Cities’ labor administrative penalties and labor income share of enterprises

Abstract

The labor administrative penalties of a city are enforced by the city's labor security administrative department for any breaches of labor security laws, regulations, or norms. The severity of labor administrative penalties differs across cities; thus, this study aims to determine how a city's penalties affect the labor income share of enterprises. We conduct a practical investigation to examine the influence of labor administrative penalties imposed by cities on the internal income distribution structure of firms. This study utilizes theoretical analysis and data on labor administrative penalties in Chinese cities, as well as samples of A-share listed businesses in Shanghai and Shenzhen. From the perspective of the internal income distribution structure, we examine the labor income share of firms and discover that labor administrative penalties in cities significantly raise the labor income share of these enterprises. The share of labor income of enterprises registered in the city increases by 0.9707 % for each additional unit of cities' labor administrative penalties (i.e., for a one-time labor administrative penalty per 10,000 people). The conclusion remains valid even after excluding the endogeneity and robustness tests. Regional labor administrative penalties can enhance the internal management of enterprise quality by promoting transparency and deterring non-compliance. This, in turn, mitigates credit risk for enterprises by fostering stable labor relations. Enhancing the quality of internal control and mitigating credit risk can lead to an increase in the labor income share of firms. An analysis of heterogeneity shows that the impact of labor administrative penalties in cities on increasing the percentage of labor income varies. The impact is more pronounced for state-owned firms and enterprises with low levels of investment.

1. Introduction

The 20th National Congress of the Communist Party of China suggested prioritizing the increase of individual income in the distribution of national revenue and enhancing the amount of labor compensation in the initial distribution, which can enhance workers' sense of gain [1,2]. Nonetheless, The ongoing enhancement of China's capital market has hindered the flow of capital returns, such as dividends, into the household sector, leading to a diminished proportion of labor income [3]. In China, the Labor Security Supervision Regulations grant the Labor Security Administrative Department the authority to enforce labor administrative penalties. These penalties involve overseeing businesses that pay employees' salaries, engaging in different social insurance programs, and punishing those who break labor security laws, regulations, or rules. However, the severity of labor administration penalties differs among different cities in China. Can the labor administrative penalties imposed by a city impact the proportion of labor revenue that firms in the region receive, through the mechanisms of publicity and deterrence? If such is the case, what is the specific mechanism involved?

Prior researchers have investigated the oversight of the labor market for both newly established and established businesses. Regarding startups, labor market regulation determines wage rates [4] and influences workers' decisions to establish companies [5,6]. Stringent regulation can impede entrepreneurship and diminish the quantity of new ventures. Furthermore, labor market regulation might decrease the quantity of newly established businesses and restrict their adaptability [7,68]. There has been a lack of extensive research on the impact of labor administrative fines and labor market regulation solely on established businesses. Academics have expanded their viewpoint to encompass market regulation, with a specific emphasis on the expansion of businesses [9,10], enterprise strategy [11], and risk-taking [12]. For example, market regulation can aid enterprises’ growth [10]. Furthermore, the oversight of inquiry letters carried out by securities regulatory agencies can effectively mitigate the financial limitations faced by firms and deter them from engaging in excessively aggressive marketing tactics [11].

Another field of literature strongly associated with this subject is the examination of the labor income share. Existing literature studies factors influencing labor income share, encompassing both intrinsic and extrinsic elements. Regarding internal considerations, firms encounter financial limitations [13,14], bargaining power of labor and capital [2], and the substitution relationship between labor and capital [17] affect the share of labor income of enterprises. For instance, mitigating the financial limitations encountered by businesses [14] and increasing the bargaining power of laborers [2] has the potential to enhance the proportion of labor income received by businesses. Regarding external factors, including social security burden [15], industry concentration [16,17], inclusive digital finance [18], capital market opening [19], and big data technology [20] can impact the proportion of money allocated to labor. Increasing industry concentration results in the redistribution of industry revenue to larger firms within the industry, which is then assimilated into the capital of these larger firms. Consequently, industry concentration will diminish the proportion of income allocated to workers [16,17]. The imposition of social security obligations leads to the departure of certain enterprises and hinders the establishment of new companies, thereby strengthening the negotiating power of existing businesses and decreasing the proportion of income received by workers [15].

