https://orcid.org/0009-0009-6991-5472
Figures
Abstract
Economic institutional change is a vital driving force behind the rapid rise of China’s economy. However, the incremental approach to economic institutional change has caused unbalanced transformation and economic growth. To this end, we adopted the entropy method to measure the economic institutional change index, and employed social network analysis to reveal its spatial correlation characteristics. We then applied QAP analysis to empirically demonstrate the impact of China’s economic institutional change on regional disparities in economic growth. The findings indicated a gradual increase in the level of economic institutions over time and a spatial gradient between the eastern, central, and western regions. Moreover, the spatial correlation network of China’s economic institutional change is stable and gradually improving. Nevertheless, the role of provinces in the process of economic institutional change varies: the eastern coastal provinces play a dominant role, the central and western provinces benefit to a lesser extent, and some provinces in northeastern China play a “bridging” and “intermediary” role. Regional differences in China’s economic institutional change have widened the regional disparities in China’s economic growth, and the impact of each dimension of economic institutions on regional disparities in economic growth is characterized by phases.
Citation: Jia W, Di Q, Chen X (2024) The spatial correlation of economic institutional change in China and its impact on economic growth: A social network analysis approach. PLoS ONE 19(10): e0297354. https://doi.org/10.1371/journal.pone.0297354
Editor: Changjian Wang, Guangzhou Institute of Geography, Guangdong Academy of Sciences, CHINA
Received: July 29, 2023; Accepted: January 3, 2024; Published: October 22, 2024
Copyright: © 2024 Jia et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Data Availability: All relevant data are within the paper and its Supporting Information files.
Funding: This work was supported by National Natural Science Foundation of China (grant numbers 42076222). The funder had role in visualization, investigation, supervision, software, writing-reviewing and editing of the manuscript.
Competing interests: The authors have declared that no competing interests exist.
Introduction
Since the introduction of China’s reform and opening up policy, its economy has leapfrogged into being the world’s second largest. Its GDP per capita rose from 423 yuan in 1979 to 85,698 yuan in 2022, achieving the “Chinese miracle” of economic growth. This rapid economic rise can be attributed to economic institutional change, through which the associated “institutional dividend” brought development opportunities [1, 2]. Throughout the process of economic institutional change over the past 40 years, China has undergone a series of incremental and systematic institutional innovations as well as institutional and structural evolution to liberate and develop its productive forces and successfully transition from a socialist planned economy to a socialist market economy [3].
China’s economic institutional changes are clearly market oriented: the power of control, investment, and distribution of resources and economy gradually transitioned from government to market regulation [4]. A major step in China’s economic transformation is the adjustment of the property rights system, which features the restructuring of state-owned enterprises and encouraging the development of a non-state-owned economy, thereby promoting the diversification of the property rights system and economic growth [5]. The widening and deepening of China’s opening up has broken down barriers to trade liberalization, while foreign trade and investment have provided new opportunities for economic transformation and development [6, 7]. The core of economic institutional change lies in the reform of the distribution system, which includes establishing and improving a distribution system, which sets in place incentive mechanisms, balances or accommodates efficiency and fairness, and forms a new income distribution structure [8]. Specifically, the success of China’s economic institutional change owes much to the incremental change approach, that is, adopting the unbalanced (also known as non-uniform or uneven) strategy to achieve economic institutional change by piloting it in some areas and then promoting it to wider areas [9, 10]. The approach’s spatial and temporal dispersal of the contradictions and conflicts of interest in economic institutional innovation provide a buffer zone for resolving risks in economic institutional innovation [11].
However, the incremental approach to economic institutional change, mostly province and region based, has created a spatial and temporal sequence in the institutional and policy environment for unbalanced transformation in China, which has also indirectly affected its spatial pattern of economic development [12]. Furthermore, the long-term neglect of multiple spatial effects in the process of economic institutional change has affected China’s balanced economic growth and regional economic development [13]. Against this backdrop, this study innovatively adopted the spatial correlation perspective to integrate the economic institutional changes in provinces and municipalities across China into a unified overall framework to examine the spatial and temporal characteristics of their economic institutional changes and constitutive networks. This assisted to clarify the status and roles of provinces and municipalities in the network of economic institutional changes in China, which is particularly important for the spatial balance of China’s economic institutions and the construction of a higher level of socialist economic institutions. Moreover, this study extensively investigated the impact of unbalanced economic institutional change on regional disparities in economic growth, which assisted in providing fresh ideas for reducing regional economic disparities and achieving balanced regional economic development.
