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Detecting multiple factors in panel data: an application on the growth of local regions in China

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  • W.D. Chen

Abstract

Due to unbalanced growth in China’s local regions, we construct a panel data model with multiple common factors to examine the differences among the growth factors in these areas. This article shows the various impacts from the supply and demand sides on economic growth. Different from the demand side, the supply-side impacts have permanent influences. This article focuses on these deep and profound impacts to explain the reasons behind China’s fast economic growing. By using data on 27 regions from 1958 to 2013, we summarize the main permanent influences along three lines. The first comes from the coastal regions, which have learned modern technology and systems from foreign companies, such as in Guangdong, Zhejiang, Fujian and Liaoning. The second comes from big cities, such as Beijing and Shanghai, in which a huge migration has given the companies opportunities to recruit excellent workers, making the resource allocation specialized and more efficient. The third is from the government’s major public works, which have improved areas’ infrastructure and assisted long-run economic growth, such as for Sichuan, Guangxi and Yunnan.

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  • W.D. Chen, 2016. "Detecting multiple factors in panel data: an application on the growth of local regions in China," Applied Economics, Taylor & Francis Journals, vol. 48(37), pages 3558-3568, August.
    • Handle: RePEc:taf:applec:v:48:y:2016:i:37:p:3558-3568
    DOI: 10.1080/00036846.2016.1142654
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    Cited by:

    1. Chen, W.D., 2018. "Upward wage rigidity and Japan's dispatched worker system," Economic Modelling, Elsevier, vol. 73(C), pages 152-162.
    2. Hongbo Wang & Dan Rickman, 2018. "Regional growth differences in China for 1995–2013: an empirical integrative analysis of their sources," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 60(1), pages 99-117, January.

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