Technological Innovation, Regional Heterogeneity and Marine Economic Development-Analysis of Empirical Data Based on China's Coastal Provinces and Cities

Dongling ZHANG, Weili FAN, Jingshuai CHEN

Journal of Systems Science and Information ›› 2019, Vol. 7 ›› Issue (5) : 437-451.

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Journal of Systems Science and Information ›› 2019, Vol. 7 ›› Issue (5) : 437-451. DOI: 10.21078/JSSI-2019-437-15
 

Technological Innovation, Regional Heterogeneity and Marine Economic Development-Analysis of Empirical Data Based on China's Coastal Provinces and Cities

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Abstract

In order to analyze the impact of technological innovation and regional differences in marine economy on the development of marine economy, the paper uses the regional panel data of China's total marine production value from 2006 to 2015, and uses the Theil index to measure regional differences in the marine economy based on the logarithm of the Cobb-Douglas production function. Finally, the paper establishes a random effect panel data model for empirical analysis. The research indicates that the regional differences in the marine economy show a narrowing trend, which promotes or inhibits the development of the marine economy; The extent of the impact of regional differences in the marine economy on the development of the marine economy is inconsistent; Scientific and technological innovation in various regions has promoted the development of marine economy.

Key words

marine economy / technological innovation / regional differences / Theil index

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Dongling ZHANG , Weili FAN , Jingshuai CHEN. Technological Innovation, Regional Heterogeneity and Marine Economic Development-Analysis of Empirical Data Based on China's Coastal Provinces and Cities. Journal of Systems Science and Information, 2019, 7(5): 437-451 https://doi.org/10.21078/JSSI-2019-437-15

