdon: Taylor &amp; Francis Ltd</publisher><subject>Econometrics ; Economic models ; Ill posed problems ; Inverse problems ; Nonparametric statistics ; Regularization</subject><ispartof>Journal of nonparametric statistics, 2018-04, Vol.30 (2), p.368-391</ispartof><rights>American Statistical Association and Taylor &amp; Francis 2018</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c281t-7d6d13852d27509714a6a3d6581d15e37fd3f57c9b4f3c95946a070a6031d6593</citedby><cites>FETCH-LOGICAL-c281t-7d6d13852d27509714a6a3d6581d15e37fd3f57c9b4f3c95946a070a6031d6593</cites><orcidid>0000-0001-8713-7197</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,777,781,27905,27906</link.rule.ids></links><search><creatorcontrib>Florens, J. P.</creatorcontrib><creatorcontrib>Racine, J. S.</creatorcontrib><creatorcontrib>Centorrino, S.</creatorcontrib><title>Nonparametric instrumental variable derivative estimation</title><title>Journal of nonparametric statistics</title><description>The focus of this paper is the nonparametric estimation of the marginal effects (i.e. first partial derivatives) of an instrumental regression function π defined by conditional moment restrictions that stem from a structural econometric model [Formula omitted.] , and involve endogenous variables Y and Z and instruments W. The derivative function [Formula omitted.] is the solution of an ill-posed inverse problem and we propose an estimation procedure based on Landweber-Fridman regularisation. We provide theoretical underpinnings of the proposed approach, examine finite-sample performance, and consider an illustrative application.</description><subject>Econometrics</subject><subject>Economic models</subject><subject>Ill posed problems</subject><subject>Inverse problems</subject><subject>Nonparametric statistics</subject><subject>Regularization</subject><issn>1048-5252</issn><issn>1029-0311</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2018</creationdate><recordtype>article</recordtype><recordid>eNo1kEtLxDAUhYMoOI7-BKHguvXePJpkKYMvGHSj65BpUujQl0lb8N-bMuPqnsXHPYePkHuEAkHBIwJXggpaUEBVIKdKcnFBNghU58AQL9fMVb5C1-QmxiMAspLBhuiPoR9tsJ2fQlNlTR-nMHe-n2ybLTY09tD6zPnQLHZqFp_5ODVdikN_S65q20Z_d75b8v3y_LV7y_efr--7p31eUYVTLl3pkKV9jkoBWiK3pWWuFAodCs9k7VgtZKUPvGaVFpqXFiTYMg1PlGZb8nD6O4bhZ0795jjMoU-VhgIDyTUXKlHiRFVhiDH42owhDQ2_BsGslsy_JbNaMmdL7A_PG1kh</recordid><startdate>20180403</startdate><enddate>20180403</enddate><creator>Florens, J. P.</creator><creator>Racine, J. S.</creator><creator>Centorrino, S.</creator><general>Taylor &amp; Francis Ltd</general><scope>AAYXX</scope><scope>CITATION</scope><scope>7SC</scope><scope>8FD</scope><scope>JQ2</scope><scope>L7M</scope><scope>L~C</scope><scope>L~D</scope><orcidid>https://orcid.org/0000-0001-8713-7197</orcidid></search><sort><creationdate>20180403</creationdate><title>Nonparametric instrumental variable derivative estimation</title><author>Florens, J. P. ; Racine, J. S. ; Centorrino, S.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c281t-7d6d13852d27509714a6a3d6581d15e37fd3f57c9b4f3c95946a070a6031d6593</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2018</creationdate><topic>Econometrics</topic><topic>Economic models</topic><topic>Ill posed problems</topic><topic>Inverse problems</topic><topic>Nonparametric statistics</topic><topic>Regularization</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Florens, J. P.</creatorcontrib><creatorcontrib>Racine, J. S.</creatorcontrib><creatorcontrib>Centorrino, S.</creatorcontrib><collection>CrossRef</collection><collection>Computer and Information Systems Abstracts</collection><collection>Technology Research Database</collection><collection>ProQuest Computer Science Collection</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>Computer and Information Systems Abstracts – Academic</collection><collection>Computer and Information Systems Abstracts Professional</collection><jtitle>Journal of nonparametric statistics</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Florens, J. P.</au><au>Racine, J. S.</au><au>Centorrino, S.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Nonparametric instrumental variable derivative estimation</atitle><jtitle>Journal of nonparametric statistics</jtitle><date>2018-04-03</date><risdate>2018</risdate><volume>30</volume><issue>2</issue><spage>368</spage><epage>391</epage><pages>368-391</pages><issn>1048-5252</issn><eissn>1029-0311</eissn><abstract>The focus of this paper is the nonparametric estimation of the marginal effects (i.e. first partial derivatives) of an instrumental regression function π defined by conditional moment restrictions that stem from a structural econometric model [Formula omitted.] , and involve endogenous variables Y and Z and instruments W. The derivative function [Formula omitted.] is the solution of an ill-posed inverse problem and we propose an estimation procedure based on Landweber-Fridman regularisation. We provide theoretical underpinnings of the proposed approach, examine finite-sample performance, and consider an illustrative application.</abstract><cop>Abingdon</cop><pub>Taylor &amp; Francis Ltd</pub><doi>10.1080/10485252.2018.1428745</doi><tpages>24</tpages><orcidid>https://orcid.org/0000-0001-8713-7197</orcidid></addata></record>
fulltext fulltext
identifier ISSN: 1048-5252
ispartof Journal of nonparametric statistics, 2018-04, Vol.30 (2), p.368-391
issn 1048-5252
1029-0311
language eng
recordid cdi_proquest_journals_2030749458
source Taylor and Francis Science and Technology Collection
subjects Econometrics
Economic models
Ill posed problems
Inverse problems
Nonparametric statistics
Regularization
title Nonparametric instrumental variable derivative estimation
url http://sfxeu10.hosted.exlibrisgroup.com/loughborough?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-21T07%3A30%3A46IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_cross&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Nonparametric%20instrumental%20variable%20derivative%20estimation&rft.jtitle=Journal%20of%20nonparametric%20statistics&rft.au=Florens,%20J.%20P.&rft.date=2018-04-03&rft.volume=30&rft.issue=2&rft.spage=368&rft.epage=391&rft.pages=368-391&rft.issn=1048-5252&rft.eissn=1029-0311&rft_id=info:doi/10.1080/10485252.2018.1428745&rft_dat=%3Cproquest_cross%3E2030749458%3C/proquest_cross%3E%3Cgrp_id%3Ecdi_FETCH-LOGICAL-c281t-7d6d13852d27509714a6a3d6581d15e37fd3f57c9b4f3c95946a070a6031d6593%3C/grp_id%3E%3Coa%3E%3C/oa%3E%3Curl%3E%3C/url%3E&rft_id=info:oai/&rft_pqid=2030749458&rft_id=info:pmid/&rfr_iscdi=true