INTERSECTION BOUNDS: ESTIMATION AND INFERENCE

We develop a practical and novel method for inference on intersection bounds, namely bounds defined by either the infimum or supremum of a parametric or nonparametric function, or, equivalently, the value of a linear programming problem with a potentially infinite constraint set. We show that many b...

Ausführliche Beschreibung

Gespeichert in:

Bibliographische Detailangaben
Veröffentlicht in:	Econometrica Jg. 81; H. 2; S. 667 - 737
Hauptverfasser:	Chernozhukov, Victor, Lee, Sokbae, Rosen, Adam M.
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Oxford, UK Econometric Society 01.03.2013 Blackwell Publishing Ltd
Schlagworte:	adaptive moment selection anti‐concentration inequalities Approximation Bias Bound analysis concentration inequalities conditional moments Critical values Econometrics Economic analysis Economic models Empirical tests Estimation bias Estimation methods Estimators Induktive Statistik Inequality Inference infinite‐dimensional constraints Interval estimators Linear programming Mathematical functions Mathematical independent variables Mathematische Optimierung moderate deviations non‐Donsker empirical process methods partial identification Probabilities Schätztheorie Series convergence Statistical inference strong approximation Studies Theorie
ISSN:	0012-9682, 1468-0262
Online-Zugang:	Volltext
Tags:	Tag hinzufügen Keine Tags, Fügen Sie den ersten Tag hinzu!

Abstract	We develop a practical and novel method for inference on intersection bounds, namely bounds defined by either the infimum or supremum of a parametric or nonparametric function, or, equivalently, the value of a linear programming problem with a potentially infinite constraint set. We show that many bounds characterizations in econometrics, for instance bounds on parameters under conditional moment inequalities, can be formulated as intersection bounds. Our approach is especially convenient for models comprised of a continuum of inequalities that are separable in parameters, and also applies to models with inequalities that are nonseparable in parameters. Since analog estimators for intersection bounds can be severely biased in finite samples, routinely underestimating the size of the identified set, we also offer a medianbias-corrected estimator of such bounds as a by-product of our inferential procedures. We develop theory for large sample inference based on the strong approximation of a sequence of series or kernel-based empirical processes by a sequence of "penultimate" Gaussian processes. These penultimate processes are generally not weakly convergent, and thus are non-Donsker. Our theoretical results establish that we can nonetheless perform asymptotically valid inference based on these processes. Our construction also provides new adaptive inequality/moment selection methods. We provide conditions for the use of nonparametric kernel and series estimators, including a novel result that establishes strong approximation for any general series estimator admitting linearization, which may be of independent interest.
AbstractList	We develop a practical and novel method for inference on intersection bounds, namely bounds defined by either the infimum or supremum of a parametric or nonparametric function, or, equivalently, the value of a linear programming problem with a potentially infinite constraint set. We show that many bounds characterizations in econometrics, for instance bounds on parameters under conditional moment inequalities, can be formulated as intersection bounds. Our approach is especially convenient for models comprised of a continuum of inequalities that are separable in parameters, and also applies to models with inequalities that are nonseparable in parameters. Since analog estimators for intersection bounds can be severely biased in finite samples, routinely underestimating the size of the identified set, we also offer a median‐bias‐corrected estimator of such bounds as a by‐product of our inferential procedures. We develop theory for large sample inference based on the strong approximation of a sequence of series or kernel‐based empirical processes by a sequence of “penultimate” Gaussian processes. These penultimate processes are generally not weakly convergent, and thus are non‐Donsker. Our theoretical results establish that we can nonetheless perform asymptotically valid inference based on these processes. Our construction also provides new adaptive inequality/moment selection methods. We provide conditions for the use of nonparametric kernel and series estimators, including a novel result that establishes strong approximation for any general series estimator admitting linearization, which may be of independent interest. We develop a practical and novel method for inference on intersection bounds, namely bounds defined by either the infimum or supremum of a parametric or nonparametric