The framework of this paper proceeds as follows (Fig 1). The Literature Review section summarizes and reviews the existing literature. The Materials and Methods section introduces the data sources and research methods. The Results section presents our results of this study. The Discussion section is the discussion. The Conclusions section draws the conclusion.
Literature review
Institutions and institutional change
The Western institutional school began to study the role of institutional factors in social and economic development early. The old institutional school, represented by Veblen [14], Commons [15] and others, defined the concept of institution broadly in terms of ownership, distributive relations, and legal institutions, among others. The 1950s saw the rise of a new school of institutional economics, represented by Galbraith [16], Coase [17] and others, which redefined institutions as norms of behavior and interactions between people or organizations.
North’s theory of institutional change is an important branch of the new institutional economics stream. North [18] views institutions as a set of norms and social structures that regulate and constrain the behavior of individuals. In his 2001 book, Institutions, institutional change and economic performance, he explained institutional change as the process by which individuals with the ability to negotiate over rules adjust to a comprehensive or integrated institutional framework constructed by formal and informal rules, which impacts economic performance through transaction costs. In addition, the theory of evolutionary institutional change [19] and the theory of institutional change from the evolutionary game view [20] are the main analytical frameworks for institutional change in the West. The driving force of institutional change, there are two explanations of endogenous change and exogenous change, exogenous change refers to new knowledge, the emergence of new technologies will change the external environment, resulting in institutional imbalances to generate new institutional needs, when the expected benefits of the new institutional arrangements are higher than transaction costs of institutional change when institutional change has occurred [21]. Endogenous change that the intrinsic characteristics of the institutions induces its own change, the institutions of self-reinforcement, self-weakening corresponds to the system of institutional stabilization, system of institutional change in two phases, respectively [22, 23].
Institutional change affects economic growth
Regarding the relationship between institutional change and economic growth, North [24] established a theoretical framework to investigate economic growth. In The rise of the Western world, North and Thomas [25] pointed out that institutional change determines economic growth by influencing the motivation of economic entities and the efficiency of economic organizations. Transactions, as the smallest structural unit of an economic institutions, are the basis for comparative analysis of institutions, and institutional change acts on economic growth through transaction costs [26]. At the same time, there are differences in the impact of different dimensions of institutions on economic growth, with institutional flexibility contributing more significantly to economic growth [27]. Easterly and Levine [28] as well as Rodrik et al. [29] and Acemoglu et al. [30] employed regression analysis to demonstrate, empirically, the impact of institutional factors on the efficiency of economic growth based on cross-country data.
In addition to the micro-paths of institutional change and economic growth, researchers also focus on their spatial effects. Institutions exhibit a spatial spillover effect in development, that is, the level of institutions between countries and regions displays a mutual influence [31]. Additionally, institutions not only influence local economic growth, but also affect the economic growth of surrounding regions through spillover effects [32, 33]. Moreover, some scholars have associated institutional change with “space of flows,” a factor that affects economic growth. Lothian [34] and Alfaro et al. [35] associated institutions with capital flows to investigate the impact of institutions on cross-national capital flows. Krammer [36] and Vargo et al. [37] analyzed the relationship between institutions and the spatial spillover effects of technological innovation, confirming the impact of institutions on technological innovation flows. Sun et al. [38] empirically demonstrated the role of institutional soft environment on regional talent attraction, taking the impact of institutional distance on talent flow patterns and cross-regional mobility in China as an example.
Economic institutional change and economic development in China
Since the 1970s, China has carried out economic reforms, opened up to the outside world, encouraged the development of the non-state economy, and gradually shifted from a planned economic system to a market economic system, which is in essence a process of economic institutional change, and has greatly contributed to China’s economic growth [39, 40]. At the same time, China’s economic institutional change process is also characterized by gradualism, lagging and path dependence [41, 42].
