Visualizing bivariate local spatial autocorrelation between commodity revealed comparative advantage index of China and USA from a new space perspective

Sijing Ye, Changxiu Cheng, Changqing Song and Shi Shen
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Sijing Ye: Beijing Normal University, China
Changxiu Cheng: Beijing Normal University, China; National Tibetan Plateau Data Center, China

Environment and Planning A, 2021, vol. 53, issue 2, 223-226

Abstract: The development of trade research plays an important role in enhancing the understanding of the trade relationship structure, evolution and relevant driving factors. While there is little research on analyzing and visualizing bilateral trade patterns and the evolution of numerous kinds of commodities. In this paper, we respectively calculate revealed comparative advantage index (RCAI) of each traded commodity of China and USA in 2017. Then the RCAI of thousands of commodities have been mapped to a two-dimensional space and visualized in a grid system by using digital trade feature map method. On that basis, bivariate local spatial auto-correlation features between China – USA have been comprehensively depicted.

Keywords: Geographic information science; international trade; spatial thinking; geovisualization; revealed comparative advantage index (search for similar items in EconPapers)
Date: 2021
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Persistent link: https://EconPapers.repec.org/RePEc:sae:envira:v:53:y:2021:i:2:p:223-226

DOI: 10.1177/0308518X20957336

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