1 Introduction

Building a maritime power is an important part of the cause of socialism with Chinese characteristics. The connotation of the current marine development strategy is increasingly enriched and improved. The core and support for building a maritime power are to develop the marine economy. The ocean has become an important direction for the development of human society and the sustainable use of resources in the 21st century[1]. The marine economy accounts for about one-tenth of the national economy. In recent years, from the perspective of growth rate, the marine economy is in a period of high growth during the "11th Five-Year Plan" period. The average growth rate of marine production during the "12th Five-Year Plan" period has declined. During the "13th Five-Year Plan" period, the marine economy will be in a period of structural transformation and deep adjustment, from the high-speed development stage to the medium-high-speed development stage, and the growth rate will be slightly slowed down. The sustainable development of the marine economy will become the main body of China's blue revolution[2]. Although the marine economy is booming, there are still some problems. On the one hand, under the background of the transformation of new and old kinetic energy, the scientific and technological innovation drive of marine economic development are insufficient. China's economic development has entered a new normal, and the implementation of innovation-driven development strategies has been implemented. Technological innovation has become an emerging driving force for economic development. To achieve a higher level of economic development, promote economic restructuring and supply-side structural reforms, it is inevitable to transform and upgrade traditional kinetic energy and accelerate the transformation of new and old kinetic energy. The change in the stage of economic growth is not only the adjustment of growth rate but more importantly, the transformation of power to promote economic growth. The structural transformation of marine economic growth is also inseparable from the transformation of old and new kinetic energy and is inseparable from the promotion of technological innovation. On the other hand, due to differences in natural foundations, economic bases, policies, and technological levels, there are regional differences in the development of the marine economy. Moderate regional differences in the marine economy will promote economic growth. It will also lead to insufficient effective demand in backward areas, thereby inhibiting the growth of the marine economy. In-depth analysis of the trends in regional differences in marine economy, as well as the impact of technological innovation, it has an important practical significance for promoting the growth of the marine economy and accelerating the structural transformation and deep adjustment of the marine economic growth in the background of the new normal of economic development and the transformation of old and new kinetic energy.
In the existing literature, most scholars pay attention to the relationship between technological innovation and economic growth. Chandrashekar and Basvarajappa[3] studied the impact of the R & D expenditure on economic development base on the data of India form 1994 to 1995 and 1999 to 2000. And the results show that technological expenditure can improve the competitiveness of India's economic development. Dhrifi[4] explored the impact of technological innovation on economic development by using the data of 83 countries from 1990 to 2012. And the research shows that technological innovation has a significant impact on FDI and economic growth. Jiao[5] pointed out that only relying on scientific and technological progress can ensure the sustained and healthy development of the national economy by establishing a macroeconomic distribution parameter model. Ye and Chen[6] analyzed the relationship between independent innovation and economic growth by using provincial panel data from 1997 to 2012. The conclusion is that there is a clear spatial correlation between independent innovation and economic growth, and there is a non-linear relationship between them.
In recent years, the role of marine economic development in economic growth is becoming more and more obvious[7]. Chinese scholars' research on the impact of technological innovation and regional differences in the marine economy on the development of the marine economy has been carried out mainly from the following aspects: The first is the impact of technological innovation on the development of the marine economy. Science and technology innovation drive industrial structure upgrading, economic development mode transformation and regional economic strength related research is a hot issue in academic circles[8-12]. Some scholars use the analytic hierarchy process, the comprehensive index method[13], the principal component analysis method[14], and the entropy method[15] to evaluate the marine science and technology innovation capability and the level of marine economic development in China's coastal areas. Some scholars construct a VEC model[16] to analyze the dynamic equilibrium relationship between technological innovation and marine economic growth, or to use the coordination degree evaluation model[13, 15] to calculate the degree of coordination between marine science and technology innovation capability and marine economic development level. Therefore, it provides theoretical support for revealing the inherent mechanism of scientific and technological innovation to effectively drive the growth of the marine economy and lays the foundation for providing policy recommendations. The second is the study of the regional difference measurement of the marine economy: The existing literature uses the coefficient of variation, the Theil index and other indicators to measure the regional differences in marine economy, and obtains the trend of differential changes; Based on this, qualitative analysis and quantitative analysis are combined to analyze the influencing factors affecting regional marine economy such as natural resources, economic foundation, industrial spatial agglomeration, government regional policies, foreign direct investment, and scientific and technological level. Then, the overall data is quantitatively analyzed, and the intensity of each influencing factor is determined through the panel data. Finally, from the perspective of policy analysis, recommendations are proposed for the balanced growth of the marine economic region[16-20].
Through combing the relevant research literature, we can easily find that due to the rapid development of the marine economy, scientific and technological innovation has become a new impetus for economic development. Due to differences in natural resources and economic bases in various regions, there are differences in the development of the marine economy. The study of the relationship between regional economic differences and the development of the marine economy has become the focus of research by scholars, and the research methods are constantly improving and improving. Although the research methods of regional differences in the marine economy have been continuously enriched and improved, most of the current literature focuses on the study of the influencing factors of regional differences in the marine economy, and the role of regional differences in the marine economy has not been deeply analyzed. Given this, the possible research contributions of the paper mainly include the following two points. First, using the Theil index method to measure the regional differences of the marine economy, quantitatively analyzing the changes in the regional differences of the marine economy since 2006 in China; Second, analyze the regional differences in China's marine economy and the impact of marine science and technology innovation on the marine economy based on the total value of marine production, the measurement of marine science and technology innovation statistics. Through the analysis of the impact of different regions, it is expected to provide a practical reference for promoting the transformation and deep adjustment of the marine economy structure under the background of new and old kinetic energy conversion.

