Analysis of urbanization, industrialization and population agglomeration in Northeast China based on PVAR model

LI Tianzi1 WANG Wei1 DENG Lijun2

(1.Northeast Asia Research Center of Jilin University, Changchun, Jilin 130012)
(2.Changchun Institute of Urban Planning & Design, Changchun, Jilin 130000)

【Abstract】There is great significance to study the flow and spatial distribution of Northeast population during the process of urbanization and industrialization. Based on the analysis of the historical evolution process and the development characteristics of urbanization and industrialization in Northeast China, this paper uses the relevant urban data from 1987 to 2015, the PVAR model, the GMM, Granger causality test, impulse response, and other methods to study the relationship between industrialization, urbanization, and population agglomeration in Northeast China. The results show that: the increase in urbanization level has strengthened the influence of the four central cities, Shenyang, Dalian, Changchun and Harbin, which is beneficial for the population of the whole province to gather in four central cities. Under the influence of heavy industry development model and capital-intensive investment tendencies, the increase in the level of industrialization is not conducive to the agglomeration of the province’s population to the four central cities. In addition, the slow marketization process and the influence of the command economy have weakened the cyclical cumulative effect between industrialization and urbanization, resulting in weak interaction between industrialization and urbanization, the duration of which is not long. In further discussion, the static panel data model is used for robustness testing. The findings are consistent with the PVAR model. This article suggests that in the context of the loss of the Northeast population, Northeast region should give full play to the economies of scale and resource clustering advantages of big cities, reasonably arrange the proportion of industry, improve the industrial layout, determine the development relationship between heavy industry and light industry, and promote the development of industrialization to a higher level. In addition, it is necessary to reduce the frictional cost and coordination cost between urbanization and industrialization, and realize the interactive and coordinated development of the two in order to bring the advantages of population agglomeration and drive the development of the Northeast regional economy.

【Keywords】 industrialization; urbanization; population agglomeration; Northeast China;


【Funds】 Major Project of Key Research Base of Ministry of Education (16JJD790013) Key Research Project of Philosophy and Social Sciences of Ministry of Education (12JZD050) Project of Changchun Institute of Urban Planning & Design

Download this article

(Translated by ZHONG Yehong)


    [1]. ① The relevant explanation of population changes in Northeast China of National Development and Reform Commission in December 2016. [^Back]

    [2]. ① The urbanization index is measured by the proportion of non-agricultural population in the total population. [^Back]

    [3]. ② The industrialization index is measured by the proportion of the output value of the secondary industry in GDP. [^Back]


    [1] Fei, X. 中国城镇化之路. Huhhot: Inner Mongolia People’s Publishing House, (2010).

    [2] Qin, Z. On Economic Problems (经济问题), (10): 1–3 (2003).

    [3] Fan, G. & Guo, F. Rethinking China’s Urbanization and Metropolis (中国城市化和特大城市问题再思考). Beijing: China Economic Publishing House, (2017).

    [4] Ye, Y. Journal of Renmin University of China (中国人民大学学报), (2): 73–79 (2002).

    [5] [America] Chenery, H. B. and Syrquin, M. Patterns of Development. Beijing: China Financial & Economic Publishing House, 56 (1989).

    [6] Wang, C. Finance & Trade Economics (财贸经济), 38 (9): 111–128 (2017).

    [7] Li, G. Areal Research and Development (地域研究与开发), (5): 6–16 (2008).

    [8] Liu, Q. East China Economic Management (华东经济管理), (2): 13–17 (2013).

    [9] Xia, X. & Hao, J. Journal of Huazhong Agricultural University (华中农业大学学报), (1):19–24 (2013).

    [10] Jiang, H. & Wang, Z. Scientia Geographica Sinica (地理科学), (5): 591–595 (2012).

    [11] Wang, D., Cui, H., Ruan, R. & Zheng, F. Regional Economic Review (区域经济评论), (2): 26–34 (2015).

    [12] Guo, J. & Xu, Y. Economic Review (经济评论), (4): 39–49 (2016).

    [13] Li, G. & Wei, P. Inquiry Into Economic Issues (经济问题探索), (5): 72–79 (2013).

    [14] Su, F. Journal of Dalian University of Technology (大连理工大学学报), (3): 45–50 (2012).

    [15] Sun, C. Economic Survey (经济经纬), (6): 17–21 (2012).

    [16] Wu, B. & Wang, L. Inquiry Into Economic Issues (经济问题探索), (5): 7–12 (2014).

    [17] Sabyasachi Tripathi, Shupinder Kaur. Do Negative Externalities have any Impact on Population Agglomerations? Evidence from Urban India. MPRA Paper, 2017.

    [18] Zhou, Y. & Sun, J. China Economic Studies (中国经济问题), (2): 74–85 (2015).

    [19] Chen, J., Gao, J. & Wei, Y. Research of Agricultural Modernization (农业现代化研究), (3): 274–278 (2013).

    [20] Berlianta, Marcus, Konishi. The Endogenous Formation of a City: Population Agglomeration and Marketplaces in a Location-Specific Production Economy. Regional Science and Urban Economics, 2000, 30 (3): 289–324.

    [21] Wang, S. & Wang, Z. Population Journal (人口学刊), (6): 43–50 (2017).

    [22] Xu, Q., Hu, C. & Liu, D. Chinese Journal of Population Science (中国人口科学), (1): 29–37 (2015).

    [23] Lu, M. & Chen, Z. Economic Research Journal (经济研究), (6): 50–58 (2004).

    [24] Holtz-Eakin, Newey W. Estimating Vector Autoregressions with Panel Data. Econometrica: Journal of the Econometric Society, 1988, 56 (6): 1371–1395.

    [25] Love I, Zicchino L. Financial Development and Dynamic Investment Behavior: Evidence from Panel VAR. The Quarterly Review of Economics and Finance, 2006, 46 (2): 190–210.

This Article


CN: 22-1017/C

Vol 40, No. 06, Pages 75-85

November 2018


Article Outline


  • 1 Introduction
  • 2 Literature review
  • 3 Trends of industrialization, urbanization and population agglomeration in Northeast China
  • 4 Empirical analysis based on PVAR
  • 5. Conclusions and suggestions
  • Footnote