Determinants of global coffee trade: Do RTAs matter? Gravity model analysis

Abstract

This study investigates the patterns of global coffee trade flows and identifies the major determinants of global coffee trade by incorporating RTAs as important variable. Gravity modeling with OLS and PPML estimator was employed for the analysis using panel data on bilateral coffee trade flows of 18 major coffee exporters and 201 trading partners for the period 2001–2015. Both exporter GDP (and population) as well as importer GDP were found to be important determinants enhancing coffee trade. Of the bilateral distance variables, physical distance is found to impede coffee trade, while common border was found to enhance it. On the other hand, cultural (distance) variables like colonial link, common colonizer and common language were also found to enhance coffee trade. Other variables that were found to significantly enhance coffee trade include depreciation in exporting country’s exchange rate, the amount of arable land in exporting country, infrastructure and global financial crisis. On the other hand, importing country tariff was found to significantly reduce coffee trade as expected. Surprisingly, the RTA variable had no significant impact on coffee bilateral trade.

Keywords:

• Coffee
• gravity model
• bilateral trade
• exports
• imports

PUBLIC INTEREST STATEMENT

This study investigates the patterns of global coffee trade flows and identifies the major determinants of global coffee trade by incorporating RTAs as an important variable. Result highlights that both exporter GDP (and population) as well as importer GDP were found to be important determinants enhancing coffee trade. Physical distance is found to hamper coffee trade, while common border was found to enhance it. On the other hand, cultural (distance) variables like colonial link, common colonizer and language were also found to enhance coffee trade. Other variables that were found to significantly enhance coffee trade include depreciation in exporting country’s exchange rate, the amount of arable land in exporting country and infrastructure. On the other hand, importing country tariff was found to significantly reduce coffee trade as expected. The RTA variable had no significant impact on coffee bilateral trade.

Acknowledgements

We would like to thank the journal editor and four anonymous reviewers for their critical comments and suggestions during the review process.

Disclosure statement

No potential conflict of interest was reported by the authors.

Notes

1. Narayanan and Vashisht (2008b) provides list of Free Trade Agreement (FTA) that has been negotiated between India and Thailand, which involves tariff cut proposals at HS-6 level.

2. Kepaptsoglou et al. (2010), also provides a 10-year review of empirical studies on the recent use of the gravity specification for modeling international trade flows and FTA effects.

3. They make their assessment based on three levels of data aggregation (total exports, total agricultural exports and 2-digit industry code)

4. In general, GDP and population are the most common mass variables (with a few exceptions), while impedance is described by distance and a variety of factors enhancing or discouraging trade (Kepaptsoglou et al., 2010).

5. See appendix D for the detailed classification of coffee products traded internationally.

6. Cameroon, Cote d’Ivoire, Ethiopia, Kenya, Uganda, and United Rep. of Tanzania from Africa; India, Indonesia, Malaysia, Thailand, and Viet Nam from Asia and Brazil, Colombia, Costa Rica, Guatemala, Honduras, Mexico, and Peru from the Americas

7. For the analysis the estimation was limited to the period of 2001–2015 due to data limitation on such variables as infrastructure, arable land, and applied tariff rate by importing countries.

8. Centre d’Etudes Prospectivesetd’Informations Internationales (CEPII)

9. cccccc

10. This list may be modified depending on the final data compilation.

11. World Development Indicators

Additional information

Funding

The authors received no direct funding for this research.

Notes on contributors

Jemal Abafita

Tekilu Tadesse is an Assistant Professor of Economics and researcher at Jimma University. His research interests include financial economics, efficiency analysis, impact evaluation; market analysis; macroeconomics, and microeconomics policies analysis. He has published nine papers in pre-reviewed international journals.

Jemal Abafita (Ph.D.) is an Associate Professor at the department of economics, Jimma University. His research interests include poverty, (rural) markets, rural development; natural and environmental economics; policy impact evaluation, and microeconometrics, and health economics. He has published 22 papers in peer-reviewed international journals.