{"id":"https://openalex.org/W7216340774","doi":"https://doi.org/10.48550/arxiv.2610.00933","title":"Quantile Social Autoregressive Model","display_name":"Quantile Social Autoregressive Model","publication_year":2026,"publication_date":"2026-10-01","ids":{"openalex":"https://openalex.org/W7216340774","doi":"https://doi.org/10.48550/arxiv.2610.00933"},"language":"en","primary_location":{"id":"pmh:oai:arXiv.org:2610.00933","doi":null,"is_oa":true,"landing_page_url":"https://arxiv.org/abs/2610.00933","pdf_url":"https://arxiv.org/pdf/2610.00933","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"},"volume":null,"type":"preprint","is_traditional":true,"indexed_in":["arxiv","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2610.00933","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5155446038","display_name":"Liyuan Wang","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I78988378","display_name":"Renmin University of China","ror":"https://ror.org/041pakw92","country_code":"CN","type":"education","lineage":["https://openalex.org/I78988378"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wang, Liyuan","raw_affiliation_strings":["Center for Applied Statistics and School of Statistics , Renmin University of China , Beijing , China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Center for Applied Statistics and School of Statistics , Renmin University of China , Beijing , China","institution_ids":["https://openalex.org/I78988378"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5041510321","display_name":"Danyang Huang","orcid":"https://orcid.org/0000-0002-4053-2680","observed_orcids":["https://orcid.org/0000-0002-4053-2680"]},"institutions":[{"id":"https://openalex.org/I78988378","display_name":"Renmin University of China","ror":"https://ror.org/041pakw92","country_code":"CN","type":"education","lineage":["https://openalex.org/I78988378"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Huang, Danyang","raw_affiliation_strings":["Center for Applied Statistics and School of Statistics , Renmin University of China , Beijing , China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Center for Applied Statistics and School of Statistics , Renmin University of China , Beijing , China","institution_ids":["https://openalex.org/I78988378"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5155523346","display_name":"Wei Lan","orcid":null,"observed_orcids":[]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Lan, Wei","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5154388621","display_name":"Chih-Ling Tsai","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I84218800","display_name":"University of California, Davis","ror":"https://ror.org/05rrcem69","country_code":"US","type":"education","lineage":["https://openalex.org/I84218800"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Tsai, Chih-Ling","raw_affiliation_strings":["Graduate School of Management , University of California , Davis , CA , USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Graduate School of Management , University of California , Davis , CA , USA","institution_ids":["https://openalex.org/I84218800"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":true,"cited_by_count":0,"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/T11911","display_name":"Spatial and Panel Data Analysis","score":0.5952000021934509,"subfield":{"id":"https://openalex.org/subfields/2002","display_name":"Economics and Econometrics"},"field":{"id":"https://openalex.org/fields/20","display_name":"Economics, Econometrics and Finance"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},"topics":[{"id":"https://openalex.org/T11911","display_name":"Spatial and Panel Data Analysis","score":0.5952000021934509,"subfield":{"id":"https://openalex.org/subfields/2002","display_name":"Economics and Econometrics"},"field":{"id":"https://openalex.org/fields/20","display_name":"Economics, Econometrics and Finance"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T10845","display_name":"Advanced Causal Inference Techniques","score":0.1597999930381775,"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/T11031","display_name":"Game