In terms of economic institutions measurement, the entropy method and principal component analysis are often adopted to obtain institution proxy variables to characterize China’s economic institutional change [43, 44]. In the study of the relationship between economic institutional change and economic growth in China, scholars at home and abroad have also achieved a lot of results. Two schools of thought—the “experimental school” and the “convergence school”—are popular among foreign scholars who explain China’s economic growth from the perspective of economic institutional change. Nevertheless, both focus on the role and impact of different perspectives of economic institutional change on economic growth [45]. Liu [46] and Qiang and Jian [47] quantified institutional factors and empirically analyzed the impact of China’s institutional change on economic growth from the degrees of market resource allocation, market openness, and diversification of property rights. Zhang and Wang [48] analyzed the impact of economic institutional change on China’s economic growth in the context of the country’s high-quality economic development goal at the current stage. Moreover, the issue of uneven economic institutional change and economic development in China has received extensive attention. Young [49] analyzed the reform process led to the fragmentation of the domestic market and the distortion of regional production away from patterns of comparative advantage, while Huang [50] proved that economic institutions are a key influencing factor of regional economic disparities in China.
Materials and methods
Data sources
Considering the consistency of statistical data and caliber, as well as the impact of COVID-19 on statistical data in 2019, the study time interval from 1997 to 2018 was selected. And 31 provinces and municipalities in China were selected as the study area units. The data in this paper are from China Statistical Yearbook and statistical year-book of China’s province and municipalities from 1996 to 2019.
Index system construction
Drawing on the research outcomes of previous studies and considering the connotation and trend characteristics of China’s economic institutional change, we constructed a system of indices for evaluating China’s economic institutional change from the opening up, distribution pattern, government-market relationship, and property rights system perspectives [51], as shown in Table 1.
Methods
The logic of this research is shown in Fig 2. The specifics of the methods for each step are listed below.
Entropy method.
Entropy method is an objective weighting method commonly used in the comprehensive evaluation of index system, and the weight of each index is determined by objective difference degree. This method can more objectively and effectively measure the economic institutional changes of provinces and municipalities in China. Since entropy method is a common objective weighting method, it will not be introduced here.
Modified gravity model.
The modified gravity model is based on the law of universal gravity and gravity model, and proposed by Tinbergen and Pobyhobnen after considering the developmental characteristics, laws and influencing factors in the field of economic research [52, 53]. It is widely used in the calculation of interaction between cities and regions and the determination of spatial correlation.
Where Rij represents the gravitational strength between province i and j, Lij represents the gravitational coefficient between province i and j. Gi and Gj are the GDP of provinces i and j respectively, Pi and Pj are the permanent population of province i and j respectively, Ii and Ij are the economic institutional change indexes of provinces i and j respectively. Dij indicates the distance between provincial capitals, gi and gj are the per capita GDP of province i and j respectively.
Social network analysis.
Social network analysis is an analytical method used to describe and analyze the relationship characteristics and types of social things and their relationship networks through relational data, including overall network analysis and individual network analysis [54, 55]. Its various index, formulas and meanings are shown in Table 2.
QAP.
Based on the replacement of matrix data, quadratic assignment procedure explores the relationship between corresponding elements in two or more matrices, and obtains the test method of matrix correlation and regression [56, 57]. This method can effectively solve the problems of multicollinearity and false correlation.
Where Ω represents the spatial network relation matrix of the research object, Xm (m = 1,2,⋯,n) represents the influencing factor matrix.
Results
Measurement of economic institutional change in provinces and municipalities across China
Based on the index system constructed above and the index weights derived from the entropy method, we measured the index of economic institutional change in provinces and municipalities across China.
As can be observed from Figs 3 and 4, the temporal and spatial distribution of economic institutional change in China is uneven and exhibits significant differences. From a temporal perspective, the mean value increases from 0.738 to 1.114, the index of China’s economic institutional change generally exhibits an increasing trend: economic institutional change was slow before 2000, rapid from 2000 to 2008, and slowly increasing after 2008 owing to the economic crisis. In nuclear density analysis, the main peak of nuclear density curve shifted to the right obviously, the height of the crest decreases and the width of the crest widens from narrow, indicating that the level of China’s economic institutions is increasing, and the regional gap in the level of economic institutions is expanding continuously. Spatially, the economic institutional change of these regions is uneven and exhibits significant regional differences: the economic institutional change in the eastern region is faster than in the central and western regions. Guangdong, Shanghai, Zhejiang, Beijing, and Jiangsu rank among the top provinces and municipalities, while the economic institutional change in the western provinces and municipalities such as Tibet, Qinghai, and Xinjiang rank lower than others (S1 Fig and S1 Table).
