Location quotients (LQ) are a transformation of raw data stored in contingency tables.

This transformation has been used frequently in studies involving international trade (under the name ‘revealed comparative advantage’) and in multiple other settings where a total can be disaggregated under at least two independent criteria and thus arranged in a cross sectional table: eg. employment by industry and city, etc.

The spread of LQ values is influenced by row, column and table totals, which prevents us from comparing LQ levels safely across entities, over time or between datasets.

This issue dramatically undermines the usefulness of the location quotient transformation.

In this paper I offer viable paths for characterizing these so-called size distortions in location quotients.

位置商 (LQ) 是存储在列联表中的原始数据的转换。

这种转换经常用于涉及国际贸易的研究（以“显示的比较优势”为名）和多种其他环境中，其中总数可以根据至少两个独立标准进行分解，从而排列在横截面表中：例如。按行业和城市等的就业。

LQ 值的分布受行、列和表总计的影响，这使我们无法安全地跨实体、跨时间或跨数据集比较 LQ 级别。

这个问题极大地破坏了位置商变换的有用性。

在本文中，我提供了一些可行的路径来表征这些所谓的位置商中的大小失真。