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C H A P T E R 2 The Variables Used in the Analysis: Their Properties and Sources of Data Economics studies facts, and seeks to arrange the facts in such ways as to make it possible to draw conclusions from them. As always, it is the arrangement which is the delicate operation. Facts arranged in the right way speak for themselves, unarranged they are as dead as mutton. —J. R. Hicks (1971) The methods of many empirical studies in economics are constrained by the absence of appropriate data. This is especially the case for cross-national studies, for which one must negotiate the Babel created by differing procedures of data collection across countries. To understand the techniques of analysis used in subsequent chapters, it is therefore necessary to have a basic overview of the types of data that were available for this study. The present chapter has a dual purpose. First, for those interested only in absorbing the basic results of this book, there is a brief description of all data used. The description aims to be as succinct as possible, given the requirement that readers should find sufficient detail to enable them to follow the material presented in subsequent chapters. This overview of the data is contained in Sections 2.1 and 2.3. Section 2.4 lists the regional groupings of countries that are used in the presentation of results in Chapters 4, 6, and 7. Another group of readers might want to follow the procedures closely enough so that they could use the methods later. Thus, a second aim is to give information sufficient for any reader to understand the detailed properties of the study's methods. The material included to accomplish the second aim is embodied in Sections 2.2, 2.5, and 2.6. Most readers could skip those sections without any loss of continuity. As the ensuing section makes clear, it was necessary to transform the trade data before it could be used in the analysis. This study uses the transformation that produces the "revealed comparative advantages" (RCAs) of Balassa (1967). These measures have been used frequently in empirical studies of trade, so the rationale underlying their construction is familiar to many readers. However, there is still much discussion on the appropriateness of their use 26 Chapter 2 and on the nature of their properties. I examine those properties in Section 2.2. The results in that section are new. The theorems show the conditions under which one can safely use the RCAs in empirical studies. Because these conditions are weak, the theorems justify the use of RCAs in ensuing chapters. 2.1. The Trade Data: An Overview The present section focuses on the trade data. The source of information is described, and the transformations producing the "revealed comparative advantages" are defined. This study uses trade data at both the two-digit and the three-digit levels of the U.N. Standard International Trade Classification, Revision 1 (SITC). The three-digit data, which contain 182 commodity groups, were employed primarily in creating the summary trade statistics presented in Chapter 4. For reasons best examined in Chapter 5, fewer than 182 commodity groups could be employed when estimating the multiendowment regression model. Therefore , the results presented in Chapters 6 and 7 use data on sixty-one trade aggregates defined at the two-digit level.1 The raw trade data were all expressed in U.S. dollars, using the exchange rates employed by the United Nations. The method of creating a country's trade statistics was determined partially by data availability and partially by a methodological consideration regarded as central to the present work. The present research aims to be truly comparative —that is, the results are derived using methods that treat all countries in an identical manner. Only by using such methods can one be sure that those results are the product of real differences between countries, not caused by some artifact of the data collection process. If one insists on exact comparability of trade measures across countries, difficulties arise when a nation's report of its own foreign trade is used. The trade reports of most CMEA countries cannot be easily made comparable with those of Western nations. The U.N. and CMEA classification systems are so different that they make reconciliation at the required level of aggregation impossible. Prices within the Council for Mutual Economic Assistance are so far removed from world-market prices that the meaning of value measures is unclear...


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