Evaluating Performance and Elucidating the Mechanisms of Collaborative Development within the Beijing–Tianjin–Hebei Region, China
Abstract
:1. Introduction
2. Materials and Methods
2.1. Framework for the Performance Assessment of Collaborative Development
2.2. Methods
2.2.1. The Gini Coefficient
2.2.2. The TOPSIS Method Supported by Entropy Weight Model
2.2.3. Impulse Response Functions
3. Data and Description
3.1. Data Source
3.2. The General Situation in the Case Study Area
4. Results and Discussion
4.1. Gini Coefficient Analyses
4.2. Evaluating the Performance of Collaborative Development
4.3. Analysis of Collaboration Development Mechanism
5. Conclusions and Outlook
5.1. Conclusions
5.2. Limitations and Prospect
Supplementary Materials
Acknowledgments
Author Contributions
Conflicts of Interest
References
- Perroux, F. Economic space: Theory and applications. Q. J. Econ. 1950, 64, 89–104. [Google Scholar] [CrossRef]
- Vernon, R. The product cycle hypothesis in a new international environment. Oxf. Bull. Econ. Stat. 1979, 41, 255–267. [Google Scholar] [CrossRef]
- Brookfield, H. Interdependent Development; Routledge: Abingdon, UK, 2012. [Google Scholar]
- Lucas, R.E., Jr. On the mechanics of economic development. J. Monetary Econ. 1988, 22, 3–42. [Google Scholar] [CrossRef]
- Romer, P.M. Increasing returns and long-run growth. J. Political Econ. 1986, 94, 1002–1037. [Google Scholar] [CrossRef]
- Krugman, P.R. Geography and Trade; MIT Press: Cambridge, MA, USA, 1993. [Google Scholar]
- Porter, M.E. Competitive Advantage of Nations: Creating and Sustaining Superior Performance; Simon and Schuster: New York, NY, USA, 2011; Volume 2. [Google Scholar]
- Humphrey, J.; Schmitz, H. Governance and Upgrading: Linking Industrial Cluster and Global Value Chain Research; Institute of Development Studies: Brighton, UK, 2000; Volume 120. [Google Scholar]
- Gereffi, G.; Humphrey, J.; Sturgeon, T. The governance of global value chains. Rev. Int. Political Econ. 2005, 12, 78–104. [Google Scholar] [CrossRef]
- Orenstein, D.E.; Shach-Pinsley, D. A comparative framework for assessing sustainability initiatives at the regional scale. World Dev. 2017, 98, 245–256. [Google Scholar] [CrossRef]
- Cottour, C.; Lelarge, P.; Milan, O. Une Brève Histoire de l’aménagement de Paris et sa Région; DREIF Paris: Paris, France, 2008. [Google Scholar]
- Abercrombie, P. Greater London Plan; University of London Press: London, UK, 1944; Available online: https://www.researchgate.net/publication/282815561_London_1944_Greater_London_Plan (accessed on 20 December 2017).
- Kreins, J.M. Histoire du Luxembourg, 3rd ed.; Presses Universitaires de France: Paris, France, 2003. (In French) [Google Scholar]
- Akins, J.E. The oil crisis: This time the wolf is here. Foreign Aff. 1973, 51, 462–490. [Google Scholar] [CrossRef]
- Brundtland, G.H. Report of the World Commission on Environment and Development: “Our Common Future”; United Nations: New York, NY, USA, 1987. [Google Scholar]
- Evrendilek, F.; Doygun, H. Assessing major ecosystem types and the challenge of sustainability in Turkey. Environ. Manag. 2000, 26, 479–489. [Google Scholar] [CrossRef] [PubMed]
- Albino, V.; Kuhtz, S. Enterprise input-output model for local sustainable development—The case of a tiles manufacturer in Italy. Resour. Conserv. Recycl. 2004, 41, 165–176. [Google Scholar] [CrossRef]
- Oliveira, C.; Antunes, C.H. A multiple objective model to deal with economy-energy-environment interactions. Eur. J. Oper. Res. 2004, 153, 370–385. [Google Scholar] [CrossRef]
- Oliveira, C.; Antunes, C.H. A multi-objective multi-sectoral economy-energy-environment model: Application to Portugal. Energy 2011, 36, 2856–2866. [Google Scholar] [CrossRef]
- Allan, G.; Hanley, N.; McGregor, P.; Swales, K.; Turner, K. The impact of increased efficiency in the industrial use of energy: A computable general equilibrium analysis for the United Kingdom. Energy Econ. 2007, 29, 779–798. [Google Scholar] [CrossRef]
