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Research on Financial Support, Technological Improvement and Marine Economic Development for China’s Coastal Regions

School of Economics and Management, Liaoning University of Technology, No. 169, Shi Ying Street, Guta District, Jinzhou 121000, China
Management Information System, Benedictine University, Lisle, IL 60532, USA
Author to whom correspondence should be addressed.
Water 2022, 14(17), 2740;
Received: 29 June 2022 / Revised: 26 August 2022 / Accepted: 31 August 2022 / Published: 2 September 2022
(This article belongs to the Special Issue Marine Economic Development and Conservation)


Financial support (capital) and technological improvement are the crucial factors in any industry, and they are also the major factors of marine economics. However, the government has supplied a great deal of capital and the marine economy has been deeply explored and researched using advanced technology. The marine industry is still not the mainstay industry in Chinese industry. Considering this, the issues of how to address financial support, technical improvement and marine economics are common foci within the government and society, especially regarding the economic growth of China. It is necessary to develop the marine economy. However, many scholars only pay attention to the aspects of marine financial support, marine technology and marine economic development separately, and no scholars have studied the relationship between the three at present. Therefore, this article establishes a model to conduct empirical tests regarding the relationship between financial support, technological improvement and marine economic development using panel data from 11 coastal regions in China. The results show that financial support has a negative impact on technological improvement, but it has a positive impact on marine economic efficiency. Technological improvement has a positive impact on financial support and marine economic efficiency. However, marine economic efficiency has a negative impact on financial support, and it has a positive impact on technological improvement. Through impulse response analysis, there is a significant correlation between them. This article calculates marine economic efficiency with the SBM-DEA model and analyzes relationships with the BVAR model, which is proposed to improve the development and efficiency of the marine economy. Financial support should be used in the rather important parts of the marine economy so that the marine economy can achieve returns in the short-term and attract more circulating funds to enter the marine economy, which impacts the long-term stable and sustainable growth of the marine economy. Moreover, financial support, financial liberalization, technological research and technological creation in the progress of marine economic construction should focus on effectively using circulating funds, which provides geo-advantages and aids in building a new marine economic ecological circle.

1. Introduction

With the development of economies and the acceleration of globalization, the limited resources on the road are becoming more and more obvious. Two-thirds of Earth’s surface are covered by oceans; the global ocean area is about 360 million km2. Especially, China’s ocean area accounts for one third of the global ocean area. Therefore, there is profound significance regarding the development of the ocean economy in terms of exploiting the Chinese marine industry. At present, China’s marine economic governance and other policies are emerging from an endless stream, mainly including the development of “blue ocean economy, green marine economy”, etc. At the same time, corresponding financial policies are also proposed to support the development of the marine economy. The development experience of China’s marine economy has important reference significance to the development of the global marine economy. In the process of marine economic development, there are a series of problems, such as low efficiency of marine scientific and technological innovation, difficulties in the approval of marine-related projects and many financial and technical difficulties. In the high-quality development of China’s marine economy, it remains to be verified whether financial support and technical support can play their due role. At present, most scholars in the study of financial support for the development of the marine economy have mainly focused on the study of marine economic policy support for the influence of the marine economy. With the development of the economy, technology and financial aspects are indispensable aspects regarding the marine economy. Xusheng (2021) [1,2]. put forward that financial aspects have an impact on marine economy efficiency in terms of science and technology using the three-stage DEA model for analysis. Qinglong Shao (2020) [3,4] believes that there is a nonlinear impact on marine economic development from scientific and technological innovation on marine pollution From the perspective of input and output, marine pollution is an unexpected output in economic development. Chi-wei Su (2021) [5] analyzed the relationship between China’s financial development and marine economic development from the perspective of causal analysis. Marine industry needs to make full use of financial resources, but financial development cannot depend on marine economic growth. The development of the marine economy by technological innovation is not considered. The above studies and the three relations are not integrated and analyzed, and the three relations are not combined with specific examples of comprehensive evaluation and analysis.
The suggestions put forward are often too rigid regarding empirical results, and there is a lack of substantive suggestions combined with actual production activities. In the aspect of addressing marine economic efficiency, only expected output is considered and non-expected output is not considered. Impulse response analysis of the relationship between the three is not carried out.
From the perspective of the relationship between financial support, technological improvement and marine economic development, this paper uses the Bayes vector autoregressive model (BVAR model) to put forward constructive suggestions for marine economic development so as to establish and improve the marine economic system. The Slacks-based data envelopment analysis model (SBM-DEA model) is used to analyze the efficiency of the marine economy, and the undesired output is taken as the basis of calculation. Marine environmental protection is taken as an important link to the development of the marine economy. Then, the key strategic goals that are beneficial to short-term marine economic development are put forward and the long-term and short-term marine economic development goals are combined in order to better promote the development of China’s marine economy.

2. Literature Review

In terms of financial support, technological improvement and marine economic efficiency, domestic and foreign scholars’ studies have focused on the impact of financial support on the marine economy, the impact of financial support on technological progress and the impact of technological progress on marine economic efficiency. There are also studies related to policy optimization and technological aspects.

