我国制造业产业安全监测预警系统的开发与应用研究
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摘要
经济全球化背景下,产业安全受到越来越多国家(尤其是发展中国家)的重视,在我国,产业安全已经逐渐从国家经济安全研究中分离出来,并开始了分行业独立评价与监测预警研究。但是这些产业安全实证研究主要考察农业、石油行业、汽车产业等特殊产业,缺乏对制造业整体及其子行业的全面关注。
本文首先根据现有文献,阐述我国制造业产业安全定义及其内涵,积极寻找影响我国制造业产业安全的各种不利因素;其次根据制造业整体及各子行业自身特点,设计具有代表性、标志性的产业安全评价指标,并收集相应的定量或定性数据,设计制造业产业安全数据仓库。最后,在制造业产业安全数据仓库基础上,根据不同数据类型,选择合适的数据分析和数据挖掘方法对我国制造业整体及其子行业产业安全进行系统、全面的监测预警实证研究。通过比较、综合实证分析结果,发现:外资确实对我国制造业及其各个子行业产业安全产生重大威胁,这种威胁作用超过了外资对我国制造业产生的技术拉动作用,也超过了出口贸易问题对我国制造业产业安全产生的不利影响。
本文创新之处有如下三点:一,运用时差相关分析等方法筛选出制造业子行业产业安全警兆指标,并利用景气指数和景气预警信号系统方法对制造业子行业产业安全进行监测和预警;二,以内资企业亏损率作为制造业产业安全的特征或衡量标准,先运用普通面板回归模型考察了外资强度、出口问题对我国制造业各个子行业产业安全的具体影响,其次运用面板二元选择模型对我国制造业子行业产业安全进行了监测和预警;三,突出了生态与能源环境对我国制造业整体产业安全的影响,结合现有产业安全研究中的代表性评价指标,先独立预测,后用BP神经网络进行制造业整体产业安全监测预警。
Industrial safety has always been an important component of national economic security ,as well as the starting point of the Government's industrial policies, coordinating economic development and safeguarding the national interests. In the background of Economic globalization, regional economic integration and trade and investment integration, the interference and the impact of external factors or international factors on national industrial security become increasingly evident, . As the largest developing and manufacturing state, its survival and development of the manufacturing sector heavily dependent on the level of foreign direct investment and import and export levels, the manufacturing industrial security has become the main and urgent topics of our national economic security and industrial security. At present, academics have not formed a unified theory of industrial security (or further manufacturing industrial security theory), and compared with the theoretical study, empirical studies is fewer. Combined with the existing industrial securiy literature, this paper establish a Monitoring and Warning System of Manufacturing Industrial Security and.This system contains historical, realistic evaluation and prospects of prediction, risk warning about the whole and partial set of manufacturing industrial security.It is Integrated, comprehensive and complete.
In chapter I, we introduces the research background papers, research significance, carding the existing literature of domestic industrial security. This article briefly describes the content, structure, method and innovation.
In chapter II, we delimit the manufacturing industrial security and investigate the connotation and characteristics based on the theory of industry protection industrial injury, industrial control, international competitiveness and national economic security at first. Next, according to the connotation and characteristics of manufacturying industrial security, we analyse a variety of factors (including internal and external factors, macroeconomic factors and micro factors) and its mechanism which influence the Chinese manufacturing industrial security. Finally, conbined with the related theories of monitoring and early warning, build monitoring and warning system framework of our manufacturing industrial security.
In chapter III, we design the appropriate data warehouse according to the requirements of indicators and data for monitoring and warning system of our manufacturing industrial security. In the process of design, build the corresponding dimension table and fact table through a detailed needs analysis and thematic analysis, and use Microsoft SQL Server2000 to achieve the logical model design and the corresponding physical design.
In chapter IV, we card main applications and theoretical developments on the Sentiment Analysis methods, panel data analysis and BP neural network analysis, while briefly describe the application of the three methods on the current industrial security and early warning research, so as to provide a theoretical basis for selection of approachs that monitor and early warn our manufacturing industrial security,.
