The growth path of high-tech industries: Statistical laws and evolution demands

Siyu Huang, Yi Shi, Qinghua Chen and Xiaomeng Li

Physica A: Statistical Mechanics and its Applications, 2022, vol. 603, issue C

Abstract: The development history of human society has always been accompanied by the continuous upgrading of industrial structures brought about by technological progress. Due to different production technologies, industries generally have different driving forces for their economic and social development, which can be described with scale characteristics. In recent years, studies have been conducted on the evolution path and growth conditions of high-tech industries; however, most of these studies have been limited by focusing on specific countries or cities. Based on gross domestic production (GDP) data and the urban scaling law for the counties of the United States, the current paper presents a universal path of industrial upgrading from a cross-regional perspective. The results show that while low-GDP counties have a comparative advantage in regard to low-tech industries, with the expansion of economic scale, high-GDP counties show a comparative advantage in regard to high-tech industries. This reversal phenomenon demonstrates the presence of a stable transition point at a GDP near $1010 during the period ranging from 2001 to 2019. The use of the scaling law and comparative advantage helps to capture the path of industrial upgrading using GDP empirical data. This information could help shed light on suggestions for the healthy and effective evolution of counties, both for governments and the research field.

Keywords: High-tech industry; Revealed comparative advantage; Industrial structure; Phase transition; Evolutionary bifurcation (search for similar items in EconPapers)
Date: 2022
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Citations: View citations in EconPapers (1)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:phsmap:v:603:y:2022:i:c:s0378437122004770

DOI: 10.1016/j.physa.2022.127719

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