In general, the economic consequences of labor market regulations and the factors that influence the labor income share have been the subject of research in both domestic and international literature, as evidenced by the following conclusions. The labor income share of enterprises can be increased by alleviating the financing constraints of enterprises and enhancing the bargaining power of workers. Administrative penalties for labor are becoming an increasingly important legal tool for safeguarding the legitimate rights and interests of workers within the framework of the comprehensive rule of law. However, the current literature has largely disregarded the correlation between the intensity of labor administrative penalties in cities and the proportion of labor income in enterprises. This relationship has the potential to enhance the sense of gain experienced by workers and foster a sense of commonwealth within enterprises [1,2]. It is of significant practical importance to clarify the matter of increasing the labor income share in enterprises. This study is founded on theoretical analysis in order to achieve this objective. We propose a research hypothesis and conduct empirical tests based on Chinese city data and samples of A-share listed enterprises from 2008 to 2020. This method enables us to investigate the mechanism and impact of the intensity of labor administrative penalties in cities on the share of labor income.

The potential innovations of this study are as follows. Little literature exists on this topic; for example, Yu [10] conducted a heterogeneity analysis of market penalties, including administrative labor penalties. This study improves market regulation concerning labor administrative penalties by analyzing the impact of a city's labor administrative penalties on the labor income shares of companies. In addition, we enhance the existing body of research by examining the determinants that impact the proportion of labor income. Although Prior study has thoroughly investigated external issues, such as the equitable distribution of social security responsibilities [15] and industry concentration [16,17], the impact of a city's labor administrative penalties has received less attention. This study contributes to the existing body of knowledge by examining the factors that affect the distribution of labor income, specifically focusing on labor security monitoring and cities' labor administrative fines.

Furthermore, this study introduces fresh evidence that supports the enhancement of labor administrative penalties. Enforcing labor oversight and implementing administrative sanctions on companies that breach the law are essential for upholding the rule of law and fulfilling the legal responsibilities of labor security administrative agencies. This study proposes that imposing labor administrative fines in a city can improve the effectiveness of internal control measures in firms and reduce their credit risk, ultimately leading to an increase in the proportion of labor revenue earned by these enterprises. Improving the quality of internal controls and reducing credit risk is undoubtedly beneficial to enterprises, while increases in the share of enterprises’ labor income are undoubtedly beneficial to workers; thus, labor administrative penalties positively affect both workers and enterprises. These findings offer fresh data that bolsters the case for the implementation and enforcement of labor regulations by labor security administrations.

The remainder of this study is arranged as follows. Section 2 presents the theoretical analysis, Section 3 describes the research design, and Section 4 presents the empirical test. Section 5 presents the mechanism test, Section 6 presents the heterogeneity analysis, and the study concludes with a summary and policy implications.

2. Theoretical analysis

This section analyzes the role of cities' labor administrative penalties on the share of enterprises’ labor income in terms of direct and indirect effects and accordingly develops hypotheses.

2.1. Direct impact

This study proposes a qualitative hypothesis based on existing research findings. It suggests that labor administrative penalties imposed by cities can have several positive effects. These include encouraging enterprises to honestly pay social insurance premiums, enhancing the bargaining power of workers, alleviating financial constraints faced by enterprises, and ultimately increasing the share of labor income for these enterprises.

First, labor administrative penalties encourage enterprises to pay social security premiums truthfully. The social security system is vital as it directly impacts the proportion of labor income that firms receive [21]. In China, the responsibility for making social security payments is substantial, while the amount of social security benefits provided is very small [22]. Enterprises occasionally evade social security payment duties by under-reporting, omitting, or neglecting to pay social security premiums [23]. This scenario has the potential to result in inadequate adherence to the obligations of making social security payments [18]. The “Regulations on the Supervision of Labor Security” grant the labor security administrative department the authority to oversee firms' compliance with various social insurance schemes and payment of social insurance premiums. Individuals who fail to engage in social insurance or pay social insurance contributions in accordance with the law may be subject to administrative fines. From a practical standpoint, this non-compliance is a significant basis for labor security administrative departments to apply labor administrative penalties. Administrative sanctions exert a potent deterrent influence on businesses operating in the same geographical area [24]. The imposition of higher labor administrative fines on cities will raise the financial burden of evading payments for regional firms, thus diminishing their incentive to avoid costs and significantly decreasing instances of social security infractions. Consequently, businesses in the area will fully comply with policy requirements by paying social security premiums to their employees, thereby enhancing the proportion of labor income received by these businesses [18].

