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The New Regionalism and Policy Interdependence

Published online by Cambridge University Press:  24 June 2011

Leonardo Baccini  and
Andreas Dür
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Abstract

Since 1990, the number of preferential trade agreements has increased rapidly. The argument in this article explains this phenomenon, known as the new regionalism, as a result of competition for market access; exporters facing trade diversion because of their exclusion from a preferential trade agreement concluded by foreign countries push their governments into signing an agreement with the country in which their exports are threatened. The argument is tested in a quantitative analysis of the proliferation of preferential trade agreements among 167 countries between 1990 and 2007. The finding that competition for market access is a major driving force of the new regionalism is a contribution to the literature on regionalism and to broader debates about global economic regulation.

Type
Research Article
Information
British Journal of Political Science , Volume 42 , Issue 1 , 01 December 2011 , pp. 57 - 79
Copyright
Copyright © Cambridge University Press 2011

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References

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7 We provide a detailed explanation of how we arrived at these numbers below.

8 As some countries, for example, states in the area of the former Soviet Union, enter the dataset later than 1990, the actual number of dyads in our database varies between 10,153 and 13,861.

9 See, for example, Oye, Economic Discrimination and Political Exchange; Baldwin, ‘A Domino Theory of Regionalism’; and Mattli, The Logic of Regional Integration.

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20 In the case of Chile, the South Korea–Chile agreement (2003) also had a negative impact on Japanese exports, especially of automobiles.

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23 The Chile–United States example provided in the following section on operationalization further illustrates this idea.

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32 These databases are available at http://rtais.wto.org/UI/PublicMaintainRTAHome.aspx; http://www.dartmouth.edu/~tradedb/; and http://ptas.mcgill.ca/. We also relied on other sources, such as www.bilaterals.org, to get a full list of agreements signed more recently [all pages last accessed on 7 January 2010]. It should be noted that we coded countries joining the EU as signing up to all trade agreements that the EU forms part of at the time of accession. This is legally correct and appropriate in the context of our study; however, it biases results against our argument, as a country such as Hungary, which joined the EU in 2004, may have had little interest in an agreement with Mexico or Chile.

33 Egger and Larch, ‘Interdependent Trade Agreement Memberships’, p. 389, for example, only distinguish 127 agreements over a period of fifty (1955 to 2005) years, whereas we were able to identify 247 agreements for the period 1990 to 2007 alone.

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37 The five-year cut-off point is consistent with the operationalization chosen by Egger and Larch, ‘Interdependent Trade Agreement Memberships’. Below we assess the robustness of our findings to variation in the cut-off point.

38 Trade diversion also depends on the height of trade barriers in the countries participating in the preferential trade agreement. Preferential trade agreements should impose higher costs on exporters in third countries – and thus lead to a stronger mobilization of export interests – the larger the difference between the trade barriers faced by insiders and outsiders. As trade barriers are difficult to measure, we omit this variable in the present analysis.

39 For a detailed discussion of this case, see Andreas Dür, ‘EU Trade Policy as Protection for Exporters: The Agreements with Mexico and Chile’, Journal of Common Market Studies, 45 (2007), 833–55.

40 We used data from the World Bank's World Development Indicators database, which allows disaggregating exports by twelve sectors (agricultural raw materials, arms, communications equipment, food, fuel, high-technology goods, insurance and financial services, international tourism, ores and metals, other commercial services transport services and travel services). We then correlated the export mix of all countries, which allowed us to arrive at an index of export similarity. For a similar approach, see Elkins et al., ‘Competing for Capital’, p. 830. In robustness checks (not reported), we used related indices that capture similarity in both export composition and destination. For these indices, see Cao, Xun and Prakash, Aseem, ‘Trade Competition and Domestic Pollution: A Panel Study, 1980–2003’, International Organization 64 (2010), 481–503CrossRefGoogle Scholar; and Polillo, Simone and Guillén, Mauro F., ‘Globalization Pressures and the State: The Worldwide Spread of Central Bank Independence’, American Journal of Sociology, 110 (2005), 1764–1802CrossRefGoogle Scholar. These measures are highly correlated with ours and lead to substantially the same results. These results are available from the corresponding author.

41 The spatial matrices have been calculated using the software MATLAB 7.0 using a programme designed by the authors for this purpose. Although weighting matrices are commonly row-normalized so that all entries sum to 1 (see Franzese and Hays, ‘Spatial Analysis’, p. 580), we do not standardize here for theoretical reasons since we are interested in the absolute pressure on a dyad, independent of the pressure on another dyad. See Plümper and Neumayer, ‘Model Specification in the Analysis of Spatial Dependence’, p. 16–20.