Temporal distribution of China’s economic institutional change (a)Descriptive statistics (b)Nuclear density.
Analysis of the spatial correlation network of China’s economic institutional change
Construction and analysis of the spatial correlation network.
We employed the modified gravity model to construct a spatial spillover relationship matrix for China’s economic institutional change and used Gephi to select part of the cross-sectional data in order to construct a spatial correlation network (S2 Fig). As shown in Fig 5 and Table 3, the spatial correlation network of China’s economic institutional change is relatively stable, and its network density is increasing but remains relatively low. The network relevance is constantly at 1, implying that no provinces and municipalities are in isolated development. The network rank is in a fluctuating state, and the recent upper limit (with the exception of 1999) is also stable at around 0.95. The network efficiency value and network spillover pathway are increasing and the network stability is gradually improving. Beijing, Shanghai, Jiangsu, Guangdong, Zhejiang, and Tianjin are strongly correlated with other provinces and municipalities and play a strong dominant and controlling role in the network. In contrast, the western and central provinces and municipalities are less correlated and are in a weaker position in the network owing to their level of economic development and geographical location. However, the correlation between them gets stronger over time, and their position and role in the overall network gradually improve.
The spatial correlation network of China’s economic institutional change (a)1997 (b)2007 (c)2018.
Centrality is a quantification of the position of China’s provinces and municipalities in the spatial correlation network of economic institutional change. Fig 6 indicates the degree, closeness, and betweenness centrality of China’s provinces and municipalities. According to the figure, the spatial correlation networks of China’s economic institutional change generally exhibit more receiving relationships than spillover relationships, and the spillover effect is weak. The node connection pathway is relatively unitary, with strong reliance on intermediate cities. With a relatively high in-degree centrality and a strong factor adsorption capacity, the eastern region is in a dominant and leading position in these networks. With a high closeness centrality and a short distance from other provinces and municipalities in the network, Jilin, Heilongjiang, Shaanxi, Gansu, Qinghai, Ningxia, Tibet, and Xinjiang are “central actors” in the spatial correlation network. Beijing, Shanghai, and Guangdong, given their high betweenness centrality and more receiving and spillover relationships, play a strong controlling role in the spatial correlation of other provinces and municipalities, and are key nodes in the network (S2 Table).
The analysis of centrality of provinces and municipalities across China (a)degree centrality (b)closeness centrality (c)betweenness centrality.
Block model analysis.
To reveal the spatial clustering characteristics of the spatial correlation network of China’s economic institutional change further, we utilized the block model to divide the status of China’s 31 provinces and municipalities in the network into four major segments (S3 Table), as shown in Fig 7. According to the block model analysis, the status and role of Chinese provinces and municipalities in the spatial correlation networks differ significantly. The “agent” segment mainly covers the northeastern and central provinces, whose geographical location and development level enable them to play a bridging and linking role in the network. The “net spillover” segment mainly covers some provinces and municipalities in the central and western regions, which exhibit more spillover relationships than receiving relationships, and whose external economic dependence is high. The “bidirectional spillover” segment is mainly composed of Beijing, Tianjin, and Shandong. The “net beneficial” segment is mainly composed of Jiangsu, Shanghai, Guangdong, Zhejiang, and Fujian, mainly involving the eastern coastal provinces and municipalities, with high levels of economic development and strong attractiveness to factors from other provinces and municipalities.
Spillover effect of spatially related plates of China’s economic institutional changes (a)1997 (b)2018.
In sum, the provinces and municipalities on the eastern coast of China, which have faster economic institutional change, are still in a stage where the polarization effect is greater than the trickle-down effect. They have a stronger attraction to factors from other regions, exhibiting evident polarization. That is, they are in a dominant position in the spatial correlation network of economic institutional change. Central and western provinces and municipalities, where economic institutional change is slower, exhibit more spillover relationships than receiving relationships, and exhibit a productive factor spillover effect. They are at a disadvantage in the spatial correlation network.