Second, labor administrative penalties can alleviate enterprises' financing constraints. Financing limitations often constrain enterprises’ investment behavior [25]; thus, enterprises may need to postpone or decrease their investments [26], this can result in a reduction in the demand for labor [27]. This scenario will result in a decline in production efficiency and profitability for businesses, leading to a reduction in the percentage of worker income [26,28]. When businesses have limited access to funding, they may choose to use their own profits to finance their operations. This can result in a decrease in the amount of money allocated to paying workers and a decrease in the proportion of income that workers receive [29,30]. Essentially, limitations on funding can reduce the proportion of labor revenue that firms receive. The imposition of labor administrative penalties by cities can serve as a strong deterrent and establish uniformity in the conduct of businesses, thereby fostering a regulatory-compliant business climate. This scenario enables banks to leverage legal regulations to recoup loans and mitigate their credit risk. China operates a financial system that is primarily headed by banks, with state-owned and joint-stock banks playing a dominant role in distributing credit resources across the country. As a result, when cities impose stricter penalties on labor violations, it sends stronger signals to banks about the low level of credit risk. As a result, more credit resources are directed towards the region, which helps to reduce the financial limitations faced by businesses and enhance their share of labor income.

Finally, workers' bargaining power should be increased. In a perfectly competitive labor market, workers' income is determined by labor supply and demand; however, in a realistic, imperfectly competitive labor market, workers' income also depends on the bargaining power of workers and enterprises [1,31]. In China, workers' income in enterprises is not closely tied to changes in the value of marginal labor output; thus, the growth of worker income has not kept pace with the increase in the value of marginal labor output [32]. In addition, an asymmetry exists in bargaining power between laborers and enterprises, with enterprises consistently holding a stronger bargaining position than laborers [33,34]. The Regulations on Labor Security Supervision authorize labor security administrative departments to supervise enterprises' labor law violations through labor administrative penalties. Considering the preventive impact, a city's labor administrative penalties solve the worries of workers after conflicts between workers and enterprises at the legal level. This situation gives their workforce the courage and motivation to protect themselves, which can enhance the ability of workers to negotiate more favorable terms [35]. Cities' labor administrative penalties provide workers with basic survival and development rights, such as unemployment insurance, pensions, and medical insurance, which address workers' survival concerns and can improve their bargaining power [33]. Increased bargaining power can lead to higher labor income shares for enterprises [35,36].

In summary, a city's labor administrative penalties can encourage enterprises to pay social security contributions truthfully, ease enterprises' financing constraints, and improve workers' bargaining power, thereby increasing enterprises' labor income share. To this end, we propose the following research hypothesis.

H1

Cities' labor administrative penalties can increase labor income share.

2.2. Mechanism of action

2.2.1. Internal control channel

Based on the deterrent effect, implementing labor administrative penalties in cities can enhance the internal control quality of firms. The mechanism lies in the following. First, the warning effect: The Guidelines for Auditing Internal Control of Enterprises mandate that certified public accountants provide audit views regarding the efficacy of internal control. When an audited enterprise is penalized by labor administrative authorities, certified public accountants can immediately see the regulatory authorities' stance on the internal control issues and potential hazards of the enterprise [35]. This scenario compels accountants to provide unfavorable assessments regarding the efficacy of internal control inside the penalized firm, hence compelling the enterprise to enhance and enhance the caliber of internal control [10]. Simultaneously, there is a peer effect in enterprise behavior at the local level, which is influenced by the deterrent effect of regulatory penalties [[38], [39], [40]]. When multiple businesses in a certain area face administrative labor penalties, it creates a deterrent impact on other businesses. Enterprises who have not faced penalties will also assess the issues present in their internal control systems and enhance their construction accordingly. Next, the impact of information: Information asymmetry creates agency conflicts between the management, board of directors, and shareholders of the firm [41]. This circumstance compels the firm management to be more inclined to carry out irregularities that are not in line with internal control [42], thereby diminishing the quality of internal control [43]. According to the regulatory department's public notice of the penalty decision, administrative penalties, such as labor penalties, serve the purpose of disclosing information. This function has the ability to decrease the imbalance of information and mitigate conflicts of interest, therefore enhancing the effectiveness of internal control [41]. The regulatory department's public disclosure of the infractions committed by the penalized firm exerts regulatory pressure, compelling the enterprise to enhance its internal control framework in order to operate in a lawful and compliant manner. Based on the public announcement by the labor security administrative department regarding the violations of the punished enterprise, the board of directors and shareholders of non-punished enterprises in the same region might mitigate information asymmetry and address agency conflicts by utilizing information on infractions. This can enhance their internal control framework.

