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Do Default Loss Risks Matter for Arab Exports? Evidence from a Gravity Modelling Approach

  • Riadh Ben Jelili ORCID logo EMAIL logo
Veröffentlicht/Copyright: 16. Dezember 2020
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Abstract

In the literature, it has been common to use credit risk scores to investigate impacts of external sources of risk and political institutions on foreign investment location choice-decisions. However, only a few studies have specifically examined the relationship between importing country’s credit risk scores and exports. Side stepping the limited availability of statistics on ECAs activities in the Arab countries, this paper investigates empirically the relationship between merchandise exports and credit scores of importing countries. Based on a gravity equation augmented with the risks of default on international payments, measured by intra-country risk ratings, the principal contribution of the present research is to scrutinize the impact of commercial and political risks on merchandise trade in the Arab region. The findings suggest that in the absence of insurance contracts against the risk of defaulting payments, firms are more likely to export to countries with higher prior probabilities to secure payments. It logically follows that provisions of export credit guarantees well targeted towards reducing buyer risks are likely to boost-up exports.

JEL Classification: C23; F13; F14

Corresponding author: Riadh Ben Jelili, Director, Research & Country Risk Analysis Department, The Arab Investment and Export Credit Guarantee Corporation “DHAMAN”, Arab Organizations Headquarters Building, P.O. Box 23568, Safat 13096, State of Kuwait, E-mail:

Acknowledgements

This paper has benefited greatly from valuable comments and suggestions of two anonymous reviewers. To them goes my full appreciation. I also extend special thanks to Professor Ali Arifa for his inputs and comments. The views expressed in this paper cannot be attributed to the Arab Investment & Export Credit Guarantee Corporation or its Member countries. All remaining errors are my responsibility.

Appendix
Table 4:

Description of the data set.

VariableDescriptionSource
ExportThe dependent variable in LSDV model is the logarithm of the bilateral exports value US$ million transformed using an inverse hyperbolic sine transformation in order to deal with zero bilateral exports. The dependent variable is the value of exports and the logarithm of the value of exports in PPML model and Heckman model respectively.

In addition to initial total merchandise product group, three other export broad sub-categories defined according to the Standard international trade Classification (SITC) Revision 3 are considered: primary commodities, manufactured goods, and machinery and transport equipment. Each category of export value is expressed in US$ million.
UNCTADstat Data Center
Economic sizeSum of the logarithm of gross domestic product (GDP) across country-pairs in US$ millionUNCTADstat Data Center
DistanceWeighted distance (pop-wt, km) across country-pairs in logarithmCentre d’Etudes Prospectives et d’Informations Internationales (CEPII) GeoDist database.
ManufacturingLogarithm of manufacturing imports to overall merchandise imports ratio in importing country.UNCTADstat Data Center
Risk scoreAssessment of the risk of default on international payments initially on a scale from 0 to 7, first converted into 1–100 point scales and taking the logarithm, higher value of the index corresponds to higher risk.Compiled from OECD Country risk classification according to established methodology for assessing country credit risk and classifying countries in connection with their agreement on minimum premium fees for official export credits.
Regional trade agreementNominal variable equal 1 if a regional trade agreement is in force between the exporter and the importer.Centre d’Etudes Prospectives et d’Informations Internationales (CEPII) GeoDist database.
Common languageNominal variable equal 1 for a common official language between the exporter and the importer.Centre d’Etudes Prospectives et d’Informations Internationales (CEPII) GeoDist database.
Bilateral investment treatyNominal variable equal 1 if a bilateral investment treaty agreement is in force between the exporter and the importer.World Bank, ICSID Database.
Colonial linkNominal variable equal 1 if a colonial history between the exporter and the importer.Centre d’Etudes Prospectives et d’Informations Internationales (CEPII) GeoDist database.
Table 5:

Country coverage and OECD risk classification.

Risk classHigh incomeUpper middle incomeLower middle incomeLow income
0Australia, Austria, Belgium, Canada, Cyprus, Czechia, Denmark, Estonia, Finland, France, Germany, Greece, Hungary, Iceland, Ireland,

Israel, Italy, Japan, Korea, Latvia, Lithuania, Luxembourg, Malta, Netherlands, New Zealand, Norway, Poland, Portugal, Singapore, Slovakia, Slovenia, Spain, Sweden, Switzerland, Liechtenstein, United Kingdom, United States of America
1Taiwan
2Chile, China, Hong Kong SAR, Kuwait, Saudi Arabia, United Arab Emirates, Brunei DarussalamBotswana, China, Malaysia
3Bahamas, Qatar, Trinidad and Tobago, UruguayBulgaria, Costa Rica, Mexico, Panama, Peru, Romania, ThailandIndia, Indonesia, Morocco, Philippines
4Bahrain, OmanAlgeria, Colombia, Croatia, Dominican Republic, Namibia, Russian Federation, South AfricaGuatemala
5Azerbaijan, Brazil, Paraguay, TurkeyBangladesh, Bolivia, El Salvador, Honduras, Jordan, Tunisia, Viet NamSenegal
6Albania, Argentina, Belarus, Ecuador, Gabon, Guyana, Iran, Jamaica, Kazakhstan, SurinameAngola, Armenia, Cameroon, Côte d’Ivoire, Egypt, Ghana, Kenya, Mongolia, Nigeria, Papua New Guinea, Sri Lanka, ZambiaTogo, Uganda
7Iraq, Lebanon, Libya, VenezuelaCongo, Nicaragua, Pakistan, Sudan, Ukraine, YemenBurkina Faso, Ethiopia, Gambia, Guinea, Guinea-Bissau, Haiti, Liberia, Madagascar, Malawi, Mali, Mozambique, Niger, Sierra Leone
  1. Categories for default risk refer to the OECD classification of the year 2018 and income groups defined as by the World Bank.

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Received: 2019-05-19
Accepted: 2020-11-05
Published Online: 2020-12-16

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Heruntergeladen am 17.11.2025 von https://www.degruyterbrill.com/document/doi/10.1515/rmeef-2019-0013/html
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