Research on the Coordinated Development of Innovation Ability and Regional Integration in Guangdong–Hong Kong–Macao Greater Bay Area

Abstract

This paper selects the panel data of 11 cities in the Guangdong–Hong Kong–Macao Greater Bay Area (GHMA) from 2010 to 2020, calculates the Malmquist index of urban agglomerations to measure regional innovation, constructs the evaluation system of regional integration and measures the integration index. This paper conducts qualitative analysis and empirical research on the synergistic interaction between regional innovation and regional integration and examines the synergistic development between innovation capability and integrated development from theory and experience. The results show that from 2010 to 2020, the overall level of integration in the GHMA shows a rising trend, and the level of integration between regions has shown a narrowing trend since 2016. Regional innovation capacity is on the rise, and there is a clear gap between regions. Regional innovation ability has a positive impact on regional integration, which decreases first and then increases. Regional integration development has always played a strong role in promoting regional innovation. Accordingly, the regional integration process of Guangdong, Hong Kong, and Macao should be further promoted, and regional innovation should be improved through the regional integration process.

1. Introduction

In 2019, the National Development and Reform Commission issued the “Outline of the Development Plan for the Guangdong–Hong Kong–Macao Greater Bay Area (GHMA)”, which aimed at forming an economic development model driven by scientific and technological innovation in 2035 and strove to turn the GHMA into a world-class advanced first-class bay area. China is trying to turn the GHMA into an international first-class bay area and a world-class urban agglomeration. In June 2020, the GHMA launched a “cross-border wealth management” business pilot to form a FinTech cluster, aiming to use the innovative sharing diffusion mechanism to promote regional innovation capabilities, and to help the integration and high-quality development of the GHMA through inter-regional financial and innovation linkages. In 2021, the GHMA will create a GDP of about CNY 11.7 trillion, with a per capita GDP of 134,000, exceeding that of the Yangtze River Delta and the Beijing–Tianjin–Hebei region. China is actively promoting inter-regional cooperation in infrastructure, scientific and technological innovation, industrial upgrading, the ecological environment and market systems in the urban agglomerations of the GHMA, aiming to form a new path for cross-regional high-quality economic development and giving full play to the potential of joint governance by the government, market and environment. Relying on the institutional advantages of “one country, two systems,” the GHMA urban agglomeration has continuously improved the degree of regional openness. In the study of the integrated development of the GHMA, some scholars have pointed out that the integrated development process of the GHMA is relatively fast, and its key influencing factors include economic development, industrial agglomeration, technological innovation, trade development and energy transformation [1]. Qiu et al. [2] studied the characteristics and evolution process of the environmental governance cooperation network structure of the mega-urban agglomerations in the GHMA, summarized the spatial structure and agglomeration characteristics of the mega-urban agglomerations in the GHMA, and thus repositioned the development strategies of 11 cities. It is proposed that the four central cities of “Hong Kong, Macao, Guangzhou, and Shenzhen” should further improve the degree of industrial specialization, to have a positive external effect, drive the development of marginal cities and form the layout of the center driving the edge. From the perspective of collaborative development, this paper analyzes the urban agglomeration in the GHMA, mainly including the research on the mechanism of sharing and cooperation [3], the measurement of integration level [4], etc., and points out that we should pay attention to the integration of production factors, the integration of system integration and the integration of all-round integration, and reasonably realize the evolution of the three stages to form the mechanism of collaborative development of urban agglomeration in the GHMA [5]. We can find that most of the research on the integration level of the GHMA is based on the research of coordination mechanisms, and studies of the economic development or circulation between cities. For the measurement of the integration level of urban agglomerations, most scholars focus on the integration of urban agglomerations in the Yangtze River Delta, the Yangtze River Economic Belt or the Beijing–Tianjin–Hebei region. Liu et al. [6] use network analysis and interlocking network models to measure the mobility, connectivity and boundary effects between cities in the Yangtze River Economic Belt. At present, there are relatively few studies focusing on the integrated development of the GHMA. Because of the regional innovation of the GHMA, some scholars have started from the factors driving the innovation ability, constructed the evaluation system of the innovation-driving ability of the urban agglomeration, and measured the innovation-driving ability of 11 cities in the GHMA [7]. However, another question remains: how does regional innovation interact with the level of regional integration? Are they related? Related research needs to be further improved.

In 2010, the governments of Guangdong, Hong Kong and Macao jointly formulated the “Key Action Plan for the Construction of Livable Bay Area around the Pearl River Delta” to implement the above cross-border regional cooperation. In view of the complementary characteristics of the three advantageous industries of Guangdong, Hong Kong and Macao, the cooperation of Guangdong, Hong Kong and Macao at this stage takes the service industry as the main content, especially in the field of producer services. Based on this, this paper selects the Hong Kong Special Administrative Region, the Macao Special Administrative Region and 9 cities in the Pearl River Delta of China’ s GHMA from 2010 to 2020, forming a panel data of 11 cities.

The research objective is to measure the regional innovation, examine the correlation between the level of regional integration and regional innovation in GHMA, clarify the channel mechanism of regional innovation driving the development of Guangdong–Hong Kong–Macao integration and reveal the interactive mechanism of regional integration and regional innovation capability over the next 25 years. The GHMA is one of the four major bay areas in the world, along with the New York Bay Area, San Francisco Bay Area and Tokyo Bay Area. The research on the regional innovation capability and regional integration of the GHMA has important theoretical significance for the international community.

