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Analyzing spatial disparities of economic development in Yellow River Basin, China

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Abstract

Economic density refers to the degree of labor, population, and tangible capital that concentrate in a physical space. It represents the efficiency of economic activities and intensity of land use in an area. This article presents an in-depth analysis spatial disparity of economic densities in Yellow River Basin in China by using 2000 and 2014 country level data. A composite index of economic density that integrates a suite of population, land, and production indicators through a grey-relation entropy model was applied for the spatial analysis in economic densities. The overall economic density levels in Henan Province and Shandong Province were higher than those of other provinces. Other major spatial agglomerations of counties with high economic density were in central parts of Inner Mongolia and Henan Province, the south of Shanxi Province, and the middle regions of Shaanxi Province. Finally, the indicators that might have influenced the level of economic density and the formation spatial economic disparity within Yellow River Basin were identified as the basic environmental conditions, transportation infrastructure, social and economic infrastructure, level and structure of industrialization level, and strategic policies for regional economic development. The results show that there is indeed spatial economic disparity in the studied region and that it may have been mainly affected by the geographically uneven distribution of per capita income and per capita land use intensity.

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References

  • Ahlfeldt, G. M., Redding, S. J., Sturm, D. M., et al. (2015). The economy of density: evidence from the Berlin Wall. Econometrica, 83(6), 2127–2189.

    Article  Google Scholar 

  • Alejandro, D. B. (2005). Agglomeration economies, economic growth and the new economic geography in Mexico. Econ WPA in its Series Urban /Regional, No. 0508001, 28–32.

  • Allen, T., & Arkolakis, C. (2014). Trade and the topography of the spatial economy. Quarterly Journal of Economics, 129(3), 1085–1140.

    Article  Google Scholar 

  • Andersson, F., Burgess, S., & Lane, J. I. (2007). Cities, matching and the productivity gains of agglomeration. Journal of Urban Economics, 61(1), 112–128.

    Article  Google Scholar 

  • Anselin, L. (1995). Local indicators of spatial association—LISA. Geographical Analysis, 27(2), 93–115.

    Article  Google Scholar 

  • Arribas-Bel, D. (2014). Accidental, open and everywhere: Emerging data sources for the understanding of cities. Applied Geography, 49(2), 45–53.

    Article  Google Scholar 

  • Barrios, T., Diamond, R., Imbens, G., et al. (2012). Clustering, spatial correlations, and randomization inference. Journal of the American Statistical Association, 107(498), 578–591.

    Article  Google Scholar 

  • Bei, H. L., Wu, C. F., Feng, K., et al. (2009). Regional disparity and dynamic evolution of land economic density—Evidence from the Yangtze River Delta area. Journal of Natural Resources, 24(11), 1952–1961.

    Google Scholar 

  • Bivand, R., Müller, W. G. , Reder, M.,et al. (2009). Power calculations for global and local Moran’s I. Computational Statistics & Data Analysis, 53(8), 2859–2872.

  • Brakman, S., Garretsen, H., & Marrewijk, C. V. (2009). Economic geography within and between European antions: The role of market potential and density across sapce and time. Journal of Regional Science, 49(4), 777–800.

    Article  Google Scholar 

  • Broersma, L., & Oosterhaven, J. (2009). Regional labor productivity in the Netherlands: Evidence of agglomeration and congestion. Journal of Regional Science, 49, 483–511.

    Article  Google Scholar 

  • Brunello, G., & Paola, M. D. (2008). Training and economic density: Some evidence from Italian provinces. Labour Economics, 15(1), 118–140.

    Article  Google Scholar 

  • Cao, G. Z., & Bai, X. (2010). On the location difference and influencing indicators of the economic density of urban construction land in China: Evidence from 273 prefecture-level cities. China Population, Resources and Environment, 20(2), 12–18.

    Google Scholar 

  • Chen, C., Cheng, L., & Xiu, C. L. (2013). Distribution of centrality of traffic network and its relationship with economic density of tertiary industry in Shenyang. Progress in Geography, 32(11), 1612–1621.