- Duan, H.B.; Zhu, L.; Fan, Y. Modelling the evolutionary paths of multiple carbon-free energy technologies with policy incentives. Environ. Model. Assess. 2015, 20, 55–69. [Google Scholar] [CrossRef]
- Chen, P.Y.; Chen, S.T.; Hsu, C.S.; Chen, C.C. Modeling the global relationships among economic growth, energy consumption and CO2 emissions. Renew. Sustain. Energy Rev. 2016, 65, 420–431. [Google Scholar] [CrossRef]
- Wang, Q.S.; Yuan, X.L.; Cheng, X.X.; Mu, R.M.; Zuo, J. Coordinated development of energy, economy and environment subsystems-A case study. Ecol. Indic. 2014, 46, 514–523. [Google Scholar] [CrossRef]
- Li, H.D.; Wang, S.; Liu, Y. Evolution method and empirical research of regional synergetic development degree based on grey relational theory and distance collaborative model. Syst. Eng. Theory Pract. 2014, 34, 1749–1755. [Google Scholar]
- Wang, J.J. The evaluation and analysis of the coordination degree between economic and resources environment in Zhujiang Delta. J. Anhui Agric. Sci. 2011, 39, 2867–2869. [Google Scholar]
- Zhang, Z.Y.; Liu, L.; Tang, X.L.; Xu, L.P. Evaluation of coordinated development degree of urban human settlement environment and economic development—A case of Urumqi. J. Arid Land Resour. Environ. 2011, 25, 18–22. [Google Scholar]
- Oliveira, C.; Coelho, D.; Antunes, C.H. Coupling input-output analysis with multiobjective linear programming models for the study of economy-energy-environment-social (E3S) trade-offs: A review. Ann. Oper. Res. 2016, 247, 471–502. [Google Scholar] [CrossRef]
- Yuan, B.L.; Ren, S.G.; Chen, X.H. Can environmental regulation promote the coordinated development of economy and environment in China’s manufacturing industry?—A panel data analysis of 28 sub-sectors. J. Clean. Prod. 2017, 149, 11–24. [Google Scholar] [CrossRef]
- Li, Y.; Wu, F.L. The transformation of regional governance in China: The rescaling of statehood. Prog. Plan. 2012, 78, 55–99. [Google Scholar] [CrossRef]
- Nygaard, K.; Bosak, K. A critical assessment of the Mineral County Challenge: The role and implications of scale in collaborative development. J. Rural Stud. 2014, 34, 235–245. [Google Scholar] [CrossRef]
- Li, L.; Liu, Y. The driving forces of regional economic synergistic development in china: Empirical study by stages based on haken model. Geogr. Res. 2014, 33, 1603–1616. [Google Scholar]
- Leng, S.Y.; Zhai, Y.Z.; Jiang, S.J.; Lei, Y.; Wang, J.S. Water-environmental risk assessment of the Beijing-Tianjin-Hebei collaborative development region in China. Hum. Ecol. Risk Assess. 2017, 23, 141–171. [Google Scholar] [CrossRef]
- Wang, G.; Cheng, S.Y.; Li, J.B.; Lang, J.L.; Wen, W.; Yang, X.W.; Tian, L. Source apportionment and seasonal variation of PM2.5 carbonaceous aerosol in the Beijing-Tianjin-Hebei region of China. Environ. Monit. Assess. 2015, 187, 143. [Google Scholar] [CrossRef] [PubMed]
- Li, X.; Zhang, Q.; Zhang, Y.; Zheng, B.; Wang, K.; Chen, Y.; Wallington, T.J.; Han, W.J.; Shen, W.; Zhang, X.Y.; et al. Source contributions of urban pm2.5 in the beijing-tianjin-hebei region: Changes between 2006 and 2013 and relative impacts of emissions and meteorology. Atmos. Environ. 2015, 123, 229–239. [Google Scholar] [CrossRef]
- Bilal, M.; Nichol, J.E. Evaluation of modis aerosol retrieval algorithms over the Beijing-Tianjin-Hebei region during low to very high pollution events. J. Geophys. Res. Atmos. 2015, 120, 7941–7957. [Google Scholar] [CrossRef]
- Xiong, L.C.; Yu, C.; de Jong, M.; Wang, F.T.; Cheng, B.D. Economic transformation in the Beijing-Tianjin-Hebei region: Is it undergoing the environmental kuznets curve? Sustainability 2017, 9, 869. [Google Scholar] [CrossRef]
- LGFEA. The Outline of Collaborative Development of Beijing, Tianjin and Hebei Province. Available online: http://news.china.com.cn/node_7222674.htm (accessed on 10 October 2017).