2 Regional Differences Analysis of Marine Economy Based on the Theil Index

2.1 Research Definition

Outline of the National Marine Economic Development Plan (2003) considers that the marine economy is a combination of various marine industries and related economic activities for the exploitation and utilization of the ocean. The marine economy includes two aspects: Production and service activities that take marine resources and marine space as the basic factors of production, and economic activities that do not depend on marine resources and marine space but directly serve other marine industries[21, 22].
Regional differences are the differences between one region and another in terms of natural characteristics, economic development, social progress, culture, and physical environment, which are manifested in regional natural characteristics, humanistic atmosphere, economic development, and differences in institutional environment. The regional differences of marine economy are one of the regional differences of economy. The analysis of regional differences in the terrestrial economy can be used to analyze regional differences in the marine economy. Regional differences in the marine economy are based on marine resources and take marine regions as a unit. Regional differences in the marine economy are the differences in total volume, growth rate, structure and even development conditions of the marine economy. If we merely use the indicator of the total output value of the marine economy in each region to measure the level of marine economy's development, we can only explore one aspect of the regional differences in the marine economy. The regions vary greatly in terms of geographical area and the size of the population. If we simply compare the differences in the total economic development of each region, the conclusion is too one-sided. Therefore, when studying the regional differences in the marine economy, the Theil index is selected as the indicator for measuring regional differences in the marine economy, and the results of regional differences are analyzed based on the size of Theil index.
Eleven Chinese coastal provinces and cities were selected as research samples, and eleven provinces and cities were divided into three regions to analyze regional differences in the marine economy separately. Among them, Tianjin, Hebei, Liaoning and Shandong form the Bohai Rim region, Shanghai, Jiangsu and Zhejiang form the Yangtze River Delta region, and Fujian, Guangdong, Guangxi and Hainan form the Pan-Pearl River Delta region.

2.2 Measurement of Regional Differences in Marine Economy

2.2.1 Regional Difference Analysis Method Based on the Theil Index

There are generally two methods to analyze the variables as well as the differences between them. One is the mean differences test method, which analyzes the differences between the samples from the perspective of mean value. However, this method cannot decompose the total differences into regional differences, which means it does not apply to regional heterogeneity studies. The other is the Theil index method, which can be decompose and can directly measure the differences between countries and regions.
The Theil index, also known as Tell Entropy, was first proposed by Theil and Henri in 1967. The Theil coefficient has two indicators: Theil coefficient T (weighted by GDP) and Theil coefficient L (weighted by population). The Theil coefficient T is used to measure regional differences in China's marine economy. The larger the coefficient T is, the greater the differences in economic development between regions are[12]. Using the Theil index, the regional differences in the overall marine economy and regional economic differences in the Bohai Rim, Yangtze River Delta, and Pan-Pearl River Delta regions can be calculated. The overall Theil index is measured as:
T=(IiIln(Ii/IPi/P)),
(1)
T represents the overall Theil index, Ii represents the income of the region i, I represents the total income, Pi represents the population of the region i, and P represents the total population. If the T value is smaller, it means that the differences between the regions are smaller; if the income share is equal to the population share, then the calculated T value is 0, indicating that there are no differences between the regions; if the ratio of income share to population share is greater than 1, it indicates that the area is developed, the corresponding Theil index value is greater than 0. Otherwise, the value of the Theil index would be less than zero.
Suppose a sample containing n individuals is divided into K groups, each of which is gk (k=1,2,), where the number of individuals in the kth group is nk, then k=1knk=n the Theil index can be decomposed into the in-group Theil index TI and the group's Theil index TB, are expressed separately as follows:
T=TB+TI=k=1kyklnyknk/n+k=1kyk((yiyklnyi/yk1/nk)).
(2)
Among them TB=k=1kyklnyknk/n, TI=k=1kyk((yiyklnyi/yk1/nk)). From this we can use the Theil index to measure the overall situation of the total marine production in coastal provinces and cities:
T=i=111[ZiZln(Zi/ZHi/H)],
(3)
where i=1,2,,11 represents 11 provinces and cities along the coast; Zi is the total marine production value of the ith province; Z is the sum of the total marine production value of 11 coastal provinces and cities; Hi is the sea-related employment population of the ith province; H is the sum of the sea-related employment population of 11 coastal provinces and cities. In the same way, we can also figure out the Theil index of the marine economic growth of China's Bohai Sea region, the Yangtze River Delta, and the Pan-Pearl River Delta, and are represented by T1,T2,T3 respectively as follows:
T1=i=14[ZiZ1ln(Zi/Z1Hi/H1)],
(4)
T2=i=13[ZiZ2ln(Zi/Z2Hi/H2)],
(5)
T3=i=14[ZiZ3ln(Zi/Z3Hi/H3)].
(6)
Furthermore, according to the decomposability of the Theil index, the overall Theil index is decomposed into in-group Thiel index TB and the inter-group Thiel index TI.
T=TB+TI=Z1Zln(Z1/ZH1/H)+Z2Zln(Z2/ZH2/H)+Z3Zln(Z3/ZH3/H),
(7)
TI=Z1ZT1+Z2ZT2+Z3ZT3.
(8)
Based on this, we can calculate the overall Theil index of China's total marine production value from 2006 to 2015, and the Theil index of the three major regions of the Bohai Sea region, the Yangtze River Delta region and the Pan-Pearl River Delta region, and we can further decompose the overall Theil index into the Theil index of the Bohai Rim region, the Yangtze River Delta region, and the Pan-Pearl River Delta region, as shown in Figure 1:
Figure 1 The chart of the Theil index of China's gross marine production (2006–2015)