function, or, equivalently, the value of a linear programming problem with a potentially infinite constraint set. We show that many bounds characterizations in econometrics, for instance bounds on parameters under conditional moment inequalities, can be formulated as intersection bounds. Our approach is especially convenient for models comprised of a continuum of inequalities that are separable in parameters, and also applies to models with inequalities that are nonseparable in parameters. Since analog estimators for intersection bounds can be severely biased in finite samples, routinely underestimating the size of the identified set, we also offer a medianbias-corrected estimator of such bounds as a by-product of our inferential procedures. We develop theory for large sample inference based on the strong approximation of a sequence of series or kernel-based empirical processes by a sequence of "penultimate" Gaussian processes. These penultimate processes are generally not weakly convergent, and thus are non-Donsker. Our theoretical results establish that we can nonetheless perform asymptotically valid inference based on these processes. Our construction also provides new adaptive inequality/moment selection methods. We provide conditions for the use of nonparametric kernel and series estimators, including a novel result that establishes strong approximation for any general series estimator admitting linearization, which may be of independent interest. We develop a practical and novel method for inference on intersection bounds, namely bounds defined by either the infimum or supremum of a parametric or nonparametric function, or, equivalently, the value of a linear programming problem with a potentially infinite constraint set. We show that many bounds characterizations in econometrics, for instance bounds on parameters under conditional moment inequalities, can be formulated as intersection bounds. Our approach is especially convenient for models comprised of a continuum of inequalities that are separable in parameters, and also applies to models with inequalities that are nonseparable in parameters. Since analog estimators for intersection bounds can be severely biased in finite samples, routinely underestimating the size of the identified set, we also offer a median-bias‐ ;corrected estimator of such bounds as a by-product of our inferential procedures. We develop theory for large sample inference based on the strong approximation of a sequence of series or kernel-based empirical processes by a sequence of “ ;penultimate' Gaussian processes. These penultimate processes are generally not weakly convergent, and thus are non‐ ;Donsker. Our theoretical results establish that we can nonetheless perform asymptotically valid inference based on these processes. Our construction also provides new adaptive inequality/moment selection methods. We provide conditions for the use of nonparametric kernel and series estimators, including a novel result that establishes strong approximation for any general series estimator admitting linearization, which may be of independent interest. Reprinted by permission of the Econometric Society We develop a practical and novel method for inference on intersection bounds, namely bounds defined by either the infimum or supremum of a parametric or nonparametric function, or, equivalently, the value of a linear programming problem with a potentially infinite constraint set. We show that many bounds characterizations in econometrics, for instance bounds on parameters under conditional moment inequalities, can be formulated as intersection bounds. Our approach is especially convenient for models comprised of a continuum of inequalities that are separable in parameters, and also applies to models with inequalities that are nonseparable in parameters. Since analog estimators for intersection bounds can be severely biased in finite samples, routinely underestimating the size of the identified set, we also offer a median-bias-corrected estimator of such bounds as a by-product of our inferential procedures. We develop theory for large sample inference based on the strong approximation of a sequence of series or kernel-based empirical processes by a sequence of "penultimate" Gaussian processes. These penultimate processes are generally not weakly convergent, and thus are non-Donsker. Our theoretical results establish that we can nonetheless perform asymptotically valid inference based on these processes. Our construction also provides new adaptive inequality/moment selection methods. We provide conditions for the use of nonparametric kernel and series estimators, including a novel result that establishes strong approximation for any general series estimator admitting linearization, which may be of independent interest. [PUBLICATION ABSTRACT]
Author	Lee, Sokbae Chernozhukov, Victor Rosen, Adam M.