- Cobb, C.W.; Douglas, P.H. A theory of production. Am. Econ. Rev. 1928, 18, 139–165. [Google Scholar]
- De Wulf, K.; Odekerken-Schroder, G.; Iacobucci, D. Investments in consumer relationships: A cross-country and cross-industry exploration. J. Mark. 2001, 65, 33–50. [Google Scholar] [CrossRef]
- Lakshmanan, T.R. The broader economic consequences of transport infrastructure investments. J. Transp. Geogr. 2011, 19, 1–12. [Google Scholar] [CrossRef]
- Gini, C. Variabilità e mutabilità. In Reprinted in Memorie di Metodologica Statistica; Pizetti, E., Salvemini, T., Eds.; Libreria Eredi Virgilio Veschi: Rome, Italy, 1912. [Google Scholar]
- Yoon, K.; Hwang, C.-L. Multiple Attribute Decision Making: Methods and Applications; Springer: Berlin, Germany, 1981. [Google Scholar]
- Yoon, K. A reconciliation among discrete compromise solutions. J. Oper. Res. Soc. 1987, 38, 277–286. [Google Scholar] [CrossRef]
- Hwang, C.-L.; Lai, Y.-J.; Liu, T.-Y. A new approach for multiple objective decision making. Comput. Oper. Res. 1993, 20, 889–899. [Google Scholar] [CrossRef]
- Sun, L.-Y.; Miao, C.-L.; Yang, L. Ecological-economic efficiency evaluation of green technology innovation in strategic emerging industries based on entropy weighted TOPSIS method. Ecol. Indic. 2017, 73, 554–558. [Google Scholar] [CrossRef]
- Sims, C.A. Macroeconomics and reality. Econ. J. Econ. Soc. 1980, 48, 1–48. [Google Scholar] [CrossRef]
- Lütkepohl, H. New Introduction to Multiple Time Series Analysis; Springer Science & Business Media: Berlin, Germany, 2005. [Google Scholar]
- Zhang, K.Y.; Cai, Z.B. The history review, limiting factors and future direction of the collaborative development of the Beijing-Tianjin-Hebei region (in Chinese). Hebei Acad. J. 2014, 34, 101–105. [Google Scholar]
- Dvouletý, O. Relationship between unemployment and entrepreneurship dynamics in the Czech Regions: A Panel VAR Approach. Acta Univ. Agric. Silvicult. Mendel. Brun. 2017, 65, 987–995. [Google Scholar] [CrossRef]
- Diebold, F.X. Elements of Forecasting; South-Western College Pub.: Nashville, TN, USA, 1998. [Google Scholar]
- Shen, G.; Chen, B. Zombie firms and over-capacity in Chinese manufacturing. China Econ. Rev. 2017, 44, 327–342. [Google Scholar] [CrossRef]
Target | Criteria | Indicators |
---|---|---|
Evaluation index system of collaborative development performance for BTH region | Population | Population density, Urbanization rate |
Economy | GDP per capita, Economic growth rate | |
Industry | Labor productivity in the primary industry, Labor productivity in the second industry, Labor productivity in the tertiary industry, Proportion of tertiary industry in GDP | |
Transportation | Road density, Passenger volume per capita, Freight volume per capita | |
Environment | Comprehensive utilization rate of industrial solid waste | |
Public services | Number of college students per 10,000 population, Number of licensed physicians per 10,000 population | |
Living standards of residents | Per capita disposable income of urban households, Per capita disposable income of rural households | |
Opening up to the outside world | Total amount of Foreign Investment actually utilized, Total value of imports and exports |
Indicators | Maximum | Minimum | Mean | Obs. | Tendency |
