Distinct clubs or one big party? Global value chain convergence: Supply concentration and susceptibility to supply shocks
DOI:
https://doi.org/10.24136/eq.2911Keywords:
global value chains, input concentration, production fragmentation, convergence clubs, OECD ICIO databaseAbstract
Research background: Recent events, such as the COVID-19 pandemic or Russia’s aggression on Ukraine, raise important questions about the stability of supply chains and their resilience to supply shocks.
Purpose of the article: This paper investigates convergence clubs in global value chains, focusing on supply concentration measured with the Herfindahl-Hirschman Index.
Methods: Using country-sector pairs from the OECD’s ICIO database, we employed the Phillips-Sul (2007) algorithm with the Schnurbus-Haupt-Meier (2017) augmentation to distinguish convergence clubs in the global trade network.
Findings & value added: Our main policy-related finding is that there are two main convergence clubs — one covering roughly 80% of all units and the other one close to 20% (the number of divergent sectors is practically negligible). The dominant club is characterised by high and growing concentration, which poses a risk to the trade network, as, over time, it makes trading partners more susceptible to supply-side shocks. Since the global economy has proven to be surprisingly homogenous in terms of concentration patterns, it seems justified that growing concentration could be considered a systemic feature for future theoretical international trade models. Our main methodological finding is that the WIOD database, which is still used as a standard for such analyses, may be misleading due to its limitations. While the results based on the ICIO and WIOD databases do not align, ICIO seems to be superior in terms of coverage.
Downloads
References
Acemoglu, D., & Azar, P. D. (2020). Endogenous production networks. Econometrica, 88(1), 33–82. DOI: https://doi.org/10.3982/ECTA15899
View in Google Scholar
Acemoglu, D., Akcigit, U., & Kerr, W. (2016). Networks and the macroeconomy: An empirical exploration. NBER Macroeconomics Annual, 30(1), 273–335. DOI: https://doi.org/10.1086/685961
View in Google Scholar
Acemoglu, D., Carvalho, V. M., Ozdaglar, A., & Tahbaz-Salehi, A. (2012). The network origins of aggregate fluctuations. Econometrica, 80(5), 1977–2016. DOI: https://doi.org/10.3982/ECTA9623
View in Google Scholar
Alessandria, G., Khan, S. Y., Khederlarian, A., Mix, C., & Ruhl, K. J. (2023). The aggregate effects of global and local supply chain disruptions: 2020–2022. Journal of International Economics, 146, 103788. DOI: https://doi.org/10.1016/j.jinteco.2023.103788
View in Google Scholar
Alfaro, L., & Chor, D. (2023). Global supply chains: The looming “Great Reallocation.” NBER Working Paper, 31661. DOI: https://doi.org/10.3386/w31661
View in Google Scholar
Ali, A., Arbouch, M., & Canuto, O. (2022). Pandemic, war, and global value chains 1. Retrieved from https://www.policycenter.ma/sites/default/files/2022-10/paper-pcns-pandemic-war-and-global-value-chains-by-otaviano-canuto-abdelaaziz-ait -ali-mahmoud-arbouch.pdf.
View in Google Scholar
Amighini, A., Maurer, A., Garnizova, E., Hagemejer, J., Stoll, P.-T., Dietrich, M., Roy, R., Skowronek, A., & Tentori, D. (2023). Global value chains: Potential synergies between external trade policy and internal economic initiatives to address the strategic dependencies of the EU. Retrieved from https://www.europarl.europa.eu/RegData/etudes/STUD/2023/702582/EXPO_STU(2023)702582_EN.pdf.