2.1. The Relationship between Financial Support and Marine Economic Efficiency

Currently, China is still in a relatively immature situation in terms of financial support in the ocean. Scholars’ research on marine financial support possesses the following three characteristics. First, many scholars are studying the important topic of the relationship between finance and the development of the marine industry. There is currently a lack of professional marine financial support institutions to provide sufficient and continuous financial support for the marine industry in China, which hinders the development of the marine industry and makes it more difficult to improve the efficiency of the marine economy. However, the risk of marine investment has a negative influence on the development of the marine economy, which is mainly reflected in the large amount of investment capital, the long capital recovery cycle and the greater impact of natural disasters (such as tsunamis and earthquakes) on investment. From the research on marine economy and financial support for marine economic development, Ma J. (2021) [6,7] argued that marine capital investment and marine scientific and technological progress are the main factors for high-quality development of the marine economy. Relevant policy is put forward to strengthen the financial guarantee of the development of the marine economy and the investment in marine economic education. In terms of the development model of marine finance, Pan J. and Yan X.Q. (2012) [8,9,10,11]. proposed that interest rate liberalization promotes competition among the banking industry, makes the funds of the banking industry flow into the marine economy and optimizes the credit structure and stock scales. At the same time, it will promote the inflow of private capital into the marine economy to expand investment in the marine industry For marine financial institutions, Yao X.Y. (2012) [12] used the grey correlation degree to analyze the relationship between marine economic development and financial support and financial policy support. The problems of marine finance are the lack of professional financial institutions, innovation ability of marine financial products and the imperfect systems and policies on the development of ocean finance. In view of the low professional level of financial services, it is necessary to increase the innovation ability of marine financial products [13,14].
Financial support is mainly divided into three aspects: the contribution of financial support to marine-related enterprises, the contribution of financial support to the marine industry and the contribution of financial support to the development of the marine economy. Lv Z. and Li B. (2021) [15] proposed that the development of the marine economy should be enhanced by relevant foreign technologies. Based on financial investment, it can create diversified financial institutions and innovate the marine economic development system in line with socialism with Chinese characteristics. Special training for marine financial practitioners and marine financial technology innovation should be increased.

2.2. The Relationship between Technological Improvement and Marine Economic Efficiency

Shao Q. (2021) [16] clearly indicated that marine technological improvement is the main factor for China’s marine economic growth of the future, and it has a directive function regarding the strategy of marine power in technological improvement and adjustment of the marine industry. The cyclical characteristics of marine technological improvement also have a negative impact on the adjustment of the marine industrial structure [17]. China’s marine technology innovation capacity, marine researchers and scientific research funds are insufficient for marine science, and the scientific research institutions of the marine industry are small in scale, low in level and weak in strength (Yu D., 2020) [18]. The main problems of marine technological improvement are the efficiency of resource input allocation and the ability of transforming and applying technology. At the same time, the coastal industrial structure has a negative effect on the marketing of marine science and technology, and the optimization of scientific research and members of the marine industry are also important issues. Due to the different coastal areas in China, the relevant marine policies and technological investment are also different [19]. Therefore, it is necessary to strengthen the connection and cooperation between various coastal cities and jointly improve marine technological innovation. Further, ükrü Merey (2020) [20] analyzed increasing early investment in marine technological improvement and the industrialization of innovative technologies, which guided social capital into the field of blue finance in the development of the marine economy from the perspective of marine industry. At present, the research in this area is still at the theoretical and macro level and there is no specific activity of technological innovation.

2.3. The Relationship between Financial Support and Technological Innovation

Financial support for the application of artificial intelligence, big data technology and cloud computing technology in marine technological improvement will change significantly. In the financial support of technological innovation, Ren W. (2018) [21] measured the level of technological improvement supported by financial aspects. At the perspectives of technology and finance, they mainly studied the contribution to finance with technological infrastructure. With the increase in the amount of marine resources and energy, there are more and more explorations thereof, so the investment demand for marine technology is increasing. However, the current financial support for technological improvement is not enough, and the state needs to increase policy guidance to ensure financial support and marine technology coordinated development of innovation and mutual promotion. Financial support for technological innovation involves large loan terms and high risks. Carvalho A.B. (2021) [22] indicated that financial support has a greater impact on technological innovation in the spatial spillover effect of financial support for technological innovation, but there are great differences regarding technological innovation capabilities. Relying on the advantages of the Special Economic Zone, financial support for technological innovation is much higher than that of other regions in the Yangtze River Delta, eastern coastal cities and Hong Kong and Macau. At present, it is also improving the policy of financial support for technological improvement, and there are many studies on the application of financial support for technological improvement in the field of agriculture. However, as of now, financial support for technological improvement has not been extended to the field of marine economic development [23,24].
In summary, the above scholars have conducted separate research on the three aspects of financial support and technological improvement, technological improvement and marine economic development and financial support and marine economic development, but there is no research on the relationship between the three aspects. There is no empirical research and analysis, and the research remains on a theoretical level. This paper focuses on analyzing the relationship between them, and it analyzes the relationship between them by panel data and proposes more specific, effective and systematic plans and suggestions. With better use of financial support, we can strengthen technological improvement and further promote the development of marine economic efficiency.

