Abstract
This paper proposes a nonparametric test in order to establish the level of accuracy of the foreign trade statistics of 17 Latin American countries when contrasted with the trade statistics of the main partners in 1925. The Wilcoxon Matched-Pairs Ranks test is used to determine whether the differences between the data registered by exporters and importers are meaningful, and if so, whether the differences are systematic in any direction. The paper tests for the reliability of the data registered for two homogeneous products, petroleum and coal, both in volume and value. The conclusion of the several exercises performed is that we cannot accept the existence of statistically significant differences between the data provided by the exporters and the registered by the importing countries in most cases. The qualitative historiography of Latin American describes its foreign trade statistics as mostly unusable. Our quantitative results contest this view.
The general mistrust placed on trade statistics, particularly those of underdeveloped countries, represents a heavy burden on economic history research, since trade statistics are one of the oldest and most complete economic series available for analysis. For instance, a research project such as the described in Carreras et al. (2003) or Carreras et al. (2004) aimed at estimating the level of economic modernization in Latin American and Caribbean countries before World War II making systematic use of the trade statistics of these countries as well as of their principal trading partners in the developed world is immediately under suspicion.
From the seminal work of Morgernstern (1963) to the present day, the users of trade figures are aware of the divergence that exists between exporters’ and importers’ figures. The impression from the economic literature is that the researcher should be even more suspicious of the data the more underdeveloped the country. Among others, the studies of Naya and Morgan (1969), Yeats (1990), Rozansky and Yeats (1994) and, Makhoul and Otterstrom (1998), show that the accuracy of trade statistics provided by developed countries is higher than that of the developing countries. For instance, Makhoul and Otterstrom (1998) found that the quality of the OECD trade statistics is much better than that provided by the non-OECD in a relatively recent period such as 1980 to 1994. Also Rozansky and Yeats (1994 ) found that discrepancies between importers’ and exporters’ reports appear especially important for the less developed countries.
That underdeveloped countries shall misreport statistics more often than developed nations comes as no much of a surprise. Allegedly many of the causes for misreporting have to do with lack of means for the collection of data, systematic distorted statistics for a specific purpose --improve credit worthiness; collect (or avoid) higher taxes--, simple corruption, smuggle, etc., all of which seem to occur more often in low income countries (see Yeats (1990)). Following such a line of reasoning the straightforward solution seemed to be to use the statistics of the more developed trade partners instead, which are expected to be of higher quality. However, Yeats (1995) concluded that ‘the partner country gap filling procedures have little or no potential for improving the general coverage or quality of international trade data’. His final remark points at the need of ‘improved procedures for data collection and reporting at the country level’.
In fact, there is a wide array of potential matters that would need to improve in order to reduce the differences between the quantities and, overall the values, annotated at the port of origin and that registered at destination: different accounting methods (CIF versus FOB, general versus special trade), different time of recording (goods movement versus money movement, fiscal versus calendar years), prices used (declared prices versus official prices), different units of measurement (currencies and exchange rates; units, dozens, weight, volume, length, etc), misclassification of products (thousand subcategories versus ‘all others’ type of categories), geographical misallocation (country of consignment versus country of origin/destination), just to name the most relevant. A detailed explanation these and more reasons for discrepancies can be found in Allen and Ely (1953) and also Federico and Tena (1991). Given the list of issues, the ample pessimism about the accuracy and usefulness of international trade statistics for economic analytical purposes is comprehensible.
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