Industrial aggregation degree evaluation method based on electric power EG index

Abstract

The invention provides an industry aggregation degree evaluation method based on a power EG index, and the method comprises the steps: 1, obtaining enterprise and industry power data of a selected region, and calculating a spatial Gini coefficient G; step 2, calculating a scale ratio of an enterprise in the industry, and calculating a HurVendall index H according to the scale ratio; 3, calculating an electric power EG index of the single industry according to the calculated space Gini coefficient G and the HurVincall index H; and 4, according to the electric power EG index, analyzing an industry gathering condition, and identifying a regional dominant industry. According to the method, the electric power EG index is constructed by combining the electric power data and the center thought of the EG index algorithm, the industrial gathering development condition can be dynamically monitored, and data support is provided for a local information department to make an industrial collaboration policy.

Description

Technical Field

[0001] The present invention relates to the technical field of power data application, and in particular to an industrial agglomeration degree evaluation method based on the power EG index. Background Art

[0002] Industrial agglomeration refers to the phenomenon of a specific industry or multiple related industries being concentrated and clustered in geographical space, reflecting the spatial distribution of the industry and the entire process of the industry's transformation from dispersion to concentration. Industrial agglomeration is conducive to enterprises sharing infrastructure and public services, improving production efficiency, reducing production and transportation costs, and improving economic benefits.

[0003] The methods for identifying and evaluating industrial agglomeration phenomena are mainly concentrated in the fields of economics and management. Common ones include location quotient, Herfindahl index, spatial Gini coefficient, EG index, etc. The location quotient is simple and intuitive, and can quickly identify regional advantageous industries, but it cannot describe the intensity of industrial agglomeration; the Herfindahl index takes into account the differences in industrial scale and can reflect the intensity of industrial agglomeration, but does not take into account the characteristics of industrial spatial distribution; the spatial Gini coefficient reflects the concentration level of industries in spatial distribution, but the calculation is complex and sensitive to extreme values; the EG index aims to solve the distortion problem of the spatial Gini index and combines the Herfindahl index. It can not only reflect the intensity of industrial agglomeration, but also consider the uneven distribution of industrial space, and can more accurately evaluate the degree of industrial agglomeration. However, the calculation of the EG index involves the distribution of each enterprise in the industry, and requires more detailed enterprise distribution and scale data, such as enterprise output value, employment population and other data, which are difficult to obtain. Summary of the invention

[0004] The present invention overcomes the shortcomings of the above-mentioned evaluation method and provides an industrial agglomeration degree evaluation method based on the power EG index. The power data has the characteristics of strong real-time, high accuracy, and fine granularity. Combining the power data and the central idea of ​​the EG index algorithm, the power EG index is constructed, which can dynamically monitor the development of industrial agglomeration and provide data support for local economic and information departments to formulate industrial coordination policies.

[0005] A method for evaluating the degree of industrial agglomeration based on the power EG index includes the following steps:

[0006] Step 1: Obtain enterprise and industry power data in the selected area and calculate the spatial Gini coefficient G;

[0007] Step 2: Calculate the scale share of the enterprise in the industry and calculate the Herfindahl index H based on the scale share;

[0008] Step 3: Calculate the electricity EG index of a single industry based on the calculated spatial Gini coefficient G and Herfindahl index H;

[0009] Step 4: Analyze industrial agglomeration based on the power EG index and identify the region’s leading industries.