Author_xml	– sequence: 1 givenname: Victor surname: Chernozhukov fullname: Chernozhukov, Victor – sequence: 2 givenname: Sokbae surname: Lee fullname: Lee, Sokbae – sequence: 3 givenname: Adam M. surname: Rosen fullname: Rosen, Adam M.
BackLink	http://www.econis.eu/PPNSET?PPN=749555645$$DView this record in ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften
BookMark	eNp9kF9rwjAUxcNwMHWDfYExYS97qcv_pntztW4FV0Hrc4lphEptXVIZfvtF3RwIG1zI5fI7J4fTAa2qrjQAtwj2SSDwUxSmA-EjcQHaiHLhQcxxC7QhRNgLuMBXoGPtCkLI3LSBFydpNJ05VTxJei-TeTKcPfeiWRq_Dw6nQTLsxckomkZJGF2Dy6Usrb75frtgPorS8M0bT17jcDD2FIOEeQuaUxwssIA854RTH_s-y3PJlBJSB0pTrnPiLwXSuaLal1wSEbgbJgs_UJB0wePRd2Pqj622TbYurNJlKStdb22GCKYBo4QThz6coat6ayqXzlFICAY5Qo66P1Ja1VVhs40p1tLsMt_ZMMYp-_1Smdpao5cnBsFs32z206xD-2eoKhrZFHXVGFmU_wg-i1Lv_jQ-LC70PszdUbCyTW1OAkwYdsUy8gVnLowQ
CODEN	ECMTA7
CitedBy_id	crossref_primary_10_1016_j_euroecorev_2020_103392 crossref_primary_10_1093_qje_qjy015 crossref_primary_10_1080_01621459_2022_2093729 crossref_primary_10_1177_1536867X1501500205 crossref_primary_10_3982_ECTA18979 crossref_primary_10_1016_j_jeconom_2022_06_013 crossref_primary_10_1111_ecin_12900 crossref_primary_10_1016_j_jeconom_2019_08_001 crossref_primary_10_1162_REST_a_00618 crossref_primary_10_1016_j_jeconom_2013_08_005 crossref_primary_10_1016_j_jeconom_2023_105553 crossref_primary_10_1016_j_jspi_2015_12_005 crossref_primary_10_1162_REST_a_00622 crossref_primary_10_1016_j_jeconom_2023_105558 crossref_primary_10_1016_j_jeconom_2022_12_010 crossref_primary_10_1016_j_jeconom_2023_105556 crossref_primary_10_1016_j_jeconom_2025_105952 crossref_primary_10_1017_S0266466614000425 crossref_primary_10_3102_1076998618776435 crossref_primary_10_1515_snde_2014_0030 crossref_primary_10_1080_07474938_2025_2460540 crossref_primary_10_1002_sim_10108 crossref_primary_10_1080_07350015_2020_1847122 crossref_primary_10_1016_j_jeconom_2018_04_002 crossref_primary_10_1016_j_jeconom_2022_04_011 crossref_primary_10_1111_1756_2171_12323 crossref_primary_10_1016_j_jeconom_2016_04_001 crossref_primary_10_1016_j_jeconom_2024_105785 crossref_primary_10_1093_restud_rdaf001 crossref_primary_10_3982_QE1367 crossref_primary_10_1016_j_jeoa_2023_100467 crossref_primary_10_1007_s40505_014_0061_5 crossref_primary_10_1080_07350015_2023_2219283 crossref_primary_10_1016_j_jeconom_2020_03_020 crossref_primary_10_1016_j_jeconom_2016_01_010 crossref_primary_10_1016_j_labeco_2022_102185 crossref_primary_10_1093_restud_rdab039 crossref_primary_10_1016_j_jeconom_2015_03_005 crossref_primary_10_1146_annurev_economics_081720_120019 crossref_primary_10_1016_j_jeconom_2015_03_006 crossref_primary_10_1214_14_AOS1235 crossref_primary_10_1007_s10614_017_9758_5 crossref_primary_10_1017_S0266466618000282 crossref_primary_10_1080_19345747_2016_1273412 crossref_primary_10_1007_s00181_014_0867_x crossref_primary_10_1111_biom_12883 crossref_primary_10_1111_ectj_12018 crossref_primary_10_1111_biom_13101 crossref_primary_10_1177_0081175019887992 crossref_primary_10_1016_j_jeconom_2017_10_007 crossref_primary_10_1214_19_AOS1865 crossref_primary_10_1093_jeea_jvz058 crossref_primary_10_1016_j_jeconom_2018_10_004 crossref_primary_10_1093_restud_rdae022 crossref_primary_10_1080_07350015_2022_2061983 crossref_primary_10_3982_QE1079 crossref_primary_10_1007_s00148_020_00769_3 crossref_primary_10_3982_QE722 crossref_primary_10_1093_ej_uead118 crossref_primary_10_1214_14_AOS1230 crossref_primary_10_1002_jae_2473 crossref_primary_10_1111_rssa_12683 crossref_primary_10_1016_j_jeconom_2015_01_006 crossref_primary_10_1111_ectj_12081 crossref_primary_10_1080_07350015_2016_1272458 crossref_primary_10_1016_j_jeconom_2023_105549 crossref_primary_10_1111_1756_2171_12263 crossref_primary_10_1214_20_AOS2023 crossref_primary_10_1093_ectj_utz025 crossref_primary_10_1016_j_ehb_2022_101190 crossref_primary_10_1162_REST_a_00537 crossref_primary_10_3982_QE399 crossref_primary_10_3233_JEM_160423 crossref_primary_10_3982_ECTA20125 crossref_primary_10_1093_restud_rdz007 crossref_primary_10_1016_j_jeconom_2014_10_013 crossref_primary_10_1016_j_jeconom_2024_105842 crossref_primary_10_1080_07474938_2023_2178086 crossref_primary_10_1214_18_AOS1750 crossref_primary_10_1016_j_jeconom_2019_03_002 crossref_primary_10_1016_j_jeconom_2020_02_005 crossref_primary_10_1017_S0266466620000225 crossref_primary_10_3982_ECTA17764 crossref_primary_10_1093_biomet_asaa003 crossref_primary_10_1016_j_jeconom_2024_105680 crossref_primary_10_1016_j_econlet_2022_110440 crossref_primary_10_1093_biomet_asac042 crossref_primary_10_1080_01621459_2023_2252576 crossref_primary_10_1080_19439342_2020_1828999 crossref_primary_10_1146_annurev_statistics_040120_022239 crossref_primary_10_2139_ssrn_3866876 crossref_primary_10_1093_ectj_utab033 crossref_primary_10_1111_coep_12554 crossref_primary_10_1002_jae_3014 crossref_primary_10_1097_EDE_0000000000001178 crossref_primary_10_3982_QE1727 crossref_primary_10_1111_ectj_12077 crossref_primary_10_1080_07350015_2019_1569527 