Theory and Applications","score":0.03739999979734421,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/peer-effects","display_name":"peer effects","score":0.9639999866485596},{"id":"https://openalex.org/keywords/linear-in-means-model","display_name":"linear-in-means model","score":0.7850000262260437},{"id":"https://openalex.org/keywords/kernel-smoothing","display_name":"kernel smoothing","score":0.9160000085830688},{"id":"https://openalex.org/keywords/existence-and-uniqueness-of-equilibrium","display_name":"existence and uniqueness of equilibrium","score":0.9179999828338623},{"id":"https://openalex.org/keywords/identification-conditions","display_name":"identifiability conditions","score":0.7689999938011169},{"id":"https://openalex.org/keywords/consistency-and-asymptotic-normality","display_name":"consistency and asymptotic normality","score":0.9120000004768372},{"id":"https://openalex.org/keywords/social-norms","display_name":"social norms","score":0.3720000088214874}],"concepts":[{"id":"https://openalex.org/C118671147","wikidata":"https://www.wikidata.org/wiki/Q578714","display_name":"Quantile","level":2,"score":0.8492000102996826},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.6552000045776367},{"id":"https://openalex.org/C159877910","wikidata":"https://www.wikidata.org/wiki/Q2202883","display_name":"Autoregressive model","level":2,"score":0.5480999946594238},{"id":"https://openalex.org/C2776436953","wikidata":"https://www.wikidata.org/wiki/Q5163215","display_name":"Consistency (knowledge bases)","level":2,"score":0.5008999705314636},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.5004000067710876},{"id":"https://openalex.org/C63817138","wikidata":"https://www.wikidata.org/wiki/Q3455889","display_name":"Quantile regression","level":2,"score":0.38940000534057617},{"id":"https://openalex.org/C3770464","wikidata":"https://www.wikidata.org/wiki/Q775963","display_name":"Smoothing","level":2,"score":0.37549999356269836},{"id":"https://openalex.org/C65778772","wikidata":"https://www.wikidata.org/wiki/Q12345341","display_name":"Asymptotic distribution","level":3,"score":0.3709000051021576},{"id":"https://openalex.org/C19499675","wikidata":"https://www.wikidata.org/wiki/Q232207","display_name":"Monte Carlo method","level":2,"score":0.36329999566078186},{"id":"https://openalex.org/C185429906","wikidata":"https://www.wikidata.org/wiki/Q1130160","display_name":"Estimator","level":2,"score":0.3361000120639801},{"id":"https://openalex.org/C179254644","wikidata":"https://www.wikidata.org/wiki/Q13222844","display_name":"Moment (physics)","level":2,"score":0.33399999141693115},{"id":"https://openalex.org/C27406209","wikidata":"https://www.wikidata.org/wiki/Q6394203","display_name":"Kernel smoother","level":5,"score":0.3264000117778778},{"id":"https://openalex.org/C74193536","wikidata":"https://www.wikidata.org/wiki/Q574844","display_name":"Kernel (algebra)","level":2,"score":0.32510000467300415},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.32249999046325684},{"id":"https://openalex.org/C38935604","wikidata":"https://www.wikidata.org/wiki/Q4330363","display_name":"Stylized fact","level":2,"score":0.3018999993801117},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.295199990272522},{"id":"https://openalex.org/C527412718","wikidata":"https://www.wikidata.org/wiki/Q855395","display_name":"Interpretation (philosophy)","level":2,"score":0.2842999994754791},{"id":"https://openalex.org/C191795146","wikidata":"https://www.wikidata.org/wiki/Q3878446","display_name":"Norm (philosophy)","level":2,"score":0.2800999879837036},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.2797999978065491},{"id":"https://openalex.org/C120936955","wikidata":"https://www.wikidata.org/wiki/Q2155640","display_name":"Empirical research","level":2,"score":0.2712000012397766},{"id":"https://openalex.org/C31388003","wikidata":"https://www.wikidata.org/wiki/Q7624548","display_name":"Strong