3. Analysis of the Impact Mechanism of Financial Support and Technological Improvement on the Development of Marine Economy

3.1. Financial Support to Promote the Development of Marine Economy by the Utilization of Marine Capital

Stable and efficient financial support provides sustainable power for the development of the marine economy. Due to the different levels of economic development in China’s coastal provinces and cities, the methods and levels of financial support are also different. There are higher economic development levels in Tianjin, Guangdong, etc. Coastal marine economic development is the central force that has primarily driven the increase in wealth since the reform and opening up of the economy. Additionally, the financial support for the marine economy and maritime trade is the same. However, financial support is invested in projects with high technical difficulty and complexity. The short-term investment recovery is low, and is not easy with such a project to generate sustainable and stable cash flow. Therefore, the project cannot obtain high profits, so financial support must be used in short-term profitable projects in the marine economy. Only in this way can the development of the marine economy be guaranteed [25,26].

3.2. Technological Improvement in Marine Economic Efficiency through Technological Innovation and Scientific Research Person Training

Technological improvement must adhere to the principles of gradual innovation, upgrading innovation and scientific innovation. It is not permitted to ignore technological research and development that can generate economic benefits in the short-term while directly making use of challenging technologies. For example, the smart ocean project in the Shenzhen Greater Bay Area will comprehensively drive the development of the ocean economy, including seven major fields and twenty-one specific directions. It has a promoting effect on the comprehensive development of the marine economy, but 21 specific directions mean that the technological part needs to be invested in 21 directions. In view of human and financial resources, financial support should be carried out in one to two core and key directions. That can ensure the support of technical persons and financial support to a large extent, generate a sense of competition and technological improvement can be completed in a relatively short period of time [27]. At the same time, science and technology need not only to be independently developed but also cooperative with other countries. We need to form a multi-national and multi-disciplinary technology-leading scientific research team, deepen international marine cooperation and participation in global marine governance and build a marine power.

3.3. Financial Supports Promote Steady Growth of Marine Economic Efficiency by Strengthening Capital Investment in Scientific Research and Technological Innovation

The improvement to marine economic efficiency will attract more funds to the marine industry, and sufficient funds are also the foundation for ensuring technological improvement. How to improve marine economic efficiency is an important link and key issue in current economic development. China’s marine economic efficiency is also affected by the level of local economic development. With the introduction to carbon neutrality and carbon emissions, more and more attention has been paid to carbon emissions from relatively developed cities, such as Guangdong and Tianjin, and more attention has been paid to the use of clean energy. The environmental protection requirements are more strict, which has prompted the marine economy of these cities to adopt higher efficiencies. The adjustment and optimization of the marine industry structure plays an important role in the improvement in marine economic efficiency. Improving high-tech and new technology and transforming traditional industries, the development of emerging industries and high-tech industries can improve the efficiency of the marine economy [28].

4. Empirical Research

4.1. Data Sources

This paper undertakes an empirical analysis based on annual data from 2009 to 2018 in China’s coastal provinces and cities. The data come from the China Statistical Yearbook, China Financial Statistical Yearbook, China Marine Statistical Yearbook and regional Statistical Yearbooks. Matlab 2016 software (MathWorks, Natick, MA, USA) was used for the calculation of marine economic efficiency and the BVAR model, while the rest of the empirical process was completed with Stata 15 software (StataCorp LLC, College Station, TX, USA).

4.2. Variable Selection

In this paper, financial support, technological innovation and marine economic efficiency are selected as the basic data to calculate the BVAR model.

4.2.1. Financial Support Indicators

Financial deepening indicators are selected by the bank capital deepening rate (BFD), the ratio of RMB loans balances in banks and financial institutions to GDP at the end of each region, which represent the deepening level of financial capital. This paper selects the year-end RMB loan amount and GDP of each financial institution in each province and city in the coastal region from 2009 to 2018. The data source is the China Financial Yearbook. This paper selects social fixed asset investment, local fiscal expenditure and various loans (balances) of banking financial institutions as the financial support for the region. At the same time, it divides the marine industry GDP by the proportion of marine industry GDP and regional GDP to estimate the regional GDP, and it compares the financial support marine amount of the regional GDP to obtain the economic efficiency value of regional financial support. The results are shown in Table 1:
Figure 1 shows that regional financial inputs are greater than regional outputs, and regions have more inputs in finance from 2009 to 2018. However, relative to outputs, this is not as impactful as the efficiency of financial support enhancement. The magnitude of financial support economic efficiency of 11 cities is basically floating from zero to 3.50. Lower economic efficiency indicates that the efficiency of financial support is weaker. Higher economic efficiency indicates that the financial support is stronger.
The overall proportion fluctuates between 2 in financial support for each province and city. It indicates that the coastal provinces and cities have greater financial support, which is greatly related to China’s policy factor of giving priority to the development of coastal areas during the reform and opening-up period; mainly, it is greater in Hainan, Guangxi, Zhejiang, Shanghai, Tianjin and other regions. Compared with financial support, the situation of output is not very good; the proportion of gross product of the sea is especially small (shown in Figure 2) [29,30].