    Google Scholar 

  • Chen, Y., Syvitski, J. P. M., Gao, S., et al. (2012). Socio-economic impacts on flooding: A 4000-year history of the Yellow River, China. Ambio, 41(7), 682–698.

    Article  Google Scholar 

  • Chen, L. W., & Yang, K. Z. (2007). Productivity, urban scale and economic density: An empirical study on the economic effects of urban agglomeration. Social Sciences in Guizhou, 2, 113–119.

    Google Scholar 

  • Chenery, H. B., & Syrquin, M. (1975). Patterns of development, 1950–1970. Oxford: Oxford University Press.

    Google Scholar 

  • Ciccone, A. (2002). Agglomeration effects in Europe. European Economic Review, 46(2), 213–227.

    Article  Google Scholar 

  • Ciccone, A., & Hall, R. E. (1996). Productivity and the density of economic activity. American Economic Review, 86(1), 54–70.

    Google Scholar 

  • Deng, J. L. (1983). Review of grey systems. World Science, 7, 1–5.

    Google Scholar 

  • Deng, J. L. (1984). Theory and method of social economy grey system. Social Sciences in China, 6(1), 47–60.

    Google Scholar 

  • Feng, K. S., Siu, Y. L., Guan, D. B., et al. (2012). Assessing regional virtual water flows and water footprints in the Yellow River Basin, China: A consumption based approach. Applied Geography, 32(2), 691–701.

    Article  Google Scholar 

  • Feng, K., Wu, C. F., & Lu, Z. W. (2008). Discussions about spatial–temporal characters and the law of land economic density distribution-evidence from provincial panel data in China. Economic Geography, 28(9), 817–820.

    Google Scholar 

  • Friedmann, J. (1969). A general theory of polarized development (Rev ed.). University of California at Los Angeles, School of Architecture and Urban Planning.

  • Onishi, A., Imura, H., Han, J., Shi, E., & Fukushima, Y. (2007). Socio-economic activities and the balance between water resource supply and demand in the Yellow River basin, China. Changes in Water Resources Systems: Methodologies to Maintain Water Security and Ensure Integrated Management, 315–320.

  • Graham, D. J., & Kim, H. Y. (2008). An empirical analytical framework for agglomeration economies. The Annals of Regional Science, 42(2), 267–289.

    Article  Google Scholar 

  • Gu, C. L., Yu, T. F., Li, W. M., et al. (2008). Urbanization pattern, process and mechanism in China (pp. 88–91). Beijing: Science Press.

    Google Scholar 

  • He, Y. J., & Hu, L. (2008). Defining regional spatial structure with economic density measures: A case study of Jiangxi province. Planners, 24(10), 68–72.

    Google Scholar 

  • Henderson, J. V. (2002). Marshall’s scale economies. Journal of Urban Economics, 53(1), 1–28.

    Article  Google Scholar 

  • Hotta, K. (2011). Local autocorrelation of similarities with subspaces for shift invariant scene classification. Pattern Recognition, 44(4), 794–799.

    Article  Google Scholar 

  • Ji, B., Zhang, X., & Kong, S. Y. (2007). Establishing indicator system for metropolitan area’s developing ability. Modern Urban Research, 6, 68–74.

    Google Scholar 

  • Larsson, J. P. (2014). The neighborhood or the region? Reassessing the density–wage relationship using geocoded data. The Annals of Regional Science, 52(2), 367–384.

    Article  Google Scholar 

  • Lee, J., & Wong, D. W. (2001). Statistical analysis of geographical information with ArcView GIS. New York: Wiley.

    Google Scholar 

  • Li, M. N., Cai, S. & Tan, C. L. (2011). An analysis of situation of economic spatial dissimilarity in the Yellow River Valley. Economic Geography, 31(3), 379–389, 419.

  • Li, X., & Griffin, W. A. (2013). Using ESDA with social weights to analyze spatial and social patterns of preschool children’s behavior. Applied Geography, 43, 67–80.

