Complex Networks: Structure, Dynamics and ControlNo Access

VARIETIES OF INTERGOVERNMENTAL ORGANIZATION MEMBERSHIPS AND STRUCTURAL EFFECTS IN THE WORLD TRADE NETWORK

Singapore University of Social Sciences, 463 Clementi Road, Singapore 599494, Singapore

https://doi.org/10.1142/S0219525918500017Cited by:15 (Source: Crossref)

Abstract

To what extent does joint membership in intergovernmental organizations (IGOs) matter for bilateral trade? How and under what conditions do the various types of IGOs — economic, socio-cultural and general purpose — influence bilateral trade between their members? How do complex interdependencies in world trade matter? Existing research tends to examine aggregate joint IGO memberships and has done little to analyze how specific types of IGO membership matter in trade. Using a detailed IGO dataset and a novel network analysis approach called the temporal exponential random graph model, I assess the importance of three main IGO types — economic, socio-cultural and general purpose — in helping members to establish major trading ties. The results provide support for general purpose and socio-cultural IGOs and point to the importance of network phenomena such as popularity, activity and transitivity effects. Moreover, joint economic IGO memberships exhibit slightly more complex relations with bilateral trade. A robustness test reveals that preferential trade agreements are significant in fostering trade, while the World Trade Organization and other economic IGOs such as development banks are not. This paper presents a nuanced way of analyzing IGOs and provides the impetus for the study of complex interdependencies in international trade.

Keywords:

References

1. Hyvärinen, A., Consistency of pseudolikelihood estimation of fully visible boltzmann machines, Neural Comput. 18 (2006) 2283–2292. Web of Science, Google Scholar
2. Anderson, J. and Marcouiller, D., Insecurity and the pattern of trade: An empirical investigation, Rev. Econ. Stat. 84 (2002) 342–352. Web of Science, Google Scholar
3. Bagwell, K. and Staiger, R., Multilateral trade negotiations, bilateral opportunism and the rules of the gatt/wto, J. Int. Econ. 63 (2004) 1–29. Web of Science, Google Scholar
4. Bagwell, K. and Staiger, R., The world trade organization: Theory and practice, Ann. Rev. Econ. 2 (2010) 223–256. Web of Science, Google Scholar
5. Bearce, D. H. and Bondanella, S., Intergovernmental organizations, socialization, and member-state interest convergence, Int. Organ. 61 (2007) 703–733. Web of Science, Google Scholar
6. Beck, N. and Katz, J. N., Modeling dynamics in time-series-cross-section political economy data, Ann. Rev. Polit. Sci. 14 (2011) 331–352. Web of Science, Google Scholar
7. Beckfield, J., Inequality in the world policy: The structure of international organization, Am. Sociol. Rev. 68 (2013) 401–424. Web of Science, Google Scholar
8. Bennett, D. S. and Stam, A., Eugene: A conceptual manual, Int. Interact. 26 (2000) 179–204. Web of Science, Google Scholar
9. Bhamidi, S., Bresler, G. and Sly, A., Mixing time of exponential random graphs (2008), arxiv preprint arXiv:0812.2265. 1, 2.2.1. Google Scholar
10. Bliss, H. and Russett, B., Democratic trading partners: The liberal connection, J. Polit. 60 (1998) 1126–1147. Web of Science, Google Scholar
11. Boehmer, C., Gartzke, E. and Nordstrom, T., Do intergovernmental organizations promote peace? World Politics 57 (2004) 1–38. Web of Science, Google Scholar
12. Boehmer, C., Jungblut, B. and Stoll, R., Tradeoffs in trade data: Do our assumptions affect our results? Conflict Management and Peace Science 28 (2011) 145–167. Web of Science, Google Scholar
13. Chandrasekhar, A. G. and Jackson, M. O., Tractable and consistent random graph models (2014), nBER Working Papers 20276, National Bureau of Economic Research, Inc. Google Scholar
14. Chatterjee, S., Diaconis, P. and Sly, A., Random graphs with a given degree sequence (2010), arxiv preprint arXiv:1005.1136. 1. Google Scholar
15. Cranmer, S. J. and Desmarais, B. A., Inferential network analysis with exponential random graph models, Political Analysis 19 (2011) 66–86. Web of Science, Google Scholar
16. Cranmer, S. J. and Desmarais, B. A., Statistical inference for valued-edge networks: The generalized exponential random graph model, PloS ONE 7 (2012) e30136. Web of Science, Google Scholar
17. Cranmer, S. J., Desmarais, B. A. and Menninga, E. J., Complex dependencies in the alliance network, Conflict Management and Peace Science 29 (2012) 279–313. Web of Science, Google Scholar
18. De Benedictis, L. and Tajoli, L., The world trade network, The World Economy 34 (2011) 1417–1454. Web of Science, Google Scholar
19. De Bruyne, K., Magerman, G. and Van Hove, J., Revealed multilateral trade resistance in gravity models — a network approach (2013), the World Economy Series, Published by the Basil Blackwell for the Trade Policy Research Center, WebSite: https://lirias.kuleuven.be/handle/123456789/455927. Last accessed: 11th October 2017. Google Scholar
20. De Groot, H., Linders, G., Rietveld, P. and Subramanian, U., The institutional determinants of bilateral trade patterns, Kyklos 57 (2004) 103–123. Web of Science, Google Scholar
21. Dejniak, D., Power law and self-similarity in the distribution of national income, Information Systems in Management 3 (2014) 113–121. Google Scholar
22. Dorussen, H. and Ward, H., Intergovernmental organizations and the kantian peace, Journal of Conflict Resolution 52 (2008) 189–212. Web of Science, Google Scholar
23. Eicher, T. and Henn, C., In search of wto trade effects: Preferential trade agreements promote trade strongly, but unevenly, J. Int. Econ. 83 (2011) 137–153. Web of Science, Google Scholar
24. Faust, K. and Skvoretz, J., Comparing networks across space and time, size and species, Sociological Methodology 32 (2002) 267–299. Web of Science, Google Scholar
25. Fowler, J. H., Connecting the congress: A study of cosponsorship networks, Political Analysis 14 (2006) 456–487. Web of Science, Google Scholar
26. Garlaschelli, D. and Loffredo, M. I., Fitness-dependent topological properties of the world trade web, Phys. Rev. Lett. 93 (2004) 188701. Web of Science, Google Scholar
27. Gartzke, E., Preferences and the democratic peace, Int. Stud. Quart. 44 (2000) 191–212. Web of Science, Google Scholar
28. Glick, R. and Rose, A. K., Does a currency union affect trade? The time-series evidence, Eur. Econ. Rev. 46 (2002) 1125–1151. Web of Science, Google Scholar
29. Goldstein, J. L., Rivers, D. and Tomz, M., Institutions in international relations: Understanding the effects of the gatt and the wto on world trade, Int. Organ. 61 (2007) 37–67. Web of Science, Google Scholar
30. Granovetter, M., Economic action and social structure: The problem of embeddedness, Am. J. Sociol. 91 (1985) 481–510. Web of Science, Google Scholar
31. Guiso, L., Sapienza, P. and Zingales, L., Cultural biases in economic exchange? Quart. J. Econ. 124 (2009) 1095–1131. Web of Science, Google Scholar
32. Hanneke, S., Fu, W. and Xing, E., Discrete temporal models of social networks, Electron. J. Stat. 4 (2010) 585–605. Web of Science, Google Scholar
33. Ingram, P., Robinson, J. and Busch, M. L., The intergovernmental network of world trade: Igo connectedness, governance, and embededness, Am. J. Sociol. 111 (2005) 824–858. Web of Science, Google Scholar
34. Kali, R. and Reyes, J., Financial contagion on the international trade network, Economic Inquiry 48 (2010) 1072–1101. Web of Science, Google Scholar
35. Keohane, R., After Hegemony: Cooperation and Discord in the World Political Economy (Princeton University Press, 1984). Google Scholar
36. Kim, M., Costly procedures: Divergent effects of legalization in the gatt/wto dispute settlement procedures, Int. Stud. Quart. 52 (2008) 657–686. Web of Science, Google Scholar
37. Kim, S. and Shin, E.-H., A longitudinal analysis of globalization and regionalization in international trade: A social network approach, Social Forces 81 (2002) 445–468. Web of Science, Google Scholar
