{"id":"https://openalex.org/W3122627770","doi":"https://doi.org/10.48550/arxiv.2007.06169","title":"An Adversarial Approach to Structural Estimation","display_name":"An Adversarial Approach to Structural Estimation","publication_year":2020,"publication_date":"2020-07-13","ids":{"openalex":"https://openalex.org/W3122627770","doi":"https://doi.org/10.48550/arxiv.2007.06169","mag":"3122627770"},"language":"en","primary_location":{"id":"pmh:oai:RePEc:arx:papers:2007.06169","doi":null,"is_oa":false,"landing_page_url":"http://arxiv.org/pdf/2007.06169","pdf_url":"http://arxiv.org/pdf/2007.06169","source":{"id":"https://openalex.org/S4306401271","display_name":"RePEc: Research Papers in Economics","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I77793887","host_organization_name":"Federal Reserve Bank of St. Louis","host_organization_lineage":["https://openalex.org/I77793887"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"preprint"},"volume":null,"type":"preprint","indexed_in":["arxiv","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2007.06169","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5034521121","display_name":"Tetsuya Kaji","orcid":"https://orcid.org/0000-0003-2753-2579","observed_orcids":["https://orcid.org/0000-0003-2753-2579"]},"institutions":[{"id":"https://openalex.org/I40347166","display_name":"University of Chicago","ror":"https://ror.org/024mw5h28","country_code":"US","type":"education","lineage":["https://openalex.org/I40347166"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Kaji, Tetsuya","raw_affiliation_strings":["University of Chicago"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Chicago","institution_ids":["https://openalex.org/I40347166"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5063616328","display_name":"Elena Manresa","orcid":"https://orcid.org/0000-0003-0884-792X","observed_orcids":["https://orcid.org/0000-0003-0884-792X"]},"institutions":[{"id":"https://openalex.org/I57206974","display_name":"New York University","ror":"https://ror.org/0190ak572","country_code":"US","type":"education","lineage":["https://openalex.org/I57206974"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Manresa, Elena","raw_affiliation_strings":["New York University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"New York University","institution_ids":["https://openalex.org/I57206974"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5081750101","display_name":"Guillaume Pouliot","orcid":"https://orcid.org/0000-0002-3278-153X","observed_orcids":["https://orcid.org/0000-0002-3278-153X"]},"institutions":[{"id":"https://openalex.org/I40347166","display_name":"University of Chicago","ror":"https://ror.org/024mw5h28","country_code":"US","type":"education","lineage":["https://openalex.org/I40347166"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Pouliot, Guillaume","raw_affiliation_strings":["University of Chicago"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Chicago","institution_ids":["https://openalex.org/I40347166"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":true,"cited_by_count":5,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10845","display_name":"Advanced Causal Inference Techniques","score":0.3540000021457672,"subfield":{"id":"https://openalex.org/subfields/2613","display_name":"Statistics and Probability"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10845","display_name":"Advanced Causal Inference Techniques","score":0.3540000021457672,"subfield":{"id":"https://openalex.org/subfields/2613","display_name":"Statistics and Probability"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11195","display_name":"Simulation Techniques and Applications","score":0.1331000030040741,"subfield":{"id":"https://openalex.org/subfields/1803","display_name":"Management Science and Operations Research"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T12056","display_name":"Markov Chains and Monte Carlo Methods","score":0.0357000008225441,"subfield":{"id":"https://openalex.org/subfields/2613","display_name":"Statistics and Probability"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/structural-estimation","display_name":"structural estimation","score":0.8730000257492065},{"id":"https://openalex.org/keywords/simulation-based-estimation","display_name":"simulation-based estimation","score":0.8050000071525574},{"id":"https://openalex.org/keywords/minimax-problems","display_name":"minimax problems","score":0.7379999756813049},{"id":"https://openalex.org/keywords/model-misspecification","display_name":"model