In chapter V, we take the medical and pharmaceutical products industry for example, use the sentiment analysis methods for monitoring and early warning of manufacturing industrial security. The detailed process are as follows:
The first step, first of all, according to the definition of manufacturing industrial security police sentiment, to find the police element. Secondly, to selecte alarm indicators like the growth rate of sales revenues in all enterprises, capital, labor-intensive, foreign sales strength, export dependence, import dependence in the medical and pharmaceutical products industry, use BP filter to decompose the trendency element and cyclic fluctuations element from time series, inspect changes in alarm indicators, and finally use principal component analysis to simplify alarm indicators, synthesize alarm triggered by internal factors and external factors.
The second step, choose foreign sales strength, export dependence to be benchmark indices from alarm indicators in the medical and pharmaceutical products industry, using the time difference correlation method to selecte leading indicators from the initial index system as warning signs indicators, followed by Granger causality test to filter coincident indicators to construct the final warning signs index system. Finally, use principal component analysis and composite index method to construct the principal component index (ZI) and the leading composite index (CI) of the industrial security in the medical and pharmaceutical products industry.
The third step, analyse the police force and police degree of warning signs indicators selected on the second step , using method of economy early-warning system to show the early warning results of indicators and synthesis index.
In chapter VI ,according to the content, features and performances of manufacturing industrial security in China, we use panal data of 2001-2007 about manufacturing sector to establish two types of panel data regression model: first, inspect entry, exit and loss status of domestic enterprises, use a loss rate of domestic enterprises to be a measure mark of manufacturing industrial security, improve independent variables of model Orr (1974), and add export factors , to establish common fixed(or random) effects regression model. Second, inspect the profits in large and medium-sized domestic and foreign enterprises, divide the value of industrial security into safety and unsafety, add foreign technology strength into independent variables, establish panel logit regression models. By the two types of panel regression models, we survey the influence of foreign capital, export and technology on manufacturing industrial security in China, and compare the difference of industrial security in various sub-sectors of the manufacturing sector, to judge the safety of all industries.
In chapter VII ,based on researches about the existing industrial security, we rich indicators about ecological and energy environment and information environment, establish the manufacturing industrial security evaluation system, and choose the quantitative indicators which can be easily abtained to set a BP neural network . Before seting the BP neural network, we predict all indicators, then use methods of principal component analysis and expert evaluation to assess manufacturing industrial security over the years, and convert the evaluation value into the desired output.
Conclusions and Innovations:
(1) In this paper, based on theories of industry protection, industrial injury, industrial control , international competitiveness of industry and national economic security, we define manufacturing industrial security as follows: under the premise of national economic security, the manufacturing industry develops healthily, efficiently, sustainably and stably as a whole. he sub-sectors of manufactorying industry can maintain a high and stable comparative advantages or core competitiveness in the international market for a long time. the whole and partial manufacturing sector all have the abilities of resisting and preventing the impacts of external factors such as foreign capital, advanced foreign technology and trade barriers, especially national manufacturing industries. General manufacturing industrial security is divided into narrow manufacturing industrial security (that is, the overall manufacturing industrial security) and the manufacturing sub-sector industrial security. According to the definition of the manufacturing industrial security, the manufacturing industrial security meet five basic conditions (or have five performance). These conditions (or performances) are reasonable structure, market stability, energy efficiency, as well as adjustment or control right is not under the threats of external factors. Meanwhile, the manufacturing industrial security also has five characteristics like fuzzy and rank, diversity, systematics, hierarchy and dynamics.
(2) In this paper, we take the medical and pharmaceutical products industry for example, establish the system of the warning signs indicators on manufacturing industrial security by the time difference correlation analysis. The system includes 12 indicators, namely: the growth rate of total assets in foreign-funded enterprises, the growth rate of sales volume in foreign-funded enterprises, foreign scale strength, share of foreign labor, foreign assets strength, growth rate of total retail sales, health care and personal items consumer price index, Chinese and Western medicines and medical care supplies retail price index, ex-factory price index, U.S. consumer price rate of chain Change, the exchange rate index for yuan per dollar, the growth rate of imports. Using above indicators to establish a principal component index and a leading composite index, we find: the cycle and fluctuations of the two indices are consistent, the leading composite index is slightly ahead, it increased slightly in the first half of 2009 and decreased in the second half of 2009, this indicate that the industrial security status of the medical and pharmaceutical products industry will be eased in the future. However, with the influences of coincident indicators about foreign investment issues, the amplitude of the second wave ridge is too large for principal component indices. It means that foreign investment has a large harmful effect on the medical and pharmaceutical products industry in China. This effect increase with time, it may change the good trend predicted by the leading composite index. Using the method of early-warning system to output warning signals for the medical and pharmaceutical products industry, signals show that the synthesis index in 2009 maintend in the weight range.