Empirical analysis of the spatial correlation between China’s economic institutional change and economic growth
Model setting and explanation of variables.
Starting with the four dimensions of economic institutional change, we employed QAP analysis in UCINET to probe the impact of the spatial imbalance of economic institutional change on regional disparities in China’s economic growth. We set up the following models to probe the impact of economic institutional changes on regional disparities in economic growth:
(3)
Based on the measurement of the index of economic institutional change, the difference matrix of opening up (OU), distribution pattern (DP), government-market relationship (GMR) and property rights system (PRS) was used as the explanatory variable, and the difference in economic growth rate (EGR) of each province and municipalities was used as the predicted variable. The difference matrix of the explanatory variables and the predicted variables are 31×31, taking the EGR as an example, EGRij represents the difference in the economic growth rate between province i and j. In order to avoid the impact of dimensional inconsistency on the research results, the average value of the difference matrix is used to standardize the variables.
QAP correlation analysis.
We employed UCINET to perform QAP correlation analysis on the matrix of differences between the economic institutions’ dimensions and the matrix of differences between the provinces and municipalities’ economic growth rates. The results in Table 4 indicate that regional differences in opening up and distribution patterns are positively correlated with regional disparities in economic growth for all periods, and this correlation is significant at the 1% level. The correlation coefficients are 0.191 and 0.383, respectively. Despite this significant correlation, there is an issue of co-linearity between the explanatory variables, and therefore QAP regression analysis is required.
QAP regression analysis.
Based on the correlation analysis above, we employed QAP regression analysis to explore the influential relationships between the variables. From Table 5, it can be observed that regional disparities in terms of opening up, distribution pattern, government-market relations, and property rights system are the primary institutional factors affecting regional disparities in economic growth across provinces and municipalities in China during the 1997–2018 period, with standard regression coefficients of 0.353, 0.417, -0.337 and 0.362 respectively. In terms of opening up, distribution pattern, government-market relations, and property rights system, the regional disparities during this period widened the regional disparities in economic growth, while the widening of regional disparities in government-market relations helped to bridge the regional disparities in economic growth. This is because narrowing the regional disparities in economic growth required the government to adapt to local conditions and implement macro-regulation, thereby making the two exhibit a negative influential relationship.
Owing to the long time-interval of the full-period regressions and the crude results of the analysis, we conducted year-by-year regression analysis. As shown in Table 6, the impact of regional disparities in various dimensions of economic institutions on regional disparities in economic growth is complicated and characterized by phases. From 1997 to 2003, regional disparities in China’s economic growth were mainly caused by regional disparities in opening up and the property rights system. Since this was a period of in-depth and comprehensive reform and opening up developments, when denationalization was in full implementation, opening up and the property rights system in this period had a strong pulling effect on economic growth, causing it to have a significant impact on regional economic growth disparities. In the period 2004–2008, the regional disparity in the property rights system was the main institutional factor affecting regional economic growth disparity. Moreover, during this period, special attention was paid to state-owned enterprise reformations and the establishment of a modern property rights system, and since the denationalization of the property rights system and the development of a multi-ownership economy are long-term processes, their impact on regional economic growth disparities is also continuous. In the 2009–2017 period, regional disparities in distribution patterns and property rights systems were the main institutional reasons for the formation of regional disparities in economic growth, and apart from the impact of property rights systems, regional disparities in distribution patterns had a significant impact on regional disparities in economic growth.
In sum, regional disparities in China’s economic institutional changes have widened regional differences in its economic growth. From the economic institutions perspective, to promote balanced and coordinated regional economic development, we need to attach special attention to current regional disparities in property rights systems and distribution patterns, and reduce regional economic growth disparities by promoting a spatially balanced development of property rights systems and distribution patterns.
