# The Political Connections and Commercial Credit Financing of Privately Held Companies

Authors: Huan Liu; Juanjuan Luo; Defa Hu
Journal: Mathematical Problems in Engineering
 (2022)

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## Abstract

In order to better assist privately held companies in obtaining commercial credit financing, this article selected 1,000 Chinese privately held companies in the manufacturing industry that went public from 2008 to 2018 and discussed whether a company’s political connections serve as a resource-promoting effect on its commercial credit financing. This article proposed relevant hypotheses based on theoretical analysis and performed the descriptive statistical analysis and Hausman test analysis on all variables based on the unbalanced panel data of public companies when designing the study. Then, this article used a fixed model for regression estimation of the main effects, and the results showed that a company's political connections significantly reduce its possibility of obtaining commercial credit from suppliers. This article further analyzed the regulatory effects of market environmental factors and corporate transparency-related boundary factors and concluded that the process of marketization, the degree of market competition, and the transparency of companies will significantly weaken the inhibiting effect of political connections on commercial credit financing.


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## Body

## 1. Introduction

Building political connections, as an informal social relationship between companies and government and its agents or as a corporate social capital, has drawn much attention from scholars in recent years [1], especially in emerging markets, where the market mechanism is not complete and continued government intervention, often becomes an important nonmarket-oriented strategic means for companies to seek economic development. For survival and development, many SMEs in China would like to hire directors or executives with government backgrounds or become NPC deputies or CPPCC members to enhance their competitive advantages in the market by gaining more key resources like bank loans and tax incentives [2].Although the findings on the correlation between political connections and company performance vary depending on the definition of variables, research background, and target population, the resource-promoting effect of political connections on company performance has been generally recognized by scholars. Studies have shown that political connections can help companies obtain scarce government-controlled resources and enjoy privileges in terms of government subsidies, bank loans, tax incentives, and market access and protections [3]. Especially for financing activities, scholars generally believe that when companies request regulatory approvals to access public resources, having political connections can help them to encounter fewer bank loan setbacks and even bear lower interest rates and mortgage requirements [4].Nevertheless, funds from banks or capital markets only account for a small portion of companies’ financing needs in emerging markets. Especially for privately held companies at the end of credit capital allocation, informal finance such as commercial credit occupies a relatively large proportion in their financing structure [5]. Moreover, compared with other financing methods, commercial credit has lower risk and lower threshold, which drive the buyer and the seller to choose commercial credit instead of other financing methods when facing financing constraints. Especially in China, information asymmetry presents an important obstacle to company financing because of incomplete market regulation and inefficient property rights protection. The advantages of commercial credit in financing are more obvious by overcoming the information asymmetry between the lending and borrowing parties. [6]. While most research focuses on the impact of political connections on formal financing activities, the impact on informal financial channels has received less attention (i.e., commercial credit). Therefore, under the circumstances of an immature market mechanism and an incomplete regulatory environment, this article questions whether the resource-promoting effect of political connections still exists for such informal financing activities, such as commercial credit.Therefore, the main task of this article is to explore the role of political association in business credit financing from empirical analysis, to verify whether it is helpful to alleviate the financing constraints of private enterprises through informal financing channels, and to explore the market environment factors and the possible regulatory role of enterprises’ own factors. Based on the sample of 1000 private listed companies in Shanghai and Shenzhen A stock manufacturing industry from 2008 to 2018, we empirically verified the theoretical expectation. In this article, the private enterprises of the manufacturing industry are selected as the research object mainly for the following two considerations: first, there is a certain equity relationship between state-owned enterprises and the government and relevant agencies. The existence of this natural government connection will influence the analysis of informal political connection to some extent in this article; secondly, the equity nature of state-owned enterprises determines their unique position in resource allocation, and their dependence on informal financing is relatively small; thirdly, manufacturing enterprises are more closely linked upstream and downstream relationship and the use of commercial credit is more frequent, which provides a better research object for us to analyze the influencing factors of commercial credit financing. This article finds that the political association of private enterprises will restrain the acquisition of commercial credit financing. The marketization process and the degree of market competition will weaken the inhibitory effect of political connection on the acquisition of commercial credit; the transparency of enterprises themselves will also undermine the inhibition effect of political connection on the possibility of commercial credit acquisition.The structure of this article is as follows: firstly, the literature is reviewed and theoretical analysis is carried out, and the relevant assumptions are put forward on this basis; then, the research design process is introduced and the statistical test is carried out based on the data of listed companies; then, the main effect regression results are analyzed; then further discussion is carried out, the adjustment of related boundary factors is analyzed, and the empirical test is carried out; finally, the results are discussed and summarized.