4.2.2. Technology Innovation Indicators

In this paper, we choose the internal expenditure of R and D funds and the income of marine research institutions as the technological innovation inputs of the marine economy. We determine the proportion of the technological innovation input of the marine economy to the GDP of the marine economy, as shown in Figure 3.
As can be seen from Figure 3, Guangdong Province invested more in science and technology in 2015 and 2018. Shanghai and Shandong Provinces increased their investment in science and technology year by year, while Hainan Province invested more in science and technology in 2016. It shows that marine technology increased greatly in 2016 [31,32].
From the Figure 4, it can be seen that China has invested more in science and technology for Guangxi and Hainan and focused on developing Hainan’s economy.

4.2.3. Marine Economic Efficiency Indicators

The following table shows what this paper selects in terms of inputs with the coastal provinces and cities from 2009 to 2018.
The Table 2 shows that the most critical factor of the productivity of the marine economy is the input of capital and labor. Since the ocean itself produces energy, the ocean development itself for energy consumption is relatively small, so ignore the energy input. The desired output is the gross marine product, and the non-desired output is wastewater, waste gas and waste residues. Marine pollution is a very important element, so the non-desired output has an important impact on the efficiency of the marine economy.

4.3. Model

4.3.1. SBM-DEA Model

In this paper, the data envelopment analysis (DEA) model is selected to measure the eco-efficiency of China’s logistics industry, and it is selected in the DEA method of the SBM model with the problem of evaluating the efficiency of the existence fee expected output [33]. In this paper, the SBM-DEA model based on Jin-woo [34] is analyzed, and the SBM models considering N in inputs (x), M desired outputs (y), and I non-desired outputs (b) is as follows.
M in θ = 1 - 1 N n = 1 N s n x x n 0 1 + 1 M + I ( m = 1 M s m y y m 0 + i = 1 I s i b b i 0 ) s . t . { k = 1 K z k x n k + s n x = x n 0 , n = 1 , 2 , , N k = 1 K z k y m k + s m y = y m 0 , m = 1 , 2 , , M k = 1 K z k b i k + s i b = b i 0 , i = 1 , 2 , , I k = 1 K z k = 1 s m y 0 , s n x 0 , s i b 0 , z k 0
where θ is the eco-efficiency value of the logistics industry, taking values in [0, 1]; s n x , s m y , and s i b , respectively, slack for input factors, desired outputs and undesired outputs.

4.3.2. BVAR Model

VAR model studies the econometric model of multi-variable time series, which uses the current variable in the model to perform regression on the lag variable. The mathematical formula for VAR model is as follows [35]:
y t = α 1 y t 1 + α 2 y t 2 + α p y t p + β x t + ε t , t = 1 , 2 , T
y t is the n-dimensional endogenous variable vector. x t is the n-dimensional exogenous variable vector. P is the lag order. α 1 , , α p is ( n × n ) matrix. β of ( n × m ) matrix is the estimated coefficient matrix. ε t represents ( n × 1 ) white noise.
However, VAR model also has disadvantage that it ignores prior information. Traditional VAR requires a certain number of parameters, which leads to the problem of “parameterization”. BVAR model uses a simple method to solve the problem of VAR model over-parameterization. The BVAR expression is as follows [36]:
y t = α 1 y t 1 + α 2 y t 2 + α p y t p + δ + ε t , t = 1 , 2 , T
where y t represents the (n × 1) vector containing n elements in period t. δ is the (n × 1) constant vector. α is the coefficient matrix, including financial support, technological improvement, marine economic efficiency and other variables. BVAR requires the test of prior information. According to Litterman, the prior distribution can be assumed to be Minnesota prior distribution due to the lack of clear prior information. If all elements in the coefficient α matrix satisfy the unit root U(1) prior distribution, then the mathematical expectation expression of all elements in the coefficient matrix is:
E [ α i j ( s ) ] = { 1 , I F s = 1 , i = j 0 , I F s 1 , i j
The formula shows all elements in the coefficient α i j matrix of mathematical expectation only when a first order lag is 1; others are supposed to 0. In fact, all coefficients in the coefficient α i j matrix of prior distribution are assumed for non-stationary AR (1) process.