Discussion
This article focuses on the spatial-temporal evolutionary characteristics of China’s economic institutional change and its impact on economic growth. Indeed, China’s economic institutional level are constantly improving since China’s economic reform, but the incremental approach to economic institutional change has caused a gradient difference where the economic institutional change in the eastern region is better than in the central and western regions [12]. Therefore, when implementing economic policies in the later stages, greater attention should be given to the status quo of economic institutional development in the central and western regions, as this could help provide better conditions for economic development in the central and western regions.
In addition, institutions exhibit a spatial spillover effect in development, that is, the level of institutions between countries and regions displays a mutual influence [31–33]. We should attach greater importance to the establishment of a spatial correlation network for national-level economic institutional changes while paying attention to local economic institutional changes. Some questions merit further thoughts on, for example, how to give full play to the spillover and pulling effects of the eastern region in the spatial correlation network of economic institutional changes, and how to improve the disadvantaged position of the western region in the spatial correlation network [58]. To solve the uneven regional development and coordination between regional economic development issues, by considering the relationship between regional economic institutions disparities and regional economic growth disparities as the entry point, we should steer towards balanced regional economic development by introducing appropriate changes to the economic institutions [59].
There are still some shortcomings in the article. The article constructed the evaluation index system of the level of China’s economic institutions, but the subsequent selection of indicators can continue to be enriched and perfected. The research scale unit is relatively large in terms of the provincial area, and the subsequent research can be deepened to the level of prefectural cities and counties. The investigation of the spatial correlation between economic institutional change and economic growth needs to be in-depth.
Conclusions
In addition to measuring the index of economic institutional change, this study applied modified gravity model and social network analysis to examine the characteristics its spatial correlation network. QAP analysis was then performed to probe the impact of spatial imbalance in China’s economic institutional change on regional economic growth disparities.
The findings of this study indicate that (1) There exists spatial and temporal variation in the index of economic institutional change in China. In general, there is a gradual increase from the temporal perspective, and spatially, there exists a gradient difference where the economic institutional change in the eastern region is better than in the central and western regions. (2) The structure of the spatial correlation network of China’s economic institutional change is relatively stable and constantly improving. The “net beneficial” and “bidirectional spillover” segments, primarily in the eastern coastal provinces, play a dominant role in the network, while the “net spillover” segments, mainly in the western and central provinces, benefit to a lesser extent. Further, the “agent” segments, mainly in the northeastern provinces, play a “bridge” and an “intermediary” role. (3) Regional differences in terms of China’s economic institutions changes have affected regional disparities in China’s economic growth. Specifically, first, regional disparity in a property rights system is a long-term and stable driving force for regional economic growth disparity. Second, regional disparity in opening up contributed significantly to regional economic growth disparity in the earlier periods covered by the study. Lastly, regional disparity in distribution patterns is a key influencing factor of regional economic growth disparity in the current stage.
Supporting information
S1 Fig.
Spatial distribution of China’s economic institutional change (a)1997 (b)2004 (c)2011 (d)2018.
https://doi.org/10.1371/journal.pone.0297354.s001
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S2 Fig.
Spatial linkage strength of economic institutional change in China (a)1997 (b)2018.
https://doi.org/10.1371/journal.pone.0297354.s002
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S1 Table. The economic institutional change of provinces and cities in China.
https://doi.org/10.1371/journal.pone.0297354.s003
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S2 Table. The analysis of centrality of provinces and municipalities across China.
https://doi.org/10.1371/journal.pone.0297354.s004
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References
- 1. Allen F, Qian J, Qian MJ. A review of China’s institutions. Annu Rev Financ Econ. 2019;11:39–64.
- 2. Xu CG. The fundamental institutions of China’s reforms and development. J Econ Lit. 2011;49(4):1076–1151.
- 3. Lau LJ, Qian YY, Roland G. Reform without losers: an interpretation of China’s dual‐track approach to transition. J Polit Econ. 2000;108(1):120–143.
- 4. Brandt L, Zhu XD. Redistribution in a decentralized economy: growth and inflation in China under reform. J Polit Econ. 2000;108(2):422–439.
- 5. Che JH. A dynamic model of privatization with endogenous post-privatization performance. REStud. 2009;76(2):563–596.
- 6. Khandelwal AK, Schott PK, Wei SJ. Trade liberalization and embedded institutional reform: evidence from Chinese exporters. Am Econ Rev. 2013;103(6):2169–95.
