{"id":"https://openalex.org/W2022865075","doi":"https://doi.org/10.1080/03610910903147789","title":"Simple Tests for Exogeneity of a Binary Explanatory Variable in Count Data Regression Models","display_name":"Simple Tests for Exogeneity of a Binary Explanatory Variable in Count Data Regression Models","publication_year":2009,"publication_date":"2009-09-03","ids":{"openalex":"https://openalex.org/W2022865075","doi":"https://doi.org/10.1080/03610910903147789","mag":"2022865075"},"language":"en","primary_location":{"id":"doi:10.1080/03610910903147789","is_oa":false,"landing_page_url":"https://doi.org/10.1080/03610910903147789","pdf_url":null,"source":{"id":"https://openalex.org/S153329750","display_name":"Communications in Statistics - Simulation and Computation","issn_l":"0361-0918","issn":["0361-0918","1532-4141"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320547","host_organization_name":"Taylor & Francis","host_organization_lineage":["https://openalex.org/P4310320547"],"host_organization_lineage_names":["Taylor & Francis"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Communications in Statistics - Simulation and Computation","raw_type":"journal-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/A5082286604","display_name":"Kevin E. Staub","orcid":"https://orcid.org/0000-0002-1546-1761"},"institutions":[{"id":"https://openalex.org/I200744771","display_name":"ZHAW Zurich University of Applied Sciences","ror":null,"country_code":"CH","type":null,"lineage":["https://openalex.org/I200744771"]},{"id":"https://openalex.org/I202697423","display_name":"University of Zurich","ror":"https://ror.org/02crff812","country_code":"CH","type":"education","lineage":["https://openalex.org/I202697423"]}],"countries":["CH"],"is_corresponding":true,"raw_author_name":"Kevin E. Staub","raw_affiliation_strings":["\n                   \n               Statistics and Empirical Economic Research, Socioeconomic Institute, University of Zurich, Zurich, Switzerland","Statistics and Empirical Economic Research, Socioeconomic Institute , University of Zurich , Zurich , Switzerland"],"affiliations":[{"raw_affiliation_string":"\n                   \n               Statistics and Empirical Economic Research, Socioeconomic Institute, University of Zurich, Zurich, Switzerland","institution_ids":["https://openalex.org/I200744771"]},{"raw_affiliation_string":"Statistics and Empirical Economic Research, Socioeconomic Institute , University of Zurich , Zurich , Switzerland","institution_ids":["https://openalex.org/I202697423"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5082286604"],"corresponding_institution_ids":["https://openalex.org/I200744771","https://openalex.org/I202697423"],"apc_list":null,"apc_paid":null,"fwci":3.3922,"has_fulltext":false,"cited_by_count":24,"citation_normalized_percentile":{"value":0.92531427,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":"38","issue":"9","first_page":"1834","last_page":"1855"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10243","display_name":"Statistical Methods and Bayesian Inference","score":0.9939000010490417,"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/T10243","display_name":"Statistical Methods and Bayesian Inference","score":0.9939000010490417,"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/T10136","display_name":"Statistical Methods and Inference","score":0.9815999865531921,"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/T11911","display_name":"Spatial and Panel Data Analysis","score":0.9710000157356262,"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/endogeneity","display_name":"Endogeneity","score":0.8025112152099609},{"id":"https://openalex.org/keywords/univariate","display_name":"Univariate","score":0.6482177972793579},{"id":"https://openalex.org/keywords/monte-carlo-method","display_name":"Monte