38. Leeds, B. A. and Anac, S., Alliance institutionalization and alliance performance, Int. Interact. 31 (2005) 183–202. Web of Science, Google Scholar
39. Leifeld, P., Cranmer, S. and Desmarais, B., Temporal exponential random graph models with btergm: Estimation and bootstrap confidence intervals, J. Stat. Softw. (2017). Web of Science, Google Scholar
40. Lusher, D., Koskinen, J. and Robins, G., Exponential Random Graph Models for Social Networks: Theory, Methods, and Applications (Cambridge University Press, 2013). Google Scholar
41. Manger, M., Pickup, M. and Snijders, T., A hierarchy of preferences: A longitudinal network analysis approach to pta formation, Journal of Conflict Resolution 56 (2012) 853–878. Web of Science, Google Scholar
42. Mansfield, E. and Pevehouse, J., Democratization and international organizations, Int. Organ. 60 (2006) 137–167. Web of Science, Google Scholar
43. Marshall, M. G., Jaggers, K. and Gurr, T. R., Polity iv project: Dataset users manual. Center for systemic peace: Polity iv project (2011). Google Scholar
44. Mayer, T. and Zignango, S., Notes on cepii’s distances measures: The geodist database (2011), notes on CEPII’s Distances Measures: The GeoDist Database. Google Scholar
45. McCormick, J., Understanding the EU: A Concise Introduction (Palgrave Macmillan, 2014). Google Scholar
46. Morrow, J. D., Siverson, R. M. and Tabares, T., The political determinants of international trade: The major powers, 1907–1990, Am. Polit. Sci. Rev. 92 (1998) 649–661. Web of Science, Google Scholar
47. Pevehouse, J., Nordstrom, T. and Warnke, K., The correlates of war 2 international governmental organizations data version 2.0, Conflict Management and Peace Science 21 (2004) 101–119. Web of Science, Google Scholar
48. Reigrotski, E. and Anderson, N., National stereotypes and foreign contracts, Public Opin. Quart. 23 (1959) 515–528. Web of Science, Google Scholar
49. Rose, A. K., Do we really know that the wto increases trade? Am. Econ. Rev. 94 (2004) 98–114. Web of Science, Google Scholar
50. Russett, B. and Oneal, J., Triangulating Peace: Democracy, Interdependence, and International Organizations (W.W. Norton, 2001). Google Scholar
51. Handcock, M., Robins, G., Snijders, T., Moody J. and Besag J., Assessing degeneracy in statistical models of social networks, Journal of the American Statistical Association 76 (2003) 33–50. Google Scholar
52. Sakar and Moore, A., Dynamic social network analysis using latent space models, SIGKDD Explorations 7 (2005) 31–40. Google Scholar
53. Serrano, M. A. and Boguna, M., Topology of the world trade web, Phys. Rev. E 68 (2003) 015101. Web of Science, Google Scholar
54. Serrano, M. A., Garlaschelli, D., Bogu, M. and Loffredo, M., Identifying formal intergovernmental organizations, J. Peace Res. 45 (2010) 849–862. Web of Science, Google Scholar
55. Sinha, S., Chatterjee, A., Chakraborti, A. and Chakrabarti, B. K., Econophysics: An Introduction (Wiley, 2010). Google Scholar
56. Snijders, T., Markov chain monte carlo estimation of exponential random graph models, J. Soc. Struct. 3 (2002). Google Scholar
57. Strauss, D. and Ikeda, M., Pseudolikelihood estimation for social networks, J. Am. Stat. Assoc. 85 (1990) 204–212. Web of Science, Google Scholar
58. Subramanian, A. and Wei, S., The wto promotes trade, strongly but unevenly, J. Int. Econ. 72 (2007) 151–175. Web of Science, Google Scholar
59. van Bergeijk, P. and Brakman, S., The Gravity Model of International Trade: Advances and Applications (Cambridge University Press, 2010). Google Scholar
60. Ward, M., Ahlquist, J. and Rozenas, A., Gravity’s rainbow: A dynamic latent space model for the world trade network, Network Science 1 (2013) TBA. Google Scholar
61. Ward, M. and Hoff, P., Analyzing dependencies in geo-economics and geo-politics, in War, Peace and Security, Fontanel, J. and Chatterji, M. (eds.) (Emerald Group Publishing, 2008), pp. 133–160. Google Scholar
62. Ward, M. D., Siverson, R. M. and Cao, X., Disputes, democracies, and dependencies: A reexamination of the kantian peace, Am. J. Polit. Sci. 51 (2007) 583–601. Web of Science, Google Scholar
63. Xu, A. and Zheng, X., Dynamic social network analysis using latent space model and an integrated clustering algorithm, 2009 Eighth IEEE International Conference on Dependable, Autonomic and Secure Computing (Chengdu, China, 2009), pp. 620–625. Google Scholar
64. Xun, C., Networks of intergovernmental organizations and convergence in domestic economic policies, Int. Stud. Quart. 54 (2009) 1095–1130. Google Scholar
65. Zhou, M., Multidimensionality and gravity in global trade, 1950–2000, Social Forces 88 (2010) 1619–1643. Web of Science, Google Scholar

Vol. 21, No. 02

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History

Received 4 January 2016

Revised 9 January 2018

Accepted 12 January 2018

Published: 28 February 2018

Keywords

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Intergovernmental Organization (IGO) Memberships within the World Trade Network

What is it about?

A variety of intergovernmental organizations (IGOs) -- economic, socio-cultural and general purpose for instance-- exists in the international system. For any given pair of states, how do joint memberships in particular types of IGOs affect bilateral trade between them? How and to what extent do complex interdependencies in the world trade network matter? This paper looks at the effects of joint memberships in different types of IGOs on bilateral trade within the broader structure of the world trade network.

Why is it important?

I seek to address the various gaps in the international political economy literature by examining how and under what conditions joint membership in IGOs affect bilateral trade, taking into account the broader structure of the world trade network. Notably, I avoid treating IGOs as homogenous entities and consider separately the effects of joint memberships in three IGO types: economic, socio-cultural and general purpose. This paper presents a nuanced way of analyzing IGOs and provides the impetus for the study of complex interdependencies in international trade.

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VARIETIES OF INTERGOVERNMENTAL ORGANIZATION MEMBERSHIPS AND STRUCTURAL EFFECTS IN THE WORLD TRADE NETWORK

Abstract

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