## 2. Theoretical Analysis and Research Hypothesis

Compared with state-owned enterprises, private enterprises want to build the political connection to make up for their inherent defects in resource allocation, market competitiveness, and so on, and the informal social relations with government departments are constructed by employing directors or executives with government backgrounds, becoming deputies to the People’s Congress or CPPCC members. Most of the existing studies on the aspect of resource acquisition verify the role of political associations in promoting enterprises to obtain government subsidies, bank loans, tax concessions, and other scarce resources [2–6]. In addition to such resource effects, however, political connections can act as a signaling mechanism for transmission the reputation and position advantage of the enterprise in the course of trading.Commercial credit financing is an indirect credit behavior between enterprises due to the separation of funds and goods in time and space in the process of commodity trading. It appears when the supplier delivers the goods to the customer but does not recover the income immediately, it is a short-term financing method accompanied by natural transactions [6]. Compared to the credit of formal intermediaries such as banks, commercial credit is an implicit contract between suppliers and customers. The acquisition of commercial credit financing usually depends on the evaluation of customers by suppliers and often does not require third-party guarantees. In order to guarantee the payment of trade credit, suppliers usually rely on the evaluation of customer reputation and contract law mandatory to extend trade credit [7]. Therefore, the credibility of the customer is essential for the supplier to assess the granting of trade credit. Existing research also shows that the relationship between suppliers plays an important role when they decide whether to provide trade credit to customers [8]. Some research indicates that enterprise political connection, although this type of informal social relationship with the government cannot directly affect the relationship between enterprises, the signal effect it produces can enhance the credit base of customer enterprises on the supplier side to some extent, and its mechanism mainly includes two aspects: first, the advantages of political connection in resource allocation and market access help to improve the operation level and market recognition of affiliated enterprises, increase the market reputation of affiliated enterprises to a certain extent, and increase the willingness of suppliers to provide commercial credit; secondly, suppliers will consider their market relations in addition to their marketability when evaluating their customers’ reputation. Hence, based on the credibility of the above-mentioned political links, we propose hypothesis H1A: H1A: political connections can enhance the possibility of private enterprises obtaining commercial credit.As with financing formal financial institutions, the granting of commercial credit needs to consider not only the credit base of the customer but also the risk of default that it may have in the future, that is, the solvency of such credit loans. Engbers and Rubin pointed out that once customers had overdue payments of commercial credit, suppliers would execute contract requirements according to their own trading position in such supplier-customer relationships [7], and the effect of contract execution is often protected by the local legal system. Studies have also shown that the improvement of the legal and regulatory system could help to improve the execution of contracts, which in turn would help to stimulate the provision and use of commercial credit in the course of trading [9].In the above, we mentioned that scholars have made a lot of analysis on the role of resource promotion and market access of political connection. With the development of research, some scholars have also discussed the regulatory convenience and asylum role provided to affiliated enterprises, and this convenience and asylum role would often reduce the effectiveness of their environmental legal system. Yang et al. found that when the politically affiliated enterprises were involved in commercial fraud, it would take longer for the relevant regulatory authorities to determine the fraud and impose the corresponding penalties; that is to say, the political connection will weaken the efficiency of law enforcement protected by investors [10]. When the commercial credit of the affiliated enterprise is overdue, the political connection may reduce the efficiency of contract execution and reduce the possibility of loan recovery of the supplier by providing it with certain regulatory asylum. Therefore, in the context of contract enforcement, suppliers may maintain a more cautious attitude in maintaining a cooperative relationship with affiliated enterprises while reducing the possibility of providing business credit to affiliated enterprises, taking into account this kind of regulatory convenience and protection provided by political connections. Based on the above analysis, we propose H1B:H1B: political connections will reduce the possibility of private enterprises obtaining commercial credit.


## 3. Research Design

### 3.1. Sample Selection and Data Source

In this article, the 2008/2018 mainboard manufacturing private listed companies are taken as the initial sample, and the original data are processed as follows:(1) selected the pharmaceutical manufacturing enterprises, automobile manufacturing enterprises, and other manufacturing enterprises, which account for a large proportion of private enterprises. (2) The sample of the missing data of the company was eliminated; (3) the samples of abnormal data companies were excluded; (4) the samples of companies with abnormal operating conditions during the observation period were excluded. In addition, in order to eliminate the influence of abnormal values on regression results, all continuous variables except virtual variables are treated with 1% winsorization. The final sample included 4773 observations from 1,000 listed companies. At the same time, in order to eliminate the possible endogenous, all independent variables, intermediary variables, and control variables are delayed. The dependent variables are based on the observation data from 2009 to 2018, and the independent variables are based on the observation data from 2008 to 2017. The data sources of this article include Guotai’an database and the annual report of listed companies.


### 3.2. Study Design

Hypothesis H1A and hypothesis H1B are two opposite hypotheses about the relationship between political relevance and enterprise business credit based on different theoretical viewpoints, and we design the following model (1) to test it. When the coefficient of the political correlation variable is significantly positive, H1A is established, and when it is significantly negative, H1B is established.(1)Trade_Creditit=α0+α1Politicalit−1+∑k=1nβiControlsit−1+μi+εit,where i represents the individual, t represents the annual identity, and n represents the number of control variables. Trade_Credit represents the business credit of the enterprise, Political represents the political association variable, and Controls represents other control variables, including the variables listed in Table 1.Table 1
Definition and measurement of variables.
Variable nameComputational methodDependent variable1. Commercial standing(Enterprise accounts payable + notes payable)/general assetsArgument2. Political affiliationNumber of management personnel with a political background in the enterpriseControlled variable3. Enterprise ageLogobservation−year of incorporation4. Enterprise sizeLog(total assets)5. Corporate leverageTotal indebtedness/shareholders’ equity6. Fixed assetsTotal fixed assets/general assets7. Capital intensityCapital charges/sales income8. Corporate performanceNet margin/Average shareholder equity balance9. Equity concentrationTop five shareholders share the sum of square10. CEO two in oneCEO is the same as the general manager; assign to 1, otherwise 011. Business linkageLog( number of company executives in other companies)13. Insolvency distanceWind database algorithm for enterprise bankruptcy distance12. Regional GNPRegional gross national product


### 3.3. Definition and Interpretation of Variables

(1)
The explained variable is commercial credit (Trade_Credit). Based on the definition of commercial credit defined by Petersen & Rajan and Fisman & Love, this article used the sum of enterprise accounts payable and noted payable to measure the total assets of the enterprise.(2)
Explanatory variable (political) is the political connection, the number of managers with government background in the management team. According to the definition of political connection defined by some scholars [10], we determined the political connection background of management members (directors, members of the executive team, and members of the supervisory board): if managers were current or former government officials, deputies to the people’s Congress, CPPCC members, party representatives, etc., then the number of management personnel with political background is counted and political connection measurement results are obtained.(3)
Control variables are as follows. According to the existing research, this article used enterprise age and size, the ratio of corporate leverage to fixed assets, enterprise capital intensity, enterprise performance and equity concentration, the integration of CEO two jobs, and the distance between business connection and bankruptcy and regional GNP to control the influence of the remaining factors. The specific variable definitions and measures are shown in Table1.


## 3.1. Sample Selection and Data Source

In this article, the 2008/2018 mainboard manufacturing private listed companies are taken as the initial sample, and the original data are processed as follows:(1) selected the pharmaceutical manufacturing enterprises, automobile manufacturing enterprises, and other manufacturing enterprises, which account for a large proportion of private enterprises. (2) The sample of the missing data of the company was eliminated; (3) the samples of abnormal data companies were excluded; (4) the samples of companies with abnormal operating conditions during the observation period were excluded. In addition, in order to eliminate the influence of abnormal values on regression results, all continuous variables except virtual variables are treated with 1% winsorization. The final sample included 4773 observations from 1,000 listed companies. At the same time, in order to eliminate the possible endogenous, all independent variables, intermediary variables, and control variables are delayed. The dependent variables are based on the observation data from 2009 to 2018, and the independent variables are based on the observation data from 2008 to 2017. The data sources of this article include Guotai’an database and the annual report of listed companies.