Carlo method","score":0.6163747310638428},{"id":"https://openalex.org/keywords/wald-test","display_name":"Wald test","score":0.6062168478965759},{"id":"https://openalex.org/keywords/econometrics","display_name":"Econometrics","score":0.6026226282119751},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.5258755683898926},{"id":"https://openalex.org/keywords/binary-number","display_name":"Binary number","score":0.46548429131507874},{"id":"https://openalex.org/keywords/count-data","display_name":"Count data","score":0.443163126707077},{"id":"https://openalex.org/keywords/explanatory-power","display_name":"Explanatory power","score":0.4419136047363281},{"id":"https://openalex.org/keywords/simple","display_name":"Simple (philosophy)","score":0.4203070402145386},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.41917771100997925},{"id":"https://openalex.org/keywords/contrast","display_name":"Contrast (vision)","score":0.4156579375267029},{"id":"https://openalex.org/keywords/regression-analysis","display_name":"Regression analysis","score":0.41138380765914917},{"id":"https://openalex.org/keywords/statistical-hypothesis-testing","display_name":"Statistical hypothesis testing","score":0.35900700092315674},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.3389289677143097},{"id":"https://openalex.org/keywords/multivariate-statistics","display_name":"Multivariate statistics","score":0.23105308413505554},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.0866117775440216}],"concepts":[{"id":"https://openalex.org/C610760","wikidata":"https://www.wikidata.org/wiki/Q1340706","display_name":"Endogeneity","level":2,"score":0.8025112152099609},{"id":"https://openalex.org/C199163554","wikidata":"https://www.wikidata.org/wiki/Q1681619","display_name":"Univariate","level":3,"score":0.6482177972793579},{"id":"https://openalex.org/C19499675","wikidata":"https://www.wikidata.org/wiki/Q232207","display_name":"Monte Carlo method","level":2,"score":0.6163747310638428},{"id":"https://openalex.org/C203274628","wikidata":"https://www.wikidata.org/wiki/Q748664","display_name":"Wald test","level":3,"score":0.6062168478965759},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.6026226282119751},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.5258755683898926},{"id":"https://openalex.org/C48372109","wikidata":"https://www.wikidata.org/wiki/Q3913","display_name":"Binary number","level":2,"score":0.46548429131507874},{"id":"https://openalex.org/C33643355","wikidata":"https://www.wikidata.org/wiki/Q5176731","display_name":"Count data","level":3,"score":0.443163126707077},{"id":"https://openalex.org/C2777402642","wikidata":"https://www.wikidata.org/wiki/Q2557224","display_name":"Explanatory power","level":2,"score":0.4419136047363281},{"id":"https://openalex.org/C2780586882","wikidata":"https://www.wikidata.org/wiki/Q7520643","display_name":"Simple (philosophy)","level":2,"score":0.4203070402145386},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.41917771100997925},{"id":"https://openalex.org/C2776502983","wikidata":"https://www.wikidata.org/wiki/Q690182","display_name":"Contrast (vision)","level":2,"score":0.4156579375267029},{"id":"https://openalex.org/C152877465","wikidata":"https://www.wikidata.org/wiki/Q208042","display_name":"Regression analysis","level":2,"score":0.41138380765914917},{"id":"https://openalex.org/C87007009","wikidata":"https://www.wikidata.org/wiki/Q210832","display_name":"Statistical hypothesis