View in Google Scholar
Antràs, P. (2020). De-globalisation? Global value chains in the post-COVID-19 age. NBER Working Paper, 28115. DOI: https://doi.org/10.3386/w28115
View in Google Scholar
Apergis, N., Christou, C., Gupta, R., & Miller, S. M. (2018). Convergence in income inequality: Further evidence from the club clustering methodology across states in the U.S. International Advances in Economic Research, 24(2), 147–161. DOI: https://doi.org/10.1007/s11294-018-9675-y
View in Google Scholar
Ascari,G., Bonam, D., & Smadu, A. (2024). Global supply chain pressures, inflation, and implications for monetary policy. Journal of International Money and Finance, 142, 103029. DOI: https://doi.org/10.1016/j.jimonfin.2024.103029
View in Google Scholar
Attinasi, M. G., De Santis, R. A., Di Stefano, C., Gerinovics, R., & Tóth, M. B. (2022). Supply chain bottlenecks in the euro area and the United States: where do we stand? ECB Economic Bulletin, 2.
View in Google Scholar
Ayadi, R., Giovannetti, G., Marvasi, E., Vannelli, G., & Zaki, C. (2021). Demand and supply exposure through global value chains: Euro‐Mediterranean countries during COVID. World Economy, 45(3), 637–656. DOI: https://doi.org/10.1111/twec.13156
View in Google Scholar
Baldwin, R. (2022). The peak globalisation myth: Part 3 – How global supply chains are unwinding. CEPR.
View in Google Scholar
Baldwin, R., & Freeman, R. (2021). Risks and global supply chains: What we know and what we need to know. NBER Working Paper, 29444. DOI: https://doi.org/10.3386/w29444
View in Google Scholar
Baqaee, D., & Rubbo, E. (2023). Micro propagation and macro aggregation. Annual Review of Economics, 15, 91–123. DOI: https://doi.org/10.1146/annurev-economics-082322-012833
View in Google Scholar
Baqaee, D., & Farhi, E. (2020). Nonlinear production networks with an application to the Covid-19 crisis. NBER Working Paper, 27281. DOI: https://doi.org/10.3386/w27281
View in Google Scholar
Barro, R. J. (1991). Economic growth in a cross section of countries. Quarterly Journal of Economics, 106(2), 407–443. DOI: https://doi.org/10.2307/2937943
View in Google Scholar
Barro, R. J., & Sala-I-Martin, X. (1991). Convergence across states and regions. Brookings Papers on Economic Activity, 22(1), 107–182. DOI: https://doi.org/10.2307/2534639
View in Google Scholar
Barrot, J.-N., & Sauvagnat, J. (2016). Input specificity and the propagation of idiosyncratic shocks in production networks. Quarterly Journal of Economics, 131(3), 1543–1592. DOI: https://doi.org/10.1093/qje/qjw018
View in Google Scholar
Bartelme, D., & Gorodnichenko, Y. (2015). Linkages and economic development. NBER Working Paper, 21251. DOI: https://doi.org/10.3386/w21251
View in Google Scholar
Baumol, W. J. (1986). Productivity growth, convergence, and welfare: What the long-run data show. American Economic Review, 76(5), 1072–1085.
View in Google Scholar
Bazzi, S., Chari, A. V., Nataraj, S., & Rothenberg, A. D. (2017). Identifying productivity spillovers using the structure of production networks. Working Papers, WR-1182. Retrieved from https://ideas.repec.org/p/ran/wpaper/wr-1182.html. DOI: https://doi.org/10.7249/WR1182
View in Google Scholar
Beck, K. (2021). Why business cycles diverge? Structural evidence from the European Union. Journal of Economic Dynamics and Control, 133, 104263. DOI: https://doi.org/10.1016/j.jedc.2021.104263
View in Google Scholar
Benigno, G., di Giovanni, J., Groen, J. J., & Noble, A. I. (2022). The GSCPI: A new barometer of global supply chain pressures. Liberty Street Economics, 20220104, Federal Reserve Bank of New York. Retrieved from DOI: https://doi.org/10.2139/ssrn.4114973
View in Google Scholar
https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4114973.
