Solving the Puzzle: A New Measure of Trade Distance In The Gravity

The gravity model is a workhorse tool that has been widely used in international trade. However, one empirical question that frequently arises is related to the conceptualization and measurement of distance. To overcome this limitation, our study proposes an index of distance based on multivariate s...

Full description

Autores:
Mejía Mejía, Juan Felipe
Ramírez Hassan, Andrés
Tipo de recurso:
Fecha de publicación:
2013
Institución:
Universidad EAFIT
Repositorio:
Repositorio EAFIT
Idioma:
eng
OAI Identifier:
oai:repository.eafit.edu.co:10784/993
Acceso en línea:
http://hdl.handle.net/10784/993
Palabra clave:
Factor Analysis for Mixed Data
Gravity Equation Model
Panel Data
Trade Distance
Rights
License
Acceso abierto
id REPOEAFIT2_a78d3ce99692c02ce40358aa340615f5
oai_identifier_str oai:repository.eafit.edu.co:10784/993
network_acronym_str REPOEAFIT2
network_name_str Repositorio EAFIT
repository_id_str
spelling Medellín de: Lat: 06 15 00 N degrees minutes Lat: 6.2500 decimal degrees Long: 075 36 00 W degrees minutes Long: -75.6000 decimal degrees2013-07-11T19:34:51Z2014-06-112013-07-11T19:34:51Zhttp://hdl.handle.net/10784/993F11F14The gravity model is a workhorse tool that has been widely used in international trade. However, one empirical question that frequently arises is related to the conceptualization and measurement of distance. To overcome this limitation, our study proposes an index of distance based on multivariate statistical analysis. Specifically, we build our index using Factorial Analysis for Mixed Data. For robustness check, we use Principal Component Analysis. Both techniques summarize in one factor information related to geographical, cultural, political and economic variables that might affect international trade between countries. We use this index as proxy of distance, and Gross Domestic Product as proxy of mass, and we run some panel data exercises between 1995 and 2000 for 10 Latin American economies. Estimations indicate that the sign of the load factors in Factor Analysis for Mixed Data are intuitively plausible, and that panel data exercises give sensible robust outcomes.engUniversidad EAFITEscuela de Economía y FinanzasSolving the Puzzle: A New Measure of Trade Distance In The GravityworkingPaperinfo:eu-repo/semantics/workingPaperDocumento de trabajo de investigacióndrafthttp://purl.org/coar/version/c_b1a7d7d4d402bccehttp://purl.org/coar/resource_type/c_8042Acceso abiertohttp://purl.org/coar/access_right/c_abf2Factor Analysis for Mixed DataGravity Equation ModelPanel DataTrade DistanceMejía Mejía, Juan FelipeRamírez Hassan, Andrésjfmejia@eafit.edu.coaramir21@eafit.edu.coLICENSElicense.txtlicense.txttext/plain; charset=utf-8968https://repository.eafit.edu.co/bitstreams/bd1c5a92-851a-4ede-9d76-13abdc6cba25/download4cc960a42e07fca3808fbd6b90ab2a1fMD52ORIGINAL2013_12_Juan_Felipe_Mejia.pdf2013_12_Juan_Felipe_Mejia.pdfDocumento de trabajo de investigaciónapplication/pdf420483https://repository.eafit.edu.co/bitstreams/dbc532e1-519e-442d-8143-e4f0fcdd29f3/download9b14a8a72a9521628dba44cbde3c31c5MD5310784/993oai:repository.eafit.edu.co:10784/9932024-03-05 14:06:02.928open.accesshttps://repository.eafit.edu.coRepositorio Institucional Universidad EAFITrepositorio@eafit.edu.coQXV0b3JpemFjacOzbiBkZSBQdWJsaWNhY2nDs24gZGUgVmVyc2nDs24gZWxlY3Ryw7NuaWNhIGRlIGxhIFRlc2lzIG8gcHJveWVjdG8gZGUgR3JhZG8uClBvciBtZWRpbyBkZSBlc3RlIGVzY3JpdG8gYXV0b3Jpem8gZW4gZm9ybWEgZ3JhdHVpdGEgeSBwb3IgdGllbXBvIGluZGVmaW5pZG8gYSBsYSBVbml2ZXJzaWRhZCBFQUZJVCBwYXJhIHNpdHVhciBlbiBsYSBCaWJsaW90ZWNhIEx1aXMgRWNoYXZhcnLDrWEgVmlsbGVnYXMgdW4gZWplbXBsYXIgZGVsIHRyYWJham8gY29uIGVsIGZpbiBkZSBzZXIgY29uc3VsdGFkbyBwb3IgZWwgcMO6YmxpY28uCgpJZ3VhbG1lbnRlIGF1dG9yaXpvIGVuIGZvcm1hIGdyYXR1aXRhIHkgcG9yIHRpZW1wbyBpbmRlZmluaWRvIGEgcHVibGljYXIgZW4gZm9ybWEgZWxlY3Ryw7NuaWNhIG8gZGl2dWxnYXIgcG9yIG1lZGlvIGVsZWN0csOzbmljbyBlbCB0ZXh0byBkZWwgdHJhYmFqbyBjb24gZWwgZmluIGRlIHNlciBjb25zdWx0YWRvIHBvciBlbCBww7pibGljbyBlbiBodHRwOi8vd3d3LmVhZml0LmVkdS5jby9iaWJsaW90ZWNhLiAKClRvZG8gcGVyc29uYSBxdWUgY29uc3VsdGUgeWEgc2VhIGxhIGJpYmxpb3RlY2EgbyBlbiBtZWRpbyBlbGVjdHLDs25pY28gcG9kcsOhIGNvcGlhciBhcGFydGVzIGRlbCB0ZXh0byBjaXRhbmRvIHNpZW1wcmUgbGEgZnVlbnRlcywgZXMgZGVjaXIgZWwgdGl0dWxvIGRlbCB0cmFiYWpvIHkgZWwgYXV0b3IuIEVzdGEgYXV0b3JpemFjacOzbiBubyBpbXBsaWNhIHJlbnVuY2lhIGEgbGEgZmFjdWx0YWQgcXVlIHRlbmdvIGRlIHB1YmxpY2FyIHRvdGFsIG8gcGFyY2lhbG1lbnRlCmxhIG9icmEuCgpMYSBVbml2ZXJzaWRhZCBubyBzZXLDoSByZXNwb25zYWJsZSBkZSBuaW5ndW5hIHJlY2xhbWFjacOzbiBxdWUgcHVkaWVyYSBzdXJnaXIgZGUgdGVyY2Vyb3MgcXVlIGludm9xdWVuIGF1dG9yw61hIGRlIGxhIG9icmEgcXVlIHByZXNlbnRvLgo=