## 3.2. Study Design

Hypothesis H1A and hypothesis H1B are two opposite hypotheses about the relationship between political relevance and enterprise business credit based on different theoretical viewpoints, and we design the following model (1) to test it. When the coefficient of the political correlation variable is significantly positive, H1A is established, and when it is significantly negative, H1B is established.(1)Trade_Creditit=α0+α1Politicalit−1+∑k=1nβiControlsit−1+μi+εit,where i represents the individual, t represents the annual identity, and n represents the number of control variables. Trade_Credit represents the business credit of the enterprise, Political represents the political association variable, and Controls represents other control variables, including the variables listed in Table 1.Table 1
Definition and measurement of variables.
Variable nameComputational methodDependent variable1. Commercial standing(Enterprise accounts payable + notes payable)/general assetsArgument2. Political affiliationNumber of management personnel with a political background in the enterpriseControlled variable3. Enterprise ageLogobservation−year of incorporation4. Enterprise sizeLog(total assets)5. Corporate leverageTotal indebtedness/shareholders’ equity6. Fixed assetsTotal fixed assets/general assets7. Capital intensityCapital charges/sales income8. Corporate performanceNet margin/Average shareholder equity balance9. Equity concentrationTop five shareholders share the sum of square10. CEO two in oneCEO is the same as the general manager; assign to 1, otherwise 011. Business linkageLog( number of company executives in other companies)13. Insolvency distanceWind database algorithm for enterprise bankruptcy distance12. Regional GNPRegional gross national product


## 3.3. Definition and Interpretation of Variables

(1)
The explained variable is commercial credit (Trade_Credit). Based on the definition of commercial credit defined by Petersen & Rajan and Fisman & Love, this article used the sum of enterprise accounts payable and noted payable to measure the total assets of the enterprise.(2)
Explanatory variable (political) is the political connection, the number of managers with government background in the management team. According to the definition of political connection defined by some scholars [10], we determined the political connection background of management members (directors, members of the executive team, and members of the supervisory board): if managers were current or former government officials, deputies to the people’s Congress, CPPCC members, party representatives, etc., then the number of management personnel with political background is counted and political connection measurement results are obtained.(3)
Control variables are as follows. According to the existing research, this article used enterprise age and size, the ratio of corporate leverage to fixed assets, enterprise capital intensity, enterprise performance and equity concentration, the integration of CEO two jobs, and the distance between business connection and bankruptcy and regional GNP to control the influence of the remaining factors. The specific variable definitions and measures are shown in Table1.


## 4. Study Results and Analysis

### 4.1. Descriptive Statistics and Correlation Analysis

Before performing regression analysis, we performed the descriptive statistical analysis and correlation analysis for all variables. The mean, standard deviation, and Pearson correlation coefficients of all variables are shown in Table2. From Table 2, from 2008 to 2018, it can be seen that the average commercial credit sales income ratio of private listed companies in the manufacturing industry in China is 24.1%, the overall commercial credit financing level is high, and its standard deviation is 0.161, which indicates that there are some differences in the commercial credit acquisition of each enterprise, an average of 1.775 (SD = 0.305) for simultaneous political connections. For the number of two-phase relations of each explanatory variable, its maximum absolute value of the pair is 0.394 (<0.6), indicating that there is no serious problem of multiple collinearity between variables.Table 2
Descriptive statistics and correlation of main variables.
VariableAverage valueStandard deviation12341. Commercial standing0.2410.16112. Political affiliation1.7750.305−0.054∗∗∗13. Enterprise age2.6974.556−0.032∗∗−0.049∗∗∗14. Enterprise size9.2680.3910.092∗∗∗0.101∗∗∗0.204∗∗∗15. Corporate leverage0.3350.1830.366∗∗∗0.045∗∗∗0.190∗∗∗0.394∗∗∗6. Fixed assets0.2030.117−0.028∗0.085∗∗∗0.087∗∗∗0.065∗∗∗7. Capital intensity0.1450.1450.100∗∗∗0.038∗∗−0.150∗∗∗−0.061∗∗∗8. Corporate performance0.0890.092−0.211∗∗∗0.017∗∗∗−0.103∗∗∗0.142∗∗∗9. Equity concentration0.1550.103−0.081∗∗∗0.032∗∗−0.120∗∗∗0.032∗∗10. CEO two in one0.3950.4890.003−0.076∗∗∗−0.058∗∗∗−0.100∗∗∗11. Business linkages3.2272.0980.061∗∗∗0.163∗∗∗0.098∗∗∗0.245∗∗∗12. Insolvency distance2.0980.825−0.361∗∗∗−0.093∗∗∗−0.107∗∗∗−0.392∗∗∗13. Regional GNP4.7200.1770.096∗∗∗−0.094∗∗∗0.128∗∗∗0.134∗∗∗Variable56789105. Corporate leverage16. Fixed assets0.215∗∗∗17. Capital intensity−0.130∗∗∗0.112∗∗∗18. Corporate performance−0.104∗∗∗−0.196∗∗∗−0.078∗∗∗19. Equity concentration−0.131∗∗∗−0.067∗∗∗0.0140.194∗∗∗110. CEO two in one−0.079∗∗∗−0.090∗∗∗0.070∗0.036∗∗∗0.040∗∗111. Business linkages0.136∗∗∗0.028∗0.004−0.068∗∗−0.072∗∗∗−0.139∗∗∗12. Insolvency distance−0.301∗∗∗−0.258∗∗∗0.063∗∗∗0.2010.126∗0.077∗13. Regional GNP−0.039∗∗−0.029∗−0.044∗∗∗−0.0240.052∗∗∗0.041∗∗∗Note.∗, ∗∗, and ∗∗∗ represent significant levels of 10%, 5%, and 1%, respectively (double-tailed test).