The novelty of this paper is that it constructs an evaluation index system for the integrated development of the GHMA from the five dimensions of open integration, economic integration, industrial integration, infrastructure integration and institutional integration to measure its integration level; establishes panel VAR model to investigate the convergence of the lag effect and the influence of regional innovation and the integration of Guangdong–Hong Kong–Macao, revealing the interaction mechanism between the integration of GHMA and regional innovation capability; expands the research on regional innovation and integration; and provides a reference for the policy framework driving the integrated development of the GHMA. This study uses various indicators to calculate the level of Guangdong–Hong Kong–Macao integration and the modeling relationship between regional integration and regional innovation.

2. Literature Review

2.1. Measurement of Integration Level and Regional Innovation Capability of GHMA

2.1.1. Integration Level of GHMA

The existing research includes less quantitative research on the integrated development of the GHMA. The existing research has analyzed the financial integration, market integration, industrial integration and transportation integration of the GHMA. The measurement methods include the principal component analysis method, F-H model, “relative price” and other single index measurements, and less from the GHMA as a whole. The development level of integration in the GHMA is summarized and analyzed [8,9,10,11]. According to the “center-edge” theory, the development of central cities drives the development of marginal cities to achieve cross-regional coordinated development, which is the premise and an important basis for the integrated development of the GHMA [12]. Taking into account the development characteristics and advantages of urban agglomerations, integrated development should reflect the practice of multi-space, diversification, multi-factor and multi-path. In the research on the measurement and evaluation of the integration level of Guangdong, Hong Kong and Macao, the existing research on the measurement of regional integration mainly analyzes the flow data in the integration process and the integration results of regional economic development, price level and industrial change [2]. For example, Zeng et al. [13] analyzed the trend of the integration results of the Yangtze River Delta and analyzed the actual output distribution of the urban agglomeration to identify the important impact of the system and market on the integration. Obasaju et al. [14] analyzed the process of regional economic integration based on the integration process, big data, and traffic data from three aspects: enterprise, information, and transportation. Some scholars use the inter-city consumption flow data and the modified boundary effect model to identify the important influencing factors of regional integration and analyze the inter-provincial and urban boundary effects created by the distribution of urban agglomerations in the GHMA from multiple dimensions, such as the flow of resource elements, the industrial division of labor, institutional arrangements and policy coordination [15]. König & Ohr [16] compiled the EU integration index to measure the integration process. We draw on the above research and ideas as the theoretical basis, synthesize the evaluation indicators selected by existing scholars and the availability of data, take into account the connotation and characteristics of the integration of the GHMA and construct an integrated index system of the GHMA, which includes five secondary indicators: open integration, economic integration, industrial integration, infrastructure integration and institutional integration. The entropy weight method is used to obtain the index weight as shown in

Table 1. Guangdong–Hong Kong–Macao integration development index system.

Secondary Indicators	Third-Level Indicators	Measure Description	Weight
Market integration	Labor market openness	Average wage/GDP	0.0429
	Trade openness	Gross import and export value/GDP	0.0471
	Technology market activity	The per capita technical market turnover of researchers	0.0474
	Population mobility intensity	Total passenger volume/total population	0.0388
Economic integration	Foreign direct investment	FDI/GDP	0.0693
	Relative price index	Per capita wage/GDP	0.0422
	Capital flow intensity	Financial institutions’ loan amount/total population	0.0483
	Economic growth	Per capita GDP growth rate	0.0691
Industrial integration	Industry isomorphism coefficient	Division index: $S_i={\displaystyle \sum _{i=1}^n\left|\frac{q_{jk}}{q_j}-\frac{q_{ik}}{q_i}\right|}$	0.0456
	Industrial agglomeration	The space Gini coefficient: $Gini={{\displaystyle {\sum }_{ik}(s_{ik}-x_i)}}^2$	0.0648
	Industry expansion intensity	Average annual added value of the three industries	0.0584
	Industrial structure deviation	$R_i={\displaystyle \sum _i\left|\frac{q_{jk}/Q_j}{q_{ik}/Q_i}-1\right|}$	0.0486
Infrastructure integration	Road traffic	Road network density per unit area	0.0484
	Port construction	Port container throughput	0.0695
	New infrastructure and applications	5G, big data, cloud computing, blockchain, and other new infrastructure investment/GDP	0.0697
	Environmental infrastructure	Sewage treatment, waste treatment infrastructure investment/GDP	0.0397
Institutional integration	Financial capacity	Government revenue/GDP	0.0481
	Degree of public service sharing	Number of public service cooperation areas achieved	0.0454
	Public service level	Basic public service funds/GDP	0.0567
	Intellectual property protection	Degree of intellectual property protection	0.0429

Note: i denotes area; k denotes industry; q_ik represents the output value of k industry in region i; q_jk represents the average output value of k industries in 11 cities in the GHMA; s_ik is the proportion of employment in industry k of the city i in employment in the industry; x_i is the proportion of employment in Region i to that in 11 cities in the GHMA; Q_i represents the number of people employed in industry k in region i, and Q_j represents the average number of people employed in industry k in the 11 cities in the greater bay area.

. Among them, the industry isomorphism coefficient is a negative indicator, and other indicators are positive indicators.

However, under the new pattern, the GHMA may have an unclear division of labor, which in turn reduces the efficiency of resource allocation and restricts the integrated development of the GHMA to a certain extent. At the same time, the new coronavirus pandemic has had a certain impact on the integrated development of the GHMA. The regional development strategy presents different levels and divisions. In the process of targeting cities, unfair competition and resource inequality may be derived, hindering the flow of funds and resources between regions. As a result, the actual development of the GHMA cannot fully achieve the policy effect, affecting the integration of the GHMA strategic positioning and goal realization. We should make use of the competitive advantages brought about by technological innovation to build an international industrial agglomeration center, break the resource and environmental constraints under market segmentation and accelerate the flow of innovation elements and the formation of innovation activities. Urban agglomeration has a rich variety of production factors. It plays a linkage effect from multiple dimensions, such as the policy system, industrial structure, economic development, talent agglomeration, and green ecology, and forms an important foundation for the innovative development of regional integration of urban agglomeration.