View in Google Scholar
Bernanke, B., Gertler, M., & Gilchrist, S. (1996). The financial accelerator and the flight to quality. Review of Economics and Statistics, 78(1), 1–15. DOI: https://doi.org/10.2307/2109844
View in Google Scholar
Bernard, A. B., Moxnes, A., & Saito, Y. U. (2019). Production networks, geography, and firm performance. Journal of Political Economy, 127(2), 639–688. DOI: https://doi.org/10.1086/700764
View in Google Scholar
Boehm, C. E., Flaaen, A., & Pandalai-Nayar, N. (2019). Input linkages and the transmission of shocks: Firm-level evidence from the 2011 Tōhoku earthquake. Review of Economics and Statistics, 101(1), 60–75. DOI: https://doi.org/10.1162/rest_a_00750
View in Google Scholar
Bonadio, B., Huo, Z., Levchenko, A. A., & Pandalai-Nayar, N. (2021). Global supply chains in the pandemic. Journal of International Economics, 133(1), 103534. DOI: https://doi.org/10.1016/j.jinteco.2021.103534
View in Google Scholar
Borin, A., Mancini, M., & Taglioni, D. (2021). Measuring exposure to risk in global value chains. World Bank Research Policy Working Paper, 9785. DOI: https://doi.org/10.1596/1813-9450-9785
View in Google Scholar
Busetti, F., Forni, L., Harvey, A., & Venditti, F. (2006). Inflation convergence and divergence within the European Monetary Union. ECB Working Paper, 574.
View in Google Scholar
Cai, L., Zhang, Y., Wang, Z., & Liu, Z. (2022). Does the rise of global value chain position increase or reduce domestic income inequality? Applied Economics, 55(49), 5833–5845. DOI: https://doi.org/10.1080/00036846.2022.2140767
View in Google Scholar
Cantore, N., Lavopa, A., & Rodousakis, N. (2022). Global value chains in times of multiple crises. Industrial Analytics Platform. Retrieved from
View in Google Scholar
https://iap.unido.org/articles/global-value-chains-times-multiple-crises.
View in Google Scholar
Carvalho, V. M., Nirei, M., Saito, Y. U., & Tahbaz-Salehi A. (2021). Supply chain disruptions: Evidence from the great East Japan earthquake. Quarterly Journal of Economics, 136(2), 1255–1321. DOI: https://doi.org/10.1093/qje/qjaa044
View in Google Scholar
Caselli, F., Koren, M., Lisicky, M., & Tenreyro, S. (2020). Diversification through trade. Quarterly Journal of Economics, 135(1), 449–502. DOI: https://doi.org/10.1093/qje/qjz028
View in Google Scholar
Celasun, O., Hansen, M. N.-J. H., Mineshima, M. A., Spector, M., & Zhou, J. (2022). Supply bottlenecks: Where, why, how much, and what next? IMF Working Paper, 2022(031). DOI: https://doi.org/10.5089/9798400202476.001
View in Google Scholar
Celo, S., Nebus, J., & Wang, I. K. (2018). The role of internal and external complexity in global factory performance: An NKC application. Journal of International Management, 24(1), 65–83. DOI: https://doi.org/10.1016/j.intman.2017.12.005
View in Google Scholar
Chaney, T. (2014). The network structure of international trade. American Economic Review, 104(11), 3600–3634. DOI: https://doi.org/10.1257/aer.104.11.3600
View in Google Scholar
Cigna, S., Gunnella, V., & Quaglietti, L. (2022). Global value chains: Measurement, trends and drivers. ECB Occasional Paper, 289. DOI: https://doi.org/10.2139/ssrn.4007756
View in Google Scholar
Costinot, A., & Vogel, J. (2010). Matching and inequality in the world economy. Journal of Political Economy, 118(4), 747–786. DOI: https://doi.org/10.1086/655858
View in Google Scholar
D’Aguanno, L., Davies, O., Dogan, A., Freeman, R., Lloyd, S., Reinhardt, D., Sajedi, R., & Zymek, R. (2021). Global value chains, volatility and safe openness: Is trade a double-edged sword? Bank of England Financial Stability Paper, 46. DOI: https://doi.org/10.2139/ssrn.3766910
View in Google Scholar
Datta, D. D., Feiveson, L., Peneva, E., & Rua, G. (2022). Bottlenecks, shortages, and soaring prices in the U.S. economy. FEDS Notes, Washington: Board of Governors of the Federal Reserve System. DOI: https://doi.org/10.17016/2380-7172.3153
View in Google Scholar
De Graeve, F., & Schneider, J. D. (2023). Identifying sectoral shocks and their role in business cycles, Journal of Monetary Economics, 140(C), 124–141. DOI: https://doi.org/10.1016/j.jmoneco.2023.08.005
View in Google Scholar
De Long, J. B. (1988). Productivity growth, convergence, and welfare: Comment. American Economic Review, 78(5), 1138–1154.