### 4.2. Regression Analysis

Because of the nonequilibrium panel data used in this article, in order to control the possible endogenous and individual effects, the independent variables and dependent variables are processed in a lag phase. At the same time, based on Hausman test results, a fixed model is used for regression estimation. Table3 is based on the multiple regression results between political correlation and enterprise commercial credit. In order to test the way in which the intensity of political connection acts on commercial credit, we add a model of political correlation variables to form a model (1–2) based on model (1); the regression results show that the coefficient of political correlation is significantly negative at the level of 1%. Model (1–3) and model (1–4) further consider the annual effect and industry effect based on model (1) and model (1–2). The regression results indicate that the regression coefficient of political correlation is significantly negative, and the fitting value of the model is further improved. The average VIF of the model is 2.68, which is much less than 10, which indicates that there is no serious multiple collinear problem. The regression results show that H1B is supported by study evidence, but H1A is not valid.Table 3
Results of regression of political connectivity and commercial credit.
Model (1)Model (1-2)Model (1-3)Model (1-4)Constant term−0.025−0.008−0.046−0.030(0.167)(0.167)(0.437)(0.437)Enterprise age0.136∗∗∗0.126∗∗∗0.092∗∗0.091∗∗(0.033)(0.033)(0.041)(0.041)Enterprise size−0.043∗∗∗−0.042∗∗∗−0.044∗∗∗−0.042∗∗∗(0.012)(0.012)(0.013)(0.013)Corporate leverage0.102∗∗∗0.099∗∗∗0.103∗∗∗0.106∗∗∗(0.023)(0.023)(0.024)(0.024)Fixed assets−0.007−0.005−0.025−0.022(0.025)(0.025)(0.025)(0.025)Capital intensity0.091∗∗∗0.091∗∗∗0.099∗∗∗0.098∗∗∗(0.014)(0.014)(0.014)(0.014)Corporate performance−0.103∗∗∗−0.104∗∗∗−0.100∗∗∗−0.102∗∗∗(0.025)(0.025)(0.025)(0.025)Equity concentration−0.092∗∗−0.086∗∗−0.083∗−0.081∗(0.043)(0.043)(0.044)(0.044)CEO two in one−0.011∗∗−0.011∗∗−0.010∗∗−0.011∗∗(0.005)(0.005)(0.005)(0.005)Business linkages0.0150.020∗∗0.0140.018∗(0.010)(0.010)(0.010)(0.010)Insolvency distance−0.001−0.0030.0000.001(0.004)(0.004)(0.005)(0.005)Regional GNP0.0490.0500.0800.070(0.049)(0.049)(0.090)(0.090)Political affiliation−0.005∗∗∗−0.006∗∗∗(0.002)(0.002)IndNoNoYesYesYearNoNoYesYesObserved value3937393739373937R20.2040.2060.2160.219F32.730∗∗∗30.678∗∗∗16.932∗∗∗16.610∗∗∗Note.∗, ∗∗, and ∗∗∗ represent significant levels of 10%, 5%, and 1%, respectively (double-tailed test).The study results show that the political association of private enterprises in China will reduce the possibility of related enterprises obtaining commercial credit. The main reason lies in the regulatory preference and the role of asylum brought by political connection to enterprises. However, the political connection can bring a resource-promoting effect to the enterprise and send a good reputation foundation signal to the enterprise. At the same time, however, the regulatory advantages and the sheltered role that political connections bring to enterprises further enhance their premium ability in contract execution, leading suppliers to reduce their willingness to provide initial commercial credit out of consideration of loan recovery possibilities.


## 4.1. Descriptive Statistics and Correlation Analysis

Before performing regression analysis, we performed the descriptive statistical analysis and correlation analysis for all variables. The mean, standard deviation, and Pearson correlation coefficients of all variables are shown in Table2. From Table 2, from 2008 to 2018, it can be seen that the average commercial credit sales income ratio of private listed companies in the manufacturing industry in China is 24.1%, the overall commercial credit financing level is high, and its standard deviation is 0.161, which indicates that there are some differences in the commercial credit acquisition of each enterprise, an average of 1.775 (SD = 0.305) for simultaneous political connections. For the number of two-phase relations of each explanatory variable, its maximum absolute value of the pair is 0.394 (<0.6), indicating that there is no serious problem of multiple collinearity between variables.Table 2
Descriptive statistics and correlation of main variables.
VariableAverage valueStandard deviation12341. Commercial standing0.2410.16112. Political affiliation1.7750.305−0.054∗∗∗13. Enterprise age2.6974.556−0.032∗∗−0.049∗∗∗14. Enterprise size9.2680.3910.092∗∗∗0.101∗∗∗0.204∗∗∗15. Corporate leverage0.3350.1830.366∗∗∗0.045∗∗∗0.190∗∗∗0.394∗∗∗6. Fixed assets0.2030.117−0.028∗0.085∗∗∗0.087∗∗∗0.065∗∗∗7. Capital intensity0.1450.1450.100∗∗∗0.038∗∗−0.150∗∗∗−0.061∗∗∗8. Corporate performance0.0890.092−0.211∗∗∗0.017∗∗∗−0.103∗∗∗0.142∗∗∗9. Equity concentration0.1550.103−0.081∗∗∗0.032∗∗−0.120∗∗∗0.032∗∗10. CEO two in one0.3950.4890.003−0.076∗∗∗−0.058∗∗∗−0.100∗∗∗11. Business linkages3.2272.0980.061∗∗∗0.163∗∗∗0.098∗∗∗0.245∗∗∗12. Insolvency distance2.0980.825−0.361∗∗∗−0.093∗∗∗−0.107∗∗∗−0.392∗∗∗13. Regional GNP4.7200.1770.096∗∗∗−0.094∗∗∗0.128∗∗∗0.134∗∗∗Variable56789105. Corporate leverage16. Fixed assets0.215∗∗∗17. Capital intensity−0.130∗∗∗0.112∗∗∗18. Corporate performance−0.104∗∗∗−0.196∗∗∗−0.078∗∗∗19. Equity concentration−0.131∗∗∗−0.067∗∗∗0.0140.194∗∗∗110. CEO two in one−0.079∗∗∗−0.090∗∗∗0.070∗0.036∗∗∗0.040∗∗111. Business linkages0.136∗∗∗0.028∗0.004−0.068∗∗−0.072∗∗∗−0.139∗∗∗12. Insolvency distance−0.301∗∗∗−0.258∗∗∗0.063∗∗∗0.2010.126∗0.077∗13. Regional GNP−0.039∗∗−0.029∗−0.044∗∗∗−0.0240.052∗∗∗0.041∗∗∗Note.∗, ∗∗, and ∗∗∗ represent significant levels of 10%, 5%, and 1%, respectively (double-tailed test).