2.1.2. Regional Innovation Capability of Guangdong, Hong Kong, and Macao

The Malmquist index is defined by the input–output distance function, which reflects the allocation of input resources in the innovation system of the GHMA from multiple perspectives to measure the regional innovation. According to the “rule of thumb”, we select the full-time equivalent of scientific and technological personnel and R&D expenditure as input indicators and select the sales income of new products and the total number of effective invention patents as output indicators. Then, we add the time factor to achieve dynamic analysis of regional innovation and calculate the ratio of the input distance function and output distance function. Based on the assumption that returns to scale remain unchanged, the non-parametric DEA method is used to measure the change in total factor productivity, forming the combined effect of technical efficiency change and technological progress [17,18,19,20,21].

2.2. The Mechanism of Regional Innovation Promoting the Integration of Guangdong, Hong Kong, and Macao

2.2.1. Promoting Interregional Open Cooperation

The development concept of innovation coordination, openness and sharing formed in the process of regional innovation is an important principle to guide the high-quality integrated development of the GHMA [22]. The development of innovation platforms enables cities to tap into consumption power and tendencies, identify new demands and improve the accuracy and efficiency of technological innovation using technologies such as big data, cloud computing and artificial intelligence, thereby promoting open cooperation between regions [23]. In the study of the integrated development of the Yangtze River Delta, Chen et al. [24] studied the integrated spatial agglomeration of the Yangtze River Delta and pointed out that the cooperation of regional products can realize the relationship of economic integration, mutual benefit and win-win, deepening cooperation so that the Yangtze River Delta region can realize the new business model of service industry and promote the integrated development of high quality. Innovation drives regional economic development and promotes the economic integration of the GHMA [5].

2.2.2. Promoting Industrial Agglomeration

According to the theory of the industrial division of labor and the theory of innovative industrial agglomeration, there are certain rules in social production. With the improvement of regional innovation, the opportunities for financial institutions, government departments and multi-industry development exchanges are increasing. In recent years, the GHMA has actively built demonstration zones for scientific and technological innovation and collaborative innovation [25]. According to the theory of planned behavior, in relation to the urban agglomeration of the GHMA and the regional overall industrial planning layout, the sub-administrative regional government is a relatively passive planning executor, using the production factors to play the scale effect [26].

According to the theory of new structural economics, the improvement of regional innovation can avoid regional innovation polarization to a certain extent, achieve fair resource allocation and provide a more suitable environment, thus driving the industrial upgrading mechanism. The coordinated development pattern of financial institutions and technological innovation capabilities has led to widespread use of cloud computing technology and blockchain technology in the urban agglomeration of GHMA, realizing industrial integration and agglomeration of industries and regions and promoting the integrated development of Guangdong, Hong Kong and Macao [8].

2.2.3. Adjusting Endowment Structure

Division, competition, and cooperation are the core elements of regional integration. According to the growth screening and guidance (GIFF) framework, the development goal of economic integration includes the similarity of factor endowment structure. The adjustment of the natural endowment structure promotes the transfer and sharing of resource information and strengthens the management and transfer of elements. From the perspective of institutional endowment structure, the GHMA actively builds top-level e-government services and builds digital government, thus forming an integrated governance model. Through the establishment of an “innovative government service “platform, the level of government services and governance in the GHMA urban agglomeration has been rapidly improved, the docking process between the government and the market has been deepened, and a long-term symbiotic and compatible relationship channel for inter-regional industrial innovation and development has been created [8]. By adjusting the attached structure, the GHMA has innovatively integrated into the “internal cycle “of the national economy [7].

Therefore, we propose the following hypothesis:

Hypothesis 1. 

Regional innovation capability promotes the integration of Guangdong, Hong Kong and Macao.

2.3. The Formation Mechanism of Regional Innovation Ability Promoted by the Integration of Guangdong, Hong Kong and Macao

Under the “one country, two systems”, the diversity and complementarity of the system form the driving force for regional innovation in the GHMA. We should further expand the influence of scientific and technological innovation in the GHMA, improve the efficiency and quality of innovation and improve the degree of digitization in the context of the construction of the “Digital Bay Area” to build a “New Smart Bay Area”.