View in Google Scholar
Dhyne, E., Kikkawa, A. K., Mogstad, M., & Tintelnot, F. (2021). Trade and domestic production networks. Review of Economic Studies, 88(2), 643–668. DOI: https://doi.org/10.1093/restud/rdaa062
View in Google Scholar
Di Giovanni, J., & Levchenko, A. A. (2009). Trade openness and volatility. Review of Economics and Statistics, 91(3), 558–585. DOI: https://doi.org/10.1162/rest.91.3.558
View in Google Scholar
Di Giovanni, J., Levchenko, A. A., & Mejean, I. (2014). Firms, destinations, and aggregate fluctuations. Econometrica, 82(4), 1303–1340. DOI: https://doi.org/10.3982/ECTA11041
View in Google Scholar
Di Giovanni, J., Levchenko, A., & Mejean, I. (2024). Foreign shocks as granular fluctuations. Journal of Political Economy, 132(2), 391–433. DOI: https://doi.org/10.1086/726235
View in Google Scholar
Eaton, J., Jinkins, D., Tybout, J. R., & Xu, D. (2022). Two-sided search in international markets. NBER Working Paper, 29684. DOI: https://doi.org/10.3386/w29684
View in Google Scholar
Eppinger, P., Felbermayr, G. J., Krebs. O., & Kukharskyy, B. (2020). Covid-19 shocking global value chains. CESifo Working Paper Series, 8572. DOI: https://doi.org/10.2139/ssrn.3702124
View in Google Scholar
Erfurth, P. (2024). Is income inequality converging at the regional level? Evidence from LIS data. Journal of Economic Geography, 24(3), 375–392. DOI: https://doi.org/10.1093/jeg/lbad029
View in Google Scholar
Fadinger, H., Ghiglino, C., & Teteryatnikova, M. (2022). Income differences, productivity, and input-output networks. American Economic Journal: Macroeconomics, 14(2), 367–415. DOI: https://doi.org/10.1257/mac.20180342
View in Google Scholar
Fally, T. (2011). On the fragmentation of production in the us. Retrieved from
View in Google Scholar
https://www.etsg.org/ETSG2011/Papers/Fally.pdf.
View in Google Scholar
Feenstra, R. C. (1998). Integration of trade and disintegration of production in the global economy. Journal of Economic Perspectives, 12(4), 31–50. DOI: https://doi.org/10.1257/jep.12.4.31
View in Google Scholar
Feenstra, R. C., & Hanson, G. H. (1996). Globalization, outsourcing, and wage inequality. American Economic Review, 86(2), 240–245. DOI: https://doi.org/10.3386/w5424
View in Google Scholar
Gabaix, X. (2011). The granular origins of aggregate fluctuations. Econometrica, 79(3), 733–772. DOI: https://doi.org/10.3982/ECTA8769
View in Google Scholar
Ghani, E., & O’Connell, S. D. (2014). Can service be a growth escalator in low-income countries? World Bank Research Policy Working Paper, 6971. DOI: https://doi.org/10.1596/1813-9450-6971
View in Google Scholar
Ghassibe, M. (2021). Endogenous production networks and non-linear monetary transmission, University of Oxford. Retrieved from
View in Google Scholar
https://www.ecb.europa.eu/pub/conferences/shared/pdf/20211007_inflation/Ghassibe_paper.en.pdf.