42 We use the natural logarithm of this variable as it is characterized by occasional large observations.

43 Haggard, Stephan, ‘The Political Economy of Regionalism in Asia and the Americas’, in Edward D. Mansfield and Helen V. Milner, eds, The Political Economy of Regionalism (New York: Columbia University Press, 1997), pp. 20–49Google Scholar, at p. 40.

44 The exporter lobbying that our argument predicts for such a case either could have facilitated passage of fast-track legislation in the United States or could have allowed ratification of an agreement as an international treaty, similar to what happened in the case of the United States–Jordan agreement.

45 Franzese and Hays, ‘Spatial Analysis’, p. 572.

46 The literature on policy diffusion distinguishes between rational learning and emulation. See Simmons, Beth A., Garrett, Geoffrey and Dobbin, Frank, ‘Introduction: The International Diffusion of Liberalism’, International Organization, 60 (2006), 791–810CrossRefGoogle Scholar; Elkins et al., ‘Competing for Capital’, pp. 831–2. We do not follow this practice, as a clear measure of the ‘success’ of preferential trade agreements, which is necessary for an evaluation of the learning argument, is missing.

47 We modified the geographic distance spatial weights by using a Box–Cox transformation, and taking the square and the log of distance. In all these variations, the substantial results reported below remain unchanged. For this and the following alternative diffusion mechanisms, we use the smaller of the two directed values to represent the undirected dyad. We use the natural logarithm of the variables to deal with outliers.

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52 Univariate summary statistics and data sources for all of these variables are available in the Appendix.

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59 The results reported below do not change when using other data sources, such as the Polity IV score (Monty G. Marshall et al., ‘Political Regime Characteristics and Transitions, 1800–2007’).

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62 For this approach, see Plümper and Neumayer, ‘Model Specification in the Analysis of Spatial Dependence’, p. 7.

63 Survival analysis is the appropriate approach because our data is right-censored. See also Beck, Nathaniel, ‘Time-Series–Cross-Section Methods’, in Janet M. Box-Steffensmeier, Henry E. Brady and David Collier, eds, Oxford Handbook of Political Methodology (Oxford: Oxford University Press, 2008), 475–493Google Scholar. The study by Elkins et al., ‘Competing for Capital’ on the diffusion of bilateral investment agreements is also based on the Cox model. Darmofal, David, ‘Bayesian Spatial Survival Models for Political Event Processes’, American Journal of Political Science, 53 (2009), 241–257CrossRefGoogle Scholar, provides an extensive analysis of the use of survival models with spatial effects. A different approach is taken by Cao, Xun, ‘Networks as Channels of Policy Diffusion: Explaining Worldwide Changes in Capital Taxation, 1998–2006’, International Studies Quarterly, (2010), who uses network analysis. We estimated our models with Stata 11Google Scholar.

64 Golub, Jonathan, ‘Survival Analysis’, in Janet M. Box-Steffensmeier, Henry E. Brady and David Collier, eds, Oxford Handbook of Political Methodology (Oxford: Oxford University Press, 2008), pp. 530–546Google Scholar, makes a strong case for the advantages of the Cox model as compared with parametric models such as Weibull and Gompertz.

65 As recommended by Ward and Gleditsch, Spatial Regression Models, we checked whether the inclusion of spatial lags is appropriate by calculating the Moran index, using the total number of agreements signed by each country. The result confirms that there is statistically significant spatial correlation among countries.

66 Beck, ‘Time-Series–Cross-Section Methods’, p. 486.

67 Mansfield et al., ‘Why Democracies Cooperate More’.

68 In fact, when distance is excluded from the model, contiguity is positive and highly statistically significant.

69 Mansfield and Reinhardt, ‘Multilateral Determinants of Regionalism’.

70 These graphs are drawn and the following calculations are carried out after rescaling the distance, GDP and GDP per capita variables so that they have a mean of 0.

71 We are grateful to a reviewer for suggesting this robustness check.

72 The results are available upon request from the corresponding author.

73 Mansfield, Edward D. and Reinhardt, Eric, ‘International Institutions and the Volatility of International Trade’, International Organization, 56 (2008), 621–652CrossRefGoogle Scholar, p. 649.

74 Manger, Investing in Protection.

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