2.3.1. Expanding the Influence of Scientific and Technological Innovation

The influence of scientific and technological innovation is the key embodiment of regional innovation ability, and it plays an important role in the transformation of scientific and technological innovation achievements and the cooperation and exchange between subjects. The bottleneck of the influence of scientific and technological innovation in the GHMA may lie in the shortage of key elements in some less developed cities, such as Zhaoqing and Jiangmen. The shortage of innovation platforms makes it difficult to undertake or match the innovation of central cities due to the lack of media for achievement transformation. The urban agglomerations in the GHMA have unbalanced economic development among some regions. The financial resources, geographical location and infrastructure of the Hong Kong and Macao Special Administrative Regions are different from those of other mainland cities, making the basic elements of regional innovation different and showing a more obvious ladder [27]. Technology is an important basis for the formation of regional innovation. From the perspective of the supply side, the GHMA docks the international development strategy while Guangzhou, Shenzhen and Hong Kong form a science and technology innovation corridor to meet innovation needs. Guangzhou has also formed a platform with innovative competitive advantages and a support system. Relying on the “Hong Kong and Macao” international development advantages, the formation of inter-regional comprehensive economic partnership has institutional advantages. The GHMA actively shapes a new development pattern, thereby accelerating the construction of innovation centers in the GHMA [28]. The regional integration process of Guangdong, Hong Kong, and Macao promotes the improvement of the service function of the asset market by continuously optimizing the spatial layout of innovation cooperation, especially the opening of capital empowerment and asset services, expanding the influence of scientific and technological innovation, realizing effective distribution and technology use and building a high-standard factor market system. Singh [29] revealed the direct positive effect of cross-regional knowledge integration on innovation quality and the positive interaction effect of cross-regional knowledge integration and distributed R & D on innovation quality. Mukhametdinov [30] established an integrated analytical framework based on the theory of pluralistic integration and studied the EU by using criteria such as economic interdependence, economic convergence, intra-group size and interest asymmetry, cultural diversity and geostrategic motives. United Nations [31] focused on the four pillars of ESCAP’s strategy of deepening regional cooperation and integration and made recommendations on how to strengthen market integration, improve connectivity, and increase investment in infrastructure development to achieve synergies and make a significant contribution to the realization of the 2030 Agenda for Sustainable Development.

As a result, the GHMA has formed world-class innovation demand momentum and supply capacity, providing important opportunities for regional innovation. Under the framework of integrated development, GHMA has built and opened up big data centers and market access has attracted private capital so that more investors can participate in regional innovation and enhance regional governance capacity and vitality.

2.3.2. Improving the Efficiency and Quality of Innovation

Innovation efficiency and quality reflect the practical application of regional innovation. To some extent, the quality of innovation can be demonstrated by cost change trends. With the improvement of the integration of the GHMA, specialized industrial clusters have formed a resource agglomeration pattern aiming at technological innovation [32]. Areas far away from the central cities of the GHMA may have the advantages of low labor costs and low land costs. The integration process can expand market potential, achieve cost-effective industrial integration processes and create conditions for creating a higher level of regional innovation. The integration of the GHMA can enhance the innovation efficiency and quality of the region by enhancing the global allocation of regional innovation resources. It can also consolidate the global status of the GHMA and provide more resources for promoting steady economic growth and industrial upgrading. The domestic and international dual circulation can further smooth the flow of innovation resources in the region and contribute to regional innovation while serving the sustainable economic development of the GHMA. Sinha [33] conducted a study of 24 Asian countries to develop sustainable development goal-oriented policy frameworks. Using a phased approach to policy implementation, the approach to achieving sustainable development goals was discussed.

2.3.3. Advancing Digital Technology

The application of digital technology is an important factor in the rapid improvement of regional innovation capability [34]. The use of digital technology reduces the transmission cost of innovative achievements, and the threshold of imitation of innovative technology is gradually eliminated, making new knowledge acquisition more convenient. In the context of the integrated development of Guangdong, Hong Kong, and Macao, six digital economy innovation and development pilot zones, such as the Guangdong Province, have been launched. At the same time, various regions are actively exploring the establishment of a dialogue mechanism between the government and enterprises, exploring new regulatory frameworks through cooperation, creating a better governance framework, establishing data sharing and implementing multi-sectoral data sharing systems to develop regional innovation capabilities. The integration trend of Guangdong, Hong Kong and Macao has improved the degree of information matching, strengthened the function of platform media and helped the innovation demand achieve deep docking to stimulate individual innovation activities in a wide range, with the advantages of low cost and high efficiency. With the improvement of the integration of Guangdong, Hong Kong and Macao, the degree of information symmetry between regions increases, which promotes the development of regional innovation. Digital technology is conducive to matching the supply and demand information of regional innovation. More emerging technologies and innovation projects have attracted the attention of investors to build a multi-level innovation enterprise incubation and promotion mechanism, as well as to build a mutually beneficial symbiotic industrial ecosystem such as innovation factor and financial technology enterprises [35,36]. Therefore, the integrated development of the GHMA can improve the efficiency and ability of regional innovation through the development of digital technology and accelerate the process of transformation.

Therefore, we propose the following hypothesis:

Hypothesis 2. 

Guangdong–Hong Kong–Macao integration promotes regional innovation capability by ex-panding the influence of scientific and technological innovation.

3. Research Methods and Data Sources

3.1. Research Object

The “Study on the Coordinated Development Planning of the Greater Pearl River Delta Urban Agglomeration”, completed in 2009, listed the “Bay Area Development Plan” as a part of the overall spatial layout coordination plan and proposed four follow-up works, namely cross-border transportation cooperation, cross-border regional cooperation, ecological environment protection cooperation and coordination mechanism construction. In 2010, the governments of Guangdong, Hong Kong and Macao jointly formulated the “Key Action Plan for the Construction of Livable Bay Area around the Pearl River Delta “to implement the above cross-border regional cooperation. The 2016 government work report of Guangdong Province also includes the content of “carrying out the Pearl River Delta urban upgrading action and jointly building the GHMA”. The map of urban agglomerations in the GHMA is shown in Figure 1.

3.2. Variable Selection and Data Sources

3.2.1. Regional Innovation Capability (lnDF)

The Malmquist index can be calculated based on the quantitative data of input and output, providing a breakdown of productivity changes and thereby providing different sources of change. There is no need to use standardized measurement units for the variables involved in its calculation. Therefore, the index is used to calculate regional innovation capability. The Malmquist index of 11 cities in the GHMA is used as the variable of regional innovation.