## 4.2. Regression Analysis

Because of the nonequilibrium panel data used in this article, in order to control the possible endogenous and individual effects, the independent variables and dependent variables are processed in a lag phase. At the same time, based on Hausman test results, a fixed model is used for regression estimation. Table3 is based on the multiple regression results between political correlation and enterprise commercial credit. In order to test the way in which the intensity of political connection acts on commercial credit, we add a model of political correlation variables to form a model (1–2) based on model (1); the regression results show that the coefficient of political correlation is significantly negative at the level of 1%. Model (1–3) and model (1–4) further consider the annual effect and industry effect based on model (1) and model (1–2). The regression results indicate that the regression coefficient of political correlation is significantly negative, and the fitting value of the model is further improved. The average VIF of the model is 2.68, which is much less than 10, which indicates that there is no serious multiple collinear problem. The regression results show that H1B is supported by study evidence, but H1A is not valid.Table 3
Results of regression of political connectivity and commercial credit.
Model (1)Model (1-2)Model (1-3)Model (1-4)Constant term−0.025−0.008−0.046−0.030(0.167)(0.167)(0.437)(0.437)Enterprise age0.136∗∗∗0.126∗∗∗0.092∗∗0.091∗∗(0.033)(0.033)(0.041)(0.041)Enterprise size−0.043∗∗∗−0.042∗∗∗−0.044∗∗∗−0.042∗∗∗(0.012)(0.012)(0.013)(0.013)Corporate leverage0.102∗∗∗0.099∗∗∗0.103∗∗∗0.106∗∗∗(0.023)(0.023)(0.024)(0.024)Fixed assets−0.007−0.005−0.025−0.022(0.025)(0.025)(0.025)(0.025)Capital intensity0.091∗∗∗0.091∗∗∗0.099∗∗∗0.098∗∗∗(0.014)(0.014)(0.014)(0.014)Corporate performance−0.103∗∗∗−0.104∗∗∗−0.100∗∗∗−0.102∗∗∗(0.025)(0.025)(0.025)(0.025)Equity concentration−0.092∗∗−0.086∗∗−0.083∗−0.081∗(0.043)(0.043)(0.044)(0.044)CEO two in one−0.011∗∗−0.011∗∗−0.010∗∗−0.011∗∗(0.005)(0.005)(0.005)(0.005)Business linkages0.0150.020∗∗0.0140.018∗(0.010)(0.010)(0.010)(0.010)Insolvency distance−0.001−0.0030.0000.001(0.004)(0.004)(0.005)(0.005)Regional GNP0.0490.0500.0800.070(0.049)(0.049)(0.090)(0.090)Political affiliation−0.005∗∗∗−0.006∗∗∗(0.002)(0.002)IndNoNoYesYesYearNoNoYesYesObserved value3937393739373937R20.2040.2060.2160.219F32.730∗∗∗30.678∗∗∗16.932∗∗∗16.610∗∗∗Note.∗, ∗∗, and ∗∗∗ represent significant levels of 10%, 5%, and 1%, respectively (double-tailed test).The study results show that the political association of private enterprises in China will reduce the possibility of related enterprises obtaining commercial credit. The main reason lies in the regulatory preference and the role of asylum brought by political connection to enterprises. However, the political connection can bring a resource-promoting effect to the enterprise and send a good reputation foundation signal to the enterprise. At the same time, however, the regulatory advantages and the sheltered role that political connections bring to enterprises further enhance their premium ability in contract execution, leading suppliers to reduce their willingness to provide initial commercial credit out of consideration of loan recovery possibilities.


## 5. Further Discussion

From the test results, the political association of private enterprises will reduce the possibility of obtaining commercial credit financing; that is to say, compared with the government background of affiliated enterprises, commercial credit suppliers pay more attention to the regulatory convenience and sheltering role provided by political connections to customers, because this type of regulatory convenience and protection role will not only reduce the trading position of suppliers in the transaction process but also reduce the efficiency of contract execution and the possibility of loan recovery in the event of overdue payments. On the basis of understanding the mechanism of inhibiting the commercial credit of the enterprise, we proceed from the enterprise itself and the market environment in which it is located so that we can explore the boundary factors that may affect the political connection to reduce the possibility of obtaining the commercial credit of the enterprise.