(3) It is confirmed by the general panal regression model and the binary choice model that: foreign sales strength or foreign export strength has a large negative effect on manufacturing industrial security in China, this negative effect is greater than the negative impact generated by exports independence in domestic enterprises. Further analysis also shows that the negative impact of foreign investmen strength is far more than the positive impact of foreign investment (ie foreign investment promoting overall technical progress in manufacturing industry, or spillover effect). Through the ordinary fixed effect regression model, we also find : without negative impacts of foreign investment and exports, industries like textiles, petroleum processing, coking and nuclear fuel processing industry, chemical materials and chemical products manufacturing, pharmaceutical manufacturing, non-metallic mineral products industry and the ferrous metal smelting and rolling processing industry have a poor security situation, industries like textile and garment, footwear, and caps, leather, fur, feathers (down) and its products, wood processing and wood, bamboo, rattan, palm and grass products, furniture manufacturing, paper and paper products, printing and reproduction of recording media, Educational and Sports Goods, Rubber products, plastic products, fabricated metal products, instruments, and cultural and office machinery manufacturing industry have a good security situation. According to the random effects probit model we also find that: without random disturbance, industres like electronic and communications equipment manufacturing and instrumentation and Cultural Office Machinery Manufacturing industry have a low probability of safety, the rest have a high probability of safety.
(4)The BP neural network is well-trained, tested samples predicted well, the alarm district which the actual value (the actual evaluation) and simulated values of their industrial security belonged to was consistent, the network can alarm the manufacturing industrial security,. Combining with predicted value of all the indicators during 2008 to 2015, we used the neural netwok to proceed early warning. The results showed that the security situation of our manufacturing industry would be fine in the future, we only need to make the mild guard.
本文首先根据现有文献,阐述我国制造业产业安全定义及其内涵,积极寻找影响我国制造业产业安全的各种不利因素;其次根据制造业整体及各子行业自身特点,设计具有代表性、标志性的产业安全评价指标,并收集相应的定量或定性数据,设计制造业产业安全数据仓库。最后,在制造业产业安全数据仓库基础上,根据不同数据类型,选择合适的数据分析和数据挖掘方法对我国制造业整体及其子行业产业安全进行系统、全面的监测预警实证研究。通过比较、综合实证分析结果,发现:外资确实对我国制造业及其各个子行业产业安全产生重大威胁,这种威胁作用超过了外资对我国制造业产生的技术拉动作用,也超过了出口贸易问题对我国制造业产业安全产生的不利影响。
本文创新之处有如下三点:一,运用时差相关分析等方法筛选出制造业子行业产业安全警兆指标,并利用景气指数和景气预警信号系统方法对制造业子行业产业安全进行监测和预警;二,以内资企业亏损率作为制造业产业安全的特征或衡量标准,先运用普通面板回归模型考察了外资强度、出口问题对我国制造业各个子行业产业安全的具体影响,其次运用面板二元选择模型对我国制造业子行业产业安全进行了监测和预警;三,突出了生态与能源环境对我国制造业整体产业安全的影响,结合现有产业安全研究中的代表性评价指标,先独立预测,后用BP神经网络进行制造业整体产业安全监测预警。
Industrial safety has always been an important component of national economic security ,as well as the starting point of the Government's industrial policies, coordinating economic development and safeguarding the national interests. In the background of Economic globalization, regional economic integration and trade and investment integration, the interference and the impact of external factors or international factors on national industrial security become increasingly evident, . As the largest developing and manufacturing state, its survival and development of the manufacturing sector heavily dependent on the level of foreign direct investment and import and export levels, the manufacturing industrial security has become the main and urgent topics of our national economic security and industrial security. At present, academics have not formed a unified theory of industrial security (or further manufacturing industrial security theory), and compared with the theoretical study, empirical studies is fewer. Combined with the existing industrial securiy literature, this paper establish a Monitoring and Warning System of Manufacturing Industrial Security and.This system contains historical, realistic evaluation and prospects of prediction, risk warning about the whole and partial set of manufacturing industrial security.It is Integrated, comprehensive and complete.