4.4. Model Correlation Analysis

4.4.1. Marine Economic Development Efficiency Analysis

The marine economic efficiency of the Figure 5 is calculated by the SBM-DEA model. It can be found that the economic efficiency of Guangdong is close to 100% in 2018, which indicates that the input–output efficiency of these regions is very high. The input can basically be recovered, but the situation in other regions, such as Tianjin, Hebei, Liaoning, Zhejiang, Fujian and, especially, Guangxi is not very good. The economic efficiency of Hebei and Liaoning Bohai Economic Circle is not very high. Perhaps this is because Liaoning is in the old industrial base of the northeast. There are more inputs for marine aspects, but the output is not as good as Guangdong and Shandong regions. Although the economic efficiency of Shanghai is slower than that of Guangdong, the growth is very obvious from 2009 to 2018. Shanghai ocean GDP has been in the forefront of the country for many years, and it has advanced technology, R and D and R and D teams of ocean universities.
Hainan organized and implemented 175 projects of the National Natural Science Foundation of China, an increase of 18.2% over the previous year. A total of 3669 patents were applied for the year, an increase of 17.4%, granting 1938 patents, and an increase from 5.9%. There are seventy-four newly recognized high-tech enterprises, four new provincial engineering technology research centers, three provincial key laboratories and one national key laboratory. All kinds of professional and technical personnel were added, 170,000 people, an increase of 12.6%. The provincial ministry jointly built “the South China Sea Marine Resources Utilization State Key Laboratory”, realizing zero breakthrough in the province’s university states laboratory. The first discovery of coral debris is a new process of coral reef biology and ecology and provides new technical support for the restoration of islands and reefs. The economic efficiency of Hainan is very high.
China’s investment in science and technology is still insufficient, and there is still a large gap between China and developed countries, such as those of Europe and America, in general. The development of marine technology and the exploitation of resources not only needs to maintain the ecological balance but also needs to consider various factors, especially the balance of the marine economy on the basis of not destroying the ecological balance. For example, the “311” earthquake in Japan caused a nuclear leak that greatly polluted the marine environment. Pollution requires more money to be dealt with, and the cost of treatment is very expensive. The development of marine resources in China is still in a preliminary stage, and the current investment in science and technology mainly lies in transportation and the development of marine biology and marine wind power resources.
To analyze the efficiency of the marine economy from an industrial perspective, this paper adopts a new approach, using the input–output method. At present, China develops a profitable marine economy mainly in marine aquaculture, marine oil and gas, sand and salt industry, ship to repair, transportation, international tourism, etc. Marine aquaculture is the primary marine industry. Marine oil and gas, sand and mining, salt industry, ship repair and shipbuilding belong to the secondary marine industry. Transportation and international tourism and other commercial services are classified as the tertiary marine tertiary industry [37]. Figure 6 shows that the added value of China’s marine primary industry is RMB 389.6 billion in 2020, the added value of secondary industry is RMB 267.41 billion. The added value of the tertiary industry is RMB 4937.3 billion, accounting for 4.9%, 33.4% and 61.7% of the marine GDP, respectively.
The primary industry of marine fisheries is similar to the primary industry of agriculture in China. However, it has the same drawbacks as agriculture. Although the development of technology has improved the time and productivity of production, it cannot change the area of the land or the fishery itself. There is basically no difference in the production of products available for sale per unit acreage. Mechanization and intelligence have saved labor time to a large extent, but they bring the risk of unemployment for workers [38].
Marine secondary industry is mainly marine resources and energy industry. The development of marine resources and energy has high technical requirements. A great deal of money is needed in the research of technology. The safety of resources and energy needs to be maintained in the process of exploitation. It cannot be over-exploited according to damage to the environment.
The marine tertiary industry provides good profit in the best position, mainly in transportation and international tourism [39]. In transportation, the development of cross-border e-commerce has been a major impetus to international marine transportation. It will increase as Chinese manufacturing enjoys its price advantage in foreign markets. In international tourism, tourism is in the doldrums because of COVID-19. Marine tourism generates major gains and boosts related industry chains, such as housing, restaurants, photography, etc. It is an immediate consumption type of a short payback period. The damage to tourism of the environment is also shallow. It can be controlled and prevented as long as reasonable control and quality education for tourism personnel are carried out [40].
In summary, the marine tertiary industry contains a large proportion of the marine economy and plays an important role in the efficiency of the marine economy [41,42].

4.4.2. T-Distribution and Descriptive Statistics

Table 3 clearly shows that n = 11 and T = 10. n > T, so this is short panel data. Table 4 shows the descriptive statistics for of the data.

4.4.3. Smoothing Test

An LLC smoothness test was performed on the data, and the results are shown in the Table 5.
From the results, it can be seen that each variable is significant at the 1% level and passes the significance test, indicating that the data are stable.

4.4.4. Co-Integration Test

Table 6 shows that the Kao test and Pederoni test find that the significance level is clustered within 10%, although the Westerlund test is not clustered. It is rejected in the original hypothesis of no cointegration relationship between the variables. There is an equilibrium relationship between financial support, technological progress and marine economic efficiency.

4.4.5. GMM Test

Table 7 shows that financial support has a significant positive impact on marine economic efficiency, while marine economic efficiency has no significant impact on financial support; financial support has a significant negative impact on technological improvement, while technological improvement has a significant positive impact on financial support. For themselves, financial support and marine economic efficiency have a significant positive impact, but technological improvement has no significant impact.

4.4.6. Impulse Response Function Analysis

It can be seen from Figure 7 that the impact of financial support, technology improvement and marine economic efficiency individually is positive and gradually tends to zero as time passes. The impulse of technological improvement on financial support is opposite to the impact of financial support on technological improvement and tends to zero gradually. In the second period, technological improvement has a positive impact on financial support. Technological improvement and development improve productivity and attract capital. However, the influence of technology is gradually weakened and the ability to attract capital becomes less and less with the advancement of time. Financial support has a positive effect on marine economic efficiency, but marine economic efficiency has a negative effect on financial support. The impact of financial support on marine economic efficiency reaches the maximum in the third period. The impact of marine economic efficiency on financial support reaches the minimum value in the initial stage, and the impact gradually tends to increase. The main reason is that the efficiency of the marine economy will be improved in the short-term when the marine industry receives financial support. The impact on the efficiency of the marine economy will gradually weaken after reaching the peak from two to three years. Due to the inertia effect, the initial capital investment makes the cash flow renew, and the enthusiasm for the staff engaged in the marine economy is further improved, improving the economic efficiency. The impact of technological improvement on marine economic efficiency has the same trend as that of marine economic efficiency on technological improvement: both of them converge at zero after reaching the peak of the second period, and both have positive impacts. The reason is that technological progress and marine economic efficiency promote each other and tend to be synchronized.