---|---|---|---|---|---|
Population density | 0.298 | 0.235 | 0.259 | 15 | |
Urbanization rate | 0.294 | 0.118 | 0.184 | 15 | |
GDP per capita | 0.291 | 0.244 | 0.270 | 15 | |
Economic growth rate | 0.105 | 0.033 | 0.070 | 15 | |
Labor productivity in the primary industry | 0.267 | 0.153 | 0.204 | 15 | |
Labor productivity in the second industry | 0.280 | 0.128 | 0.206 | 15 | |
Labor productivity in the tertiary industry | 0.265 | 0.164 | 0.218 | 15 | |
Proportion of tertiary industry in GDP | 0.149 | 0.102 | 0.137 | 15 | |
Road density | 0.223 | 0.138 | 0.169 | 15 | |
Passenger volume per capita | 0.300 | 0.219 | 0.263 | 15 | |
Freight volume per capita | 0.592 | 0.199 | 0.311 | 15 | |
Comprehensive utilization rate of industrial solid waste | 0.262 | 0.140 | 0.181 | 15 | |
Number of college students per 10,000 population | 0.472 | 0.357 | 0.410 | 15 | |
Number of licensed physicians per 10,000 population | 0.464 | 0.204 | 0.307 | 15 | |
Per capita disposable income of urban households | 0.131 | 0.114 | 0.121 | 15 | |
Per capita disposable income of rural households | 0.211 | 0.171 | 0.193 | 15 | |
Total amount of Foreign Investment actually utilized | 0.805 | 0.672 | 0.739 | 15 | |
Total value of imports and exports | 0.858 | 0.811 | 0.825 | 15 |
Variables | Dickey–Fuller GLS (ERS) | Augmented Dickey–Fuller | Kwiatkowski–Philips–Schmidt–Shin |
---|---|---|---|
Collaborative development performance (Y) | −2.456 ** | −3.253 ** | 0.159 ** |
Gini Coefficient of per capita fixed asset investment (FI) | −2.734 ** | −4.79 *** | 0.510 ** |
Gini Coefficient of per capita fiscal expenditure (FE) | −2.890 ** | −2.484 ** | 0.169 ** |
Lag | LogL | LR | FPE | AIC | SC | HQ |
---|---|---|---|---|---|---|
0 | 65.593 | NA | 1.32 × 10−8 | −9.630 | −9.499 | −9.656 |
1 | 88.978 | 32.380 * | 1.54 × 10−9 * | −11.843 | −11.321 * | −11.950 |
2 | 98.194 | 8.506 | 2.04 × 10−9 | −11.876 * | −10.963 | −12.064 * |
Variables | Collaborative Development Performance (Y) | Gini Coefficient of Per Capita Fixed Asset Investment (FI) | Gini Coefficient of Per Capita Fiscal Expenditure (FE) |
---|---|---|---|
Y(−1) | 0.621 | (0.169) | 0.040 |
(0.240) | (0.168) | (0.172) | |
FI(−1) | 0.429 | 0.693 | 0.372 |
(0.201) | (0.199) | (0.204) | |
FE(−1) | 0.301 | (0.111) | 0.970 |
(0.244) | (0.220) | (0.225) | |
R−squared | 0.565 | 0.663 | 0.748 |
Adj. R−squared | 0.494 | 0.563 | 0.673 |
F−statistic | 5.200 | 6.572 | 9.914 |
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Fang, C.; Luo, K.; Kong, Y.; Lin, H.; Ren, Y. Evaluating Performance and Elucidating the Mechanisms of Collaborative Development within the Beijing–Tianjin–Hebei Region, China. Sustainability 2018, 10, 471. https://doi.org/10.3390/su10020471
Fang C, Luo K, Kong Y, Lin H, Ren Y. Evaluating Performance and Elucidating the Mechanisms of Collaborative Development within the Beijing–Tianjin–Hebei Region, China. Sustainability. 2018; 10(2):471. https://doi.org/10.3390/su10020471
Chicago/Turabian StyleFang, Chuanglin, Kui Luo, Yunlong Kong, Haoxi Lin, and Yufei Ren. 2018. "Evaluating Performance and Elucidating the Mechanisms of Collaborative Development within the Beijing–Tianjin–Hebei Region, China" Sustainability 10, no. 2: 471. https://doi.org/10.3390/su10020471