testing","level":2,"score":0.35900700092315674},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.3389289677143097},{"id":"https://openalex.org/C161584116","wikidata":"https://www.wikidata.org/wiki/Q1952580","display_name":"Multivariate statistics","level":2,"score":0.23105308413505554},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.0866117775440216},{"id":"https://openalex.org/C94375191","wikidata":"https://www.wikidata.org/wiki/Q11205","display_name":"Arithmetic","level":1,"score":0.0},{"id":"https://openalex.org/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C100906024","wikidata":"https://www.wikidata.org/wiki/Q205692","display_name":"Poisson distribution","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1080/03610910903147789","is_oa":false,"landing_page_url":"https://doi.org/10.1080/03610910903147789","pdf_url":null,"source":{"id":"https://openalex.org/S153329750","display_name":"Communications in Statistics - Simulation and Computation","issn_l":"0361-0918","issn":["0361-0918","1532-4141"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320547","host_organization_name":"Taylor & Francis","host_organization_lineage":["https://openalex.org/P4310320547"],"host_organization_lineage_names":["Taylor & Francis"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Communications in Statistics - Simulation and Computation","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":41,"referenced_works":["https://openalex.org/W93405093","https://openalex.org/W1489060568","https://openalex.org/W1505643565","https://openalex.org/W1526492707","https://openalex.org/W1579670268","https://openalex.org/W1583862312","https://openalex.org/W1948981866","https://openalex.org/W1975385327","https://openalex.org/W1983858769","https://openalex.org/W1993663963","https://openalex.org/W1995410581","https://openalex.org/W2000413188","https://openalex.org/W2003220536","https://openalex.org/W2010548614","https://openalex.org/W2037784954","https://openalex.org/W2040774619","https://openalex.org/W2052870469","https://openalex.org/W2054907758","https://openalex.org/W2071346964","https://openalex.org/W2079032770","https://openalex.org/W2100130392","https://openalex.org/W2100440978","https://openalex.org/W2104278312","https://openalex.org/W2112352537","https://openalex.org/W2119151205","https://openalex.org/W2130582315","https://openalex.org/W2141529881","https://openalex.org/W2154219987","https://openalex.org/W2344757716","https://openalex.org/W2477265419","https://openalex.org/W3122370190","https://openalex.org/W3122946840","https://openalex.org/W3123476065","https://openalex.org/W3124296889","https://openalex.org/W3124398502","https://openalex.org/W3125210883","https://openalex.org/W3125786087","https://openalex.org/W4243247664","https://openalex.org/W4285719527","https://openalex.org/W4292402584","https://openalex.org/W4297935721"],"related_works":["https://openalex.org/W2210833003","https://openalex.org/W3146412303","https://openalex.org/W1487536244","https://openalex.org/W2894699514","https://openalex.org/W2013192938","https://openalex.org/W2759839044","https://openalex.org/W2080462468","https://openalex.org/W2144986338","https://openalex.org/W3126008192","https://openalex.org/W3123204637"],"abstract_inverted_index":{"Abstract":[0],"This":[1,85,412],"article":[2],"investigates":[3],"power":[4,490,499],"and":[5,60,110,128,155,168,183,188,325,338,400,443,446,513,572,582,663,700,730],"size":[6,535,565,646,649,721,724],"of":[7,12,44,49,56,185,210,213,218,239,242,287,312,314,344,359,406,429,451,462,520,527,547,569,638,668,690,713,727],"some":[8],"tests":[9,27,33,51,73,80,509,630,695],"for":[10,90,114,125,149,204,249,373,389,474,553,559,623,680],"exogeneity":[11,586,692],"a":[13,41,266,382,423],"binary":[14,328],"explanatory":[15],"variable":[16],"in":[17,163,193,216,272,304,309,317,335,403,511,540,576,591,613,654,661,734],"count":[18,181,368,408,430],"models":[19,306,320,360,432],"by":[20,208,397,418],"conducting":[21],"extensive":[22,126],"Monte":[23,426],"Carlo":[24,427],"simulations.":[25],"The":[26,67,101,387,470,609,676],"under":[28,54,61,277,517,602],"consideration":[29,278,603],"are":[30,75,82,138,147,177,192,244,515,612,705],"Hausman":[31],"contrast":[32],"as":[34,36,199,284,538,574,617,652,703,732],"well":[35],"univariate":[37],"Wald":[38,624],"tests,":[39],"including":[40],"new":[42,92],"test":[43,534,564,645,720],"notably":[45],"easy":[46],"implementation.":[47],"Performance":[48],"the":[50,57,65,72,88,91,139,186,211,214,229,236,273,282,285,288,294,357,404,452,503,521,592,600,605,670,691],"is":[52,86,207,247,257,307,353,363,394,477,487,500,506,597,674,678],"explored":[53],"misspecification":[55],"underlying":[58],"model":[59,215,383,601],"different":[62],"conditions":[63],"regarding":[64],"instruments.":[66],"results":[68,189,611],"indicate":[69],"that":[70,74,81,301,354],"often":[71],"simpler":[76],"to":[77,104,122,180,196,281,365,384,421,484,491,599,631],"estimate":[78,677],"outperform":[79],"more":[83],"demanding.":[84],"especially":[87],"case":[89,276],"test.":[93,469,693],"Keywords:":[94],"Dummy":[95],"variableEndogeneityPoissonTestingMathematics":[96],"Subject":[97],"Classification:":[98],"62H1562F03":[99],"Acknowledgments":[100],"author":[102],"wishes":[103],"thank":[105],"Jo\u00e3o":[106],"M.C.":[107],"Santos":[108,398],"Silva":[109,399],"an":[111],"anonymous":[112],"referee":[113],"helpful":[115],"comments":[116],"on":[117,235,436],"this":[118,133,205,361],"article.":[119,134],"Special":[120],"thanks":[121],"Rainer":[123],"Winkelmann":[124,339],"discussion":[127],"advise":[129],"which":[130,514,596,673],"significantly":[131],"improved":[132],"Any":[135],"remaining":[136],"errors":[137],"author's":[140],"sole":[141],"responsability.":[142],"Notes":[143],"For":[144],"example,":[145],"there":[146],"routines":[148],"both":[150,279],"Mullahy's":[151],"(Citation1997)":[152,337],"NLIV/GMM":[153],"estimator":[154,162,362],"Terza's":[156],"(Citation1998)":[157],"full":[158],"information":[159],"maximum":[160],"likelihood":[161,628],"STATA.":[164],"See":[165],"Nichols":[166],"(Citation2007)":[167],"Miranda":[169],"(Citation2004),":[170,441],"respectively.":[171],"Evidently,":[172],"exponential":[173,369,409],"conditional":[174],"mean":[175],"functions":[176],"not":[178,233,264,292,697],"limited":[179],"data,":[182],"many":[184],"procedures":[187],"discussed":[190],"here":[191],"principle":[194],"applicable":[195,364],"continuous":[197,322],"data":[198,431,522],"well.":[200],"An":[201,341],"alternative":[202],"justification":[203],"representation":[206],"means":[209],"interpretability":[212],"terms":[217],"ceteris":[219],"paribus":[220],"marginal":[221],"effects":[222,231],"(cf.":[223],"(Winkelmann,":[224],"Citation2008;,":[225],"p.":[226],"160)).":[227],"While":[228],"partial":[230],"do":[232,696],"depend":[234],"first":[237],"element":[238],"\u03b2,":[240],"predictions":[241],"CEF":[243,370,410],"consistent":[245,248],"because":[246],"x\u2032\u03b2":[250],"+ln":[251],"E[exp":[252],"(\u03f5)].":[253],"Creel's":[254],"(Citation2004)":[255],"approach":[256],"optimal":[258],"GMM,":[259],"while":[260],"Weesie":[261],"(Citation1999)":[262],"does":[263,291],"use":[265,485,698],"second":[267],"step":[268],"weighting":[269,289],"matrix.":[270],"Clearly,":[271],"just":[274],"identified":[275],"amount":[280],"same":[283],"choice":[286],"matrix":[290],"affect":[293],"estimates.":[295],"Terza":[296],"et":[297,376],"al.":[298,377],"(Citation2008)":[299,