5. Conclusions and Recommendations

From the above empirical evidence, the main problem of ocean economics is that the total output value of ocean economics is too low. The influence of financial support and technological improvement in marine economic efficiency usually remains in the short-term, and the influence gradually decreases with the advancement of time. Therefore, financial support often stays in the short-term, and there is no long-term stable financial support. The effect of marine economic efficiency on financial support is negative, which proves that the improvement in marine economic efficiency does not provide a new round of financial support. It indicated that there are problems regarding the economic cycle [43]. After marine economic efficiency improved, improvement in marine economic efficiency did not culminate in a new round of financial support. It is necessary to improve the marine industry structure and complete a new cycle. Our suggestions for the above issues are as follows [44,45].

5.1. Science and Technology to Promote the Development of Marine Wealth Management

The current technology development and investment lies in the exploration of marine resources and energy, resulting in the problem of long payback periods for many inputs. Therefore, economic development was promoted by improving marine financial technology, improving and strengthening financial services for marine economic development and promoting the transformation of the marine economy in terms of quality and efficiency. It is important to support the training, screening and reserve for high-quality and mature sea-related enterprises [46,47]. In insurance, it strengthens the standardized development of various types of mutual insurance, explores catastrophe insurance and reinsurance mechanisms and accelerates the development of shipping insurance, coastal tourism insurance and environmental liability insurance. Necessary are exporting credit insurance coverage and encouraging insurance funds of professional asset management institutions in order to increase investment. New green fund products, green ABS, green ETF, etc. must be created. Regarding green ABS, green ABS can lower the financing threshold of green enterprises and enable them to obtain low-cost financing. Green ABS is based on cash flow for repayment; once the cash flow is insufficient, the problem of repayment difficulties will arise [48]. Therefore, green ABS companies are required to ensure sustainable growth of earnings [49]. Once sustainability is not guaranteed, green ABS will collapse. The current government policy should provide guidance as Chinese individual investment is not very trusting in the ocean. The Chinese government needs to attract more corporate, private equity, fund and institutional investors to invest in green ABS. We believe that, if this project is conducted well, it will become a financial product of particularly Chinese characteristics. Because of the unique macro-control of socialist countries, they can largely guarantee the stability of investment and the controllability of risk, but the disadvantage of conducting green ABS in socialist countries is the lack of economic dynamism to guarantee sustained and stable profitability. This part can be borrowed from Warren Buffett’s investment philosophy, as well as the portfolio concept. China’s green ABS is in its infancy, so the implementation of dynamic green ABS is a clear market choice. For example, one aspect is to choose a marine product portfolio while incorporating resources from multi-period hotspots to drive the development of the marine industry. It will help to build the infrastructure of the marine industry and carry out multi-cultural forms of marine cultural exchange. It also drives the development of marine entertainment culture [50,51].

5.2. Financial Supports for the Development of Marine Enterprises

Financial support should be based on guaranteeing the profitability of marine enterprises. There are two main aspects in the profitability part: promoting marine enterprises to improve profitability and guaranteeing marine enterprises to reduce losses. The two aspects are one thing on the surface, but they are not in reality. In terms of the use of financial support funds, they are divided into the following categories.

5.2.1. The Volume of Foreign Trade Cargo Transportation in Marine Logistics Industry

In 2021, the price of maritime freight constantly broke new highs, and container demand is tight because of COVID-19. As a result, many container enterprises have been able to obtain higher profits, and the amount of capacity has increased [52,53]. Cross-border e-commerce development leads to people engaging in more online shopping, resulting in container enterprises profitability soaring. The core product of Global Shipping Business Network (GSBN) has been putting into production application for 11 ports at home and abroad. The technology upgrade of paperless cargo that was released enables one-digital ecological diversity and creates green low-carbon intelligent shipping [54].
It is also an important profit source of the new terminal business market in the port business, and the port miscellaneous fee is also a large income. Table 8 lists the port miscellaneous charges for a 20-inch container from Dalian port, and the data are provided by a company [55,56].
In port and port miscellaneous fees, the profits of the terminal business are quite objective. The enterprise is not required to undertake any risk with the application of paperless equipment to enhance the cost of the transport industry. The cost of a paper bill of lading is 0, but it requires the domestic express of up to 50 yuan. However, the electric release bill of lading reached 350 yuan. This electronic form does not appear to have any cost, so this profit is quite large. However, it does provide convenience for the transported enterprises, especially the transport of inexperienced small- and medium-sized enterprises [57]. On the other hand, if there is no need to import or export goods, it is impossible to obtain profits in this area. The import and export of goods is affected by the sales and production situation of enterprises, and it has strong instability [58].