[0010] Furthermore, step 1 specifically includes:

[0011] Step 11: Obtain enterprise electricity consumption data and select a list of enterprises that are operating normally based on enterprise ledger information and recent electricity consumption;

[0012] Step 12: Summarize the electricity consumption data of each region and each industry. Specifically, the electricity consumption of each normally operating enterprise is summarized and summed according to the region and industry to obtain the electricity consumption data of each region and each industry;

[0013] Step 13: Calculate the spatial Gini coefficient G based on the electricity consumption data calculated in step 12. Specifically, refer to the calculation method of the spatial Gini coefficient and replace the electricity consumption of the enterprise output value. The spatial Gini coefficient G of the jth industry in the i-th region is i,j The calculation formula is: i,j =(s i,j -x i ) 2 ;

[0014] Among them, s i,j is the ratio of the electricity consumption of the jth industry in the i-th region to the electricity consumption of the jth industry in the province, s i,j =W i,j / W j , where W i,j is the electricity consumption of the jth industry in the i-th region, W j is the electricity consumption of the jth industry in the province; x i is the ratio of the electricity consumption of the ith region to the electricity consumption of the whole province, x i =W i / W, where W i is the electricity consumption of the ith region in the province, W is the cumulative electricity consumption of all industries in the province; the spatial Gini coefficient of the jth industry is G j The calculation formula is as follows, where N is the number of regions in the province:

[0015]

[0016] Furthermore, in step 11, the electricity consumption data of enterprises is obtained, and a list of enterprises operating normally is screened according to the enterprise ledger information and recent electricity consumption, including:

[0017] Collect enterprise ledger data, including enterprise name, account opening time, account cancellation time, electricity usage address, industry, city or county, and filter out the closed enterprises;

[0018] Collect enterprise electricity consumption data, calculate the cumulative electricity consumption in the past six months, define enterprises with zero cumulative electricity consumption in the past six months as zero-degree enterprises, and screen out zero-degree enterprises;

[0019] By excluding deregistered enterprises and zero-degree enterprises, we obtain a list of enterprises operating normally.

[0020] Furthermore, in step 12, it is assumed that there are K industries under the jth industry in the i-th region, then the electricity consumption of the jth industry in the i-th region is w k It represents the electricity consumption of the k-th enterprise in a period of time. The time range is monthly, quarterly or annual. It is obtained by summing up the daily electricity consumption ED, monthly electricity consumption EM or quarterly electricity consumption ES, that is, or or in On this basis, the electricity consumption of the jth industry in the province is W j , which is the sum of the electricity consumption of industry j in all N regions of the province, that is, The electricity consumption of the i-th region in the province is W i , which represents all M in the region i The sum of the electricity consumption of the industries is Electricity consumption in the province Where N is the number of regions in the province, and M is the number of industries in the province.

[0021] Furthermore, step 2 specifically includes:

[0022] Step 21: Calculate the power scale ratio z j,k , z j,k =w k / W j *100%, where z j,k is the proportion of electricity volume of enterprise k in industry j, w k is the electricity consumption of enterprise k, W j is the electricity consumption of industry j;

[0023] Step 22: Calculate the Herfindahl index H based on the electricity scale proportion calculated in step 21. The Herfindahl index is the sum of the squares of the market shares of all enterprises in an industry, with a value between 0 and 1. The larger the value, the higher the degree of geographical agglomeration of the industry. The calculation formula of the Herfindahl index H is as follows:

[0024]

[0025] Among them, H j is the Herfindahl index of industry j, and n is the number of enterprises in industry j.

[0026] Furthermore, the electricity EG index EG of a single industry in step 3 j The calculation formula is as follows:

[0027]

[0028] Among them EG j represents the electricity EG index of the jth industry, G j The space representing the jth industry

[0029] The Gini coefficient, x i is the ratio of the electricity consumption of the ith region to the electricity consumption of the whole province, H j is the Herfindahl index for industry j.

[0030] Furthermore, step 4 specifically includes:

[0031] Step 41: Calculate the EG index of J industries in the province, and calculate the agglomeration index EG of each industry according to steps 1-3 j , j=1,2,..J, the larger the EG index is, the higher the agglomeration level of the industry in the region is;

[0032] Step 42: Analyze the industrial agglomeration situation and identify the leading industries in the region based on the calculation results of the industrial EG index. Specifically, set the judgment threshold. i <λ1, industry i is of low agglomeration; λ1≤EG i <λ2, industry i is moderately concentrated; EG i When ≥λ2, industry i is highly concentrated.