Full size|PPT slide

Figure 1 shows:
First, Since 2006, the overall Theil index of China's gross marine production has dropped from 0.135 in 2006 to 0.062 in 2016 and has gradually shown a steady trend, especially during the period from 2006 to 2009, the downward trend is more obvious. The latter year shows a more gradual decline, which indicates that China's marine economic regional differences have gradually narrowed and stabilized since 2006.
Second, The Theil index of China's Yangtze River Delta region also showed a significant downward trend from 2006 to 2009. From 2009 to 2010, there was a slight increase. From 2010 to 2015, it showed a slow downward trend and gradually stabilized. Third, The Theil index in the Bohai Rim region has declined slowly in the early stage and has gradually increased in recent years.
Finally, the trend of the Theil index in the Pan-Pearl River Delta region was very stable from 2006 to 2015; this indicates that except for the Bohai Rim region, the regional differences in marine economics in other regions are declining and have shown a steady trend in recent years.

2.2.2 Analysis of Measurement Results of Regional Differences in Marine Economy

From the Theil index, the overall Theil index, the Yangtze River Delta, and the Pan-Pearl River Delta's Theil index have shown a downward trend and are gradually stabilizing, while the Bohai Sea region has been increasing in recent years. Reflecting that within nationwide, China's differences of marine economy in the Yangtze River Delta and Pan-Pearl River Delta regions are slowly narrowing except for the Bohai Rim region. According to the trend of the Theil index of the Bohai Rim region, the Yangtze River Delta region, and the Pan-Pearl River Delta region, we can be seen that the Yangtze River Delta region has the largest differences, followed by the Bohai Rim region and the Pan-Pearl River Delta region. The regional gap is constantly stabilizing. From a holistic perspective, the regional differences in the national marine economy are mainly caused by the differences in the Yangtze River Delta region.
Figure 1 shows that the Theil index in the Yangtze River Delta is the highest, basically maintaining between 0.076 and 0.217. That is, the regional differences in the marine economy in the Yangtze River Delta have significant impacts on the regional differences in the national marine economy. The internal differences in the Yangtze River Delta are higher compared with other regions. This is because Shanghai, Jiangsu, and Zhejiang provinces have large differences in natural resource endowments, regional economic bases, government regional policies, and scientific and technological levels, and as a result, the development level of marine economy in the three provinces are quite different, while the regional differences of marine economy between the Bohai Rim region and the Pan-Pearl River Delta region is relatively small, and the Theil index is maintained between 0.010.05, which has little effect on regional differences in the national marine economy.