5.2.2. Accelerate the Pace of Science and Technology Empowerment and Enhance the Strength of Enterprise Science and Technology

The development of fisheries is extremely similar to agriculture in that both produce limited output with limited resources.
The output of a fish pond is quickly limited, and too much or too little placement of juvenile fish will affect the output. The output of fisheries remains relatively stable when not subject to mega-accidents. The overall annual revenue of the company does not differ much when the fisheries company is not affected by additional factors [59]. However, there is a greater impact on the fishing industry in the current situation of international high seas fishing and increasingly strict fishing policies. Compliance with legal fishing has become the focus of the current fishing business operations.

5.3. Insurance against Marine Business Services to Promote the Development of Marine Economy

In terms of insurance, marine insurance is an important part. By the end of 2021, a company in Dalian, Liaoning Province has a cumulative premium income of 372 million yuan, payout expenditure of 546 million yuan, providing nearly 4.9 billion yuan of risk protection against the marine floating raft breeding facilities insurance, mariculture wind index insurance, aquatic seed production insurance, algae wind index, net fish breeding insurance, factory fish breeding insurance, marine fish breeding insurance, marine fish breeding additional loss, netting, and transshipment in 8 years of insurance products. It can be clearly seen that insurance plays an important role in the development of the marine economy to protect the development of marine enterprises. From the amount of insurance payout, the profit of this insurance company = 372 − 546 = 114 million yuan, of which 114 million yuan is also known as the enterprise loss. This company has a large loss in the main business within a year, so how should the business continue to operate? In terms of financial support and policy support, we must consider the actual situation of the enterprise to support the company. Sometimes, despite blindly investing a great deal of money, the enterprise for innovation and the transition to business is not suitable for the insurance operation, which is a great risk for insurance companies [60].

5.4. Tourism Cultures

Cultural tourism has been the focus of China’s marine economy development. Cultural tourism is in the short payback period, with low input costs and in line with the investment concept of the majority of Chinese investors or investment enterprises “to earn a block of money”. Therefore, marine tourism is currently the most profitable part of the marine economy [61,62]. For this part, more tourism related to coastal cities is important to promote the development of the entire coastal economy. Tourism leads to the development of related catering, hotel and service industries, but there are some areas where tourism is not very well developed and does not make good use of infrastructure for tourism development. Providing more creative tourism and culture industry is the top priority of developing marine tourism at present. The scenes of some tourist places cannot meet people’s needs because some are built too luxuriously. People cannot enjoy all the quality services in a limited time. With the advancement of time, economic changes and changes in people’s needs, the original infrastructure cannot meet the needs of people [63]. Therefore, in addition to the construction of fast-track themed and creative tourism and cultural festivals, in order to facilitate the combination of green ocean and local culture, the culture of the specific country has become a major hot spot regarding the development of the current marine tourism industry and can lead to significant consumption, thus enhancing the development of the local marine economy [64].

5.5. The Development of Marine Biology Will Generate a New Industrial Revolution in the Development of Marine Economy

At present, the development of biopharmaceuticals in China is strongly supported in the context of the COVID-19 pandemic and the outbreak of monkeypox virus in the world. Biopharmaceuticals are becoming more and more essential parts of the biological field [65]. From independent laboratories to manufacturing to various sales scenarios, each part requires significant technical input. In addition to the existing biopharmaceuticals, as the economic development and improvement in people’s living standard occur, the spread of various rare diseases worldwide is increasing. People’s demand for medicine is increasing, as is the risk of emergence. Therefore, the development of marine biomedicine provides new opportunities for China’s economy and even for the surrounding world. The wide variety of marine species is of great benefit to biomedical research, thus building a “blue medicine bank” for China’s marine economy.
In this paper, the BVAR model is selected for analysis. The BVAR model is a traditional econometric model that is widely used in economics papers. Compared with other models, BVAR can effectively solve the problem of VAR transition parameterization and can be effectively applied to the field of regional economy. It is made up of a single variable extended to a multivariate time series variable vector autoregressive model [66]. It can also examine the impulse responses of variables to variables. With the development of the economy and the progression of time, the authors will use more machine learning algorithms to further study this topic in the future.

Author Contributions

Conceptualization, Y.L. and S.Z.; methodology, Y.L.; software, S.Z.; validation, Y.L. and J.L.; formal analysis, S.Z.; investigation, L.G.; resources, Y.L.; data curation, J.L.; writing—original draft preparation, S.Z.; writing—review and editing, S.Z.; visualization, Y.L.; supervision, S.Z.; project administration, J.L.; funding acquisition, Y.L. All authors have read and agreed to the published version of the manuscript.


This paper is the result of Liaoning Provincial Higher Education Innovation Talent Support Program, the project of Liaoning Provincial Social Science Foundation: Study on High Quality Direct Investment by Enterprises in Countries along the Belt and Road from the Perspective of Human Destiny Community (L21BGJ005).

Data Availability Statement

The data presented in this study is available on request from the corresponding author.

Conflicts of Interest

The authors declare no conflict of interest.