    Article  Google Scholar 

  • Li, S. X., & Huang, Z. S. (2013). The relational analysis and empirical research on information industry and advanced manufacturing industry. Chinese Journal of Management Science, 21(s2), 587–593.

    Google Scholar 

  • Lin, J. (1991). Divergence measures based on the Shannon entropy. IEEE Transactions on Information Theory, 37(1), 145–151.

    Article  Google Scholar 

  • Lin, J., Zu, J. X., Miao, C. L., et al. (2008). Spatial difference analysis of the economic density of construction land at a county level in China. China Land Science, 22(3), 46–53.

    Google Scholar 

  • Lu, Z. (1992). Regional difference and analysis of population-economy density in China. Population & Economics, 2, 44–48.

    Google Scholar 

  • Mcanally, J. S. (2002). Fluorescence measurements with Beckman model DU spectrophotmeter. Analytical Chemistry, 26(9), 1526–1526.

    Article  Google Scholar 

  • Mills, E. S. (1972). Study in the structure of the urban economy. Baltimore, MA: Hopkins press.

    Google Scholar 

  • Muth, R. F. (1969). Cities and housing: the spatial pattern of urban residential land use. Chicago and London: The University of Chicago Press.

    Google Scholar 

  • Ng, D. K. W. (1994). Grey system and grey relational model. Acm Sigsmall/PC Notes, 20(2), 2–9.

    Google Scholar 

  • Nordhaus, W. D. (2005). Geography and macroeconomics: New data and new findings. Proceedings of the National Academy of the United States of America, 103(10), 3510–3517.

    Article  Google Scholar 

  • Porta, S., Latora, V., & Wang, F. H. (2012). Street centrality and the location of economic activities in Barcelona. Urban Studies, 49(7), 1471–1488.

    Article  Google Scholar 

  • Pratt, P. F., & Bradford, G. R. (1960). Determination of exchangeable cations in soils with the Beckman model B flame spectrophotometer. Soil Science, 89(6), 342–346.

    Article  Google Scholar 

  • Pu, Y. X., Ge, Y., Ma, R. H., et al. (2005). Analyzing regional economic disparities based on ESDA. Geographical Research, 24(6), 965–973.

    Google Scholar 

  • Pupa, D. (2010). The magnitude and causes of agglomeration economics. Journal of Regional Science, 50(1), 203–219.

    Article  Google Scholar 

  • Qin, C. L., & Li, M. N. (2010). The mechanism of the spatial dissimilarity of regional economy: A theoretical model and its application in the Yellow River Valley. Geographical Research, 29(10), 1780–1792.

    Google Scholar 

  • Qin, C. L., & Zhou, E. H. (2010). The patterns of spatial differentiation of economies in Yellow River Basin. Journal of Henan University (Natural Science), 40(1), 40–44.

    Google Scholar 

  • She, D., & Xia, J. (2012). The spatial and temporal analysis of dry spells in the Yellow River basin, China. Stochastic Environmental Research and Risk Assessment, 27(1), 29–42.

    Article  Google Scholar 

  • Shen, T. Y., Lao, X., & Zhang, X. H. (2012). Economic density: A new perspective on the study of regional economy. In Shen, G., & Huang, X. (Eds). Advanced Research on Electronic Commerce, Web Application, and Communication: proceedings in the Electronic Commerce, Web Application, and Communication 2011 Conference.  (vol 6, pp. 15–19). Guangzhou: Springer.

  • Smiriga, S. R., & Hearst, J. E. (1969). Electronic speed control for the Beckman model E analytical centrifuge. Review of Scientific Instruments, 40(2), 233–236.

    Article  Google Scholar 

  • Wang, X. M. (1993). Study on the difference of population-economy density in Guangdong Province. South China Population, 2, 20–24.

    Google Scholar 

  • Wang, F. H., Antipova, A., & Porta, S. (2011). Street centrality and land use intensity in Baton Rouge, Louisiana. Journal of Transport Geography, 19(2), 285–293.

    Article  Google Scholar 

  • Wei, Z. K. (2015). Observing the economic development trend in China from a comparative analysis of western economics and political economics. Canadian Social Science, 11(9), 100–103.