dc.title.eng.fl_str_mv Solving the Puzzle: A New Measure of Trade Distance In The Gravity
title Solving the Puzzle: A New Measure of Trade Distance In The Gravity
spellingShingle Solving the Puzzle: A New Measure of Trade Distance In The Gravity
Factor Analysis for Mixed Data
Gravity Equation Model
Panel Data
Trade Distance
title_short Solving the Puzzle: A New Measure of Trade Distance In The Gravity
title_full Solving the Puzzle: A New Measure of Trade Distance In The Gravity
title_fullStr Solving the Puzzle: A New Measure of Trade Distance In The Gravity
title_full_unstemmed Solving the Puzzle: A New Measure of Trade Distance In The Gravity
title_sort Solving the Puzzle: A New Measure of Trade Distance In The Gravity
dc.creator.fl_str_mv Mejía Mejía, Juan Felipe
Ramírez Hassan, Andrés
dc.contributor.author.none.fl_str_mv Mejía Mejía, Juan Felipe
Ramírez Hassan, Andrés
dc.subject.keyword.eng.fl_str_mv Factor Analysis for Mixed Data
Gravity Equation Model
Panel Data
Trade Distance
topic Factor Analysis for Mixed Data
Gravity Equation Model
Panel Data
Trade Distance
description The gravity model is a workhorse tool that has been widely used in international trade. However, one empirical question that frequently arises is related to the conceptualization and measurement of distance. To overcome this limitation, our study proposes an index of distance based on multivariate statistical analysis. Specifically, we build our index using Factorial Analysis for Mixed Data. For robustness check, we use Principal Component Analysis. Both techniques summarize in one factor information related to geographical, cultural, political and economic variables that might affect international trade between countries. We use this index as proxy of distance, and Gross Domestic Product as proxy of mass, and we run some panel data exercises between 1995 and 2000 for 10 Latin American economies. Estimations indicate that the sign of the load factors in Factor Analysis for Mixed Data are intuitively plausible, and that panel data exercises give sensible robust outcomes.
publishDate 2013
dc.date.available.none.fl_str_mv 2013-07-11T19:34:51Z
dc.date.accessioned.none.fl_str_mv 2013-07-11T19:34:51Z
dc.date.issued.none.fl_str_mv 2014-06-11
dc.type.eng.fl_str_mv workingPaper
info:eu-repo/semantics/workingPaper
dc.type.coarversion.fl_str_mv http://purl.org/coar/version/c_b1a7d7d4d402bcce
dc.type.coar.fl_str_mv http://purl.org/coar/resource_type/c_8042
dc.type.local.spa.fl_str_mv Documento de trabajo de investigación
dc.type.hasVersion.eng.fl_str_mv draft
dc.identifier.uri.none.fl_str_mv http://hdl.handle.net/10784/993
dc.identifier.jel.none.fl_str_mv F11
F14
url http://hdl.handle.net/10784/993
identifier_str_mv F11
F14
dc.language.iso.eng.fl_str_mv eng
language eng
dc.rights.coar.fl_str_mv http://purl.org/coar/access_right/c_abf2
dc.rights.local.spa.fl_str_mv Acceso abierto
rights_invalid_str_mv Acceso abierto
http://purl.org/coar/access_right/c_abf2
dc.coverage.spatial.eng.fl_str_mv Medellín de: Lat: 06 15 00 N degrees minutes Lat: 6.2500 decimal degrees Long: 075 36 00 W degrees minutes Long: -75.6000 decimal degrees
dc.publisher.spa.fl_str_mv Universidad EAFIT
dc.publisher.department.spa.fl_str_mv Escuela de Economía y Finanzas
institution Universidad EAFIT
bitstream.url.fl_str_mv https://repository.eafit.edu.co/bitstreams/bd1c5a92-851a-4ede-9d76-13abdc6cba25/download
https://repository.eafit.edu.co/bitstreams/dbc532e1-519e-442d-8143-e4f0fcdd29f3/download
bitstream.checksum.fl_str_mv 4cc960a42e07fca3808fbd6b90ab2a1f
9b14a8a72a9521628dba44cbde3c31c5
bitstream.checksumAlgorithm.fl_str_mv MD5
MD5
repository.name.fl_str_mv Repositorio Institucional Universidad EAFIT
repository.mail.fl_str_mv repositorio@eafit.edu.co
_version_ 1814110164394967040