[0033] Furthermore, λ1 is set to 0.05 and λ2 is set to 0.1

[0034] The present invention has the following beneficial effects:

[0035] The present invention obtains enterprise and industry power data of the selected area, determines the spatial Gini coefficient, calculates the Herfindahl index according to the scale proportion of the enterprise in the industry, integrates the Gini coefficient and the Herfindahl index, constructs the EG index from the perspective of power, analyzes the industrial agglomeration situation, and identifies the leading industries in the region; gives full play to the advantages of strong real-time and high accuracy of power data, comprehensively considers the characteristics of the number of enterprises, electricity consumption scale, industry distribution, etc., avoids directly obtaining data such as enterprise output value and employment population, and is flexible and convenient in calculation. Daily, monthly, and annual data can be selected for calculation as needed, and the changes in industrial migration under different time scales are studied. The development trend of industrial agglomeration is continuously tracked and evaluated, and data support is provided for local economic and information departments to formulate industrial coordination policies. BRIEF DESCRIPTION OF THE DRAWINGS

[0036] Figure 1 A flowchart of an industrial agglomeration degree evaluation method based on the power EG index provided in an embodiment of the present invention;

[0037] Figure 2 A flowchart of calculating the Gini coefficient in an embodiment of the present invention;

[0038] Figure 3 The flowchart of calculating the Herfindahl Index in an embodiment of the present invention is shown in FIG. DETAILED DESCRIPTION

[0039] In order to make the purpose, technical solution and advantages of the embodiments of the present invention clearer, the technical solution in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0040] Taking the industrial agglomeration of various cities in a province in October 2024 as an example, the technical solution of the embodiment of the present invention is further introduced.

[0041] like Figure 1 As shown, the embodiment of the present invention provides an industrial agglomeration degree evaluation method based on the power EG index, which specifically includes the following steps:

[0042] Step 1: Obtain enterprise and industry power data for the selected area and calculate the spatial Gini coefficient G. Figure 2 As shown, the steps for calculating the spatial Gini coefficient G are as follows:

[0043] Step S101: Obtain enterprise electricity consumption data, and filter the list of enterprises that are operating normally based on the enterprise ledger information and recent electricity consumption. Collect enterprise ledger data, including fields such as enterprise name, industry, account opening time, account cancellation time, electricity usage address, city (district or county), electricity usage category, contract capacity, operating capacity, voltage level, enterprise status, etc. Table 1 lists the key fields. Filter out the cancelled enterprises based on user ledger information. Collect enterprise electricity consumption data, calculate the cumulative electricity consumption in the past six months, define enterprises with a cumulative electricity consumption of zero in the past six months as zero-degree enterprises, and filter out zero-degree enterprises. By excluding cancelled enterprises and zero-degree enterprises, a list of enterprises that are operating normally is obtained.

[0044] Table 1 Example of enterprise ledger

[0045]

[0046]

[0047] Step S102: Summarize the electricity consumption data of each region and industry. According to the region and industry, the electricity consumption of each enterprise is summarized and summed to obtain the electricity consumption data of each region and industry. The electricity consumption can be monthly, quarterly, or annual, which can be flexibly selected according to actual needs. Assuming that there are K industries under the jth industry in the i-th region, the electricity consumption of the jth industry in the i-th region is w k It represents the electricity consumption of the k-th enterprise in a period of time. The time range can be monthly, quarterly or annual. It is obtained by summing up the daily electricity consumption ED, monthly electricity consumption EM or quarterly electricity consumption ES, that is, or or in On this basis, the electricity consumption of the jth industry in the province is W j , which can be expressed as the sum of the electricity consumption of industry j in all N regions of the province, that is, The electricity consumption of the i-th region in the province is W i , which can be expressed as all M in the region i The sum of the electricity consumption of the industries is Electricity consumption in the province Where N is the number of regions in the province, and M is the number of industries in the province.