crossref_primary_10_1093_ectj_utae020 crossref_primary_10_1016_j_jeconom_2015_02_014 crossref_primary_10_1017_S0266466616000359 crossref_primary_10_1093_restud_rdac061 crossref_primary_10_1093_restud_rdy049 crossref_primary_10_1002_jae_2956 crossref_primary_10_1017_S0266466625100042 crossref_primary_10_1177_1536867X1701700104 crossref_primary_10_1017_S0266466617000329 crossref_primary_10_3982_QE268 crossref_primary_10_2139_ssrn_5019869 crossref_primary_10_1146_annurev_economics_081919_113720 crossref_primary_10_1002_jae_3024 crossref_primary_10_1016_j_labeco_2022_102258 crossref_primary_10_1016_j_jspi_2019_09_013 crossref_primary_10_1097_EDE_0000000000000811 crossref_primary_10_1080_07350015_2016_1149071 crossref_primary_10_1016_j_jeconom_2013_10_005 crossref_primary_10_1080_07350015_2024_2388639 crossref_primary_10_1086_708724 crossref_primary_10_3982_QE490 crossref_primary_10_1016_j_econlet_2025_112197 crossref_primary_10_1002_jae_2574 crossref_primary_10_1016_j_econedurev_2016_02_006 crossref_primary_10_1016_j_jmva_2013_10_020 crossref_primary_10_1111_biom_13148 crossref_primary_10_1017_S0266466617000184 crossref_primary_10_1093_ectj_utaf001 crossref_primary_10_1016_j_jeconom_2018_12_024 crossref_primary_10_1080_07350015_2013_822760 crossref_primary_10_3982_QE377 crossref_primary_10_1016_j_jeconom_2020_11_009 crossref_primary_10_1016_j_jeconom_2022_11_009 crossref_primary_10_1111_iere_12072 crossref_primary_10_1016_j_jeconom_2016_09_010 crossref_primary_10_3982_QE1960 crossref_primary_10_1016_j_jeconom_2023_105523 crossref_primary_10_1016_j_jeconom_2023_01_010 crossref_primary_10_1016_j_jeconom_2021_09_017 crossref_primary_10_1002_wics_1614 crossref_primary_10_1016_j_jeconom_2017_11_002 crossref_primary_10_1002_jae_2780 crossref_primary_10_1016_j_jmva_2013_07_017 crossref_primary_10_2139_ssrn_3753058 crossref_primary_10_1177_1536867X1501500103 crossref_primary_10_1111_ectj_12050 crossref_primary_10_1177_1536867X1801800308 crossref_primary_10_1016_j_spl_2017_12_004 crossref_primary_10_1016_j_jeconom_2021_01_012 crossref_primary_10_1086_696228 crossref_primary_10_1007_s42973_023_00138_1 crossref_primary_10_1016_j_jeconom_2019_04_010 crossref_primary_10_1016_j_jeconom_2017_06_019 crossref_primary_10_1017_S0266466616000384 crossref_primary_10_1002_bimj_201700049 crossref_primary_10_1080_07350015_2015_1044008 crossref_primary_10_1016_j_jeconom_2019_04_012 crossref_primary_10_1257_aer_20130824 crossref_primary_10_1016_j_jeconom_2016_04_006 crossref_primary_10_3982_QE240 crossref_primary_10_1146_annurev_economics_063016_103658 crossref_primary_10_1017_S0266466615000250 crossref_primary_10_1016_j_jeconom_2025_106102 crossref_primary_10_1016_j_jeconom_2023_105571 crossref_primary_10_1016_j_jeconom_2025_106063 crossref_primary_10_1093_restud_rdy065 crossref_primary_10_1080_00036846_2022_2137456 crossref_primary_10_1080_10485252_2025_2452225 crossref_primary_10_1111_iere_12722 crossref_primary_10_1016_j_ehb_2020_100895 crossref_primary_10_1016_j_jhealeco_2022_102713 crossref_primary_10_1017_S0266466614000826 crossref_primary_10_3982_QE1776 crossref_primary_10_1111_sjos_12398 crossref_primary_10_1016_j_jeconom_2019_04_003 crossref_primary_10_7202_1026444ar crossref_primary_10_1017_S0266466623000063 crossref_primary_10_1215_00703370_11865131 crossref_primary_10_1016_j_jpubeco_2022_104621 crossref_primary_10_1080_00036846_2020_1757030 crossref_primary_10_1111_rssb_12113 crossref_primary_10_1016_j_jeconom_2019_09_011 crossref_primary_10_1080_07350015_2014_975229 crossref_primary_10_1515_jem_2017_0007 crossref_primary_10_1016_j_jeconom_2014_05_016 crossref_primary_10_1093_geronb_gbaf057 crossref_primary_10_1111_obes_12056
ContentType	Journal Article
Copyright	Copyright ©2013 The Econometric Society 2013 The Econometric Society Copyright Blackwell Publishing Ltd. Mar 2013
Copyright_xml	– notice: Copyright ©2013 The Econometric Society – notice: 2013 The Econometric Society – notice: Copyright Blackwell Publishing Ltd. Mar 2013
DBID	AAYXX CITATION OQ6 8BJ FQK JBE
DOI	10.3982/ECTA8718
DatabaseName	CrossRef ECONIS International Bibliography of the Social Sciences (IBSS) International Bibliography of the Social Sciences International Bibliography of the Social Sciences
DatabaseTitle	CrossRef International Bibliography of the Social Sciences (IBSS)
DatabaseTitleList	International Bibliography of the Social Sciences (IBSS) International Bibliography of the Social Sciences (IBSS)
DeliveryMethod	fulltext_linktorsrc
Discipline	Economics
EISSN	1468-0262
EndPage	737
ExternalDocumentID	2924261221 749555645 10_3982_ECTA8718 ECTA1315 23524295
Genre	article Feature
