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A review of spatial econometric models for count data

dc.contributor.authorGlaser, Stephaniede
dc.date.accessioned2024-04-08T08:54:44Z
dc.date.available2024-04-08T08:54:44Z
dc.date.created2017-08-24
dc.date.issued2017
dc.description.abstractDespite the increasing availability of spatial count data in research areas like technology spillovers, patenting activities, insurance payments, and crime forecasting, specialized models for analysing such data have received little attention in econometric literature so far. The few existing approaches can be broadly classified into observation-driven models, where the random spatial effects enter the moments of the dependent variable directly, and parameterdriven models, where the random spatial effects are unobservable and induced via a latent process. Moreover, within these groups the modelling approaches (and therefore the interpretation) of spatial effects are quite heterogeneous, stemming in part from the nonlinear structure of count data models. The purpose of this survey is to compare and contrast the various approaches for econometric modelling of spatial counts discussed in the literature.en
dc.identifier.swb492773122
dc.identifier.urihttps://hohpublica.uni-hohenheim.de/handle/123456789/6182
dc.identifier.urnurn:nbn:de:bsz:100-opus-13975
dc.language.isoeng
dc.relation.ispartofseriesHohenheim discussion papers in business, economics and social sciences; 2017,19
dc.rights.licensepubl-mit-poden
dc.rights.licensepubl-mit-podde
dc.rights.urihttp://opus.uni-hohenheim.de/doku/lic_mit_pod.php
dc.subject.ddc330
dc.subject.gndÖkonometrisches Modellde
dc.subject.gndZähldatende
dc.titleA review of spatial econometric models for count datade
dc.type.dcmiTextde
dc.type.diniWorkingPaperde
local.accessuneingeschränkter Zugriffen
local.accessuneingeschränkter Zugriffde
local.bibliographicCitation.publisherPlaceUniversität Hohenheimde
local.export.bibtex@techreport{Glaser2017, url = {https://hohpublica.uni-hohenheim.de/handle/123456789/6182}, author = {Glaser, Stephanie}, title = {A review of spatial econometric models for count data}, year = {2017}, school = {Universität Hohenheim}, series = {Hohenheim discussion papers in business, economics and social sciences}, }
local.export.bibtexAuthorGlaser, Stephanie
local.export.bibtexKeyGlaser2017
local.export.bibtexType@techreport
local.faculty.number3de
local.institute.number520de
local.opus.number1397
local.series.issueNumber2017,19
local.series.titleHohenheim discussion papers in business, economics and social sciences
local.universityUniversität Hohenheimde
local.university.facultyFaculty of Business, Economics and Social Sciencesen
local.university.facultyFakultät Wirtschafts- und Sozialwissenschaftende
local.university.instituteInstitute for Economicsen
local.university.instituteInstitut für Volkswirtschaftslehrede

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