View in Google Scholar
Goldberg, P. K., & Reed, T. (2023). Is the global economy deglobalizing? And if so, why? And what is next? NBER Working Paper, 31115. DOI: https://doi.org/10.3386/w31115
View in Google Scholar
Grossman, G. M., & Rossi-Hansberg, E. (2008). Trading tasks: A simple theory of offshoring. American Economic Review, 98(5), 1978–1997. DOI: https://doi.org/10.1257/aer.98.5.1978
View in Google Scholar
Grossman, G. M., Helpman, E., & Lhuillier, H. (2023a). Supply chain resilience: Should policy promote international diversification or reshoring? Journal of Political Economy, 131(12), 3462–3496. DOI: https://doi.org/10.1086/725173
View in Google Scholar
Grossman, G. M., Helpman, E., & Sabal, A. (2023b). Resilience in vertical supply chains. NBER Working Paper, 31739. DOI: https://doi.org/10.3386/w31739
View in Google Scholar
Hallak, J. C. (2006). Product quality and the direction of trade. Journal of International Economics, 68(1), 238–265. DOI: https://doi.org/10.1016/j.jinteco.2005.04.001
View in Google Scholar
Hayakawa, K., & Mukunoki, H. (2021). Impacts of Covid‐19 on global value chains. Developing Economies, 59(2), 154–177. DOI: https://doi.org/10.1111/deve.12275
View in Google Scholar
Helpman, E., Melitz, M., & Rubinstein, Y. (2008). Estimating trade flows: Trading patterns and trading volumes. Quarterly Journal of Economics, 123(2), 441–487. DOI: https://doi.org/10.1162/qjec.2008.123.2.441
View in Google Scholar
Hosseini, S., & Ivanov, D. (2021). A multi-layer Bayesian network method for supply chain disruption modelling in the wake of the COVID-19 pandemic. International Journal of Production Research, 60(17), 1–19. DOI: https://doi.org/10.1080/00207543.2021.1953180
View in Google Scholar
Inoue, H., & Todo, Y. (2019). Firm-level propagation of shocks through supply-chain networks. Nature Sustainability, 2(9), 841–847. DOI: https://doi.org/10.1038/s41893-019-0351-x
View in Google Scholar
Inoue, H., & Todo, Y. (2020). The propagation of economic impacts through supply chains: The case of a mega-city lockdown to prevent the spread of COVID-19. Plos One, 15(9), e0239251. DOI: https://doi.org/10.1371/journal.pone.0239251
View in Google Scholar
Jangam, B. P., & Rath, B. N. (2020). Cross-country convergence in global value chains: Evidence from club convergence analysis. Journal of International Economics, 163(C), 134–146.
View in Google Scholar
Jangram, B. P., & Rath, B. N. (2020). Cross-country convergence in global value chains: Evidence from club convergence analysis. Journal of International Economics, 163, 134–146. DOI: https://doi.org/10.1016/j.inteco.2020.06.002
View in Google Scholar
Jones, C. I. (2011). Intermediate goods and weak links in the theory of economic development. American Economic Journal: Macroeconomics, 3(2), 1–28. DOI: https://doi.org/10.1257/mac.3.2.1
View in Google Scholar
Karadimitropoulou, A. (2018). Advanced economies and emerging markets: Dissecting the drivers of business cycle synchronization. Journal of Economic Dynamics and Control, 93, 115–130. DOI: https://doi.org/10.1016/j.jedc.2018.01.029
View in Google Scholar
Karanasos, M., Koutroumpis, P., Karavias, Y., Kartsaklas, A., & Arakelian, V. (2016). Inflation convergence in the EMU. Journal of Empirical Finance, 39, 241–253. DOI: https://doi.org/10.1016/j.jempfin.2016.07.004
View in Google Scholar
Koren, M., & Tenreyro, S. (2013). Technological diversification. American Economic Review, 103(1), 378–414. DOI: https://doi.org/10.1257/aer.103.1.378
View in Google Scholar
Lafrogne-Joussier, R., Martin, J., & Mejean, I. (2022). Supply shocks in supply chains: Evidence from the early lockdown in China. IMF Economic Review, 71. DOI: https://doi.org/10.1057/s41308-022-00166-8
View in Google Scholar
Lanz, R., & Piermartini, R. (2018). Specialization within global value chains: The role of additive transport costs. World Trade Organization Working Papers, 2018(05).