GroupedDBID	-DZ -ET -~X .L6 0R~ 1OC 1OL 2AX 33P 4.4 5GY 702 7WY 8-1 85S 8FL AABCJ AABNI AAESR AAHQN AAMMB AAMNL AAOUF AARRQ AASGY AAWIL AAXLS AAXRX AAYCA AAZKR ABAWQ ABBHK ABBNM ABCUV ABFAN ABJNI ABKVW ABLJU ABPFR ABPQH ABSOO ABXSQ ABYWD ABYYQ ABZIE ACAHQ ACBKW ACCZN ACHJO ACHQT ACMTB ACNCT ACPOU ACTMH ACUBG ACXJH ACXQS ADBBV ADEOM ADGDI ADKYN ADMGS ADMHG ADODI ADULT ADXAS ADZMN AEFGJ AEIGN AENEX AEUPB AEUYR AEYWJ AFAIT AFBPY AFFNX AFFPM AFGKR AFTQD AFVYC AFWVQ AFXHP AGKTX AGLNM AGXDD AHAJD AHBTC AIDQK AIDYY AIHAF AIURR ALIPV ALMA_UNASSIGNED_HOLDINGS ALRMG ALSLI ALUQN ALVPJ AMYDB APTMU ASMEE ASTYK AZVAB BFHJK BKOMP BMXJE BNVMJ BQESF CBXGM CCKSF CS3 CYVLN DCZOG DQDLB DRFUL DRSSH DSRWC DU5 EBS ECEWR EJD EOH F5P GODZA HGLYW HQ6 IHE IPSME JAAYA JAS JBC JBMMH JBZCM JENOY JHFFW JKQEH JLEZI JLXEF JMS JPL JPPEU JST K60 K6~ L7B LATKE LEEKS LH4 LITHE LOXES LUTES LW6 LYRES MEWTI MRFUL MRSSH MSFUL MSSSH MS~ MXFUL MXSSH MY~ N9A NHB OIG P2P P2W ROL RWL RXW SA0 SUPJJ TAE TN5 U5U UHB WBKPD WH7 WIH WII WOHZO WXSBR XSW ZZTAW .Y3 0-V 29G 31~ 3R3 3V. 8FI 8G5 8R4 8R5 A00 AAHHS ABEFU ABUWG ABYAD ACCFJ ACTWD ADMHC ADZOD AEEZP AELPN AEQDE AFKRA AFPWT AFYRF AFZJQ AI. AIFKG AIWBW AJBDE AQUVI ARALO AS~ AZQEC BENPR BEZIV BPHCQ BVXVI CAG CCPQU COF DWQXO FEDTE FRNLG FVMVE FYUFA GNUQQ GROUPED_ABI_INFORM_ARCHIVE GROUPED_ABI_INFORM_COMPLETE GROUPED_ABI_INFORM_RESEARCH GUPYA GUQSH HGD HVGLF H~9 JSODD M0C M0T M2O M2R MVM P4E PADUT PQBIZ PQBZA PQQKQ PRG PROAC Q2X RNS S0X UKHRP VH1 VQA WHG WYJ YYP ZCG AAYXX AFFHD AGHNM CITATION O8X PHGZM PHGZT PJZUB PPXIY PRQQA OQ6 8BJ FQK JBE
ID	FETCH-LOGICAL-c5035-b4d429b2806d636472775dda5cc8ae9ce46ed37f81edc4e7a6a3896ed23b79c03
IEDL.DBID	DRFUL
ISICitedReferencesCount	202
ISICitedReferencesURI	http://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=Summon&SrcAuth=ProQuest&DestLinkType=CitingArticles&DestApp=WOS_CPL&KeyUT=000316631600006&url=https%3A%2F%2Fcvtisr.summon.serialssolutions.com%2F%23%21%2Fsearch%3Fho%3Df%26include.ft.matches%3Dt%26l%3Dnull%26q%3D
ISSN	0012-9682
IngestDate	Sun Sep 28 01:35:17 EDT 2025 Mon Nov 10 21:41:35 EST 2025 Sat Mar 08 16:22:40 EST 2025 Sat Nov 29 06:25:48 EST 2025 Tue Nov 18 20:51:28 EST 2025 Wed Jan 22 16:52:41 EST 2025 Thu Jul 03 21:28:44 EDT 2025
IsPeerReviewed	true
IsScholarly	true
Issue	2
Language	English
License	http://doi.wiley.com/10.1002/tdm_license_1.1
LinkModel	DirectLink
MergedId	FETCHMERGED-LOGICAL-c5035-b4d429b2806d636472775dda5cc8ae9ce46ed37f81edc4e7a6a3896ed23b79c03
Notes	We are especially grateful to D. Chetverikov, K. Kato, Y. Luo, A. Santos, five anonymous referees, and a co‐editor for making several extremely useful suggestions that have led to substantial improvements. We thank T. Armstrong, R. Blundell, A. Chesher, F. Molinari, W. Newey, C. Redmond, N. Roys, S. Stouli, and J. Stoye for detailed discussion and suggestions, and participants at numerous seminars and conferences for their comments. This paper is a revised version of “Inference on Intersection Bounds,” which initially was presented and circulated at the University of Virginia and the Harvard/MIT econometrics seminars in December 2007, and presented at the March 2008 CEMMAP/Northwestern Conference on Inference in Partially Identified Models With Applications. We gratefully acknowledge financial support from the National Science Foundation, the Economic and Social Research Council (RES‐589‐28‐0001, RES‐000‐22‐2761), and the European Research Council (ERC‐2009‐StG‐240910‐ROMETA). SourceType-Scholarly Journals-1 ObjectType-Feature-1 content type line 14 ObjectType-Article-2 content type line 23
PQID	1318850611
PQPubID	48030
PageCount	71
ParticipantIDs	proquest_miscellaneous_1324954363 proquest_journals_1318850611 econis_primary_749555645 crossref_primary_10_3982_ECTA8718 crossref_citationtrail_10_3982_ECTA8718 wiley_primary_10_3982_ECTA8718_ECTA1315 jstor_primary_23524295
PublicationCentury	2000
PublicationDate	March 2013
PublicationDateYYYYMMDD	2013-03-01
PublicationDate_xml	– month: 03 year: 2013 text: March 2013
PublicationDecade	2010
PublicationPlace	Oxford, UK
PublicationPlace_xml	– name: Oxford, UK – name: Evanston
PublicationTitle	Econometrica
PublicationYear	2013
Publisher	Econometric Society Blackwell Publishing Ltd
Publisher_xml	– name: Econometric Society – name: Blackwell Publishing Ltd
References	2007; 102 1991; 59 1984; 25 1993; 21 1982; 10 2005; 20 2008; 76 1977; 22 2008; 146 2007; 75 2003; 111 2009; 159 2009; 12 2004; 72 2010; 26 2010; 1 1982; 20 2010; 156 2007; 6 1983; 62 1984 1999; 96 2007; 2 2011; 29 2010; 78 2009; 25 2012; 80 1996; 17 2012 2011 1997; 65 2010 1997; 64 2000; 68 2009 1996 1995 2005 2011; 79 2003 2002 1989; 24 2001; 69 2009; 27 1990; 80 2012; 94 2009; 77 1997; 79 2013; 81 2008; 138 2013 2013; 172 1956; 1 1973; 1 2009; 149 1989; 17 1994; 98