3.2.2. Integration Level of the GHMA (lnITG)

The integration level of 11 cities in the GHMA is measured using the established index system for the integration development of the GHMA. In the process of evaluating the level of integrated development of urban agglomerations, to balance the index differences of existing research, the above variables were logarithmically processed and standardized, and the evaluation results were used as integration-level variables.

The GDP data of nine cities in the Pearl River Delta region come from the statistical yearbook of the city calendar year, and the GDP data of Hong Kong and Macao come from the World Bank data network [37]. The GDP data are calculated in the 2010 constant dollar, and the annual average exchange rate is further used to convert into RMB units. Other data are derived from the “China GHMA Thematic Study Report”, the Hong Kong–Macao Statistical Yearbook, the “China Regional Innovation Capability Report”, the website data of the Hong Kong Statistical Department, the statistical data of the Macao Statistical Bureau, the statistical yearbook of science and technology over the years and the website data of the Urban Statistics Bureau.

The Malmquist index concerning technology T_t in period t is expressed as:

$$M_t=\frac{D_t(X_{t+1},Y_{t+1})}{D_t(X_t,Y_t)}$$

(1)

where X is the input quantity; Y is the output; similarly, the Malmquist index constructed concerning technology T_t+1 in the t + 1 period is expressed as:

$$M_{t+1}=\frac{D_{t+1}(X_{t+1},Y_{t+1})}{D_{t+1}(X_t,Y_t)}$$

(2)

The Malmquist productivity index, which measures productivity changes from period t to period t + 1, measures regional innovation, namely

$$M_{t,t+1}={[\frac{D_t(X_{t+1},Y_{t+1})}{D_t(X_t,Y_t)}\times \frac{D_{t+1}(X_{t+1},Y_{t+1})}{D_{t+1}(X_t,Y_t)}]}^{1/2}$$

(3)

Further decomposed into technical change index (PTE) and efficiency improvement index (SE):

$$PT{E}_{t,t+1}={[\frac{D_t(X_{t+1},Y_{t+1})}{D_{t+1}(X_{t+1},Y_{t+1})}\times \frac{D_t(X_t,Y_t)}{D_{t+1}(X_t,Y_t)}]}^{1/2}$$

(4)

$$S{E}_{t,t+1}=\frac{D_{t+1}(X_{t+1},Y_{t+1})}{D_t(X_t,Y_t)}$$

(5)

3.3. The Gray Correlation Coefficient Analysis

Gray correlation coefficient analysis can determine whether the variables are related and determine the degree of correlation between variables. Referring to the results of Liu et al. [38], the gray correlation coefficient is established to measure the correlation between regional innovation and the integration level of Guangdong–Hong Kong–Macao and analyze the evolution trend of the development between the two systems. The model is expressed as:

$${\delta }_i=\alpha {\theta }_i+(1-\alpha ){\gamma }_i,\alpha \in [0,1]$$

(6)

Among them, ${\delta }_i$ is the gray comprehensive correlation degree, ${\gamma }_i$ is the gray relative correlation degree, and $\rho$ is the resolution coefficient, which is generally 0.5. Referring to the existing research on the setting of correlation interval, when 0 < ${\delta }_i$ ≤ 0.35, the correlation degree is low; when 0.35 < ${\delta }_i$ ≤ 0.65, the correlation degree is medium; when 0.65 < ${\delta }_i$ ≤ 0.85, the correlation degree is high; when 0.85 < ${\delta }_i$ ≤ 1, the correlation degree is very high [1].

3.4. Panel VAR Model

The regional integration variables and regional innovation variables in the system are regarded as endogenous variables to explore the dynamic changes in variables. Set the GMM model to:

$$y_{it}={\alpha }_i+{\beta }_0+{\displaystyle {\sum }_{j=1}{\beta }_j{y}_{i,t-j}+{\mu }_t+{\epsilon }_{it}}$$

(7)

Among them, y_it is the column vector of the logarithm of the regional integration index (lnITG_it) and the logarithm of the regional innovation capability (lnDF_it). i represents the city; t represents the year;${\alpha }_i$is the spatial effect vector;${\mu }_t$is the time effect vector;${\epsilon }_{it}$is the interference term; j is the lag order.

4. Empirical Results and Analysis

4.1. Analysis of Integration Development Level and Regional Innovation Ability of GHMA

4.1.1. Guangdong–Hong Kong–Macao Integration Development Index

According to the index weight and index measurement of the regional integration development index system, the integrated index of 11 cities in the GHMA and five indexes of market integration, economic integration, industrial integration, infrastructure integration and institutional integration can be obtained. The integrated development index of 11 cities in the GHMA is shown in

Table 2. Ranking of Integration Level of GHMA in 2020.

City	2010	2011	2012	2013	2014	2015	2016	2017	2018	2019	2020
Hong Kong	0.342	0.401	0.460	0.519	0.578	0.637	0.670	0.646	0.708	0.773	0.801
Macao	0.286	0.297	0.335	0.391	0.416	0.542	0.574	0.579	0.635	0.644	0.713
Guangzhou	0.242	0.303	0.337	0.396	0.516	0.655	0.687	0.689	0.696	0.713	0.726
Foshan	0.276	0.347	0.317	0.392	0.342	0.371	0.403	0.454	0.478	0.489	0.519
Shenzhen	0.320	0.361	0.402	0.493	0.584	0.625	0.691	0.728	0.733	0.789	0.804
Zhuhai	0.358	0.401	0.424	0.447	0.410	0.463	0.481	0.549	0.577	0.625	0.638
Huizhou	0.279	0.302	0.360	0.380	0.393	0.419	0.424	0.487	0.493	0.527	0.553
Dongguan	0.323	0.348	0.352	0.411	0.423	0.434	0.452	0.485	0.515	0.480	0.592
Zhongshan	0.365	0.377	0.386	0.394	0.355	0.375	0.356	0.396	0.427	0.457	0.478
Jiangmen	0.322	0.331	0.382	0.438	0.458	0.446	0.458	0.498	0.505	0.558	0.621
Zhaoqing	0.308	0.332	0.316	0.412	0.416	0.432	0.399	0.423	0.431	0.496	0.532

