New nonlinear estimators of the gravity equation

<p dir="ltr">The gravity model of international trade is often applied by economists to explain bilateral trade between countries. Nevertheless, some estimation practices have been subject to criticism, namely how zero trade values and the heteroskedasticity are handled. This paper p...

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محفوظ في:
التفاصيل البيبلوغرافية
المؤلف الرئيسي: Ayman Mnasri (16932486) (author)
مؤلفون آخرون: Salem Nechi (16932489) (author)
منشور في: 2021
الموضوعات:
الوسوم: إضافة وسم
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author Ayman Mnasri (16932486)
author2 Salem Nechi (16932489)
author2_role author
author_facet Ayman Mnasri (16932486)
Salem Nechi (16932489)
author_role author
dc.creator.none.fl_str_mv Ayman Mnasri (16932486)
Salem Nechi (16932489)
dc.date.none.fl_str_mv 2021-02-01T00:00:00Z
dc.identifier.none.fl_str_mv 10.1016/j.econmod.2020.12.011
dc.relation.none.fl_str_mv https://figshare.com/articles/journal_contribution/New_nonlinear_estimators_of_the_gravity_equation/24083661
dc.rights.none.fl_str_mv CC BY 4.0
info:eu-repo/semantics/openAccess
dc.subject.none.fl_str_mv Economics
Econometrics
Gravity model
Heteroscedasticity
Structural zeros
Generalized Heckman two-step
Generalized nonlinear least squares
PPML
dc.title.none.fl_str_mv New nonlinear estimators of the gravity equation
dc.type.none.fl_str_mv Text
Journal contribution
info:eu-repo/semantics/publishedVersion
text
contribution to journal
description <p dir="ltr">The gravity model of international trade is often applied by economists to explain bilateral trade between countries. Nevertheless, some estimation practices have been subject to criticism, namely how zero trade values and the heteroskedasticity are handled. This paper proposes new nonlinear estimation techniques to address these issues. In particular, we propose standard and generalized versions of the nonlinear Heckman two-step approach that do not require the log-linearization of the gravity equation and corrects for non-random selection bias, and a generalized nonlinear least squares estimator that can be viewed as an iterative version of the normal family Quasi-Generalized Pseudo-Maximum-Likelihood estimator. Monte Carlo simulations show that our proposed estimators outperform existent linear and nonlinear estimators and are very efficient in correcting the selection bias and reducing the standard deviation of the estimates. Empirical results show that previous studies have overestimated the contribution of variables such as importer’s income, distance, remoteness, trade agreements, and openness.</p><h2>Other Information</h2><p dir="ltr">Published in: Economic Modelling<br>License: <a href="http://creativecommons.org/licenses/by/4.0/" target="_blank">http://creativecommons.org/licenses/by/4.0/</a><br>See article on publisher's website: <a href="https://dx.doi.org/10.1016/j.econmod.2020.12.011" target="_blank">https://dx.doi.org/10.1016/j.econmod.2020.12.011</a></p>
eu_rights_str_mv openAccess
id Manara2_7a6040388198c4bd4d7d86fe66700493
identifier_str_mv 10.1016/j.econmod.2020.12.011
network_acronym_str Manara2
network_name_str Manara2
oai_identifier_str oai:figshare.com:article/24083661
publishDate 2021
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spelling New nonlinear estimators of the gravity equationAyman Mnasri (16932486)Salem Nechi (16932489)EconomicsEconometricsGravity modelHeteroscedasticityStructural zerosGeneralized Heckman two-stepGeneralized nonlinear least squaresPPML<p dir="ltr">The gravity model of international trade is often applied by economists to explain bilateral trade between countries. Nevertheless, some estimation practices have been subject to criticism, namely how zero trade values and the heteroskedasticity are handled. This paper proposes new nonlinear estimation techniques to address these issues. In particular, we propose standard and generalized versions of the nonlinear Heckman two-step approach that do not require the log-linearization of the gravity equation and corrects for non-random selection bias, and a generalized nonlinear least squares estimator that can be viewed as an iterative version of the normal family Quasi-Generalized Pseudo-Maximum-Likelihood estimator. Monte Carlo simulations show that our proposed estimators outperform existent linear and nonlinear estimators and are very efficient in correcting the selection bias and reducing the standard deviation of the estimates. Empirical results show that previous studies have overestimated the contribution of variables such as importer’s income, distance, remoteness, trade agreements, and openness.</p><h2>Other Information</h2><p dir="ltr">Published in: Economic Modelling<br>License: <a href="http://creativecommons.org/licenses/by/4.0/" target="_blank">http://creativecommons.org/licenses/by/4.0/</a><br>See article on publisher's website: <a href="https://dx.doi.org/10.1016/j.econmod.2020.12.011" target="_blank">https://dx.doi.org/10.1016/j.econmod.2020.12.011</a></p>2021-02-01T00:00:00ZTextJournal contributioninfo:eu-repo/semantics/publishedVersiontextcontribution to journal10.1016/j.econmod.2020.12.011https://figshare.com/articles/journal_contribution/New_nonlinear_estimators_of_the_gravity_equation/24083661CC BY 4.0info:eu-repo/semantics/openAccessoai:figshare.com:article/240836612021-02-01T00:00:00Z
spellingShingle New nonlinear estimators of the gravity equation
Ayman Mnasri (16932486)
Economics
Econometrics
Gravity model
Heteroscedasticity
Structural zeros
Generalized Heckman two-step
Generalized nonlinear least squares
PPML
status_str publishedVersion
title New nonlinear estimators of the gravity equation
title_full New nonlinear estimators of the gravity equation
title_fullStr New nonlinear estimators of the gravity equation
title_full_unstemmed New nonlinear estimators of the gravity equation
title_short New nonlinear estimators of the gravity equation
title_sort New nonlinear estimators of the gravity equation
topic Economics
Econometrics
Gravity model
Heteroscedasticity
Structural zeros
Generalized Heckman two-step
Generalized nonlinear least squares
PPML