### 5.1. The Regulating Effect of Market Environment Factors

The market environment in which the enterprise is located will not only have a direct impact on the market-oriented operation of the enterprise but also have an indirect impact on the development of the enterprise by affecting the implementation effect of laws and regulations. Then this article will discuss the adjustment function of the market from two aspects of the market-oriented process and market competition intensity.From the market-oriented process, because China’s market economy is in the transition period; that is, the market mechanism is not perfect enough, and enterprises still face a lack of legal protection, excessive government intervention, delayed financial development, and other institutional constraints [5]. In the process of China’s transformation from a traditional planned economy to a market economy, the process of marketization in different regions is significantly different due to the influence of historical, geographical, cultural, and political factors. With the continuous improvement of the market-oriented process, the government’s control of scarce resources is reduced, and the market intermediary and legal constraints are more perfect. In one way, the continuous improvement of the legal system and norms brought by the process of marketization further increases. In another, the development of intermediary structure and the perfection of the legal system will strengthen the supervision and restraint of the market to the government’s behavior, which will lead to the decrease of the government’s supervision preference and asylum for the affiliated enterprises. In this case, once the related enterprises have an overdue payment phenomenon, the interest of commercial credit suppliers relying on signing contracts to carry out loan recovery will be effectively protected, and their willingness to provide commercial credit will be improved. Therefore, we speculate that as the market-oriented process continues to improve, the role of political connection to provide regulatory concessions and asylum for affiliated enterprises will be relatively reduced, so the inhibition of suppliers’ willingness to provide commercial credit is also relatively weakened; that is, the market-oriented process will reduce the inhibition effect of private enterprise political association on commercial credit.From the point of market competition, the enhancement of the competition intensity of the industry market will bring continuous improvement of the competition degree of the enterprises in the industry for the existing resources, the product market, and the market opportunity in the future [11], and the market transparency and the perfection of the market mechanism will also be strengthened continuously. With the increasing transparency of the market, competitors are watching each other more closely, and the implementation of related contracts and contracts between enterprises is more transparent and objective; in order to ensure their credibility in the future trading process, the possibility of affiliated enterprises using the advantages of political connection supervision to refuse to pay loans is reduced, and the willingness of suppliers to provide commercial credit is also reduced.In order to analyze the adjustment effect of market environment factors such as market process and market competition, we add these two variables to the original study model (1) to form the new model as follows (2):(2)Trade_Creditit=α0+α1Politicalit−1+β1Market_Developmentit−1+β2Competitionit−1,+β3×Politicalit−1×Market_Developmentit−1+β4×Politicalit−1×,Competitionit−1+∑k=1nβiControlsit−1+μind+μyear+μi+εit.Among them, Market_Development indicates the market-oriented process of the region in which the enterprise is located, measured by the proportion of fixed assets investment of the nonstate-owned enterprises in the province where the enterprise is located [11]. The market competition strength of the industry in which Competition enterprise is located is measured by 1−∑1MPi2, where M represents the number of enterprises in the industry where the i-enterprise is located and Pi means the market share of the i-enterprise. To measure the ratio of sales revenue, the greater the value of the Competition, the greater the strength of the market competition.Table4 reports our regression results. In this table, model (2) is consistent with model (1–4), and the effect of the political connection on the business credit of the enterprise is estimated by the two-way fixed-effect model. In this part, in order to analyze the regulation of the market process and the market competition strength, first, we join the two variables into the model (2_1) based on model (2); the regression results show that the direct effect of the two on the business credit of enterprises is not significant. Then, based on the model (2_1), we join the market-based process and the market competition strength into the model (2_2) with the product term of the political association, respectively; the results show that the regression coefficients of both were significantly positive (β1 = 0.041, SE = 0.021；β2 = 0.063, SE = 0.036). It is shown that both the market-oriented process and the intensity of market competition will significantly weaken the inhibitory effect of political connection on the commercial credit of enterprises. That is, when the market-oriented process is low or the market competition strength is weak, the possibility that a private enterprise with a political association obtains the commercial credit of the supplier is lower.Table 4
Modifications of market factors and corporate transparency.
Model (2)Model (2_1)Model (2_2)Model (3_1)Model (3_2)Constant term−0.0300.0570.1090.0250.011(0.437)(0.468)(0.469)(0.437)(0.437)Political affiliation−0.006∗∗∗−0.006∗∗∗−0.006∗∗∗−0.006∗∗∗−0.006∗∗∗(0.002)(0.002)(0.002)(0.002)(0.002)Enterprise age0.091∗∗0.090∗∗0.096∗∗0.095∗∗0.096∗∗(0.041)(0.041)(0.041)(0.041)(0.041)Enterprise size−0.042∗∗∗−0.042∗∗∗−0.042∗∗∗−0.047∗∗∗−0.047∗∗∗(0.013)(0.013)(0.013)(0.013)(0.013)Corporate leverage0.106∗∗∗0.106∗∗∗0.107∗∗∗0.106∗∗∗0.107∗∗∗(0.024)(0.024)(0.024)(0.024)(0.024)Fixed assets−0.022−0.022−0.023−0.020−0.022(0.025)(0.025)(0.025)(0.025)(0.025)Capital intensity0.098∗∗∗0.098∗∗∗0.098∗∗∗0.103∗∗∗0.103∗∗∗(0.014)(0.014)(0.014)(0.014)(0.014)Corporate performance−0.102∗∗∗−0.102∗∗∗−0.102∗∗∗−0.117∗∗∗−0.116∗∗∗(0.025)(0.025)(0.025)(0.026)(0.026)Equity concentration−0.081∗−0.082∗−0.079∗−0.075∗−0.075∗(0.044)(0.044)(0.044)(0.044)(0.044)CEO two in one−0.011∗∗−0.011∗∗−0.011∗∗−0.011∗∗−0.011∗∗(0.005)(0.005)(0.005)(0.005)(0.005)Business linkages0.018∗0.018∗0.018∗0.018∗0.018∗(0.010)(0.010)(0.010)(0.010)(0.010)Insolvency distance0.0010.0010.0010.0010.001(0.005)(0.005)(0.005)(0.005)(0.005)Regional GNP0.0700.0620.0530.0680.070(0.090)(0.091)(0.091)(0.090)(0.090)Process of marketization−0.044−0.041(0.073)(0.073)Market competition−0.017−0.047(0.128)(0.129)Political affiliation×0.041∗∗Process of marketization(0.021)Political affiliation×0.063∗Market competition(0.036)Enterprise transparency−0.0 hy 25−0.023(0.026)(0.026)Political affiliation×0.026∗∗Enterprise transparency(0.012)N3,9373,9373,9373,9373,937R20.2190.2290.2310.2200.223F16.610∗∗∗15.386∗∗∗14.575∗∗∗16.160∗∗∗15.633∗∗∗Note:∗, ∗∗, and ∗∗∗ represent significant levels of 10%, 5%, and 1%, respectively (double-tailed test).


### 5.2. The Regulating Function of Enterprise Transparency

Aside from the located market environment affecting the possibility of obtaining the commercial credit of the politically affiliated enterprise, the operating state presented by the enterprise will also affect the supplier’s judgment on its credit basis and the efficiency of contract execution and influence the influence of the political association on the commercial credit.The transparency of the enterprise determines how the relevant interest groups react to their market behavior. Studies have also shown that transparency in business operations often led to positive responses from relevant interest groups, including positive evaluations from investors and intermediary media and alliance willingness from potential partners of peers. From this point, the degree of transparency of the enterprise can improve the credibility of the associated enterprises in the suppliers so as to improve their will to provide commercial credit. On the one hand, enterprises will pay more attention to the transparency of their related behaviors, which will lead to a higher degree of concern for the market stakeholders. Even if they pay more attention to the transparency of their related behaviors, their chances of using their privileges to seek relevant benefits have been reduced. To sum up, we speculate that the degree of transparency of enterprises will force the possibility of defaulting on outstanding loans to a certain extent by weakening the possibility that affiliated enterprises rely on the regulatory preferences and asylum provided by political connections so as to enhance their reputation based in the hearts of suppliers and enhance their willingness to provide commercial credit. In other words, the degree of transparency of enterprises will weaken the inhibition of political connections on the possibility of obtaining commercial credit from affiliated enterprises.In order to analyze the regulation of the degree of transparency of the enterprise, we add these two variables based on model (2) to form a new model as follows:(3)Trade_Creditit=α0+α1Politicalit−1+γ1Firm_Visibilityit−1+γ2×Politicalit−1×,Firm_Visibilityit−1+∑k=1nβiControlsit−1+μind+μyear+μi+εit,where Firm_Visibility indicates the degree of transparency of the business and can be measured by the degree of marketing of the enterprise, and the sum of enterprise sales cost and daily management cost is used to measure the proportion of sales revenue.As we can see from Table4, model (3–1) adds the variable of the degree of transparency of the enterprise to model (2). The regression results show that the regression coefficient of enterprise transparency is not significant (γ1 = 0.025, SE = 0.026) and its direct effect on the possibility of obtaining commercial credit is not significant; on the basis of model (3–1), the product of transparency and political association of the enterprise is added to model (3–2). The results show that the regression coefficient of the project is obviously positive (γ1 = 0.026, SE = 0.012). The degree of transparency of enterprises will significantly weaken the inhibitory effect of political relevance on the commercial credit of affiliated enterprises.