In chapter I, we introduces the research background papers, research significance, carding the existing literature of domestic industrial security. This article briefly describes the content, structure, method and innovation.
In chapter II, we delimit the manufacturing industrial security and investigate the connotation and characteristics based on the theory of industry protection industrial injury, industrial control, international competitiveness and national economic security at first. Next, according to the connotation and characteristics of manufacturying industrial security, we analyse a variety of factors (including internal and external factors, macroeconomic factors and micro factors) and its mechanism which influence the Chinese manufacturing industrial security. Finally, conbined with the related theories of monitoring and early warning, build monitoring and warning system framework of our manufacturing industrial security.
In chapter III, we design the appropriate data warehouse according to the requirements of indicators and data for monitoring and warning system of our manufacturing industrial security. In the process of design, build the corresponding dimension table and fact table through a detailed needs analysis and thematic analysis, and use Microsoft SQL Server2000 to achieve the logical model design and the corresponding physical design.
In chapter IV, we card main applications and theoretical developments on the Sentiment Analysis methods, panel data analysis and BP neural network analysis, while briefly describe the application of the three methods on the current industrial security and early warning research, so as to provide a theoretical basis for selection of approachs that monitor and early warn our manufacturing industrial security,.
In chapter V, we take the medical and pharmaceutical products industry for example, use the sentiment analysis methods for monitoring and early warning of manufacturing industrial security. The detailed process are as follows:
The first step, first of all, according to the definition of manufacturing industrial security police sentiment, to find the police element. Secondly, to selecte alarm indicators like the growth rate of sales revenues in all enterprises, capital, labor-intensive, foreign sales strength, export dependence, import dependence in the medical and pharmaceutical products industry, use BP filter to decompose the trendency element and cyclic fluctuations element from time series, inspect changes in alarm indicators, and finally use principal component analysis to simplify alarm indicators, synthesize alarm triggered by internal factors and external factors.
The second step, choose foreign sales strength, export dependence to be benchmark indices from alarm indicators in the medical and pharmaceutical products industry, using the time difference correlation method to selecte leading indicators from the initial index system as warning signs indicators, followed by Granger causality test to filter coincident indicators to construct the final warning signs index system. Finally, use principal component analysis and composite index method to construct the principal component index (ZI) and the leading composite index (CI) of the industrial security in the medical and pharmaceutical products industry.
The third step, analyse the police force and police degree of warning signs indicators selected on the second step , using method of economy early-warning system to show the early warning results of indicators and synthesis index.
In chapter VI ,according to the content, features and performances of manufacturing industrial security in China, we use panal data of 2001-2007 about manufacturing sector to establish two types of panel data regression model: first, inspect entry, exit and loss status of domestic enterprises, use a loss rate of domestic enterprises to be a measure mark of manufacturing industrial security, improve independent variables of model Orr (1974), and add export factors , to establish common fixed(or random) effects regression model. Second, inspect the profits in large and medium-sized domestic and foreign enterprises, divide the value of industrial security into safety and unsafety, add foreign technology strength into independent variables, establish panel logit regression models. By the two types of panel regression models, we survey the influence of foreign capital, export and technology on manufacturing industrial security in China, and compare the difference of industrial security in various sub-sectors of the manufacturing sector, to judge the safety of all industries.
In chapter VII ,based on researches about the existing industrial security, we rich indicators about ecological and energy environment and information environment, establish the manufacturing industrial security evaluation system, and choose the quantitative indicators which can be easily abtained to set a BP neural network . Before seting the BP neural network, we predict all indicators, then use methods of principal component analysis and expert evaluation to assess manufacturing industrial security over the years, and convert the evaluation value into the desired output.