- 7. Lo D, Hong FH, Li GC. Assessing the role of inward foreign direct investment in Chinese economic development, 1990–2007: towards a synthesis of alternative views. Struct. 2016;37:107–120.
- 8. Xie ZH. The distribution system transformation is the core issue in economic system reform. J B Technol Bus Univ(Soc Sci). 2007;(01):1–6+21.
- 9. Whyte MK. Paradoxes of China’s economic boom. Annu Rev of Sociol. 2009;35:371–392.
- 10. Cao SX. Why China’s approach to institutional change has begun to succeed. Econ Model. 2012;29(3):679–683.
- 11. Zhang YA. A view from behavioral political economy on China’s institutional change. China Econ Rev. 2012;23(4):991–1002.
- 12. Yang YC, Song MN, Shi KB, Jin ST, Wang MM, Zhang WF. The spatial differentiation of urban transition in China with the model of gradual institutional changes. Sci Geogr Sin. 2016;36(10):1466–1473.
- 13. Wang Y, Zhang JX. The mechanism and effect of regional integration: an explanation of spatial development based on institutional distance. Econ Geogr. 2022;42(01):28–36.
- 14.
Veblen T. The Theory of the Leisure Class. 1st ed. New York: Rouledge; 1992.
- 15. Commons JR. Institutional economics. Am Econ Rev. 1936;26:237–249. https://www.jstor.org/stable/1807784.
- 16.
Galbraith J. American Capitalism. 1st ed. New York: Routledge; 1993.
- 17.
Coase RH. The nature of the firm. London: Macmillan Education UK; 1995.
- 18.
North DC. Institutions, Institutional Change and Economic Performance. Cambridge: Cambridge University Press; 1990.
- 19. Kornai J. Centralisation and the capitalist market economy. Econ Transit. 2012;20(4):569–591.
- 20. Greif A. Historical and comparative institutional analysis. Am Econ Rev. 1998;88(2):80–84. https://www.jstor.org/stable/116897.
- 21.
The new institutionalism in organizational analysis. Chicago: University of Chicago press; 2012.
- 22. Greif A, Laitin DD. A theory of endogenous institutional change. Am polit sci rev. 2004;98(4):633–652.
- 23. Zheng WB, Feng L. Conflicts and coordination in institutional changes—Review and discussions on the theoretical development. Econ Perspect. 2020;(01):83–97.
- 24. North DC. Institutions and economic growth: an historical introduction. World Dev. 1989;17(9):1319–1332.
- 25.
North DC, Thomas RP. The Rise of the Western World: A New Economic History. Cambridge: Cambridge University Press; 1973.
- 26.
Williamson OE. The economic institutions of capitalism. Firms, markets, relational contracting. Wiesbaden: Gabler; 2007.
- 27. Davis LS. Institutional flexibility and economic growth. J Comp Econ. 2010;38(3):306–320.
- 28. Easterly W, Levine R. Tropics, germs, and crops: how endowments influence economic development. JME. 2003;50(1):3–39.
- 29. Rodrik D, Subramanian A, Trebbi F. Institutions rule: the primacy of institutions over geography and integration in economic development. JEG. 2004;9:131–165.
- 30. Acemoglu D, Johnson S, Robinson J. The rise of Europe: Atlantic trade, institutional change, and economic growth. Am Econ Rev. 2005;95(3):546–579.
- 31. Kelejian HH, Murrell P, Shepotylo O. Spatial spillovers in the development of institutions. J Dev Econ. 2013;101:297–315.
- 32. Tian P, Liu Y, Li J, et al. Spatiotemporal patterns of urban expansion and trade-offs and synergies among ecosystem services in urban agglomerations of China. Ecol Indic. 2023;148:110057.
- 33. Ashraf J, Luo LQ, Khan MA. The spillover effects of institutional quality and economic openness on economic growth for the Belt and Road Initiative (BRI) countries. Spat Stat. 2022;47:100566.
- 34. Lothian JR. Institutions, capital flows and financial integration. J Int Money and Finance. 2006;25(3):358–369.