References_xml	– year: 2011 – year: 2009 – volume: 98 start-page: 21 year: 1994 end-page: 45 article-title: Local Invariance Principles and Their Application to Density Estimation publication-title: Probability Theory and Related Fields – year: 2013 article-title: Inference for Parameters Defined by Conditional Moment Inequalities publication-title: Econometrica – year: 2005 – volume: 27 start-page: 193 issue: 2 year: 2009 end-page: 205 article-title: Reform of Unemployment Compensation in Germany: A Nonparametric Bounds Analysis Using Register Data publication-title: Journal of Business & Economic Statistics – volume: 21 start-page: 1926 issue: 4 year: 1993 end-page: 1947 article-title: Comparing Nonparametric versus Parametric Regression Fits publication-title: The Annals of Statistics – volume: 78 start-page: 119 issue: 1 year: 2010 end-page: 157 article-title: Inference for Parameters Defined by Moment Inequalities Using Generalized Moment Selection publication-title: Econometrica – volume: 22 start-page: 236 year: 1977 end-page: 247 article-title: On the Error of the Gaussian Approximation for Convolutions publication-title: Theory of Probability and Its Applications – volume: 111 start-page: 1 issue: 1 year: 2003 end-page: 51 article-title: Inference With an Incomplete Model of English Auctions publication-title: Journal of Political Economy – volume: 65 start-page: 1311 issue: 6 year: 1997 end-page: 1334 article-title: Monotone Treatment Response publication-title: Econometrica – volume: 94 start-page: 659 issue: 3 year: 2012 end-page: 671 article-title: Identification With Imperfect Instruments publication-title: Review of Economics and Statistics – volume: 96 start-page: 4730 year: 1999 end-page: 4734 article-title: Local Instrumental Variables and Latent Variable Models for Identifying and Bounding Treatment Effects publication-title: Proceedings of the National Academy of Sciences – volume: 80 start-page: 2805 issue: 6 year: 2012 end-page: 2826 article-title: Inference for Parameters Defined by Moment Inequalities: A Recommended Moment Selection Procedure publication-title: Econometrica – volume: 138 start-page: 2786 issue: 9 year: 2008 end-page: 2807 article-title: Inference for Identifiable Parameters in Partially Identified Econometric Models publication-title: Journal of Statistical Planning and Inference – volume: 17 start-page: 266 issue: 1 year: 1989 end-page: 291 article-title: Strong Approximation for Multivariate Empirical and Related Processes, via KMT Constructions publication-title: The Annals of Probability – volume: 20 start-page: 105 year: 1982 end-page: 134 article-title: Consistent Model Specification Tests publication-title: Journal of Econometrics – volume: 75 start-page: 323 issue: 2 year: 2007 end-page: 363 article-title: Changes in the Distribution of Male and Female Wages Accounting for Unemployment Composition Using Bounds publication-title: Econometrica – volume: 156 start-page: 408 issue: 2 year: 2010 end-page: 425 article-title: EL Inference for Partially Identified Models: Large Deviations Optimality and Bootstrap Validity publication-title: Journal of Econometrics – volume: 1 start-page: 255 issue: 2 year: 2010 end-page: 277 article-title: Set Identification and Sensitivity Analysis With Tobin Regressors publication-title: Quantitative Economics – volume: 149 start-page: 191 year: 2009 end-page: 208 article-title: Estimating Distributions of Potential Outcomes Using Local Instrumental Variables With an Application to Changes in College Enrollment and Wage Inequality publication-title: Journal of Econometrics – volume: 72 start-page: 1845 issue: 6 year: 2004 end-page: 1857 article-title: Confidence Intervals for Partially Identified Parameters publication-title: Econometrica – volume: 77 start-page: 1299 issue: 4 year: 2009 end-page: 1315 article-title: More on Confidence Regions for Partially Identified Parameters publication-title: Econometrica – volume: 146 start-page: 107 year: 2008 end-page: 117 article-title: Confidence Sets for Partially Identified Parameters that Satisfy a Finite Number of Moment Inequalities publication-title: Journal of Econometrics – start-page: 254 year: 1995 end-page: 275 – volume: 26 start-page: 1529 year: 2010 end-page: 1564 article-title: Uniform Bahadur Representation for Local Polynomial Estimates of m‐Regression and Its Application to the Additive Model publication-title: Econometric Theory – volume: 75 start-page: 1243 issue: 5 year: 2007 end-page: 1284 article-title: Estimation and Confidence Regions for Parameter Sets in Econometric Models publication-title: Econometrica – volume: 12 start-page: S200 issue: s1 year: 2009 end-page: S216 article-title: More on Monotone Instrumental Variables publication-title: Econometrics Journal – volume: 79 start-page: 949 issue: 3 year: 2011 end-page: 955 article-title: Partial Identification in Triangular Systems of Equations With Binary Dependent Variables publication-title: Econometrica – volume: 78 start-page: 575 issue: 2 year: 2010 end-page: 601 article-title: Instrumental Variable Models for Discrete Outcomes publication-title: Econometrica – volume: 172 start-page: 14 year: 2013 end-page: 32 article-title: Testing Functional Inequalities publication-title: Journal of Econometrics – volume: 1 start-page: 261 year: 1956 end-page: 290 article-title: Limit Theorems for Stochastic Processes