3 Empirical Analysis Based on Regional Panel Data

3.1 Sample Selection and Data Source

Eleven coastal provinces and cities were selected as research samples. Among the data used, based on the availability of data, the gross marine product per capita, the recurrent income of marine science research institutions in coastal provinces, and the number of professional technicians in marine scientific research institutions in coastal provinces and cities are from 2007–2016 China Marine Statistical Yearbook. Among them, each variable is processed by natural logarithm.

3.2 Variable Selection and Descriptive Statistics

The selection of related variables mainly refers to the research examples of the existing literature. In the paper of Xu[23], the scientific and technological activity staff of marine scientific research institutions were used as indicators to measure the investment in marine science and technology. Wang and Liu[13] used marine scientific research practitioners and scientific and technological fundraising as a measure of marine science and technology innovation. Xie[14] using the total amount of funds from marine scientific research institutions and the number of personnel engaged in marine science and technology activities to measure the scientific and technological input of marine science and technology innovation, Ma, Wang, Wu[15] used the number of professional technicians in scientific research institutions and the investment of scientific research institutions to measure marine scientific and technological capabilities. Most literature measures the degree of development of the ocean economy by the per capita ocean production. Refer to the existing literature to select the recurrent income of marine scientific research institutions in coastal provinces and cities, and the number of professional technicians in marine scientific research institutions in coastal provinces and cities as the measurement indicators of marine science and technology innovation. Based on this, the settings for the variables are shown in Table 1.
Table 1 related variable settings
toprule category variable name variable measurement method
explanation variables marine economy (Z) the ratio of the gross Marine product of coastal provinces and cities to the total population of Marine industry.
explanatory variables ocean scientific research institutions input (I) recurrent income of marine scientific research institutions in coastal provinces and cities.
explanatory variables number of professionals in marine scientific research institutions (H) number of professional technicians in marine scientific research institutions in coastal provinces and cities.
explanatory variables Regional differences in marine economy (T) theil index of marine production in coastal provinces and cities
The statistical characteristics of the main variables are shown in Table 2.
Table 2 The descriptive statistics of the main variables
variable number of samples mean standard deviation minimum maximum
Z 110 11.6711 0.6606 10.2229 13.1810
I 110 1.43192 1.6919 3.2089 3.7219
H 110 6.9664 0.9825 4.234107 8.4805
T 110 0.0076 0.0439 0.0519 0.2120

3.3 Model Construction and Estimation

3.3.1 Research Method

To analyze the impact of regional heterogeneity of marine production on the growth of the marine economy, the logarithmic form of the Cobb-Douglas production function is selected as the basic analysis model, and the regional differences T of the marine economy is taken as an important factor affecting the growth of the marine economy. Municipal marine scientific research institutions' regular fee income I, and the number of professional technicians H in marine scientific research institutions in coastal provinces and cities is used as an indicator to measure marine science and technology innovation. By establishing a static panel data model to analyze the relationship among the regular fee income of coastal scientific research institutions in coastal provinces and cities I, the number of professional technicians in marine scientific research institutions H, the regional differences between marine economics T and marine economics Z[17], the logarithmic form of the Cobb-Douglas production function is:
Zi,t=c+αIi,t+βHi,t+γTi,t+μi,t,
(9)
Zit, Iit, Hit, Tit, μit, represent the per capita marine economy, the recurrent income of scientific research institutions in coastal provinces and cities, the number of professional technicians in marine scientific research institutions in coastal provinces and cities, the differences in marine economic regions, and the error items, i, t indicating the cross-section and time units. By taking the logarithm of the variable to reduce the heteroscedasticity as follows:
lnZi,t=c+α×lnIi,t+β×lnHit+γ×lnTit+Pi+μit.
(10)