. On the whole, from 2010 to 2020, the degree of integration of the GHMA has gradually soared in recent years. This shows that the level of integration of Guangdong–Hong Kong–Macao has continuously improved, the market system has been opened in an orderly manner, and a new system of opening to the outside world has gradually formed. Therefore, the sub-indicator integration index has generally shown an increasing trend in recent years. Based on the internal structure of the cities in the GHMA, there are certain differences in the development between regions. The four central cities of Hong Kong, Macao, Guangzhou and Shenzhen have a high level of integration. By 2016, the integration level of the central cities had become more and more different from other cities, and the polarization characteristics were significant. From 2016 to 2020, the integration level of central cities continued to improve, but the difference in integration level compared to that of other surrounding cities decreased, and the overall performance was stable.

From the perspective of development integration, Hong Kong and Shenzhen have a higher degree of openness, leading the GHMA urban agglomeration. Shenzhen has a high degree of openness to the outside world and has become one of the most active regions in the mainland market. At the same time, the trade services in the GHMA are more convenient, and the ability of urban agglomerations to attract foreign investment is constantly improving. Zhaoqing and Jiangmen and other cities are relatively backward in the degree of openness, but they are showing strong development potential. In recent years, the degree of openness increased steadily. From the analysis of the performance of market opening, Shenzhen, Dongguan and other cities have a high level of technology market development, are forming an international, comprehensive, and open industrial base and effectively play a leading role in other cities. Technological openness in Hong Kong and Macao has increased in recent years but has not yet formed a technological innovation-driven economic development model. The technology spillover effect of the GHMA is the focus of further improvements to openness in the future. The openness of the labor market in the GHMA does not show convergence in different regions. As an international financial center, Hong Kong has a strong ability to absorb talent and a highly open labor market. The labor market in Jiangmen, Zhaoqing and other regions has developed steadily; the labor market in Macao and other regions is relatively stable. Therefore, the degree of open integration of the GHMA has significantly improved in recent years. From the perspective of economic integration and from the perspective of economic growth, the overall economic development of the urban agglomeration in the GHMA shows a trend of rapid development, thus creating a new high-quality and efficient growth pole.

From the perspective of the relative price index, which measures market integration, the GHMA should further realize the free flow of products and factors. From the perspective of capital flow, the capital flow intensity of the GHMA is relatively high. The reason for this may be that the GHMA actively promotes the digitization of financial services, thereby creating diversified financial formats and improving the interoperability of financial products in urban agglomerations. At the same time, many cities (such as Shantou) actively promote the construction of international financial centers, aiming to become sub-central cities.

From the perspective of industrial integration, the industrial agglomeration index of the GHMA needs to be further improved. Guangdong needs to build an automobile industry cluster, as Hong Kong’s electronic industry development is better. In general, the proportion of the secondary industry in the urban agglomeration of the GHMA is slightly higher than that of the tertiary industry, and the industrial structure of different cities is different. However, it should be noted that the urban agglomerations in the GHMA have the characteristics of industrial isomorphism.

From the perspective of infrastructure integration, the level of transportation integration in the GHMA has increased significantly in recent years, and the density of transportation networks has increased rapidly, thus accelerating the process of regional integration. The GHMA has formed a relatively developed transportation network as a whole, promoted the free flow of factor endowments, used the urban brain to enhance the system governance capabilities of transportation and tourism and promoted the integrated level of the GHMA.

From the perspective of institutional integration, the level of institutional integration of Guangdong, Hong Kong and Macao has continuously improved in recent years and has been significantly enhanced from the aspects of institutional arrangements, policy coordination and financial capacity. There are some differences in the level of institutional integration between regions. With the continuous improvement of public service, the overall level of public services in the Greater Bay Area has increased rapidly.

4.1.2. Innovation Capability Analysis of GHMA

The Malmquist index of 11 cities in the GHMA from 2010 to 2020 has been measured, and the ranking of the innovation ability of urban agglomerations in the GHMA in 2020 is shown in

Table 3. Ranking of innovation capability of GHMA urban agglomeration in 2020.

City	Total Factor Productivity (DF)	Technology Change Index (PTE)	Efficiency Improvement Index (SE)
Hong Kong	0.650	0.846	0.768
Macao	0.444	0.639	0.695
Guangzhou	0.617	0.689	0.896
Foshan	0.489	0.654	0.748
Shenzhen	0.721	0.898	0.803
Zhuhai	0.711	0.849	0.837
Huizhou	0.524	0.687	0.763
Dongguan	0.652	0.745	0.875
Zhongshan	0.356	0.596	0.597
Jiangmen	0.358	0.598	0.598
Zhaoqing	0.299	0.563	0.531
Average value	0.529	0.706	0.737

. From the perspective of the overall innovation of each region, the urban agglomerations in the GHMA have made achievements in scientific and technological progress in many fields and have continuously formed the first-mover advantage of integrated development of innovation and economic integration. Around the central cities such as Hong Kong, Shenzhen, and Zhuhai, there is a great demand for economic integration and industrial agglomeration. Therefore, urban agglomerations actively build organizational management mechanisms and jointly develop scientific and technological innovation projects to achieve collaborative innovation. Therefore, with the coordination and linkage of regional scientific and technological innovation, the central city actively builds an information and technology trading platform, thus promoting the sharing of scientific and technological achievements such as patents among regions. For example, Shenzhen and Dongguan actively explore the strategy of scientific and technological innovation to support urban development, improve the corresponding measures and supporting policies, encourage multi-agent participation in collaborative innovation and improve the efficiency of resource allocation to improve the regional innovation.