publication-title: Theory of Probability and Its Applications – volume: 24 start-page: 343 issue: 3 year: 1989 end-page: 360 article-title: Anatomy of the Selection Problem publication-title: The Journal of Human Resources – volume: 79 start-page: 147 year: 1997 end-page: 168 article-title: Convergence Rates and Asymptotic Normality for Series Estimators publication-title: Journal of Econometrics – volume: 25 start-page: 303 issue: 3 year: 1984 end-page: 325 article-title: Least Absolute Deviations Estimation for the Censored Regression Model publication-title: Journal of Econometrics – volume: 25 start-page: 669 year: 2009 end-page: 709 article-title: Validity of Subsampling and Plug‐In Asymptotic Inference for Parameters Defined by Moment Inequalities publication-title: Econometric Theory – volume: 62 start-page: 509 year: 1983 end-page: 552 article-title: Invariance Principles for Sums of Banach Space Valued Random Elements and Empirical Processes publication-title: Zeitschrift für Wahrscheinlichkeitstheorie und verwandte Gebiete – year: 2003 – volume: 78 start-page: 735 issue: 2 year: 2010 end-page: 753 article-title: Bootstrap Inference for Partially Identified Models Defined by Moment Inequalities: Coverage of the Identified Set publication-title: Econometrica – volume: 102 start-page: 432 issue: 478 year: 2007 end-page: 441 article-title: Disability and Employment: Reevaluating the Evidence in Light of Reporting Errors publication-title: Journal of the American Statistical Association – volume: 29 start-page: 61 issue: 1 year: 2011 end-page: 72 article-title: Estimating Income Poverty in the Presence of Missing Data and Measurement Error Problems publication-title: Journal of Business & Economic Statistics – year: 1996 – volume: 12 start-page: S172 issue: s1 year: 2009 end-page: S199 article-title: Invalidity of the Bootstrap and m Out of n Bootstrap for Interval Endpoints Defined by Moment Inequalities publication-title: Econometrics Journal – volume: 10 start-page: 1040 issue: 4 year: 1982 end-page: 1053 article-title: Optimal Global Rates of Convergence for Nonparametric Regression publication-title: The Annals of Statistics – volume: 17 start-page: 571 year: 1996 end-page: 599 article-title: Multivariate Local Polynomial Regression for Time Series: Uniform Strong Consistency and Rates publication-title: Journal of Time Series Analysis – volume: 78 start-page: 169 issue: 1 year: 2010 end-page: 211 article-title: Inference for the Identified Set in Partially Identified Econometric Models publication-title: Econometrica – volume: 6 start-page: 5549 year: 2007 end-page: 5632 – volume: 159 start-page: 186 issue: 2 year: 2009 end-page: 196 article-title: A Test of Non‐Identifying Restrictions and Confidence Regions for Partially Identified Parameters publication-title: Journal of Econometrics – year: 2010 – year: 2012 – volume: 69 start-page: 599 issue: 3 year: 2001 end-page: 631 article-title: An Adaptive, Rate‐Optimal Test of a Parametric Mean‐Regression Model Against a Nonparametric Alternative publication-title: Econometrica – volume: 81 issue: Econometrica Supplementary Material year: 2013 – volume: 80 start-page: 1769 issue: 4 year: 2012 end-page: 1790 article-title: Impossibility Results for Nondifferentiable Functionals publication-title: Econometrica – year: 1984 – volume: 80 start-page: 319 issue: 2 year: 1990 end-page: 323 article-title: Nonparametric Bounds on Treatment Effects publication-title: American Economic Review – year: 2002 – volume: 1 start-page: 1071 issue: 6 year: 1973 end-page: 1095 article-title: On Some Global Measures of the Deviations of Density Function Estimates publication-title: The Annals of Statistics – volume: 64 start-page: 487 year: 1997 end-page: 537 article-title: Making the Most Out of Programme Evaluations and Social Experiments: Accounting for Heterogeneity in Programme Impacts publication-title: Review of Economic Studies – volume: 68 start-page: 997 issue: 4 year: 2000 end-page: 1010 article-title: Monotone Instrumental Variables: With an Application to the Returns to Schooling publication-title: Econometrica – volume: 59 start-page: 307 issue: 2 year: 1991 end-page: 345 article-title: Asymptotic Normality of Series Estimators for Nonparametric and Semiparametric Regression Models publication-title: Econometrica – volume: 20 start-page: 771 year: 2005 end-page: 795 article-title: Nonparametric Bounds on the Returns to Language Skills publication-title: Journal of Applied Econometrics – volume: 76 start-page: 763 issue: 4 year: 2008 end-page: 814 article-title: Asymptotic Properties for a Class of Partially Identified Models publication-title: Econometrica – volume: 2 start-page: 46 year: 2007 end-page: 85
SSID	ssj0005005
Score	2.548354
Snippet	We develop a practical and novel method for inference on intersection bounds, namely bounds defined by either the infimum or supremum of a parametric or...