3.3.2 Unit Root Test of Panel Data Model

Using the LLC test and the Fisher-ADF test, the results of the panel test for stationarity test are shown in Table 3:
Table 3 The unit root test results
variable ADF-F LLC
lnZi,t 4.56626 7.59421
(0.8027) (1.0000)
lnIi,t 15.1746 5.53898
(0.0773) (0.0000)
lnHi,t 3.86386 1.62762
(0.8692) (0.0518)
lnTi,t 7.94517 2.08704
(0.4388) (0.0184)
D(lnZi,t) 2.81820 0.51150
(0.9452) (0.6955)
D(lnIi,t) 33.6339 8.98758
(0.0000) (0.0000)
D(lnHi,t) 17.0260 2.80378
(0.0298) (0.0025)
D(lnTi,t) 27.2397 6.43671
(0.0006) (0.0000)
D2(lnZi,t) 16.6965 3.29564
(0.0334) (0.0005)
D2(lnIi,t) 24.6934 6.63090
(0.0018) (0.0000)
D2(lnHi,t) 25.0304 7.36586
(0.0015) (0.0000)
D2(lnTi,t) 44.3363 7.82156
(0.0000) (0.0000)

3.3.3 Cointegration Test of Panel Data Model

The results of Pedroni test and Kao test for data variable cointegration test are shown in Table 4:
Table 4 The Pedroni test and Kao test results
test method statistics statistics results P test results
Pedroni test Panel v-Statistic 0.395699 0.3462 accept the null hypothesis
Pedroni test Panel rho-Statistic 0.453777 0.6750 accept the null hypothesis
Pedroni test Panel PP-Statistic 1.822168 0.0342 reject the null hypothesis
Pedroni test Panel ADF-Statistic 1.857686 0.0316 reject the null hypothesis
Pedroni test Group rho-Statistic 1.453322 0.9269 accept the null hypothesis
Pedroni test Group PP-Statistic 2.825576 0.0024 reject the null hypothesis
Pedroni test Group ADF-Statistic 1.385179 0.0830 accept the null hypothesis
Kao test ADF 2.553305 0.0053 reject the null hypothesis
From Table 4 we can see that Panel v-Statistic, Panel rho-Statistic, Group rho-Statistic, Group ADF-Statistic did not pass the 5% significance level test, and other results passed the 5% significance level test. That is to say, the null hypothesis should be rejected, and there is a cointegration relationship. Due to the statistical data selected are of the per capita marine production value of the 11 provinces and cities in China from 2006 to 2015, the recurrent income of marine scientific research institutions in coastal provinces and cities, the number of professional technicians in marine scientific research institutions in coastal provinces, and the differences in marine economic areas, the sample size is small, and it is suitable for both Panel ADF-Statistic and Group PP-Statistic. The P-values of both tests are less than 0.05, rejecting the null hypothesis that there is no cointegration relationship, and the ocean economy and coastal provinces can be obtained. There are co-integration relationships among the four variables.