From the technical change index, the technical change index of the GHMA urban agglomeration is higher. Urban agglomerations actively set up science and technology innovation vouchers and contribute to interregional technology exchange and sharing. The flexible talent flow system between Hong Kong and Guangdong has been gradually improved, thus deepening innovation. Central cities such as Hong Kong and Shenzhen first form strong innovation and radiate to the surrounding areas to improve the overall level of regional technological innovation, achieve complementary advantages and coordinated linkage between regions and actively build a Guangdong–Hong Kong–Macao science and technology innovation circle. From the perspective of efficiency improvement, the economic development level of Jiangmen, Zhaoqing and other peripheral cities in the GHMA urban agglomeration is relatively weak, and the degree of industrial agglomeration is low, so the attraction of population, capital and technology is relatively weak. Therefore, there is a certain gap in the efficiency improvement of the central city.

4.2. Synergy Measurement of Regional Integration and Urban Regional Innovation Capability

The changing trend of the absolute value, relative value, and comprehensive value of the gray correlation coefficient between the level of Guangdong–Hong Kong–Macao integration (lnITG) and regional innovation (lnDF) from 2010 to 2020 are shown in

Table 4. The gray correlation coefficient between regional integration level and innovation ability of Guangdong, Hong Kong and Macao from 2010 to 2020.

Year	Absolute Value	Relative Value	Composite Value	Year	Absolute Value	Relative Value	Composite Value
2010	0.534	0.811	0.673	2016	0.600	0.686	0.643
2011	0.531	0.818	0.675	2017	0.680	0.749	0.715
2012	0.533	0.806	0.670	2018	0.468	0.721	0.595
2013	0.546	0.794	0.671	2019	0.562	0.798	0.680
2014	0.630	0.741	0.685	2020	0.610	0.841	0.726
2015	0.696	0.705	0.700	-	-	-	-

.

From the results of Table 3, the integration of the GHMA is closely related to regional innovation, and the two are highly correlated. The degree of correlation between the level of regional integration and regional innovation of Guangdong, Hong Kong and Macao is in the middle and high range. It was relatively stable from 2010 to 2013. It rose rapidly to 0.680 in 2014–2017 and then fell to 0.468. After that, it rose steadily and showed a trend of fluctuation. From the relative value, the correlation between the two is high. From the comprehensive value, in 2010–2020, most years showed a high degree of correlation. For example, in 2015, 2017, and 2020, the comprehensive correlation degree was higher than 0.7, and a few years showed a moderate degree of correlation. There is a high correlation between regional integration and regional innovation.

4.3. Stability Test and Causality Test

4.3.1. Stationarity Test of Variables

Firstly, the stability test is carried out to avoid the occurrence of spurious regression. The LLC test and Fisher’s test are used to enhance the reliability of the test. According to the test results of

Table 5. Stability test.

Variables	LLC		Fisher-ADF		Conclusion
	Statistics	p-Value	Statistics	p-Value
lnITG	−17.947	0.0000	222.758	0.0000	Stable
lnDF	−18.983	0.0000	156.265	0.0000	Stable

, the panel sequence is stationary.

4.3.2. Granger Causality Test

The Granger method is used to test the causality between lnITG and lnDF, and the regional innovation index is further decomposed into the technical change index (PTE) and efficiency improvement (SE) for the Granger causality test. The test results are shown in

Table 6. Granger causality test.

Variables	Null Hypothesis	Statistical Test	Conclusion
lnITG-lnDF	lnITG is not the Granger cause of lnDF	10.623 ***	Reject the null hypothesis
lnPTE-lnDF	lnPTE is not the Granger cause of lnDF	9.386 ***	Reject the null hypothesis
lnSE-lnDF	lnSE is not the Granger cause of lnDF	13.492 ***	Reject the null hypothesis
lnDF-lnITG	lnDF is not the Granger cause of lnITG	13.274 ***	Reject the null hypothesis
lnDF-lnPTE	lnDF is not the Granger cause of lnITG	7.693 ***	Reject the null hypothesis
lnDF-lnSE	lnDF is not the Granger cause of lnSE	6.938 ***	Reject the null hypothesis

Note: *** is significant at 1%.

.

From the test results of Table 5, it can be seen that there is a two-way interactive Granger causality between the integration level of the GHMA and regional innovation. From the sub-indicators of regional innovation, the technological index and the efficiency index also show a significant Granger causality with the integration level of the GHMA. Therefore, there is a synergistic correlation between the two, and a panel VAR model should be established to analyze the interaction between the two.

4.4. Panel VAR Model Results Analysis

Using the GMM estimation method to explore the interaction between the integration of the GHMA and regional innovation. First, we determine the optimal lag order. According to the BIC information criterion, the optimal lag order is determined to be 5, and the VAR model estimation results are shown in

Table 7. Estimation results of panel VAR model based on the GMM method.