Enhancing the quality of internal control can increase the proportion of labor income in firms. The causes are as follows. First, investment efficiency effect: internal control enhances the precision of information transmission by implementing scientifically rigorous methods, regulated processes, and reasonable institutional arrangements. Moreover, the implementation of scientifically standardized power and responsibility distribution can enhance the efficiency of asset investment and mitigate resource wastage by regulating subjective and non-subjective inappropriate investment behavior by firm management [44,45]. Such action can improve asset investment efficiency, avoid resource waste [44,45], and assist businesses in expanding their market share and improving their capacity to boost the proportion of labor income. Second, operational efficiency effects: Operational efficiency can be attained by implementing a scientifically rigorous internal control system and standardized internal procedures. Internal control enhances the efficacy of internal management reports, enabling enterprise management to rapidly and precisely comprehend the company's production and operational state. This condition promotes prompt business decisions that are beneficial to the company's long-term growth, improving the operational effectiveness of the organization, aiding in the expansion of the company's market share, and expanding their capacity to enhance labor income share. Third, there is a phenomenon known as the talent attraction effect. As the internal control of a company improves in quality, the information becomes more open, and both internal and external stakeholders gain a better understanding of the enterprise's labor need [46]. Consequently, the firm has the ability to attract top-tier employees. The company also provides larger wages to its employees, hence increasing the proportion of labor income [47]. Fourth, the erosion prevention effect plays a crucial role in establishing and enhancing power balance and coordination mechanisms within the organization. This effect effectively curbs and prevents opportunistic behaviors, such as management embezzlement and controlling shareholders' tunneling [48]. Additionally, it has the ability to limit the erosion of labor income share by managing owners [49], therefore leading to an increase in labor income share.

Therefore, we propose the following research hypothesis:

H2

Cities' labor administrative penalties can improve the quality of internal control of enterprises, thereby increasing labor income share.

2.2.2. Credit risk channel

The financial stability of businesses is a crucial determinant of their credit risk. Imposing labor administrative penalties on cities enhances the financial stability of firms by mitigating their credit risk. First, it stimulates entrepreneurial creativity and enhances financial stability. City labor administrative fines serve as a means of safeguarding workers' rights and make it challenging for businesses to terminate employees [50,51]. Predicting the anticipated value of technical innovation is challenging, and both businesses and employees typically struggle to establish a fair method for revenue sharing. Enterprises possess the authority to terminate employees after the accomplishment of innovation projects [52]. Consequently, workers encounter challenges in receiving the advantages of technological innovation, thereby diminishing their motivation to participate in technological innovation. The labor administrative fines imposed by cities are intended to bolster labor protection, so empowering workers in labor relations [50] and fostering greater worker excitement for investing in technological innovation initiatives. Consequently, the implementation of labor protection measures, such as labor administrative penalties imposed by cities, can enhance enterprise innovation [51,52], leading to improved profitability and solvency of enterprises. Second, the labor administrative penalties imposed by cities increase solvency and improve production efficiency. City labor administrative fines serve as a means of safeguarding workers' rights and make it challenging for businesses to terminate employees [50,51]. This scenario can incentivize businesses to augment their investment in human capital, specifically through on-the-job training and learning, to boost the abilities and overall proficiency of workers, and to bolster specialized expertise [53]. Simultaneously, workers are motivated to acquire the specific skills necessary for the organization, which labor protection can facilitate, encouraging people to make these investments [8]. Enhancing the enterprise's specialist talents will lead to a boost in its production efficiency [8,53], enhance its profitability, and strengthen its solvency. Moreover, the implementation of labor protection measures, such as labor administrative penalties imposed by cities, results in higher costs for firms when they need to terminate employees. This condition leads to firms becoming more discerning in their hiring practices [54], resulting in an improvement in the caliber of workers and an increase in output per worker. This, in turn, enhances the financial stability of enterprises.