584],"showed":[300],"residual":[302,315],"inclusion":[303,316],"nonlinear":[305],"inconsistent":[308,679,706],"general.":[310],"Discussions":[311],"consistency":[313,667,689],"Poisson":[318,390],"PML":[319],"with":[321,327,433,588,615],"endogenous":[323,437],"regressors":[324,329],"inconsistency":[326],"can":[330],"be":[331],"found":[332],"inter":[333],"alia":[334],"Wooldridge":[336],"(Citation2008).":[340],"important":[342],"aspect":[343],"leaving":[345],"f(y":[346],"|":[347],"d,":[348],"x,":[349],"z,":[350],"\u03f5)":[351],"unspecified":[352],"it":[355],"broadens":[356],"class":[358],"other":[366],"non":[367,407],"models.":[371,411],"See,":[372],"instance,":[374],"Egger":[375],"(Citation2009)":[378],"who":[379],"applied":[380],"such":[381],"bilateral":[385],"trade.":[386],"argument":[388],"pseudo-MLE":[391],"against":[392],"NLS":[393],"presented":[395],"extensively":[396],"Tenreyro":[401],"(Citation2006)":[402],"context":[405],"technique":[413],"has":[414],"also":[415],"been":[416],"used":[417],"Angrist":[419],"(Citation2001)":[420],"approximate":[422],"Tobit":[424],"MLE.":[425],"studies":[428],"unit":[434],"coefficient":[435],"variables":[438],"include":[439],"Creel":[440],"Romeu":[442,662],"Vera-Hernandez":[444,664],"(Citation2005),":[445],"Chmelarova":[447],"(Citation2007).":[448],"*Marginal":[449],"distributions":[450],"copulae:":[453],"\u03f5":[454],"\u223cexpGamma(1,":[455],"1),":[456],"v":[457],"\u223cLogistic(0,":[458],"3/\u03c0).":[459],"Notes:":[460,525,545,636,711],"Number":[461,526,546,637,712],"replications":[463,476,528,548,552,558,639,714],"=10,000":[464,529,549,640,715],"(FIML:":[465,530,550,641,716],"2,000":[466,475,531,551,642,717],"replications).":[467,532,643,718],"Nominal":[468,533,563,644,719],"corresponding":[471],"confidence":[472],"interval":[473],"approximately":[478],"[0.405,":[479],"0.595].":[480],"Some":[481],"authors":[482],"prefer":[483],"what":[486],"called":[488],"size-corrected":[489,498],"make":[492],"comparisons":[493],"across":[494],"tests.":[495,625],"Here,":[496],"no":[497,589],"presented,":[501],"since":[502],"question":[504],"addressed":[505],"how":[507],"these":[508,704],"work":[510],"practice":[512],"useful":[516],"given":[518],"characteristics":[519],"generating":[523],"process.":[524],"=0.05.":[536,647,722],"IV-strength":[537,568,651,726],"detailed":[539,575,653,733],"text":[541,577,655,735],"or":[542,578,656,736],"Table":[543,579,657,737],"1.":[544,580,658,738],"N":[554,560],"=":[555,561,566,709],"500,":[556],"1,000":[557],"2,000).":[562],"0.05.":[567],"columns":[570,728],"(1)":[571,729],"(2)":[573,731],"Monfardini":[581],"Radice":[583],"investigated":[585],"testing":[587],"instruments":[590],"bivariate":[593,606],"probit":[594],"model,":[595],"related":[598],"through":[604],"normality":[607],"assumption.":[608],"present":[610],"line":[614],"theirs,":[616],"they":[618],"report":[619],"high":[620],"overrejection":[621],"rates":[622],"They":[626],"find":[627],"ratio":[629],"have":[632],"appropriate":[633],"empirical":[634],"size.":[635],"Sample":[648,723],"=500.":[650,725],"Corollary":[659],"1":[660],"(Citation2005)":[665],"established":[666],"excluding":[669],"constant":[671],"element,":[672],"shifted.":[675],"\u03c1":[681,686,708],"but":[682],"equals":[683],"0":[684],"whenever":[685],"does,":[687],"securing":[688],"Second-stage":[694],"RI-TSA":[699],"GRI-TSA":[701],"estimates":[702],"unless":[707],"0.":[710]},"counts_by_year":[{"year":2021,"cited_by_count":1},{"year":2019,"cited_by_count":5},{"year":2018,"cited_by_count":1},{"year":2016,"cited_by_count":2},{"year":2014,"cited_by_count":2},{"year":2013,"cited_by_count":1},{"year":2012,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}