View in Google Scholar
Levchenko, A. A., & Sauré, P. (2019). International inflation spillovers through input linkages. Review of Economics and Statistics, 101(3), 507–521. DOI: https://doi.org/10.1162/rest_a_00781
View in Google Scholar
Liu, T.-Y., & Lee, C.-C. (2021). Global convergence of inflation rates. North American Journal of Economics and Finance, 58, 101501. DOI: https://doi.org/10.1016/j.najef.2021.101501
View in Google Scholar
Mayneris, F., & Ourens, G. (2024). Geographic concentration of imports and economic vulnerability of countries. Retrieved from https://guzmanourens.com/wp-content/uploads/2024/05/draft_apr2024.pdf.
View in Google Scholar
Miah, M. R., & Ichihashi, M. (2024). Supply shocks in global value chains and export performance: Evidence from Bangladesh using triple difference-in-differences. Journal of Development Studies. DOI: https://doi.org/10.1080/00220388.2024.2354237
View in Google Scholar
Moore, A. E. (2012). Milton Friedman’s Pencil. The New Inquiry. Retrieved from https://thenewinquiry.com/milton-friedmans-pencil/.
View in Google Scholar
Ndubuisi, G., & Owusu, S. (2023). Trade for catch-up: Examining how global value chains participation affects productive efficiency. Journal of Productivity Analysis, 59, 195–215. DOI: https://doi.org/10.1007/s11123-023-00663-6
View in Google Scholar
Oberfield, E. (2018). A theory of input-output architecture. Econometrica, 86(2), 559–589. DOI: https://doi.org/10.3982/ECTA10731
View in Google Scholar
Patel, D., Sandefur, J., & Subramanian, A. (2021). The new era of unconditional convergence. Journal of Development Economics, 152, 102687. DOI: https://doi.org/10.1016/j.jdeveco.2021.102687
View in Google Scholar
Phillips, P. C. B., & Sul, D. (2007). Transition modeling and econometric convergence Tests. Econometrica, 75(6), 1771–1855. DOI: https://doi.org/10.1111/j.1468-0262.2007.00811.x
View in Google Scholar
Phillips, P. C. B., & Sul, D. (2009). Economic transition and growth. Journal of Applied Econometrics, 24(7), 1153–1185. DOI: https://doi.org/10.1002/jae.1080
View in Google Scholar
Raei, M. F., Ignatenko, A., & Mircheva, B. (2019). Global value chains: What are the benefits and why do countries participate? IMF Working Papers, 2019(018). DOI: https://doi.org/10.2139/ssrn.3333741
View in Google Scholar
Ravallion, M. (2003). Inequality convergence. Economics Letters, 80(3), 351–356. DOI: https://doi.org/10.1016/S0165-1765(03)00141-1
View in Google Scholar
Rodrik, D. (2013). Unconditional convergence in manufacturing. Quarterly Journal of Economics, 128(1), 165–204. DOI: https://doi.org/10.1093/qje/qjs047
View in Google Scholar
Savoia, F. (2024). Income inequality convergence among EU regions. Socio-Economic Planning Sciences, 92(C), 101803. DOI: https://doi.org/10.1016/j.seps.2024.101803
View in Google Scholar
Schnurbus, J., Haupt, H., & Meier, V. (2017). Economic transition and growth: A replication. Journal of Applied Econometrics, 32(5), 1039–1042. DOI: https://doi.org/10.1002/jae.2544
View in Google Scholar
Silva, J. M. C. S., & Tenreyro, S. (2006). The log of gravity. Review of Economics and Statistics, 88(4), 641–658. DOI: https://doi.org/10.1162/rest.88.4.641
View in Google Scholar
Strange, R. (2020). The 2020 Covid-19 pandemic and global value chains. Journal of Industrial and Business Economics, 47, 455–465. DOI: https://doi.org/10.1007/s40812-020-00162-x
View in Google Scholar
Tempest, R. (1996). Barbie and the world economy. Los Angeles Times.