Reducing credit risk can increase the share of labor income for enterprises. First, it reduces the cost of debt financing. It is important to note that China has a bank-dominated financial system [55], and bank loans are the primary source of external finance for Chinese enterprises. Following several reforms, China's banks have become more efficient, and credit supply has become more effective [56]. If the risk of loan default is high, the bank will charge a higher interest rate [57]. For example, enterprises are usually more risk-resistant than individuals; thus, the risk of default is lower for enterprises than individuals. As a result, banks lend to enterprises at lower interest rates. For example, China Changshu Bank's interest rate for enterprise loans in the fourth quarter of 2023 was 4.76 %, while the interest rate for riskier personal loans was 6.73 %. Conversely, banks will demand lower interest rates if the risk of enterprise debt default is lower than the market average, which means that reducing enterprise credit risk can reduce the interest expense of the enterprise. Labor income share is the proportion of labor compensation to all factor compensation [3]. Reducing interest expenses can increase the labor income share of the enterprise and weaken the incentive to retain earnings to cope with risks. Furthermore, it weakens the incentive to retain earnings to cope with risks. The 2008 financial crisis served as a warning for global enterprise risk management, leading Chinese enterprises to implement comprehensive risk management [58]. Credit risk, which is related to the survival of the enterprise, is the focus of comprehensive risk management control. To manage credit risk, enterprises often retain earnings and use other methods to increase their anti-risk capacity; however, this can reduce the share of labor income. Conversely, reducing credit risk can decrease this effect and increase labor income share. Furthermore, reducing credit and enterprise risks can enhance worker effort [59], improve labor productivity, and increase worker compensation, boosting the enterprise's labor income share.

Based on this, we propose the following hypothesis:

H3

Cities' labor administrative penalties may decrease enterprises' credit risk, increasing the share of labor income.

In summary, cities' labor administrative penalties, directly and indirectly affect enterprises’ labor income shares. Section 3 develops the research design of the models, variables, and data to lay the foundation for empirically testing the direct and indirect effects.

3. Models, variables, and data

3.1. Data sources

We performed empirical studies using data obtained from publicly traded corporations. Listed firms have been subject to the implementation of the Ministry of Finance's Accounting Standards for Business Enterprises since 2007. The 2008 global financial crisis considerably changed the global economy and profoundly affected Chinese companies. We created macro variables using the information from the city data. This study conducted an empirical analysis using Chinese city data from 2008 to 2020 and all samples of A-share listed companies in the Shanghai and Shenzhen stock markets, as the data in the China City Statistical Yearbook was updated to 2020. The data was processed by eliminating missing samples, financial enterprise samples, ST and *ST enterprise samples, and by applying natural logarithms to mitigate the impact of outliers. We Winsorized and took the natural logarithm to reduce the interference of outliers. Some variables must be generated by taking the natural logarithm; therefore, following the extant literature, we do Winsorize such variables. For variables that do not need to be generated by taking natural logarithms, we apply the Winsorize trimming procedure using a 1 % upper and lower threshold. Ultimately, we acquired a total of 30,731 observations of enterprises on a yearly basis.

The labor administrative penalties in cities are sourced from the Enterprise Early Warning System, while other city data is obtained from the China City Statistical Yearbook. The disclosure index of internal control information in enterprises is sourced from Shenzhen Dibo Enterprise Risk Management Technology Co., Ltd. Additional data is sourced from the Wind database, developed by China Wande Information Company Limited. The Wind database regularly collects data from the annual reports of all listed companies in China and makes it available to researchers.

3.2. Model

3.2.1. Direct impact model

This study used a panel effects model to examine the influence of labor administrative penalties imposed by cities on the labor income share of companies. In addition, following the literature [18], we construct a two-way fixed-effects model of enterprises and year:

$${LSHR}_{it}={\alpha }_0+{\beta }_1*{LBRP}_{it}+\eta *X+{\alpha }_i+{\lambda }_t+{\epsilon }_{it}$$ (1)

where i and t are the subscripts for enterprises and time, respectively. The variable ${\alpha }_i$ represents the fixed effect of enterprises, ${\lambda }_t$ represents the year fixed effect, and ${\epsilon }_{it}$ represents the random error term. The variable ${LSHR}_{it}$ represents the labor income share of the i-th enterprise in the t-th year. The major independent variable in this study is the ${LBRP}_{it}$ , which represents the intensity of labor administrative penalties in cities during the t-th year for the i-th firm. The coefficient ${\beta }_1$ determines the impact on the labor income share of enterprises when cities' labor administrative fines increase. A very positive ${\beta }_1$ value indicates an increase in the labor income share. The control variable, denoted as X, will be further elucidated in the following section.