misspecification","score":0.8970000147819519},{"id":"https://openalex.org/keywords/convergence-rate","display_name":"convergence rate","score":0.6399999856948853},{"id":"https://openalex.org/keywords/simulation-based-inference","display_name":"simulation-based inference","score":0.36399999260902405}],"concepts":[{"id":"https://openalex.org/C2779803651","wikidata":"https://www.wikidata.org/wiki/Q5282088","display_name":"Discriminator","level":3,"score":0.942602813243866},{"id":"https://openalex.org/C185429906","wikidata":"https://www.wikidata.org/wiki/Q1130160","display_name":"Estimator","level":2,"score":0.8181347846984863},{"id":"https://openalex.org/C149728462","wikidata":"https://www.wikidata.org/wiki/Q751319","display_name":"Minimax","level":2,"score":0.7744091749191284},{"id":"https://openalex.org/C2780992000","wikidata":"https://www.wikidata.org/wiki/Q17016113","display_name":"Generator (circuit theory)","level":3,"score":0.7694328427314758},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6684213280677795},{"id":"https://openalex.org/C117251300","wikidata":"https://www.wikidata.org/wiki/Q1849855","display_name":"Parametric statistics","level":2,"score":0.6419334411621094},{"id":"https://openalex.org/C37736160","wikidata":"https://www.wikidata.org/wiki/Q1801315","display_name":"Adversarial system","level":2,"score":0.586845874786377},{"id":"https://openalex.org/C2777303404","wikidata":"https://www.wikidata.org/wiki/Q759757","display_name":"Convergence (economics)","level":2,"score":0.5425072908401489},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.5161874890327454},{"id":"https://openalex.org/C165696696","wikidata":"https://www.wikidata.org/wiki/Q11287","display_name":"Exploit","level":2,"score":0.48481646180152893},{"id":"https://openalex.org/C24574437","wikidata":"https://www.wikidata.org/wiki/Q7135228","display_name":"Parametric model","level":3,"score":0.4485793709754944},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.2767787575721741},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.20369359850883484},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.11705377697944641},{"id":"https://openalex.org/C163258240","wikidata":"https://www.wikidata.org/wiki/Q25342","display_name":"Power (physics)","level":2,"score":0.11362636089324951},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0771821141242981},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.0},{"id":"https://openalex.org/C50522688","wikidata":"https://www.wikidata.org/wiki/Q189833","display_name":"Economic growth","level":1,"score":0.0},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C94915269","wikidata":"https://www.wikidata.org/wiki/Q1834857","display_name":"Detector","level":2,"score":0.0}],"mesh":[],"locations_count":7,"locations":[{"id":"pmh:oai:RePEc:arx:papers:2007.06169","doi":null,"is_oa":false,"landing_page_url":"http://arxiv.org/pdf/2007.06169","pdf_url":"http://arxiv.org/pdf/2007.06169","source":{"id":"https://openalex.org/S4306401271","display_name":"RePEc: Research Papers in Economics","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I77793887","host_organization_name":"Federal Reserve Bank of St. Louis","host_organization_lineage":["https://openalex.org/I77793887"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"preprint"},{"id":"pmh:oai:arXiv.org:2007.06169","doi":null,"is_oa":true,"landing_page_url":"http://arxiv.org/abs/2007.06169","pdf_url":"https://arxiv.org/pdf/2007.06169","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"pmh:oai:RePEc:bfi:wpaper:2020-144","doi":null,"is_oa":false,"landing_page_url":"https://repec.bfi.uchicago.edu/RePEc/pdfs/BFI_WP_2020144.pdf","pdf_url":"https://repec.bfi.uchicago.edu/RePEc/pdfs/BFI_WP_2020144.pdf","source":{"id":"https://openalex.org/S4306401271","display_name":"RePEc: Research Papers in Economics","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I77793887","host_organization_name":"Federal Reserve Bank of St. Louis","host_organization_lineage":["https://openalex.org/I77793887"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"preprint"},{"id":"pmh:oai:RePEc:ifs:cemmap:39/20","doi":null,"is_oa":false,"landing_page_url":"https://www.ifs.org.uk/uploads/CWP3920-An-adversarial-approach-to-structural-estimation.pdf","pdf_url":"https://www.ifs.org.uk/uploads/CWP3920-An-adversarial-approach-to-structural-estimation.pdf","source":{"id":"https://openalex.org/S4306401271","display_name":"RePEc: Research Papers in Economics","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I77793887","host_organization_name":"Federal Reserve Bank of St. Louis","host_organization_lineage":["https://openalex.org/I77793887"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"preprint"},{"id":"doi:10.48550/arxiv.2007.06169","doi":"https://doi.org/10.48550/arxiv.2007.06169","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2007.06169","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article-journal"},{"id":"doi:10.6082/63m72-41g85","doi":"https://doi.org/10.6082/63m72-41g85","is_oa":true,"landing_page_url":"https://doi.org/10.6082/63m72-41g85","pdf_url":null,"source":{"id":"https://openalex.org/S7407053018","display_name":"University of Chicago","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"JournalArticle"},{"id":"doi:10.6082/ad85r-f1d61","doi":"https://doi.org/10.6082/ad85r-f1d61","is_oa":true,"landing_page_url":"https://doi.org/10.6082/ad85r-f1d61","pdf_url":null,"source":{"id":"https://openalex.org/S7407053018","display_name":"University of Chicago","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"JournalArticle"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2007.06169","doi":null,"is_oa":true,"landing_page_url":"http://arxiv.org/abs/2007.06169","pdf_url":"https://arxiv.org/pdf/2007.06169","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[],"sustainable_development_goals_aurora":[{"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10","score":0.7400000095367432}],"study_designs":[],"awards":[{"id":"https://openalex.org/G8923403094","display_name":"Collaborative Research: Deep Inference - Artificial Intelligence for Structural Estimation","funder_award_id":"1824304","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"},{"id":"https://openalex.org/F4320332552","display_name":"Booth School of Business, University of Chicago","ror":"https://ror.org/024mw5h28"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":18,"referenced_works":["https://openalex.org/W1460189015","https://openalex.org/W1509689762","https://openalex.org/W1972320266","https://openalex.org/W1997817606","https://openalex.org/W2019302713","https://openalex.org/W2094788121","https://openalex.org/W2581485081","https://openalex.org/W2789278215","https://openalex.org/W2936995161","https://openalex.org/W2946302218","https://openalex.org/W2971792935","https://openalex.org/W3025979550","https://openalex.org/W3040842183","https://openalex.org/W3125644974","https://openalex.org/W3142916893","https://openalex.org/W3160429390","https://openalex.org/W3161062409","https://openalex.org/W4320013936"],"related_works":["https://openalex.org/W4293202849","https://openalex.org/W1980965563","https://openalex.org/W1489300767","https://openalex.org/W2387995142","https://openalex.org/W4380714744","https://openalex.org/W4319453655","https://openalex.org/W17155033","https://openalex.org/W2089959425","https://openalex.org/W2995777218","https://openalex.org/W4283320637"],"abstract_inverted_index":{"We":[0,57,80,102],"propose":[1],"a":[2,20,24,35,61,85,89],"new":[3],"simulation-based":[4],"estimation":[5],"method,":[6],"adversarial":[7,66],"estimation,":[8],"for":[9,133],"structural":[10,32],"models.":[11],"The":[12,44],"estimator":[13,67,116],"is":[14,42],"formulated":[15],"as":[16,88,121],"the":[17,31,47,53,65,75,82,107,118,128,134],"solution":[18],"to":[19,106],"minimax":[21],"problem":[22],"between":[23],"generator":[25,54],"(which":[26,37],"generates":[27],"simulated":[28],"observations":[29],"using":[30],"model)":[33],"and":[34,74,96,112],"discriminator":[36,45,90],"classifies":[38],"whether":[39],"an":[40,122],"observation":[41],"simulated).":[43],"maximizes":[46],"accuracy":[48],"of":[49,84,100,125],"its":[50],"classification":[51],"while":[52],"minimizes":[55],"it.":[56],"show":[58,113],"that,":[59],"with":[60],"sufficiently":[62],"rich":[63],"discriminator,":[64],"attains":[68],"parametric":[69,76],"efficiency":[70],"under":[71,78],"correct":[72],"specification":[73],"rate":[77],"misspecification.":[79],"advocate":[81],"use":[83],"neural":[86],"network":[87],"that":[91,114],"can":[92],"exploit":[93],"adaptivity":[94],"properties":[95],"attain":[97],"fast":[98],"rates":[99],"convergence.":[101],"apply":[103],"our":[104,115],"method":[105],"elderly's":[108],"saving":[109,126],"decision":[110],"model":[111],"uncovers":[117],"bequest":[119],"motive":[120],"important":[123],"source":[124],"across":[127],"wealth":[129],"distribution,":[130],"not":[131],"only":[132],"rich.":[135]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":2},{"year":2020,"cited_by_count":1}],"updated_date":"2026-10-16T09:59:22.235173","created_date":"2025-10-10T00:00:00"}