A spatiotemporal analysis of agricultural prices: An application to Colombian data

This study focusses on whether the geographical separation of markets constitutes a factor that helps explain the dynamics of agricultural prices. To do this, the authors employ a highly disaggregated dataset for Colombia that consists of weekly observations on wholesale prices for 18 agricultural p...

Full description

Autores:
Tipo de recurso:
Fecha de publicación:
2013
Institución:
Universidad del Rosario
Repositorio:
Repositorio EdocUR - U. Rosario
Idioma:
eng
OAI Identifier:
oai:repository.urosario.edu.co:10336/23863
Acceso en línea:
https://doi.org/10.1002/agr.21319
https://repository.urosario.edu.co/handle/10336/23863
Palabra clave:
O18
Q13
R12
Rights
License
Abierto (Texto Completo)
id EDOCUR2_17372864a61898f94211b86836e8ef05
oai_identifier_str oai:repository.urosario.edu.co:10336/23863
network_acronym_str EDOCUR2
network_name_str Repositorio EdocUR - U. Rosario
repository_id_str
spelling 1f1a7996-5b8a-4390-bdc9-3ff88367043b-1792428146002020-05-26T00:06:10Z2020-05-26T00:06:10Z2013This study focusses on whether the geographical separation of markets constitutes a factor that helps explain the dynamics of agricultural prices. To do this, the authors employ a highly disaggregated dataset for Colombia that consists of weekly observations on wholesale prices for 18 agricultural products traded in markets scattered around the country. The sample period spans almost a decade. According to their results, which are based on generalized impulse response functions, distance (and thus transportation costs) is a factor that helps explain the speed at which prices adjust to shocks in other locations, thus confirming that price adjustments take longer for markets farther apart. © 2012 Wiley Periodicals, Inc.application/pdfhttps://doi.org/10.1002/agr.213190742447715206297https://repository.urosario.edu.co/handle/10336/23863eng508No. 4497AgribusinessVol. 29Agribusiness, ISSN:07424477, 15206297, Vol.29, No.4 (2013); pp. 497-508https://www.scopus.com/inward/record.uri?eid=2-s2.0-84885184468&doi=10.1002%2fagr.21319&partnerID=40&md5=28d53495d12f3cf1566e4f58db4b3104Abierto (Texto Completo)http://purl.org/coar/access_right/c_abf2instname:Universidad del Rosarioreponame:Repositorio Institucional EdocURO18Q13R12A spatiotemporal analysis of agricultural prices: An application to Colombian dataarticleArtículohttp://purl.org/coar/version/c_970fb48d4fbd8a85http://purl.org/coar/resource_type/c_6501Iregui, Ana MaríaOtero Cardona, Jesús Gilberto10336/23863oai:repository.urosario.edu.co:10336/238632022-05-02 07:37:21.243352https://repository.urosario.edu.coRepositorio institucional EdocURedocur@urosario.edu.co
dc.title.spa.fl_str_mv A spatiotemporal analysis of agricultural prices: An application to Colombian data
title A spatiotemporal analysis of agricultural prices: An application to Colombian data
spellingShingle A spatiotemporal analysis of agricultural prices: An application to Colombian data
O18
Q13
R12
title_short A spatiotemporal analysis of agricultural prices: An application to Colombian data
title_full A spatiotemporal analysis of agricultural prices: An application to Colombian data
title_fullStr A spatiotemporal analysis of agricultural prices: An application to Colombian data
title_full_unstemmed A spatiotemporal analysis of agricultural prices: An application to Colombian data
title_sort A spatiotemporal analysis of agricultural prices: An application to Colombian data
dc.subject.keyword.spa.fl_str_mv O18
Q13
R12
topic O18
Q13
R12
description This study focusses on whether the geographical separation of markets constitutes a factor that helps explain the dynamics of agricultural prices. To do this, the authors employ a highly disaggregated dataset for Colombia that consists of weekly observations on wholesale prices for 18 agricultural products traded in markets scattered around the country. The sample period spans almost a decade. According to their results, which are based on generalized impulse response functions, distance (and thus transportation costs) is a factor that helps explain the speed at which prices adjust to shocks in other locations, thus confirming that price adjustments take longer for markets farther apart. © 2012 Wiley Periodicals, Inc.
publishDate 2013
dc.date.created.spa.fl_str_mv 2013
dc.date.accessioned.none.fl_str_mv 2020-05-26T00:06:10Z
dc.date.available.none.fl_str_mv 2020-05-26T00:06:10Z
dc.type.eng.fl_str_mv article
dc.type.coarversion.fl_str_mv http://purl.org/coar/version/c_970fb48d4fbd8a85
dc.type.coar.fl_str_mv http://purl.org/coar/resource_type/c_6501
dc.type.spa.spa.fl_str_mv Artículo
dc.identifier.doi.none.fl_str_mv https://doi.org/10.1002/agr.21319
dc.identifier.issn.none.fl_str_mv 07424477
15206297
dc.identifier.uri.none.fl_str_mv https://repository.urosario.edu.co/handle/10336/23863
url https://doi.org/10.1002/agr.21319
https://repository.urosario.edu.co/handle/10336/23863
identifier_str_mv 07424477
15206297
dc.language.iso.spa.fl_str_mv eng
language eng
dc.relation.citationEndPage.none.fl_str_mv 508
dc.relation.citationIssue.none.fl_str_mv No. 4
dc.relation.citationStartPage.none.fl_str_mv 497
dc.relation.citationTitle.none.fl_str_mv Agribusiness
dc.relation.citationVolume.none.fl_str_mv Vol. 29
dc.relation.ispartof.spa.fl_str_mv Agribusiness, ISSN:07424477, 15206297, Vol.29, No.4 (2013); pp. 497-508
dc.relation.uri.spa.fl_str_mv https://www.scopus.com/inward/record.uri?eid=2-s2.0-84885184468&doi=10.1002%2fagr.21319&partnerID=40&md5=28d53495d12f3cf1566e4f58db4b3104
dc.rights.coar.fl_str_mv http://purl.org/coar/access_right/c_abf2
dc.rights.acceso.spa.fl_str_mv Abierto (Texto Completo)
rights_invalid_str_mv Abierto (Texto Completo)
http://purl.org/coar/access_right/c_abf2
dc.format.mimetype.none.fl_str_mv application/pdf
institution Universidad del Rosario
dc.source.instname.spa.fl_str_mv instname:Universidad del Rosario
dc.source.reponame.spa.fl_str_mv reponame:Repositorio Institucional EdocUR
repository.name.fl_str_mv Repositorio institucional EdocUR
repository.mail.fl_str_mv edocur@urosario.edu.co
_version_ 1814167496729559040