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The Operationalization of Some Variables Related to Regional Integration: A Research Note
Published online by Cambridge University Press: 22 May 2009
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As common markets, free trade associations, and limited-purpose regional arrangements continue to proliferate in many corners of the globe, the basic question of the relevance of these efforts to the process of building political communities also continues to be posed for theorist and practitioner alike. One approach for linking these two phenomena is the intensive and comparative study of common markets and free trade associations in terms of their capacity to transform member states into a political union. In principle, at least, the careful and comparative study of key variables in the process of achieving and perfecting economic unity at the regional level could yield propositions which might have predictive value for assessing the chances of success of various discrete efforts at regional unification. In methodological terms such an approach would combine case studies with the use of aggregate data.
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References
1 Haas, Ernst B. and Schmitter, Philippe C., “Economics and Differential Patterns of Political Integration: Projections about Unity in Latin America,” International Organization, 08 1964 (Vol. 18, No. 4), pp. 705–737Google Scholar.
2 The most persuasive advocate of the importance of this variable is Nye, Joseph S. Jr, Sec his “Central American Regional Integration,” International Conciliation, 03 1967 (No. 562), especially pp. 50–57Google Scholar, and “Patterns and Catalysts in Regional Integration,” International Organization, Autumn 1965 (Vol. 19, No. 4), pp. 870–884Google Scholar. The same variable is treated in the form of the domination of external elites by Etzioni, Amitai, Political Unification: A Comparative Study of Leaders and Forces (New York: Holt, 1965), pp. 47–50Google Scholar.
3 The panel consisted of the following people: Aaron Segal (LAFTA, CACM, Africa); Branislav Gosovic (COMECON); Abdul Jalloh (West Africa, Central Africa); Isebill Gruhn (East Africa, West Africa); Daniel Baedeker (CACM); and Ernst B. Haas (EFTA, EEC, Latin America).
4 Haas and Schmitter, p. 711.
5 Banks, Arthur S. and Textor, Robert B., A Cross-Polity Survey (Cambridge, Mass: M.I.T. Press, 1963)Google Scholar.
6 Data on gross national product, education, and communications are from Russett and others. Data on energy consumption and urbanization are fromGinsburg, Norton, Aslas of Economic Development (Chicago: University of Chicago Press, 1961)Google Scholar. For a more complete account of this measure seeBarrera, Mario, Modernization and Coercion (Berkeley, Calif: Institute of. International Studies, forthcoming)Google Scholar.
7 SeeEdwards, Allen, Statistical Methods for the Behavioral Sciences (New York: Rinehart, 1959), pp. 111–113Google Scholar. The formula used here for the T-scores was:
where X1 represents the successive values of the variable, X the mean of the distribution, and s the standard deviation of the variable. Use of the T-scores enables us to express the variables in standardized form, that is, in terms of standard deviations from their means. In addition, the measure transforms the terms so as to eliminate negative values, thus aiding in computation. Scales derived from this method have means of 50 and standard deviations of 10. Since the T-scores are standardized terms, different measures can be added together to produce composite scales.
8 This is done to a very considerable extent in a methodological effort similar to ours and successful in the delineation of influence patterns. SeeReinton, Per Olav, “International Structure and International Integration,” Journal of Peace Research, 1967 (No. 4), pp. 334–365Google Scholar.
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