Type	Variable	Coefficient	Variable	Coefficient
lnITG equation	L1_h_lnITG	0.636 (2.838) **	L1_h_lnDF	0.536 (5.325) ***
	L2_h_lnITG	0.202 (6.378) ***	L2_h_lnDF	0.454 (2.361) **
	L3_h_lnITG	0.150 (5.793) ***	L3_h_lnDF	0.319 (4.745) ***
	L4_h_lnITG	0.084 (2.046) **	L4_h_lnDF	0.375 (2.083) **
	L5_h_lnITG	0.054 (2.769) **	L5_h_lnDF	0.439 (2.021) **
lnDF equation	L1_h_lnITG	0.545 (4.678) ***	L1_h_lnDF	0.578 (6.735) ***
	L2_h_lnITG	0.491 (3.498) ***	L2_h_lnDF	0.351 (3.904) ***
	L3_h_lnITG	0.333 (2.164) **	L3_h_lnDF	0.215 (3.256) ***
	L4_h_lnITG	0.216 (3.858) ***	L4_h_lnDF	0.244 (2.826) **
	L5_h_lnITG	0.149 (2.295) **	L5_h_lnDF	0.289 (2.043) **

Note: *** and ** are significant at 1% and 5% respectively.

.

According to the results of Table 7, first of all, from the perspective of the impact of the lag term of the two variables on themselves, lag term 5 of the integration of the GHMA and lag term 5 of the regional innovation have positive effects on the current period. The coefficients are 0.636, 0.202, 0.150, 0.084, 0.054 and 0.578, 0.351, 0.215, 0.244 and 0.289, respectively, showing a self-enhancement mechanism. The positive effect of regional innovation and the lagged term of regional integration is gradually increasing, with a strong cumulative effect, with the accumulation of experience to achieve a strong role in promoting. Secondly, from the perspective of the impact of regional innovation on regional integration, the regression coefficients of model lag 5 are 0.536, 0.454, 0.319, 0.375 and 0.439, respectively. The direction of action is positive, and the promotion effect decreases first and then increases, indicating that its impact on regional integration presents a certain periodic dynamic.

Regional innovation ability has a strong promoting effect on the development of regional integration in the early stage. In the later stage, the promoting effect gradually decreases and increases rapidly, which is conducive to the deep integration of the GHMA. The reason may be that in the early stage of the integration of Guangdong, Hong Kong, and Macao, by increasing the intensity of investment in innovation factors, industrial agglomeration and resource allocation optimization are realized, thus promoting a rapid increase in innovation ability and improving the level of regional integration. With the deepening of integration, the number of capital elements and resources required for the improvement of innovation capabilities has increased rapidly, touching the bottleneck of integration development, and the promotion of regional integration has been weakened. However, with the breakthrough of innovation ability, by strengthening the driving effect of advanced technology and the allocation efficiency optimization of central cities such as Hong Kong and Guangzhou, the cumulative benefits of innovation ability are further strengthened, and the integration and double circulation between cities are realized, thus forming the integrated layout of GHMA.

The development of regional integration has always played a strong role in promoting regional innovation. The results of the five-period lag of regional integration level show that it has always had a positive impact on regional innovation, with coefficients of 0.545,0.491,0.333,0.216 and 0.149, respectively. The promoting effect of regional integration development on regional innovation has gradually weakened, indicating that the promoting effect of Guangdong–Hong Kong–Macao integration on regional integration has convergence, and measures such as factor optimization configuration mean that regional innovation capabilities tend to converge.

5. Policy Implications

By exploring the synergy and interaction between Guangdong–Hong Kong–Macao regional integration and regional innovation capabilities, the following policy recommendations are further proposed.

(1)

Promote the in-depth development of regional innovation capabilities. Explore the regional innovation system with “global demonstration value”, accelerate the promotion and application of digital technology, optimize the supply quality and efficiency of regional innovation capability and give full play to the role of regional innovation capability in promoting integration.

(2)

Give full play to the role of regional innovation in promoting the integration of the GHMA. In technological innovation, we should explore the deep integration of regional innovation and industry, building science and technology industry clusters, and improve the degree of regional integration.

(3)

Focus on the role of Guangdong–Hong Kong–Macao integration in promoting regional innovation. Improve the supervision system of regional innovation, strengthen the construction of regional data centers and digital platforms, further deepen the regional innovation of Guangdong, Hong Kong, and Macao, promote the effective docking of innovation resources and improve infrastructure construction to meet the development needs of emerging technologies, thereby improving regional innovation capabilities.

(4)

Strengthen the policy guidance role of the GHMA, promote integrated governance with regional innovation capabilities and achieve synergistic interaction between the two. Based on the background of regional integration, the rational allocation of resources and elements between regions and industries is promoted. We need to strengthen the interaction of urban agglomerations, give full play to the demonstration and leading role of central cities such as Hong Kong and Shenzhen in other regions and balance the regional differences in regional innovation capabilities. We also need to optimize the development environment of the overall regional innovation of the GHMA, break through the space constraints of finance and services and give full play to the interaction between regional innovation capability and the integration of the GHMA.

6. Conclusions

By discussing the mechanism of synergy between regional integration and regional innovation capability of Guangdong, Hong Kong and Macao, the system GMM method is used to reveal the synergy effect between regional innovation capability and regional integration. The research results show that the integration level and innovation capability of the GHMA are constantly improving. There is a clear gap between urban agglomerations, which is manifested in the spatial layout of “center-periphery”. The regional integration of the GHMA is related to the regional innovation capability. Both of them have a self-enhancement mechanism from a long-term perspective. The regional innovation capability has a strong promotion effect on the development of regional integration in the early stage. In the later stage, the promotion effect gradually decreases and increases rapidly.