The location quotient technique is commonly utilized to analyze economic development or compare regional industrial compositions. However, the location quotient is a static concept, which cannot reflect the growing advantages of different industrial sectors. In this paper, a new measurement termed growth quotients is proposed for comparing urban and regional industry compositions. Two kinds of growth quotient are defined:one is the sectoral growth quotient (SGQ) based on the relationship between an individual sector in a sub-region and the corresponding sector of a region, and the other is the regional growth quotient (RGQ) based on the relationship between an individual sector in a sub-region and all sectors of the whole region. The growth quotients are dynamic concepts, which can reflect the growing advantage of different industrial sectors. Further, two new spatial measurements of industrial development termed location entropy and growth entropy are defined by analogy with Theil's entropy. The similarity and differences between location quotient, growth quotient, growth entropy, and growth rates are discussed and illustrated by means of case analysis. In practice, the growth quotients, location quotient, growth entropy, location entropy, and shift share analysis can be integrated into a new analytical technique for comparing urban and regional industrial advantage.The location quotient mainly indicates the competitive advantage, while the growth quotients mainly reveal the competitive advantage of an industrial sector.
Key words
growth quotient /
location quotient /
growth entropy /
shift share analysis /
urban and regional eco nomics /
Xinyang
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References
[1] Haggett P, Cliff A D, Frey A. Locational Analysis in Human Geography[M]. London:Edward Arnold, 1977:301.
[2] Dunn Jr. E S. A statistical and analytical technique for regional analysis[J]. Papers and Proceedings of the Regional Science Association, 1960,6(1):97-112.
[3] Diebold F X. Elements of Forecasting (4thed.)[M]. Mason, Ohio:Thomson, 2007:156.
[4] 陈彦光.地理数学方法:基础和应用[M].北京:科学出版社,2011:328.[Chen Yanguang. Mathematical Methods for Geography[M]. Beijing:Science Press, 2011:328.]
[5] 张日旭.地方政府竞争引起的产能过剩问题研究[J].经济与管理, 2012,26(11):77-82.[Zhang Rixu. Research on the overcapacity problem which is caused by the local government competition[J]. Economy and Management, 2012,26(11):77-82.]
[6] Taylor P J. Quantitative Methods in Geography[M]. Prospect Heights, Illinois:Waveland Press, 1983:37.
[7] Wheelan C. Naked Statistics:Stripping the Dread from the Data[M]. New York and London:W. W. Norton & Company, 2013:1-6.
[8] Jiang B, Yao X (Eds). Geospatial Analysis and Modeling of Urban Structure and Dynamics[M]. New York:Springer-Verlag, 2010:91-117.
[9] 陈彦光,刘明华.城市土地利用结构的熵值定律[J].人文地理,2001, 16(4):20-24.[Chen Yanguang, Liu Minghua. The basic laws of the Shannon entropy values of urban land-use composition[J]. Human Geography, 2001,16(4):20-24.]
[10] 陈彦光.区域和城市产业发展阶段的信息熵分析[J].科技信息, 2008,25(27):385-387.[Chen Yanguang. Phase analysis of urban and regional industrial development using information entropy[J]. Scientific and Technical Information, 2008,25(27):385-387.]
[11] Theil H. Economies and Information Theory[M]. Amsterdam:North Holland, 1967:91-96.
[12] 陈彦光.中国城市化水平统计数据的问题分析[J].现代城市研究, 2012,27(7):4-8.[Chen Yanguang. On the enigma of China's level of urbanization[J]. Modern Urban Research, 2012, 27(7):4-8.]
[13] Hirschman A O. The Strategy of Economic Development[M]. New Haven:Yale University Press, 1958:98-119.
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