Conclusions and Innovations:
(1) In this paper, based on theories of industry protection, industrial injury, industrial control , international competitiveness of industry and national economic security, we define manufacturing industrial security as follows: under the premise of national economic security, the manufacturing industry develops healthily, efficiently, sustainably and stably as a whole. he sub-sectors of manufactorying industry can maintain a high and stable comparative advantages or core competitiveness in the international market for a long time. the whole and partial manufacturing sector all have the abilities of resisting and preventing the impacts of external factors such as foreign capital, advanced foreign technology and trade barriers, especially national manufacturing industries. General manufacturing industrial security is divided into narrow manufacturing industrial security (that is, the overall manufacturing industrial security) and the manufacturing sub-sector industrial security. According to the definition of the manufacturing industrial security, the manufacturing industrial security meet five basic conditions (or have five performance). These conditions (or performances) are reasonable structure, market stability, energy efficiency, as well as adjustment or control right is not under the threats of external factors. Meanwhile, the manufacturing industrial security also has five characteristics like fuzzy and rank, diversity, systematics, hierarchy and dynamics.
(2) In this paper, we take the medical and pharmaceutical products industry for example, establish the system of the warning signs indicators on manufacturing industrial security by the time difference correlation analysis. The system includes 12 indicators, namely: the growth rate of total assets in foreign-funded enterprises, the growth rate of sales volume in foreign-funded enterprises, foreign scale strength, share of foreign labor, foreign assets strength, growth rate of total retail sales, health care and personal items consumer price index, Chinese and Western medicines and medical care supplies retail price index, ex-factory price index, U.S. consumer price rate of chain Change, the exchange rate index for yuan per dollar, the growth rate of imports. Using above indicators to establish a principal component index and a leading composite index, we find: the cycle and fluctuations of the two indices are consistent, the leading composite index is slightly ahead, it increased slightly in the first half of 2009 and decreased in the second half of 2009, this indicate that the industrial security status of the medical and pharmaceutical products industry will be eased in the future. However, with the influences of coincident indicators about foreign investment issues, the amplitude of the second wave ridge is too large for principal component indices. It means that foreign investment has a large harmful effect on the medical and pharmaceutical products industry in China. This effect increase with time, it may change the good trend predicted by the leading composite index. Using the method of early-warning system to output warning signals for the medical and pharmaceutical products industry, signals show that the synthesis index in 2009 maintend in the weight range.
(3) It is confirmed by the general panal regression model and the binary choice model that: foreign sales strength or foreign export strength has a large negative effect on manufacturing industrial security in China, this negative effect is greater than the negative impact generated by exports independence in domestic enterprises. Further analysis also shows that the negative impact of foreign investmen strength is far more than the positive impact of foreign investment (ie foreign investment promoting overall technical progress in manufacturing industry, or spillover effect). Through the ordinary fixed effect regression model, we also find : without negative impacts of foreign investment and exports, industries like textiles, petroleum processing, coking and nuclear fuel processing industry, chemical materials and chemical products manufacturing, pharmaceutical manufacturing, non-metallic mineral products industry and the ferrous metal smelting and rolling processing industry have a poor security situation, industries like textile and garment, footwear, and caps, leather, fur, feathers (down) and its products, wood processing and wood, bamboo, rattan, palm and grass products, furniture manufacturing, paper and paper products, printing and reproduction of recording media, Educational and Sports Goods, Rubber products, plastic products, fabricated metal products, instruments, and cultural and office machinery manufacturing industry have a good security situation. According to the random effects probit model we also find that: without random disturbance, industres like electronic and communications equipment manufacturing and instrumentation and Cultural Office Machinery Manufacturing industry have a low probability of safety, the rest have a high probability of safety.
(4)The BP neural network is well-trained, tested samples predicted well, the alarm district which the actual value (the actual evaluation) and simulated values of their industrial security belonged to was consistent, the network can alarm the manufacturing industrial security,. Combining with predicted value of all the indicators during 2008 to 2015, we used the neural netwok to proceed early warning. The results showed that the security situation of our manufacturing industry would be fine in the future, we only need to make the mild guard.
引文
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