Trade Effects of Eurasian Economic Union and Global Production Sharing: A Gravity Analysis

Abstract

This study examines the effects of the Eurasian Economic Union (EAEU) on global production sharing and trade in parts and components. With a panel dataset of disaggregated bilateral exports of EAEU members and 28 partners, we estimate an augmented gravity model for 2010–2017. To mitigate endogeneity issues, we employ the Hausman and Taylor Estimator. The study has two important findings. First, there are significant trade diversion effects on the exports of parts and components. Second, the formation of EAEU has resulted in a reduction in intra-bloc exports. In addition to these, we find that market size, inter-country differentials of income, business-friendly climate, and cultural similarities are the other significant determinants of bilateral trade. Based on the empirical analysis, we propose that the EAEU normalise the Common External Tariff below the current level to minimise trade diversion.

KEYWORDS:

• Eurasian economic union
• trade effects
• global production sharing
• parts and components trade
• gravity model
• Hausman and Taylor Estimator

Subject classification codes:

• F10
• F14

Acknowledgements

We thank the editor of the journal and the anonymous referee for their insightful comments and suggestions.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Correction Statement

This article has been corrected with minor changes. These changes do not impact the academic content of the article.

Notes

1 In this paper, we identify Belarus, Kazakhstan and Russia as the core members of Eurasian integration. Armenia and the Kyrgyz Republic are identified as new members.

2 The Vinerian specification identified trade creation as replacing less efficient production with low cost imports and trade diversion as the replacement of imports from an efficient non-member with less efficient imports from member countries of an economic integration agreement (Deme and Ndrianasy, 2017).

3 We define machinery goods as comprising the machinery and transport equipment (SITC 7) and miscellaneous manufactured articles (SITC 8) commodity categories at 1-digit classification. Parts and components are identified from the same groups at 5-digit classification.

4 See Athukorala (2011) for the list of parts and components identified from SITC Rev 3.

5 We include Azerbaijan, Georgia, Republic of Moldova, Tajikistan, Turkmenistan, Ukraine, and Uzbekistan, along with the EAEU member countries in defining the whole Eurasian region.

6 Each of the 28 partner countries accounts for 0.03% or more of EAEU's goods in machinery goods in 2010.

7 We constructed the RER following Florensa et al. (2015). The construction is detailed at the appendix.

8 Sargan-Hansen J-statistic for the second column of HTE is χ2(10) as the specification includes time effects.

9 Alternatively, we also run the estimations replacing RER with Exchange Rate Stability (ERS) index proposed by Aizenman et al. (2010). The coefficients of ERS are statistically insignificant in all equations. However, the results are similar to the benchmark analysis in terms of direction and significance and are available upon request.

10 Results are available upon request.

11 Alternatively, we examined the effects of the ECU by considering only the core members separately. We defined ECU as a binary variable that takes unity from 2010 for all bilateral pairs between the core countries, and 0 otherwise. The results show that ECU has an insiginifcant impact on intra-bloc trade while there are significant trade diversion effects.