## 5.1. The Regulating Effect of Market Environment Factors

The market environment in which the enterprise is located will not only have a direct impact on the market-oriented operation of the enterprise but also have an indirect impact on the development of the enterprise by affecting the implementation effect of laws and regulations. Then this article will discuss the adjustment function of the market from two aspects of the market-oriented process and market competition intensity.From the market-oriented process, because China’s market economy is in the transition period; that is, the market mechanism is not perfect enough, and enterprises still face a lack of legal protection, excessive government intervention, delayed financial development, and other institutional constraints [5]. In the process of China’s transformation from a traditional planned economy to a market economy, the process of marketization in different regions is significantly different due to the influence of historical, geographical, cultural, and political factors. With the continuous improvement of the market-oriented process, the government’s control of scarce resources is reduced, and the market intermediary and legal constraints are more perfect. In one way, the continuous improvement of the legal system and norms brought by the process of marketization further increases. In another, the development of intermediary structure and the perfection of the legal system will strengthen the supervision and restraint of the market to the government’s behavior, which will lead to the decrease of the government’s supervision preference and asylum for the affiliated enterprises. In this case, once the related enterprises have an overdue payment phenomenon, the interest of commercial credit suppliers relying on signing contracts to carry out loan recovery will be effectively protected, and their willingness to provide commercial credit will be improved. Therefore, we speculate that as the market-oriented process continues to improve, the role of political connection to provide regulatory concessions and asylum for affiliated enterprises will be relatively reduced, so the inhibition of suppliers’ willingness to provide commercial credit is also relatively weakened; that is, the market-oriented process will reduce the inhibition effect of private enterprise political association on commercial credit.From the point of market competition, the enhancement of the competition intensity of the industry market will bring continuous improvement of the competition degree of the enterprises in the industry for the existing resources, the product market, and the market opportunity in the future [11], and the market transparency and the perfection of the market mechanism will also be strengthened continuously. With the increasing transparency of the market, competitors are watching each other more closely, and the implementation of related contracts and contracts between enterprises is more transparent and objective; in order to ensure their credibility in the future trading process, the possibility of affiliated enterprises using the advantages of political connection supervision to refuse to pay loans is reduced, and the willingness of suppliers to provide commercial credit is also reduced.In order to analyze the adjustment effect of market environment factors such as market process and market competition, we add these two variables to the original study model (1) to form the new model as follows (2):(2)Trade_Creditit=α0+α1Politicalit−1+β1Market_Developmentit−1+β2Competitionit−1,+β3×Politicalit−1×Market_Developmentit−1+β4×Politicalit−1×,Competitionit−1+∑k=1nβiControlsit−1+μind+μyear+μi+εit.Among them, Market_Development indicates the market-oriented process of the region in which the enterprise is located, measured by the proportion of fixed assets investment of the nonstate-owned enterprises in the province where the enterprise is located [11]. The market competition strength of the industry in which Competition enterprise is located is measured by 1−∑1MPi2, where M represents the number of enterprises in the industry where the i-enterprise is located and Pi means the market share of the i-enterprise. To measure the ratio of sales revenue, the greater the value of the Competition, the greater the strength of the market competition.Table4 reports our regression results. In this table, model (2) is consistent with model (1–4), and the effect of the political connection on the business credit of the enterprise is estimated by the two-way fixed-effect model. In this part, in order to analyze the regulation of the market process and the market competition strength, first, we join the two variables into the model (2_1) based on model (2); the regression results show that the direct effect of the two on the business credit of enterprises is not significant. Then, based on the model (2_1), we join the market-based process and the market competition strength into the model (2_2) with the product term of the political association, respectively; the results show that the regression coefficients of both were significantly positive (β1 = 0.041, SE = 0.021；β2 = 0.063, SE = 0.036). It is shown that both the market-oriented process and the intensity of market competition will significantly weaken the inhibitory effect of political connection on the commercial credit of enterprises. That is, when the market-oriented process is low or the market competition strength is weak, the possibility that a private enterprise with a political association obtains the commercial credit of the supplier is lower.Table 4
Modifications of market factors and corporate transparency.
Model (2)Model (2_1)Model (2_2)Model (3_1)Model (3_2)Constant term−0.0300.0570.1090.0250.011(0.437)(0.468)(0.469)(0.437)(0.437)Political affiliation−0.006∗∗∗−0.006∗∗∗−0.006∗∗∗−0.006∗∗∗−0.006∗∗∗(0.002)(0.002)(0.002)(0.002)(0.002)Enterprise age0.091∗∗0.090∗∗0.096∗∗0.095∗∗0.096∗∗(0.041)(0.041)(0.041)(0.041)(0.041)Enterprise size−0.042∗∗∗−0.042∗∗∗−0.042∗∗∗−0.047∗∗∗−0.047∗∗∗(0.013)(0.013)(0.013)(0.013)(0.013)Corporate leverage0.106∗∗∗0.106∗∗∗0.107∗∗∗0.106∗∗∗0.107∗∗∗(0.024)(0.024)(0.024)(0.024)(0.024)Fixed assets−0.022−0.022−0.023−0.020−0.022(0.025)(0.025)(0.025)(0.025)(0.025)Capital intensity0.098∗∗∗0.098∗∗∗0.098∗∗∗0.103∗∗∗0.103∗∗∗(0.014)(0.014)(0.014)(0.014)(0.014)Corporate performance−0.102∗∗∗−0.102∗∗∗−0.102∗∗∗−0.117∗∗∗−0.116∗∗∗(0.025)(0.025)(0.025)(0.026)(0.026)Equity concentration−0.081∗−0.082∗−0.079∗−0.075∗−0.075∗(0.044)(0.044)(0.044)(0.044)(0.044)CEO two in one−0.011∗∗−0.011∗∗−0.011∗∗−0.011∗∗−0.011∗∗(0.005)(0.005)(0.005)(0.005)(0.005)Business linkages0.018∗0.018∗0.018∗0.018∗0.018∗(0.010)(0.010)(0.010)(0.010)(0.010)Insolvency distance0.0010.0010.0010.0010.001(0.005)(0.005)(0.005)(0.005)(0.005)Regional GNP0.0700.0620.0530.0680.070(0.090)(0.091)(0.091)(0.090)(0.090)Process of marketization−0.044−0.041(0.073)(0.073)Market competition−0.017−0.047(0.128)(0.129)Political affiliation×0.041∗∗Process of marketization(0.021)Political affiliation×0.063∗Market competition(0.036)Enterprise transparency−0.0 hy 25−0.023(0.026)(0.026)Political affiliation×0.026∗∗Enterprise transparency(0.012)N3,9373,9373,9373,9373,937R20.2190.2290.2310.2200.223F16.610∗∗∗15.386∗∗∗14.575∗∗∗16.160∗∗∗15.633∗∗∗Note:∗, ∗∗, and ∗∗∗ represent significant levels of 10%, 5%, and 1%, respectively (double-tailed test).


