{"id":"https://openalex.org/W4416677009","doi":"https://doi.org/10.1109/dsaa65442.2025.11247972","title":"An Event Study Framework for Analyzing Bidirectional Causality Between House Prices and Premium Caf\u00e9 Entry","display_name":"An Event Study Framework for Analyzing Bidirectional Causality Between House Prices and Premium Caf\u00e9 Entry","publication_year":2025,"publication_date":"2025-10-09","ids":{"openalex":"https://openalex.org/W4416677009","doi":"https://doi.org/10.1109/dsaa65442.2025.11247972"},"language":null,"primary_location":{"id":"doi:10.1109/dsaa65442.2025.11247972","is_oa":false,"landing_page_url":"https://doi.org/10.1109/dsaa65442.2025.11247972","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE 12th International Conference on Data Science and Advanced Analytics (DSAA)","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5043168857","display_name":"Sachin Date","orcid":"https://orcid.org/0009-0008-4448-5827"},"institutions":[{"id":"https://openalex.org/I4210143376","display_name":"Sage Technologies (United States)","ror":"https://ror.org/04fvc0724","country_code":"US","type":"company","lineage":["https://openalex.org/I4210143376"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Sachin Date","raw_affiliation_strings":["VitalEdge Technologies,Product Management,Cary,USA"],"affiliations":[{"raw_affiliation_string":"VitalEdge Technologies,Product Management,Cary,USA","institution_ids":["https://openalex.org/I4210143376"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5043168857"],"corresponding_institution_ids":["https://openalex.org/I4210143376"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.44954959,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"10"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10632","display_name":"Housing Market and Economics","score":0.37560001015663147,"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/T10632","display_name":"Housing Market and Economics","score":0.37560001015663147,"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/T11161","display_name":"Consumer Market Behavior and Pricing","score":0.15479999780654907,"subfield":{"id":"https://openalex.org/subfields/1406","display_name":"Marketing"},"field":{"id":"https://openalex.org/fields/14","display_name":"Business, Management and Accounting"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T11014","display_name":"Regional Economics and Spatial Analysis","score":0.12520000338554382,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/causality","display_name":"Causality (physics)","score":0.7268000245094299},{"id":"https://openalex.org/keywords/endogeneity","display_name":"Endogeneity","score":0.7192999720573425},{"id":"https://openalex.org/keywords/momentum","display_name":"Momentum (technical analysis)","score":0.4814999997615814},{"id":"https://openalex.org/keywords/contrast","display_name":"Contrast (vision)","score":0.47620001435279846},{"id":"https://openalex.org/keywords/causation","display_name":"Causation","score":0.4713999927043915},{"id":"https://openalex.org/keywords/matching","display_name":"Matching (statistics)","score":0.4523000121116638},{"id":"https://openalex.org/keywords/covariate","display_name":"Covariate","score":0.42829999327659607},{"id":"https://openalex.org/keywords/price-premium","display_name":"Price premium","score":0.398499995470047},{"id":"https://openalex.org/keywords/event","display_name":"Event (particle physics)","score":0.38670000433921814},{"id":"https://openalex.org/keywords/event-study","display_name":"Event study","score":0.3799999952316284}],"concepts":[{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.7465000152587891},{"id":"https://openalex.org/C64357122","wikidata":"https://www.wikidata.org/wiki/Q1149766","display_name":"Causality (physics)","level":2,"score":0.7268000245094299},{"id":"https://openalex.org/C610760","wikidata":"https://www.wikidata.org/wiki/Q1340706","display_name":"Endogeneity","level":2,"score":0.7192999720573425},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.6362000107765198},{"id":"https://openalex.org/C60718061","wikidata":"https://www.wikidata.org/wiki/Q1414747","display_name":"Momentum (technical analysis)","level":2,"score":0.4814999997615814},{"id":"https://openalex.org/C2776502983","wikidata":"https://www.wikidata.org/wiki/Q690182","display_name":"Contrast (vision)","level":2,"score":0.47620001435279846},{"id":"https://openalex.org/C166151441","wikidata":"https://www.wikidata.org/wiki/Q4923601","display_name":"Causation","level":2,"score":0.4713999927043915},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.4523000121116638},{"id":"https://openalex.org/C119043178","wikidata":"https://www.wikidata.org/wiki/Q320723","display_name":"Covariate","level":2,"score":0.42829999327659607},{"id":"https://openalex.org/C2778268174","wikidata":"https://www.wikidata.org/wiki/Q7242628","display_name":"Price premium","level":3,"score":0.398499995470047},{"id":"https://openalex.org/C2779662365","wikidata":"https://www.wikidata.org/wiki/Q5416694","display_name":"Event (particle physics)","level":2,"score":0.38670000433921814},{"id":"https://openalex.org/C12958728","wikidata":"https://www.wikidata.org/wiki/Q1002530","display_name":"Event study","level":3,"score":0.3799999952316284},{"id":"https://openalex.org/C152877465","wikidata":"https://www.wikidata.org/wiki/Q208042","display_name":"Regression analysis","level":2,"score":0.3695000112056732},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.34470000863075256},{"id":"https://openalex.org/C2777267654","wikidata":"https://www.wikidata.org/wiki/Q3519023","display_name":"Test (biology)","level":2,"score":0.3314000070095062},{"id":"https://openalex.org/C18762648","wikidata":"https://www.wikidata.org/wiki/Q42213","display_name":"Work (physics)","level":2,"score":0.3305000066757202},{"id":"https://openalex.org/C127722929","wikidata":"https://www.wikidata.org/wiki/Q7833714","display_name":"Transaction data","level":3,"score":0.31459999084472656},{"id":"https://openalex.org/C97379794","wikidata":"https://www.wikidata.org/wiki/Q4503892","display_name":"Censored regression model","level":3,"score":0.310699999332428},{"id":"https://openalex.org/C2992949716","wikidata":"https://www.wikidata.org/wiki/Q512599","display_name":"House price","level":2,"score":0.30709999799728394},{"id":"https://openalex.org/C108650721","wikidata":"https://www.wikidata.org/wiki/Q1783253","display_name":"Counterfactual thinking","level":2,"score":0.2930999994277954},{"id":"https://openalex.org/C11671645","wikidata":"https://www.wikidata.org/wiki/Q5054567","display_name":"Causal model","level":2,"score":0.29019999504089355},{"id":"https://openalex.org/C527412718","wikidata":"https://www.wikidata.org/wiki/Q855395","display_name":"Interpretation (philosophy)","level":2,"score":0.28769999742507935},{"id":"https://openalex.org/C162144332","wikidata":"https://www.wikidata.org/wiki/Q1665305","display_name":"Instrumental variable","level":2,"score":0.27950000762939453},{"id":"https://openalex.org/C120936955","wikidata":"https://www.wikidata.org/wiki/Q2155640","display_name":"Empirical research","level":2,"score":0.27639999985694885},{"id":"https://openalex.org/C6422946","wikidata":"https://www.wikidata.org/wiki/Q857354","display_name":"Panel data","level":2,"score":0.27410000562667847},{"id":"https://openalex.org/C83546350","wikidata":"https://www.wikidata.org/wiki/Q1139051","display_name":"Regression","level":2,"score":0.2736999988555908},{"id":"https://openalex.org/C168743327","wikidata":"https://www.wikidata.org/wiki/Q1826427","display_name":"Random effects model","level":3,"score":0.26840001344680786},{"id":"https://openalex.org/C2987896495","wikidata":"https://www.wikidata.org/wiki/Q5416716","display_name":"Event data","level":3,"score":0.2621999979019165},{"id":"https://openalex.org/C175444787","wikidata":"https://www.wikidata.org/wiki/Q39072","display_name":"Microeconomics","level":1,"score":0.25529998540878296},{"id":"https://openalex.org/C196083921","wikidata":"https://www.wikidata.org/wiki/Q7915758","display_name":"Variance (accounting)","level":2,"score":0.25130000710487366}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/dsaa65442.2025.11247972","is_oa":false,"landing_page_url":"https://doi.org/10.1109/dsaa65442.2025.11247972","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE 12th International Conference on Data Science and Advanced Analytics (DSAA)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":10,"referenced_works":["https://openalex.org/W1508352817","https://openalex.org/W2051688880","https://openalex.org/W2096684396","https://openalex.org/W2123758275","https://openalex.org/W2607813124","https://openalex.org/W2732873697","https://openalex.org/W2953284850","https://openalex.org/W2965557182","https://openalex.org/W3203390144","https://openalex.org/W4248863881"],"related_works":[],"abstract_inverted_index":{"The":[0],"relationship":[1],"between":[2,125,146,232],"cafes":[3],"and":[4,30,46,67,115,122,128,149,151,174,178,180,220,235,269,281],"house":[5,126,153,236],"prices":[6,127,237],"is":[7,58],"an":[8,91],"emerging":[9],"field":[10],"of":[11,49,69,72,143],"study":[12,83,120,185],"in":[13,75,156,196],"urban":[14,266],"data":[15],"analytics.":[16],"Recent":[17],"research":[18],"suggests":[19],"that":[20,216,249],"homes":[21],"near":[22],"cafes,":[23,26],"especially":[24],"premium":[25,129],"start":[27],"out":[28],"dearer":[29],"appreciate":[31],"faster":[32],"than":[33],"the":[34,47,76,144,247,250],"broader":[35],"U.S.":[36,159],"housing":[37],"market.":[38],"However,":[39],"significant":[40,225],"endogeneity":[41],"due":[42],"to":[43,85,118,166,199],"omitted":[44],"variables":[45],"possibility":[48],"bidirectional":[50,73,226,252],"causality":[51,124],"has":[52],"made":[53],"interpretation":[54],"problematic.":[55],"This":[56],"uncertainty":[57],"compounded":[59],"by":[60,210,257],"limited":[61],"methodical":[62],"transparency,":[63],"inadequate":[64],"falsification":[65],"criteria,":[66],"absence":[68],"rigorous":[70],"analysis":[71,142],"causation":[74],"published":[77],"work":[78],"on":[79,95,265],"this":[80],"topic.":[81],"Our":[82,184,260],"aims":[84],"fill":[86],"these":[87],"gaps.":[88],"We":[89,168,214],"present":[90],"analytical":[92],"framework":[93],"based":[94],"a":[96,105,135,187,271],"Two-Way":[97],"Fixed":[98],"Effects":[99],"(TWFE)":[100],"event-study":[101],"regression":[102],"model":[103],"(i.e.,":[104],"generalized":[106],"difference-in-differences":[107],"design":[108],"for":[109,170,274],"staggered":[110],"entry)":[111],"combined":[112],"with":[113,191,229,278],"matching":[114],"covariate":[116],"adjustment,":[117],"simultaneously":[119],"forward":[121],"reverse":[123],"caf\u00e9":[130],"entry.":[131],"Using":[132],"Starbucks":[133,193],"as":[134],"case":[136],"study,":[137],"we":[138],"performed":[139],"robust":[140],"empirical":[141,276],"association":[145],"Starbucks'":[147,233],"entry,":[148],"pre-":[150,202],"post-entry":[152,204],"price":[154,172,182,205,222],"growth":[155,206],"over":[157],"500":[158],"neighborhoods":[160],"across":[161],"45":[162],"states":[163],"from":[164],"2012":[165],"2022.":[167],"controlled":[169],"nationwide":[171],"trends":[173],"shocks,":[175],"neighborhood":[176,218],"affluence,":[177],"short-":[179],"long-term":[181],"momentum.":[183],"included":[186],"placebo":[188],"arm":[189],"populated":[190],"\u201cfake\u201d":[192],"stores":[194],"opened":[195],"random":[197],"years":[198],"test":[200],"whether":[201],"or":[203],"was":[207],"driven":[208,255],"solely":[209],"non-Starbucks":[211,258],"related":[212],"covariates.":[213,259],"found":[215],"while":[217],"characteristics":[219],"historical":[221],"momentum":[223],"dominated,":[224],"effects":[227,253],"consistent":[228],"causal":[230],"influence":[231],"entry":[234],"were":[238,254],"also":[239],"observed":[240,251],"under":[241],"stated":[242],"assumptions.":[243],"Placebo":[244],"results":[245],"falsified":[246],"hypothesis":[248],"purely":[256],"findings":[261],"contribute":[262],"real-world":[263],"insights":[264],"amenity-price":[267],"dynamics":[268],"offer":[270],"generalizable":[272],"template":[273],"such":[275],"studies":[277],"strong":[279],"policy":[280],"market":[282],"relevance.":[283]},"counts_by_year":[],"updated_date":"2026-03-07T16:01:11.037858","created_date":"2025-11-25T00:00:00"}