[0048] Table 2 Examples of electricity consumption in various regions and industries

[0049] area industry Company Name This month's electricity Electricity this quarter ...... City 1 industry1 Company1 EM1 ES1 ...... City 1 industry2 Company2 EM2 ES2 ...... City 2 industry1 Company3 EM3 ES3 ...... City 3 industry3 Company4 EM4 ES4 ...... ...... ...... ...... ...... ...... ......

[0050] Step S103: Calculate the spatial Gini coefficient G. Referring to the calculation method of the spatial Gini coefficient, replace the electricity consumption of the enterprise output value, and the spatial Gini coefficient G of the jth industry in the i-th region is i,j The calculation formula is: i,j =(s i,j -x i ) 2 .

[0051] Among them, s i,j is the ratio of the electricity consumption of the jth industry in the i-th region to the electricity consumption of the jth industry in the province, s i,j =W i,j / W j , where W i,j is the regional industrial electricity consumption, indicating the electricity consumption of the jth industry in the ith region, W j is the electricity consumption of the province’s industries, indicating the electricity consumption of the jth industry in the province. i is the ratio of the electricity consumption of the ith region to the electricity consumption of the whole province, x i =W i / W, where W iis the regional electricity consumption, indicating the electricity consumption of the i-th region in the province, and W is the provincial electricity consumption, indicating the electricity consumption of all industries in the province. The spatial Gini coefficient G of the j-th industry j The calculation formula is as follows, where N is the number of regions in the province.

[0052]

[0053] Taking industry j as an example, the calculation results of the corresponding spatial Gini coefficient G are shown in the following table.

[0054] Table 3. Spatial Gini coefficient calculation example

[0055]

[0056] Step 2: Calculate the scale of the enterprise in the industry and use it as a basis to calculate the Herfindahl index H. Figure 3 As shown, the steps for calculating the Herfindahl index H are as follows:

[0057] Step S201: Calculate the scale proportion of the enterprise in the industry. In the actual calculation process, it is difficult to obtain data such as enterprise output value and employment population that can reflect the market scale of the enterprise in real time. Therefore, the enterprise electricity consumption is used as an indirect substitute for the enterprise market scale to calculate the scale proportion z j,k .z j,k =w k / W j *100%, where z j,k is the proportion of electricity volume of enterprise k in industry j, w k is the electricity consumption of enterprise k, W j is the electricity consumption of industry j. When calculating the proportion of electricity scale, in order to maintain comparability, the time dimension of enterprise and industry electricity consumption must be consistent, that is, monthly electricity, quarterly electricity or annual electricity. For example, using the monthly electricity consumption of enterprises as the basic data, there are n enterprises under industry j, and the proportion of the scale of these enterprises is shown in Table 4.

[0058] Table 4 Example of calculation of enterprise scale ratio

[0059] serial number Company Name Industry Monthly electricity consumption of the enterprise Monthly industrial electricity consumption Electricity scale share% 1 Company1 industryj 21939314 22879170 95.8921 2 Company2 industryj 140070 22879170 0.6122 3 Company3 industryj 89253 22879170 0.3901 4 Company4 industryj 710533 22879170 3.1056

[0060] Step S202: Calculate the Herfindahl index H. The Herfindahl index is the sum of the squares of the market shares of all enterprises in an industry, and its value is between 0 and 1. The larger the value, the higher the degree of geographical agglomeration of the industry. The calculation formula of the Herfindahl index H is as follows.

[0061]

[0062] Among them, H jis the Herfindahl index of industry j, and n is the number of enterprises in industry j.

[0063] Step 3: Calculate the electricity EG index for each industry. EG j represents the electricity EG index of the jth industry, x i is the ratio of the electricity consumption of the ith region to the electricity consumption of the whole province, H j is the Herfindahl index for industry j.

[0064] Step 4: Based on the EG index results, analyze industrial agglomeration and identify the region’s leading industries.