consistency","level":3,"score":0.2687999904155731},{"id":"https://openalex.org/C199163554","wikidata":"https://www.wikidata.org/wiki/Q1681619","display_name":"Univariate","level":3,"score":0.26649999618530273},{"id":"https://openalex.org/C2776157432","wikidata":"https://www.wikidata.org/wiki/Q1375683","display_name":"Normality","level":2,"score":0.2624000012874603},{"id":"https://openalex.org/C98385598","wikidata":"https://www.wikidata.org/wiki/Q1339385","display_name":"Empirical distribution function","level":2,"score":0.25929999351501465},{"id":"https://openalex.org/C194531419","wikidata":"https://www.wikidata.org/wiki/Q17104825","display_name":"Nuisance parameter","level":3,"score":0.25760000944137573},{"id":"https://openalex.org/C110121322","wikidata":"https://www.wikidata.org/wiki/Q865811","display_name":"Distribution (mathematics)","level":2,"score":0.2563999891281128}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:oai:arXiv.org:2610.00933","doi":null,"is_oa":true,"landing_page_url":"https://arxiv.org/abs/2610.00933","pdf_url":"https://arxiv.org/pdf/2610.00933","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":"doi:10.48550/arxiv.2610.00933","doi":"https://doi.org/10.48550/arxiv.2610.00933","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2610.00933","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":false,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2610.00933","doi":null,"is_oa":true,"landing_page_url":"https://arxiv.org/abs/2610.00933","pdf_url":"https://arxiv.org/pdf/2610.00933","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":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W7216340774.pdf","grobid_xml":"https://content.openalex.org/works/W7216340774.grobid-xml"},"referenced_works_count":2,"referenced_works":["https://openalex.org/W4403995742","https://openalex.org/W4415117810"],"related_works":["https://openalex.org/W4415117810","https://openalex.org/W4399765236","https://openalex.org/W3089095798","https://openalex.org/W1929299359","https://openalex.org/W4403995742","https://openalex.org/W4403451151","https://openalex.org/W4416437145","https://openalex.org/W7058398017","https://openalex.org/W7018958530","https://openalex.org/W2081816865"],"abstract_inverted_index":{"Research":[0],"on":[1,8,38],"modelling":[2],"peer":[3,13,24,49,72,162],"effects":[4,21],"has":[5],"predominantly":[6],"relied":[7],"linear-in-means":[9],"models.":[10],"However,":[11],"averaging":[12],"responses":[14],"prevents":[15],"these":[16],"models":[17],"from":[18,62],"capturing":[19],"the":[20,53,63,71,82,93,104,121,127,141,145,152,155],"of":[22,48,70,132,144,154],"extreme":[23],"behavior.":[25,79],"To":[26,80],"address":[27],"this":[28],"limitation,":[29],"we":[30,84,99,113,125],"propose":[31],"a":[32,39],"quantile":[33,41,54,94,157],"social":[34,42,95],"autoregressive":[35],"model":[36],"based":[37],"novel":[40],"norm,":[43],"which":[44,68],"uses":[45],"empirical":[46,149],"quantiles":[47],"responses.":[50],"By":[51],"treating":[52],"level":[55],"as":[56],"an":[57,148],"unknown":[58],"parameter":[59],"estimated":[60,156],"directly":[61],"data,":[64],"our":[65,133],"approach":[66],"identifies":[67],"segment":[69],"response":[73],"distribution":[74],"most":[75],"strongly":[76],"influences":[77],"individual":[78],"estimate":[81],"model,":[83],"introduce":[85],"new":[86],"moment":[87],"conditions":[88],"using":[89],"pseudo-response":[90],"instruments.":[91],"Because":[92],"norm":[96],"is":[97],"nonsmooth,":[98],"apply":[100],"kernel":[101],"smoothing":[102],"to":[103],"instruments":[105],"and":[106,117,119,129,147,159],"residuals,":[107],"ensuring":[108],"valid":[109],"statistical":[110],"inference.":[111],"Additionally,":[112],"establish":[114],"equilibrium":[115],"existence":[116],"uniqueness":[118],"derive":[120],"identification":[122],"conditions.":[123],"Furthermore,":[124],"prove":[126],"consistency":[128],"asymptotic":[130],"normality":[131],"proposed":[134],"estimator.":[135],"Finally,":[136],"Monte":[137],"Carlo":[138],"experiments":[139],"examine":[140],"finite-sample":[142],"performance":[143],"estimator,":[146],"application":[150],"illustrates":[151],"interpretation":[153],"levels":[158],"their":[160],"corresponding":[161],"effects.":[163]},"counts_by_year":[],"updated_date":"2026-11-07T11:25:07.637180","created_date":"2026-10-03T00:00:00"}