3.3.4 Regression Analysis of Panel Data Model

Firstly, the panel data of the national, Bohai Rim, Yangtze River Delta and Pan-Pearl River Delta regions were regressed by a random effects model. The regression results were obtained by the Hausman test. The P-values of the tests were all greater than 0.05, and the null hypothesis of random effects model was accepted. The random effects model was used for regression analysis. The panel data model is a regression analysis of the relevant statistical data from 2006 to 2015. The static panel data model of the marine economy, the recurrent income of marine scientific research institutions in coastal provinces, the number of professional technicians in marine scientific research institutions in coastal provinces, and the differences in marine economic regions are obtained. The panel data model is estimated as shown in Table 5:
Table 5 The Pedroni test and Kao test results
toprule variable national region Bohai Rim Yangtze River Delta Pan-Pearl River Delta
lnIi,t 0.42153 0.043348 0.127976 0.044003
(1.215286) (1.499549) (2.999120) (2.516950)
lnHi,t 2.880445 1.382539 1.353381 1.441484
(6.332537) (13.73478) (2.028070) (25.09419)
lnTi,t 1.318313 0.594596 0.239115 0.356363
(3.717763) (6.564879) (0.626267) (2.599403)
Adjust R2 0.908462 0.932169 0.750244 0.978402
F 130.0174 179.6535 40.05089 543.6198
Note: The first row of cells is the estimated regression coefficient, the second row is the t value, and *, **, and *** indicate that the levels of 10%, 5%, and 1% are significant.
Through the estimation results of the panel data model, we can see that the Adjusted R2 of the national, Bohai Rim and Pan-Pearl River Delta data are above 0.90, the fitting degree is good, and the Adjusted R2 of the data of the Yangtze River Delta is 0.75, and the fitting degree is slightly lower; The F statistic is greater than the critical value, and the saliency of the equation is more obvious. Through the correlation coefficients of the variables, we can get the regression equations of the three variables as follows:
The national panel data model estimation results are:
lnZi,t=19.80727+0.042153lnIi,t+2.880445lnHi,t+1.318313lnTi,t(1.215286)(6.332537)(3.717763).
(11)
Estimated results of the panel data model in the Bohai Rim region are:
lnZi,t=6.214060+0.043348×lnIi,t+1.382539×lnHi,t+0.594596×lnTi,t(1.499546)(13.73478)(6.564897).
(12)
Estimation results of the panel data model in the Yangtze River Delta are:
lnZi,t=7.567195+0.127976×lnIi,t+1.353381×lnHi,t+0.239115×lnTi,t(2.999120)(2.028070)(0.626267).
(13)
Pan-Pearl River Delta region panel data model estimation results are:
lnZi,t=9.911172+0.044003×lnIi,t+1.441484×lnHi,t0.356363×lnTi,t(2.516950)(25.09419)(2.599403).
(14)

4 Results Analysis

From the panel data model estimation results, we can see that the recurrent income of marine scientific research institutions in coastal provinces is positively correlated with the marine economy. Compared with the national average, the impact of the recurrent income of the marine scientific research institutions in China's Bohai Rim and Pan-Pearl River Delta regions on the marine economy is not significant. The recurrent income of marine scientific research institutions in the Yangtze River Delta region has a high level of impact on the marine economy and is highly significant. The impact of the recurrent income of scientific research institutions in various regions on the marine economy is different in the intensity and significance level. The possible reasons are that the investment in marine scientific research in the Bohai Rim and Pan-Pearl River Delta regions is relatively insufficient, and the transformation mechanism of marine scientific research results is relatively inadequate.
The results of panel data model analysis show that the number of professional technicians in marine scientific research institutions in coastal areas has a significant impact on the marine economy, and the number of professional technicians is positively correlated with the marine economy. For every 1% increase in the number of professional technicians in marine scientific research institutions in coastal areas, the marine economy in the whole country, Bohai Rim, Yangtze River Delta, and Pan-Pearl River regions increased by 2.880, 1.383, 1.353, and 1.441 percentage points. Compared with the national average, the number of professional and technical persons in the three regions has similar effects on the marine economy. The national level of influence is slightly higher than the level of influence in each region. The impact on the marine economy of the number of professional and technical persons in the three regions is analogous. It shows that the number of professional and technical personnel in the marine scientific research institutions of the stage of development in each region is relatively consistent, and the number of professionals has the same level of influence on the development of the marine economy.
From the results of the panel data model analysis, the regional differences in the marine economy across the country have a high impact on the marine economy. The regional differences in the marine economy in the Pan-Pearl River Delta region have a depressing effect on the marine economy. The differences in marine economic regions in the Bohai Rim and the Yangtze River Delta regions have slightly promoted the marine economy. The regional differences in marine economy in the whole country, the Bohai Rim region and the Pan-Pearl River Delta region have a significant effect on the development of the marine economy, while the regional differences in the marine economy in the Yangtze River Delta region have a significantly lower effect on the development of the marine economy. This is mainly due to the regional differences in the marine economy and the different economic bases in various regions. Moderate differences in the marine economy have contributed to the growth of the marine economy, but regional differences will also lead to a decline in the marine economy. The marine economy in the Pan-Pearl River Delta region developed earlier. The regional differences in the Pan-Pearl River Delta have been relatively stable, and the values are small. The regional heterogeneity has reached a stage of inhibition of marine economic growth. The marine economic development in the Bohai Rim and the Yangtze River Delta region is relatively late compared to the Pan-Pearl River Delta region. The regional differences in the marine economy are relatively large, and the regional differences in the marine economy are still in the stage of promoting the growth of the marine economy.