[0065] Step 41: Calculate the EG index of J industries in the province. According to the methods described in steps 1, 2, and 3, calculate the agglomeration index EG of each industry. j , j=1,2,..J. The larger the EG index is, the higher the agglomeration level of the industry in the region is. The calculation results of the EG index are shown in Table 5.

[0066] Table 5 EG index calculation example

[0067]

[0068]

[0069] Step 42: Analyze the industrial agglomeration situation and identify the leading industries in the region based on the calculation results of the industry EG index. Set the judgment threshold. i <λ1, industry i is of low agglomeration; λ1≤EG i <λ2, industry i is moderately concentrated; EG iWhen ≥λ2, industry i is highly concentrated. In practical application, according to the relevant literature and actual calculation results of indicators, λ1 is set to 0.05 and λ2 is set to 0.1. Some results are shown in Table 6. City A, as the "Phosphorus Capital of Central China", is rich in phosphate resources and has the only two yellow phosphorus enterprises in the province, and the scale of the enterprises is very different. Therefore, the calculated EG index of the yellow phosphorus industry is the highest; the ceramic industry in cities B, C, D, and E is rich in raw materials, and the government develops the ceramic industry as a local advantageous industry and characteristic industry; City F is rich in hydropower resources, and aluminum smelting is a high-energy-consuming industry. Choosing City F can reduce the production cost and carbon reduction pressure of enterprises; City G was built and developed because of cars. It is one of the regions with the most complete automobile industry chain and the highest degree of industrial cluster in the country. The automobile industry is also the largest industry in City A. The automobile engine manufacturing industry in these two cities has a high degree of agglomeration; City H is an important salt production base in the country, and the reserves of rock salt mineral resources rank first in the province, and the salt mining industry is concentrated; City F and City I vigorously promote green shipping, and promote the application of new energy ships through the layout and construction of port shore power. The above cities have advantages such as rich resources, policy inclination, and complete infrastructure, so the industrial agglomeration phenomenon is relatively obvious, and the EG index also verifies the relevant conclusions.

[0070] Table 6 Ranking of industries with high agglomeration degree in October 2014

[0071]

[0072]

[0073] The above is only a specific embodiment of the present invention, but the protection scope of the present invention is not limited thereto. Any changes or substitutions that can be easily thought of by a person skilled in the art within the technical scope disclosed by the present invention should be included in the protection scope of the present invention. Therefore, the protection scope of the present invention should be based on the protection scope of the claims.

Claims

1. A method for evaluating the degree of industrial agglomeration based on the power EG index, characterized in that: The steps include: Step 1: Obtain enterprise and industry power data in the selected area and calculate the spatial Gini coefficient G; Step 2: Calculate the scale share of the enterprise in the industry and calculate the Herfindahl index H based on the scale share; Step 3: Calculate the electricity EG index of a single industry based on the calculated spatial Gini coefficient G and Herfindahl index H; Step 4: Analyze industrial agglomeration based on the power EG index and identify the region’s leading industries.

2. The method for evaluating the degree of industrial agglomeration based on the power EG index according to claim 1, characterized in that: Step 1 specifically includes: Step 11: Obtain enterprise electricity consumption data and select a list of enterprises that are operating normally based on enterprise ledger information and recent electricity consumption; Step 12: Summarize the electricity consumption data of each region and each industry. Specifically, the electricity consumption of each normally operating enterprise is summarized and summed according to the region and industry to obtain the electricity consumption data of each region and each industry; Step 13: Calculate the spatial Gini coefficient G based on the electricity consumption data calculated in step 12. Specifically, refer to the calculation method of the spatial Gini coefficient and replace the electricity consumption of the enterprise output value. The spatial Gini coefficient G of the jth industry in the i-th region is i,j The calculation formula is: i,j =(s i,j -x i ) 2 ; Among them, s i,j is the ratio of the electricity consumption of the jth industry in the i-th region to the electricity consumption of the jth industry in the province, s i,j =W i,j / W j , where W i,j is the electricity consumption of the jth industry in the i-th region, W j is the electricity consumption of the jth industry in the province; x i is the ratio of the electricity consumption of the ith region to the electricity consumption of the whole province, x i =W i / W, where W i is the electricity consumption of the ith region in the province, W is the cumulative electricity consumption of all industries in the province; the spatial Gini coefficient of the jth industry is G j The calculation formula is as follows, where N is the number of regions in the province:

3. The method for evaluating the degree of industrial agglomeration based on the power EG index according to claim 2 is characterized in that: Step 11: Obtain the enterprise electricity consumption data and select a list of enterprises that are operating normally based on the enterprise ledger information and recent electricity consumption, including: Collect enterprise ledger data, including enterprise name, account opening time, account cancellation time, electricity usage address, industry, city or county, and filter out the closed enterprises; Collect enterprise electricity consumption data, calculate the cumulative electricity consumption in the past six months, define enterprises with zero cumulative electricity consumption in the past six months as zero-degree enterprises, and screen out zero-degree enterprises; By excluding deregistered enterprises and zero-degree enterprises, we obtain a list of enterprises operating normally.

4. The method for evaluating the degree of industrial agglomeration based on the power EG index according to claim 2 is characterized in that: In step 12, assume that there are K industries under the jth industry in the i-th region, then the electricity consumption of the jth industry in the i-th region is w k It represents the electricity consumption of the k-th enterprise in a period of time. The time range is monthly, quarterly or annual. It is obtained by summing up the daily electricity consumption ED, monthly electricity consumption EM or quarterly electricity consumption ES, that is, or or in On this basis, the electricity consumption of the jth industry in the province is W j , which is the sum of the electricity consumption of industry j in all N regions of the province, that is, The electricity consumption of the i-th region in the province is W i , which represents all M in the region i The sum of the electricity consumption of the industries is Electricity consumption in the province Where N is the number of regions in the province, and M is the number of industries in the province.

5. The method for evaluating the degree of industrial agglomeration based on the power EG index according to claim 1, characterized in that: Step 2 specifically includes: Step 21: Calculate the power scale ratio z j,k , z j,k =w k / W j *100%, where z j,k is the proportion of electricity volume of enterprise k in industry j, w k is the electricity consumption of enterprise k, W j is the electricity consumption of industry j; Step 22: Calculate the Herfindahl index H based on the electricity scale proportion calculated in step 21. The Herfindahl index is the sum of the squares of the market shares of all enterprises in an industry, with a value between 0 and 1. The larger the value, the higher the degree of geographical agglomeration of the industry. The calculation formula of the Herfindahl index H is as follows: Among them, H j is the Herfindahl index of industry j, and n is the number of enterprises in industry j.

6. The method for evaluating the degree of industrial agglomeration based on the power EG index according to claim 5 is characterized in that: Step 3: Electricity EG Index of Individual Industries j The calculation formula is as follows: Among them EG j represents the electricity EG index of the jth industry, G j represents the spatial Gini coefficient of the jth industry, x i is the ratio of the electricity consumption of the ith region to the electricity consumption of the whole province, H j is the Herfindahl index for industry j.

7. The method for evaluating the degree of industrial agglomeration based on the power EG index according to claim 1 or 6, characterized in that: Step 4 specifically includes: Step 41: Calculate the EG index of J industries in the province, and calculate the agglomeration index EG of each industry according to steps 1-3 j , j=1,2,..J, the larger the EG index is, the higher the agglomeration level of the industry in the region is; Step 42: Analyze the industrial agglomeration situation and identify the leading industries in the region based on the calculation results of the industrial EG index. Specifically, set the judgment threshold. i <λ1, industry i is of low agglomeration; λ1≤EG i <λ2, industry i is moderately concentrated; EG i When ≥λ2, industry i is highly concentrated.

8. The method for evaluating the degree of industrial agglomeration based on the power EG index according to claim 7, characterized in that: λ1 is set to 0.05 and λ2 is set to 0.1.

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