Calculating Trade in Value Added

Aslam, Aqib; Novta, Natalija; Rodrigues-Bastos, Fabiano

doi:10.2139/ssrn.3030771

Cited by 17 publications

(14 citation statements)

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“…These results are consistent withTaglioni and Winkler (2016) who worked with TiVA OECD andAslam et al (2017) who used data from EORA.…”

supporting

confidence: 87%

“…We built a panel from 1995 to 2015, with data from a multiregional input‐output model EORA (Lenzen, 2013) data, which incorporates the input‐output country and industry‐level relations. The computation of trade in value‐added measures was obtained according to the procedures of Aslam et al (2017), which intuitively rely on the value‐added trade from EORA. The panel includes 161 countries, of which 20 are from LA (the country list is available in Appendix A1).…”

Section: Data and Estimationmentioning

confidence: 99%

“…The measurement of such metric was made using the International Monetary Fund (IMF) algorithm, available by(Aslam et al, 2017) (the document detailed the derivation), which also adopts the multi-regional base EORA.…”

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confidence: 99%

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Trade agreements and participation in global value chains: Empirical evidence from Latin America

2021

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The rise of global sourcing implies a heterogeneous relationship between buyers and suppliers regarding the liberalisation scenarios in emerging countries. This paper analyses the effect of regional trade agreements (RTAs) on participation in the Global Value Chains of Latin American countries between 1995 and 2015. We combine the framework of gravity equations with the trade in value-added, applying a Pseudo Poisson Maximum Likelihood (PPML) estimator with panel data and fixed effects to deal with endogeneity and heteroscedasticity. Heterogeneous estimations show that the deepest RTAs reinforce the position of lower technology-industry suppliers, driven by an extra-regional strategy of Latin American trade policy. The geography of value chains has little effect on industrial upgrading in the region, reducing the development potential. The study concludes that the region's trade policy could reduce the dependent relationship between distant partners and pay more attention to creating shorter value chains as a strategy to generate local capacities to gain competitiveness in value chains.

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“…These results are consistent withTaglioni and Winkler (2016) who worked with TiVA OECD andAslam et al (2017) who used data from EORA.…”

supporting

confidence: 87%

Section: Data and Estimationmentioning

confidence: 99%

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Trade agreements and participation in global value chains: Empirical evidence from Latin America

2021

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“…With 26 sectors, Eora provides a relatively detailed sectoral classification and is consistent across all countries covered. The methodology follows the decomposition of trade in value-added based on the Leontief inverse as set in Aslam, Novta, & Rodrigues-Bastos (2017). Gross export value was divided into domestic origin value-added, regional value-added (aggregated for five Central Asian countries), and value-added from other countries (all countries outside the focus region).…”

Section: Methodsmentioning

confidence: 99%

How much do Central Asian countries participate in Regional Value Chains?

Sharafeyeva

2022

ANZJES

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This paper estimates the level of Central Asian countries’ participation in regional value chains (RVCs) and global value chains (GVCs) using data from the Eora multi-region input-output table. The contribution of foreign value-added to gross exports is low both absolutely and compared to baseline estimates for Southeast Asia. Moreover, despite their geographic, cultural, and historic closeness, Central Asian countries tend to be more integrated into GVCs, whereas RVCs are at a rudimentary stage. The high trade costs and uncertain trading environment at border-crossing points are among the reasons for underdeveloped RVCs in Central Asia.

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“…Figure3compare the host countries' fixed effects and their effects on logistics performance, with a focus on the overall LPI during the period average of2007-2017 of Table6displays the coefficients of the host countries' fixed effects in Column (ii) (PPML estimation) in Table6. Column (b) shows the period averaged LPIs of the host countries, and Column (c) computes their LPI deviations from the average LPI of the benchmark countries (Estonia, Latvia, and Lithuania).…”

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confidence: 99%

Global Value Chains’ Participation and Logistics Performance in Post-Soviet Economies

Ugli¹

2022

Bulletin of Applied Economics

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Post-Soviet countries have never been analysed in the global value chain (GVC) context. Therefore, in this study, we evaluate the degree of backward participation of GVCs in the manufacturing sector of post-Soviet countries. We also examine the quantitative linkage between GVCs and host countries’ logistics performance as a service-link component. We used the UNCTAD-Eora GVC database and employed a structural gravity trade model. The results illustrate a positive correlation between GVC backward participation in manufacturing and income levels in the post-Soviet economies. The empirical estimation using the structural gravity trade model demonstrates a quantitative linkage between GVC backward participation and the logistics performance of the host country. The level of logistics performance accounts for 70–80 percent of the degree of GVC backward participation. Our findings’ major policy implication is that post-Soviet economies’ logistics performance should be improved by erasing the Soviet era’s negative legacy. JEL Codes: F12, F13, F14, O57. Keywords: Global value chains, Logistics performance, Post-Soviet countries, Manufacturing, Structural gravity trade model.

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Calculating Trade in Value Added

Cited by 17 publications

References 0 publications

Trade agreements and participation in global value chains: Empirical evidence from Latin America

Trade agreements and participation in global value chains: Empirical evidence from Latin America

How much do Central Asian countries participate in Regional Value Chains?

Global Value Chains’ Participation and Logistics Performance in Post-Soviet Economies

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