5 Conclusion

First, the investment in marine scientific research is relatively insufficient, and the transformation mechanism of marine scientific and technological achievements is not perfect. From 2006 to 2015, China's marine scientific research funding has been increasing, but the funding for marine research is still insufficient, the increase in marine scientific research funding and the growth rate of marine scientific research funding are not large. The recurrent income of the marine research institutions increases year by year, but the influence of the recurrent income of the marine research institutions on the per capita marine gross domestic product is less significant. The investment of marine scientific research funding is large, but the return is small. The main reason is that the conversion mechanism of marine scientific and technological achievements is not perfect and the conversion rate of marine scientific and technological achievements is relatively low. The lack of rational allocation of marine science and technology resources has reduced the efficiency of scientific and technological innovation and resulted in less output of scientific and technological achievements.
Second, the number of professional technicians in marine scientific research institutions has a relatively large effect on the development of the marine economy. From the results of the panel data model analysis, the number of professional technicians in marine scientific research institutions in coastal areas has a significant impact on the marine economy. The professional and technical personnel of marine scientific research institutions have a significant effect on promoting the growth of the marine economy. However, there are some problems in the supply of marine economic talents in China. There are fewer talents capable of high-level marine science and technology innovation. On the whole, there is an imbalance in the development of marine economic talents. It is necessary to vigorously cultivate innovative marine high-level talents and optimize the structure of China's high-level marine talents. Optimizing China's high-level marine talent structure is conducive to building a maritime Silk Road and realizing a strategy of strengthening the country by sea.
Third, the downward trend of regional differences in the marine economy in various regions has slowed, and regional differences still exist. From the analysis of regional differences in the marine economy based on the Theil index method, on the one hand, we can see that the downward trend of the regional differences in the marine economy slowed down in 2006–2015. Especially in the Bohai Rim region, it has shown an upward trend in recent years. Generally speaking, the regional differences in the marine economy have gradually stabilized. The reason is that in recent years, China has paid more and more attention to the development of the marine economy, and introduced some measures to narrow regional differences. The state finances are inclined to regions with large regional differences in economic development. The difference in the Bohai Rim region is mainly because the level of marine science and technology innovation between the provinces in the Bohai Rim region is quite different compared with other regions, which makes the marine economic regional differences in the Bohai Rim region appear to be increasing. On the other hand, we can see that the marine economic regional differences are still large because there are still significant differences in the natural resources, historical basis, economic basis, policy basis, foreign direct investment, and scientific and technological level of each region. Measures and policies play different roles in different regions and at different stages. As a result, the level of development of the marine economy is still largely different in each region, leading to regional differences in the marine economy.
Finally, there are differences in the degree of impact of regional differences in marine economics on the marine economy. Through the empirical analysis of the impact of regional differences in China's marine economy on the marine economy, the direction and extent of the impact of regional differences in the marine economy on the development of the marine economy are different. The regional differences in the marine economy in the Bohai Rim region are gradually increasing, but the regional differences in the marine economy are positively related to the marine economy, and the regional differences in the marine economy in the Bohai Rim region have a significant effect on the development of the marine economy. The marine economy in the Pan-Pearl River region is sensitive to regional differences in the marine economy and has a negative correlation.

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Funding

the Social Science Foundation of China(19BJY111)
the Social Science Planning and Research Project of Shandong Province(17CJJJ30)
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