View in Google Scholar
Retrieved from https://www.latimes.com/archives/la-xpm-1996-09-22-mn-46610-story.html.
View in Google Scholar
Timmer, M. P., Los, B., Stehrer, R., & de Vries, G. J. (2016). An anatomy of the global trade slowdown based on the WIOD 2016 release. GGDC Research Memorandum. Retrieved from https://ideas.repec.org/p/gro/rugggd/gd-162.html.
View in Google Scholar
Tsekeris, T. (2017). Network analysis of inter-sectoral relationships and key sectors in the Greek economy. Journal of Economic Interaction and Coordination, 12(2), 413–435. DOI: https://doi.org/10.1007/s11403-015-0171-7
View in Google Scholar
Vrh, N. (2017). The convergence in domestic value-added of exports in the EU. Post-Communist Economies, 29(3), 405–430. DOI: https://doi.org/10.1080/14631377.2017.1319107
View in Google Scholar
World Trade Organization (2023). World trade report 2023 - re-globalization for a secure, inclusive and sustainable future. Retrieved from
View in Google Scholar
https://www.wto.org/english/res_e/publications_e/wtr23_e.htm.
View in Google Scholar
Wuester, L., & Winkler, D. (2022). Implications of Russia’s invasion of Ukraine for its value chains, CEPR. Retrieved from https://cepr.org/voxeu/columns/implications-russias-invasion-ukraine-its-value-chains.
View in Google Scholar
Wuri, J., Widodo, T., & Hardi, A. S. (2023). Speed of convergence in global value chains: Forward or backward linkage. Heliyon, 9(7), e18070. DOI: https://doi.org/10.1016/j.heliyon.2023.e18070
View in Google Scholar
Xiao, H., Sun, T., Meng, B., & Cheng, L. (2017). Complex network analysis for characterizing global value chains in equipment manufacturing. Plos One, 12(1), e0169549. DOI: https://doi.org/10.1371/journal.pone.0169549
View in Google Scholar
Xing, Y., & Detert, N. (2010). How the iPhone widens the United States trade deficit with the People’s Republic of China. Asian Development Bank Institute, 257. DOI: https://doi.org/10.2139/ssrn.1729085
View in Google Scholar
Xing, Y., Wang, R., & Dollar, D. (2023). Global value chain development report 2023. Resilient and sustainable GVCs in turbulent times. World Trade Organization.
View in Google Scholar
Zaclicever, D. (2020). A network analysis approach to vertical trade linkages: The case of Latin America and Asia. CEPAL Working Paper, 45060.
View in Google Scholar
Zhu, S. C., & Trefler, D. (2005). Trade and inequality in developing countries: A general equilibrium analysis. Journal of International Economics, 65(1), 21–48. DOI: https://doi.org/10.1016/j.jinteco.2003.11.005
View in Google Scholar
Zhu, Z., Morrison, G., Puliga, M., Chessa, A., & Riccaboni, M. (2018). The similarity of global value chains: A network-based measure. Network Science, 6(4), 607–632. DOI: https://doi.org/10.1017/nws.2018.8
View in Google Scholar
Downloads
Published
Issue
Section
License
Copyright (c) 2024 Equilibrium. Quarterly Journal of Economics and Economic Policy
This work is licensed under a Creative Commons Attribution 4.0 International License.