SourceID	proquest econis crossref wiley jstor
SourceType	Aggregation Database Index Database Enrichment Source Publisher
StartPage	667
SubjectTerms	adaptive moment selection anti‐concentration inequalities Approximation Bias Bound analysis concentration inequalities conditional moments Critical values Econometrics Economic analysis Economic models Empirical tests Estimation bias Estimation methods Estimators Induktive Statistik Inequality Inference infinite‐dimensional constraints Interval estimators Linear programming Mathematical functions Mathematical independent variables Mathematische Optimierung moderate deviations non‐Donsker empirical process methods partial identification Probabilities Schätztheorie Series convergence Statistical inference strong approximation Studies Theorie
Title	INTERSECTION BOUNDS: ESTIMATION AND INFERENCE
URI	https://www.jstor.org/stable/23524295 https://onlinelibrary.wiley.com/doi/abs/10.3982%2FECTA8718 http://www.econis.eu/PPNSET?PPN=749555645 https://www.proquest.com/docview/1318850611 https://www.proquest.com/docview/1324954363
Volume	81
WOSCitedRecordID	wos000316631600006&url=https%3A%2F%2Fcvtisr.summon.serialssolutions.com%2F%23%21%2Fsearch%3Fho%3Df%26include.ft.matches%3Dt%26l%3Dnull%26q%3D
hasFullText	1
inHoldings	1
isFullTextHit
isPrint
journalDatabaseRights	– providerCode: PRVWIB databaseName: Wiley Online Library Full Collection 2020 customDbUrl: eissn: 1468-0262 dateEnd: 99991231 omitProxy: false ssIdentifier: ssj0005005 issn: 0012-9682 databaseCode: DRFUL dateStart: 19990101 isFulltext: true titleUrlDefault: https://onlinelibrary.wiley.com providerName: Wiley-Blackwell
link	http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwpV3dS8MwED90G-iL37L5RQXBp2Kbtknq29QNBRGRDfZWsiQDQaqsm3-_d-mHCgqCb6W5tLlcLrlLLr8DOAut1crK1DfCcj_mSvipc1xFoNlsxrnUxiWbEA8PcjJJH6uoSroLU-JDNBtupBluviYFV1OXhSRKJYGGDq5HfbT25Sq0GQ7buAXtm6fh-P4zwCMIqvwFzE-5ZCX0LNW-qOt-W4w65IE-F3Vg4jeT86vh6lae4eZ_2rwFG5W96fXLAbINKzbfgbX6OnKxC77bEyxcRFbuXVGWpeLSG6Dml5caPZUb766-FrgH4-FgdH3rVzkUfJ0QGuU0NrjiTOn81HCHFS9EYoxKtJbKptrG3JpIzGRojY6tUFyhCYPvWDQVqQ6ifWjlr7ntgsc4MmGlVjrU8UwFKtI65YbhFICCNXEPzuvOzHQFME55Ll4ydDSoA7Ka_R6cNpRvJajGDzTdUh4NhUBfLiHwmx7sOwk1JQytSOQSC45qkWWVKhZZiLMWwfKFIf62KUYlopMRldvXJdFQCu444hEy4QT4a7vcA34zOfgz5SGsM5dEgyLXjqC1mC_tMXT0--K5mJ9Uw_YDqiLrcw
linkProvider	Wiley-Blackwell
linkToHtml	http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwpV1ZSwMxEB5qFfTFu1jPFQSfFvdMsvrk0VKxFpEKvi1pkkJBtuK2_n5nsocKCoJvy2aym8lkkpkk8w3AiW-MkkYkruaGuRGT3E2s48o9FYzHjAmlbbIJPhiI5-fkoQEXVSxMgQ9Rb7iRZtj5mhScNqRJy8NEEGpo53p4iea-WIDFCEdR3ITFm8fuU__zhofnlQkMAjdhIiiwZ6n2WVX322q0RC7oJK9uJn6zOb9arnbp6a79q9HrsFpanM5lMUQ2oGGyTViuApLzLXDtrmBu72RlzhXlWcrPnQ7qfhHW6MhMO7dVYOA2PHU7w-ueW2ZRcFVMeJSjSOOaM6ITVM0sWjznsdYyVkpIkygTMaNDPha-0SoyXDKJRgy-C8IRT5QXtqCZTTOzA07AkAkjlFS-isbSk6FSCdMBTgIoWh214bTqzVSVEOOU6eIlRVeDOiCt2G_DcU35WsBq_ECzUwikpuDozcUEf9OGlhVRXRKgHYlcYsF-JbO0VMY89XHeImA-38ff1sWoRnQ2IjMznRMNJeGOQhYiE1aCv7bLPuA3490_Ux7Bcm9430_7t4O7PVgJbEoNuse2D83Z29wcwJJ6n03yt8NyDH8A0T3vYw
linkToPdf	http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwpV1ZS8QwEB68UF-8xfWsIPhU7JlDnzx2cXFZRBR8K9kkBUG6i1V_vzPpoYKC4FtpJm0mk0lmksk3AEehtVpZIX3DLfMTprgvnePKAx3lOWNCG5dsgg-H4vFR3k7BWXMXpsKHaDfcSDPcfE0KbicmJy2PpSDU0O7l_Tma-2IaZpNUMtTK2au73sPgM8IjCOoEBpEvmYgq7FmqfdLU_bYazZEL-lQ2kYnfbM6vlqtbenrL_2r0CizVFqd3Xg2RVZiyxRosNBeSy3Xw3a5g6WKyCu-C8iyVp14Xdb-61uipwnj95mLgBjz0uveX136dRcHXKeFRjhKDa86ITlANc2jxnKfGqFRroazUNmHWxDwXoTU6sVwxhUYMvoviEZc6iDdhphgXdgu8iCETVmilQ53kKlCx1pKZCCcBFK1JOnDc9Gama4hxynTxnKGrQR2QNex34LClnFSwGj_QbFUCaSk4enMpwd90YNOJqC2J0I5ELrFgt5FZVitjmYU4bxEwXxjib9tiVCM6G1GFHb8RDSXhTmIWIxNOgr-2yz3gN9PtP1MewPztVS8b9Ic3O7AYuYwaFMa2CzOvL292D-b0--tT-bJfD-EPc5Hu3g
openUrl	ctx_ver=Z39.88-2004&ctx_enc=info%3Aofi%2Fenc%3AUTF-8&rfr_id=info%3Asid%2Fsummon.serialssolutions.com&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Ajournal&rft.genre=article&rft.atitle=Intersection+Bounds%3A+Estimation+and+Inference&rft.jtitle=Econometrica&rft.au=Chernozhukov%2C+Victor&rft.au=Lee%2C+Sokbae&rft.au=Rosen%2C+Adam+M&rft.date=2013-03-01&rft.pub=Blackwell+Publishing+Ltd&rft.issn=0012-9682&rft.eissn=1468-0262&rft.volume=81&rft.issue=2&rft.spage=667&rft_id=info:doi/10.3982%2FECTA8718&rft.externalDBID=HAS_PDF_LINK&rft.externalDocID=2924261221
thumbnail_l	http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/lc.gif&issn=0012-9682&client=summon
thumbnail_m	http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/mc.gif&issn=0012-9682&client=summon
thumbnail_s	http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/sc.gif&issn=0012-9682&client=summon