Achtung: hohPublica wurde am 18.11.2024 aktualisiert. Falls Sie auf Darstellungsfehler stoßen, löschen Sie bitte Ihren Browser-Cache (Strg + Umschalt + Entf). *** Attention: hohPublica was last updated on November 18, 2024. If you encounter display errors, please delete your browser cache (Ctrl + Shift + Del).
 

A new version of this entry is available:

Loading...
Thumbnail Image
ResearchPaper
2017

A review of spatial econometric models for count data

Abstract (English)

Despite 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.

File is subject to an embargo until

This is a correction to:

A correction to this entry is available:

This is a new version of:

Notes

Publication license

Publication series

Hohenheim discussion papers in business, economics and social sciences; 2017,19

Published in

Faculty
Faculty of Business, Economics and Social Sciences
Institute
Institute of Economics

Examination date

Supervisor

Edition / version

Citation

DOI

ISSN

ISBN

Language
English

Publisher

Publisher place

Classification (DDC)
330 Economics

Original object

Free keywords

Standardized keywords (GND)

Sustainable Development Goals

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}, }
Share this publication