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Figure 1. Financial support efficiency of China’s coastal cities from 2009 to 2018.
Figure 1. Financial support efficiency of China’s coastal cities from 2009 to 2018.
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Figure 2. Proportion of marine GDP to regional GDP in coastal provinces and cities.
Figure 2. Proportion of marine GDP to regional GDP in coastal provinces and cities.
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Figure 3. Marine technology input chart.
Figure 3. Marine technology input chart.
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Figure 4. Chart of marine technology investment as a share of GDP.
Figure 4. Chart of marine technology investment as a share of GDP.
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Figure 5. Marine economic development efficiency stacked chart.
Figure 5. Marine economic development efficiency stacked chart.
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Figure 6. The proportion of the three major marine industries in 2020. Data source: General Administration of Customs of China.
Figure 6. The proportion of the three major marine industries in 2020. Data source: General Administration of Customs of China.
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Figure 7. BVAR impulse response graph.
Figure 7. BVAR impulse response graph.
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Table 1. Economic efficiency value of financial support from 2009 to 2018.
Table 1. Economic efficiency value of financial support from 2009 to 2018.
Tianjin2.21 2.22 2.23 2.28 2.33 2.40 2.56 2.63 2.54 2.69
Hebei1.40 1.41 1.56 1.69 1.83 2.01 2.26 2.33 2.40 2.43
Liaoning1.93 1.56 2.01 2.13 2.20 2.19 2.57 2.23 2.23 2.18
Shanghai2.37 2.41 2.41 2.50 2.53 2.50 2.62 2.62 2.66 2.69
Jiangsu1.60 1.52 1.67 1.77 1.83 1.88 1.92 1.96 1.99 1.95
Zhejiang2.32 2.10 2.20 2.33 2.40 2.48 2.55 2.51 2.44 2.39
Fujian1.54 1.52 1.78 1.92 2.00 2.12 2.22 2.20 2.21 2.11
Shandong1.43 1.54 1.50 1.52 1.65 1.72 1.82 1.86 1.87 1.88
Guangdong1.93 2.08 1.55 1.28 1.72 1.77 1.79 1.95 2.03 2.06
Guangxi2.26 2.29 1.98 2.13 2.04 2.09 2.24 2.32 2.61 2.56
Hainan1.38 2.06 2.21 2.44 2.66 2.72 2.97 3.17 3.29 3.33
Table 2. Indicator system.
Table 2. Indicator system.
Indicator 1Indicator 2Indicator 3
Inputs:Capital:Total social fixed investment (billion yuan)
Labor:Employment of sea-related personnel (people)
Expected Output:Gross marine product (billion yuan)
Non-Expected Output:Wastewater (million tons)
Waste residue (million tons)
Exhaust gas (million tons)
Table 3. Distribution of T.
Table 3. Distribution of T.
Distribution of T_i:Min5%25%50%75%95%Max
Table 4. Descriptive statistics.
Table 4. Descriptive statistics.
VariableObservationMeanStandard DeviationSumMinimumMedianMaximum
Table 5. Smoothing test.
Table 5. Smoothing test.
Statistic−3.8661 ***−5.3900 ***−3.6588 ***
Note: the values of the table correspond to the adjusted t-statistic of the LLC test and the corresponding p-value of the probability of significance. *** significant at the 10% levels.
Table 6. Co-integration test.
Table 6. Co-integration test.
Kao Test−3.3859 ***0.0004
Pedroni Test−4.7248 ***0.0000
Westerlund Test−0.00740.4970
Note: the values of the table correspond to the unadjusted modified DF-t statistic of the Kao test, the ADF-t statistic of the Pedroni test, the statistic of the Westerlund test and the corresponding significance level p-value; *** indicate significant at the 10% levels.
Table 7. GMM test results.
Table 7. GMM test results.
lnFinSea1.65 *0.099
lnFin5.81 ***0.000
lnTec−2.79 **0.005
lnFin3.6 ***0.000
SeaSea3.93 ***0.000
Note: probability of significance p-value; ***, **, * denote, respectively, significant at the 10%, 5% and 1% levels.
Table 8. Port miscellaneous charges at Dalian port.
Table 8. Port miscellaneous charges at Dalian port.
Fee TypeFee (CNY)
Terminal Operation Fee566
VGM filing fee164
Document Fee50
Document processing fee450
Unloading Fee50
Equipment handover order50
Booking Fee65
Operating fee100
Sea freight50
Packing fee2840
Customs clearance fee350
Handling fee200
Labor packing fee110
Pallet fee100/PCS
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Liang, Y.; Zhang, S.; Li, J.; Guo, L. Research on Financial Support, Technological Improvement and Marine Economic Development for China’s Coastal Regions. Water 2022, 14, 2740.

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Liang Y, Zhang S, Li J, Guo L. Research on Financial Support, Technological Improvement and Marine Economic Development for China’s Coastal Regions. Water. 2022; 14(17):2740.

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Liang, Yingying, Shuang Zhang, Jianlu Li, and Liangliang Guo. 2022. "Research on Financial Support, Technological Improvement and Marine Economic Development for China’s Coastal Regions" Water 14, no. 17: 2740.

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