## 5.2. The Regulating Function of Enterprise Transparency

Aside from the located market environment affecting the possibility of obtaining the commercial credit of the politically affiliated enterprise, the operating state presented by the enterprise will also affect the supplier’s judgment on its credit basis and the efficiency of contract execution and influence the influence of the political association on the commercial credit.The transparency of the enterprise determines how the relevant interest groups react to their market behavior. Studies have also shown that transparency in business operations often led to positive responses from relevant interest groups, including positive evaluations from investors and intermediary media and alliance willingness from potential partners of peers. From this point, the degree of transparency of the enterprise can improve the credibility of the associated enterprises in the suppliers so as to improve their will to provide commercial credit. On the one hand, enterprises will pay more attention to the transparency of their related behaviors, which will lead to a higher degree of concern for the market stakeholders. Even if they pay more attention to the transparency of their related behaviors, their chances of using their privileges to seek relevant benefits have been reduced. To sum up, we speculate that the degree of transparency of enterprises will force the possibility of defaulting on outstanding loans to a certain extent by weakening the possibility that affiliated enterprises rely on the regulatory preferences and asylum provided by political connections so as to enhance their reputation based in the hearts of suppliers and enhance their willingness to provide commercial credit. In other words, the degree of transparency of enterprises will weaken the inhibition of political connections on the possibility of obtaining commercial credit from affiliated enterprises.In order to analyze the regulation of the degree of transparency of the enterprise, we add these two variables based on model (2) to form a new model as follows:(3)Trade_Creditit=α0+α1Politicalit−1+γ1Firm_Visibilityit−1+γ2×Politicalit−1×,Firm_Visibilityit−1+∑k=1nβiControlsit−1+μind+μyear+μi+εit,where Firm_Visibility indicates the degree of transparency of the business and can be measured by the degree of marketing of the enterprise, and the sum of enterprise sales cost and daily management cost is used to measure the proportion of sales revenue.As we can see from Table4, model (3–1) adds the variable of the degree of transparency of the enterprise to model (2). The regression results show that the regression coefficient of enterprise transparency is not significant (γ1 = 0.025, SE = 0.026) and its direct effect on the possibility of obtaining commercial credit is not significant; on the basis of model (3–1), the product of transparency and political association of the enterprise is added to model (3–2). The results show that the regression coefficient of the project is obviously positive (γ1 = 0.026, SE = 0.012). The degree of transparency of enterprises will significantly weaken the inhibitory effect of political relevance on the commercial credit of affiliated enterprises.


## 6. Conclusions

This article takes 1000 private listed companies in China’s manufacturing industry from 2008 to 2018 as a sample to analyze the influence of the political connections of private enterprises on their commercial credit financing. It is found that there is a negative correlation between the political connection of private enterprises and their commercial credit financing, which indicates that the political connection of private enterprises will significantly inhibit the possibility of obtaining commercial credit financing. That is to say, for the informal financing mode of commercial credit, the political connection does not play a role in promoting resource utility but reflect the resource inhibition effect. While political connections can have a resource-promoting effect on firms’ access to formal finance, they can also deliver to firms a good reputation base signal. However, the regulatory advantages and sheltered effects of political connections have further enhanced their premium ability in contract execution, leading suppliers to reduce their willingness to provide their initial commercial credit out of consideration of the possibility of loan recovery and reducing the acquisition of business credit financing. It is found that the market-oriented process, the degree of market competition and the transparency of enterprises will significantly weaken the restraining effect of political association on commercial credit financing. In terms of management practice, although private enterprises in the enterprise bank loans, taxes, preferential and government regulation, and other aspects reflect a strong role in promoting resources, private enterprises in the construction of political links also need to carefully examine their business credit and other informal financing constraints. In addition, its own transparency, the regional market-oriented process, and the regulatory role of the degree of competition in the industry market also further provide a situation factor reference for private enterprises to implement political association, this nonmarket-oriented strategy.This study also has some limitations. First of all, this article studies the role of private enterprise political connection on commercial credit financing based on the private listed companies in the manufacturing industry in China, which may have a sample bias effect, so the research needs to consider the data of nonlisted private enterprises more comprehensively. Secondly, for the variable of a political association, this article uses the number of people with government background in the management team of enterprises to measure and does not distinguish the government administrative level of managers and their individual positions in the company, so it is possible to ignore the influence of the intensity of political association and research needs to consider the problem more deeply in the future.



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*Source: 4564171-2022-05-30.xml*