- 35. Alfaro L, Kalemli-Ozcan S, Volosovych V. Why doesn’t capital flow from rich to poor countries? An empirical investigation. Rev Econ Stat. 2008;90(2):347–368.
- 36. Krammer MS. Do good institutions enhance the effect of technological spillovers on productivity? Comparative evidence from developed and transition economies. Technol Forecast Soc Change. 2015;94:133–154.
- 37. Vargo SL, Akaka MA, Wieland H. Rethinking the process of diffusion in innovation: a service-ecosystems and institutional perspective. J Bus Res. 2020;116:526–534.
- 38. Sun B, Peng BY, Liu SS, Peng QP. Institutional distance, flow mode and cross-regional flow of talents. Sci Technol Manage Res. 2022;42(12):213–222.
- 39. Chen X, Yu Z, Di Q. Assessing the marine ecological welfare performance of coastal regions in China and analysing its determining factors. Ecol Indic. 2023;147:109942.
- 40. Tan JS, Yao FF. Grasp the connotation innovation of basic economic system completely and accurately. Contemp Econ Res. 2021;(08):43–50.
- 41. Zhang DG. Logic of economic institutional change and reform of China’s economic system. Academic Monthly. 2022;54(01):58–67.
- 42. Xu JY. The connotation and change of the basic socialist economic sysytem-Reflections on"building a high level socialist market economy sysytem’. Huxiang Forum. 2023;36(02):78–86.
- 43. Jin YG. Analysis on macro institution for China’s economic growth in 1984–1995. Stat Res. 1998;(05):14–16.
- 44. Wang J, Zou GP, Shi XJ. Impact of institutional change on China’s economic growth—An empirical study based on VAR model. China Ind Econ. 2013;(06):70–82.
- 45. Sachs JD, Woo WT. Understanding China’s economic performance. J Policy Reform. 2001;4(1):1–50.
- 46. Liu YC. Economic institutional reform or industrial structural promotion?—On core factor of Chinese economic growth and focus of the future reform. China Ind Econ. 2003;(09):5–13.
- 47. Qiang Q, Jian C. Natural resource endowment, institutional quality and China’s regional economic growth. Resour Policy. 2020;66:101644.
- 48. Zhang HX, Wang Y. Economic institutional changes, industrial structure evolution and high-quality growth of China’s economy. Reform Econ Syst. 2020;(02):31–37.
- 49. Young A. The razor’s edge: distortions and incremental reform in the People’s Republic of China*. Q J Econ. 2000;115(4):1091–1135.
- 50. Huang H. Institutional analysis of regional differences in China’s economic growth. Econ Geogr. 2013;33(01):35–40.
- 51. Liu YK, Kuang XM. Institution changes and regional economic growth: the empirical analysis basing on the data of Hunan province. Econ Geogr. 2012;32(01):25–29.
- 52. Anderson JE. The Gravity Model. Annu Rev Econ. 2011;3:133–160.
- 53. Nojiri S, Odintsov SD, Oikonomou VK. Modified gravity theories on a nutshell: Inflation, bounce and late-time evolution. Phys Rep. 2017;692:1–104.
- 54. Streeter CL, Gillespie DF. Social Network Analysis. J Soc Serv Res. 1992;16:201–222.
- 55. Chen X, Di Q, Jia W, et al. Spatial correlation network of pollution and carbon emission reductions coupled with high-quality economic development in three Chinese urban agglomerations. Sustain Cities Soc. 2023;94:104552.
- 56. Huang R, Xie CW, Lai FF, Li X, Wu GY, Phau I. Analysis of the Characteristics and Causes of Night Tourism Accidents in China Based on SNA and QAP Methods. Int J Env Res Pub He. 2023;20(3):2584. https://doi.org/10.3390/ijerph20032584.
- 57. Krackhardt D. Predicting with networks: Nonparametric multiple regression analysis of dyadic data. Social Netwks. 1988;10(4):359–381.
- 58. Wang XH, Yang YQ, Luo XY, Wen T. The Spatial Correlation Network and Formation Mechanism of China’s High-quality Economic Development. Acta Geogr Sin. 2022;77(08):1920–1936.
- 59. Fan M. Trend of Regional Inequality under Different Economic System. Econ Surv. 2004;(01):60–63.