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Latin American exports during the first globalization: How statistical aggregation and standardization affect our understanding of trade
Historical Methods: A Journal of Quantitative and Interdisciplinary History ( IF 1.6 ) Pub Date : 2023-01-31 , DOI: 10.1080/01615440.2022.2160399
Marc Badia-Miró 1 , Anna Carreras-Marín 1 , Agustina Rayes 2
Affiliation  

Abstract

Data constraints determine the scope of historical research. The gradual digitalization of large sources has increased the number of approaches that can be applied to comprehend the past. Here, we show an example of how trade data can shed new light to better understand growth patterns of Latin America at the end of nineteenth century. Latin American exports during the First Globalization has mainly focused on the high concentration of few products to few markets. In this article, we propose a complementary way to measure diversification by considering the relative number of goods and the number of trade partners. To do so, we had to deal with historical official trade data hardly comparable, which has been homogenized for some countries in a 1910 benchmark (SITC-rev2). From that, we can offer a new measure of trade diversification, internationally comparable over time and across countries. Standardizing trade data also implies some consequences in the sense that the number of items for industrial goods is always greater than those for primary goods, arising the question if lower diversification is an inevitable result of specialization on commodities, or instead, it is a statistical artifact driven by the standard criterium we impose on data.



中文翻译:

第一次全球化期间拉丁美洲的出口:统计汇总和标准化如何影响我们对贸易的理解

摘要

数据的限制决定了历史研究的范围。大型资源的逐渐数字化增加了可用于理解过去的方法的数量。在这里,我们展示了一个例子,说明贸易数据如何为更好地了解十九世纪末拉丁美洲的增长模式提供新的启示。第一次全球化期间拉丁美洲的出口主要集中在少数产品高度集中到少数市场。在本文中,我们提出了一种通过考虑商品的相对数量和贸易伙伴数量来衡量多元化的补充方法。为此,我们必须处理几乎无法比较的历史官方贸易数据,这些数据在 1910 年基准 (SITC-rev2) 中对于某些国家来说已经同质化。由此,我们可以提供一种新的贸易多元化衡量标准,随着时间的推移和不同国家的国际可比性。贸易数据标准化还意味着一些后果,即工业产品的项目数量总是大于初级产品的项目数量,这就产生了这样的问题:较低的多样化是否是商品专业化的必然结果,或者相反,它是一种统计假象由我们对数据施加的标准标准驱动。

更新日期:2023-01-31
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