    Google Scholar 

  • Wilson, A. G. (2000). Complex spatial systems: The modeling foundations of urban and regional analysis. New York: Pearson Education.

    Google Scholar 

  • Xie, H. L., Liu, Z. F., Wang, P., et al. (2014). Exploring the mechanisms of ecological land change based on the spatial auto-regressive model: A case study of the Poyang Lake Eco-Economic Zone, China. International Journal of Environmental Research and Public Health, 11(1), 583–599.

    Article  Google Scholar 

  • Xu, J., Yin, R., Li, Z., et al. (2006). China’s ecological rehabilitation: Unprecedented efforts, dramatic impacts, and requisite policies. Ecological Economics, 57(4), 595–607.

    Article  Google Scholar 

  • Yang H., Liu J., Wang T. (2011). Analyzing economic spatial-temporal disparities at county level in Yangtze River Delta based on ESDA-GIS. In: Communications in Computer and Information Science, vol 143. Berlin: Springer.

    Google Scholar 

  • Zhang, K. B. (1999). Which regional inequality? The evolution of rural-urban and inland-coastal inequality in China form 1983 to 1995. Journal of Comparative Economics, 27(4), 686–701.

    Article  Google Scholar 

  • Zhang, G. S., Ding, Z. W., & Wang, F. Z. (2013). A study on spatial-temporal variation of economic density of central China. Economic Geography, 33(5), 15–23.

    Google Scholar 

  • Zhang, G. S., Ding, Z. W., Zhao, M., et al. (2014a). Spatial variation and its influencing factors of economic Density in CPER at county level. Economic Geography, 34(9), 19–39.

    Google Scholar 

  • Zhang, Z. L., & Jiang, A. L. (2005). Integrated investigation 0n the level of Chinese industrialization development. Industrial Engineering and Management, 10(6), 1–7.

    Google Scholar 

  • Zhang, J. Q., Wu, Y. J., Ge, Y., et al. (2014b). Eco-security assessments of poor areas based on gray correlation model: A case study in Enshi. Geographical Research, 33(8), 1457–1466.

    Google Scholar 

  • Zhang, P., Yang, Q., & Zhao, Y. C. (2012). Relationship between social economic agglomeration and labor productivity of core cities in northeast China. Chinese Geographical Science, 22(2), 221–230.

    Article  Google Scholar 

  • Zhao, G., Tian, P., Mu, X., et al. (2014). Quantifying the impact of climate variability and human activities on streamflow in the middle reaches of the Yellow River basin, China. Journal of Hydrology, 519 (Part A), 387–398.

    Article  Google Scholar 

  • Zhou, E. H. (2007). A study on the spatial differentiation of economics in the Yellow River Basin. Henan University.

  • Zhou, G. F., & Xia, X. Q. (2008). The convergence and the impact factors of regional economic growth in China—An empirical analysis of The Yellow River Basin. Statistical Research, 25(11), 3–8.

    Google Scholar 

  • Zhu, L. Y., & Su, W. C. (2014). Research on carrying capacity of water resources based on entropy-weight and grey-correlation model. Journal of Water Resources & Water Engineering, 25(5), 233–236.

    Google Scholar 

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Acknowledgements

The project reported in this article has been funded by the National Natural Science Foundation of China(Grant No. 41601175), the Foundation and Advanced Technology Research Plan of Henan Province (Grant No. 152300410067), the Key Scientific Research Project of Henan Province (Grant No. 16A610001), the Philosophy Social Sciences Planning Project of Henan Province (2014CJJ016), and by the generous support from Program for Innovative Research Team (in Science and Technology) in University of Henan Province (Grant No. 16IRTSTHN012).

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Correspondence to Pengyan Zhang or Hui Zheng.

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Zhang, P., Pang, B., Li, Y. et al. Analyzing spatial disparities of economic development in Yellow River Basin, China. GeoJournal 84, 303–320 (2019). https://doi.org/10.1007/s10708-018-9860-9

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