3.2.2. Indirect impact models

To test the indirect impact, we designed the following models concerning the existing literature on the transmission path of research (e.g. Ref. [60],).

$${MED}_{it}={\alpha }_0+\theta *{LBRP}_{it}+\eta *Z+{\alpha }_i+{\lambda }_t+{\epsilon }_{it}$$ (2)

$${LSHR}_{it}={\alpha }_0+{\beta }_1*{LBRP}_{it}+{\beta }_2*{MED}_{it}+\eta *X+{\alpha }_i+{\lambda }_t+{\epsilon }_{it}$$ (3)

${MED}_{it}$ is the mediating variable, i.e., the quality of the enterprise's internal control (IC) and the level of the enterprise's credit risk (Crsk). In equation (3), X is a control variable, the same as in equation (1). In equation (2), Z is a variable that is influenced by the mediating variable. Where the control variables in Z are different from X to identify θ from η.

First, we conduct an estimation of equation (2) in order to ascertain the impact of labor administrative penalties imposed by cities on the mediating variable. Second, we calculate the value of equation (3). If the coefficients of the intensity of labor administrative penalties in equation (2) and the coefficients of the mediating factors in equation (3) are significant, then there is a mediating impact. if only one of the variables θ in equation (2) and ${\beta }_2$ in equation (3) has a significant impact, it is necessary to assess the mediating effect using the Sobel test (see Table 1, Table 2, Table 4).

Table 1.

Variable definitions.

Type	Name	symbol	Variable definition	Reference
independent variable	Share of corporate labor income	LSHR	Cash paid to and for employees/(Operating income - Operating costs + Cash paid to and for employees + Depreciation of fixed assets) * 100	Du Y et al. (2023), Jiang Xanyu and Lin Li (2022), Liu Changgeng et al.
		rLSHR	Ln(LSHR/(100- LSHR))
dependent variable	Intensity of administrative labor penalties in urban areas	LBRP	Hradmin/the total population of the city, and Hradmin is the number of times firms in the city have been penalized by the Human Resources and Social Security Department.	New in this article
		rLBRP	Hradmin after normalization by the polar method.
mediating variable	Quality of internal control in the enterprise	IC	Icinfo/100, Icinfo is an index of internal control disclosure published by Dibb & Co.	Wan Hualin et al. (2022)
	Corporate credit risk level	Crsk	Zscroe/100	He Yanlin and Liu Guansheng (2023)
Control	Enterprise size	Size	Ln (total assets)	Du, Y. et al. (2023), Liu, C. G. et al.
	Firm Age	Age	Ln (1 + number of years the enterprise has been in existence as of that year)	Du, Y. et al. (2023), Liu, C. G. et al.
	leverage	Lev	Total liabilities/total assets*100	Du, Y. et al. (2023), Liu, C. G. et al.
	bankability	Roe	Net profit/average net worth*100	Du, Y. et al. (2023)
	Dividend and interest payments	Di	Cash disbursed for dividend and interest payments/total assets*100	Chen, Xiaohui et al. (2022)
	Financing constraints	Sa	−0.737*Enterprise size + 0.043*Enterprise size^2–0.04*Enterprise age	Xiong Jiacai et al. (2022), Liu et al. (2023)
	shareholding concentration	First	Shareholding ratio of the largest shareholder	Du Yong et al. (2023), Jiang Xuanyu and Lin Li (2022)
	Board size	Bsiz	Ln(Number of Board of Directors)
	Board independence	Indr	Number of independent directors/number of directors*100
	Institutional investor shareholding	Istr	Share held by institutional investors
	Level of economic development	Pgdp	Ln(Real GDP per capita of the city where the company is located)	Liu, Changgeng et al. (2023)
	Level of credit resource allocation	Fsiz	Loans per capita in the city where the enterprise is located	Li et al. (2023)

Table 2.

Descriptive statistical analysis.

Variables	Obs	Mean	Std.Dev.	Min	Max
LSHR	30,731	19.7104	9.5424	3.6991	54.2621
rLSHR	30,731	−1.5221	0.6691	−7.1882	3.5820
LBRP	30,731	0.0712	0.1346	0.0000	0.7842
rLBRP	30,731	0.0572	0.1215	0.0000	0.6293
IC	27,770	0.3213	0.0944	0.0500	0.4796
Crsk	30,731	0.0806	0.1604	0.0043	1.5458
Size	30,731	12.8598	1.3536	8.4456	19.4262
Age	30,731	2.8561	0.3466	0.0000	4.1897
Lev	30,731	42.4239	20.4549	5.3888	91.4575
Roe	30,731	8.5443	12.1241	−43.8700	64.6200
Di	30,731	2.4282	1.9416	0.0290	15.3177
First	30,731	35.6675	15.3725	8.8000	80.6500
Bsiz	30,731	2.1343	0.2072	0.0000	2.8904
Indr	30,731	37.2313	5.8789	0.0000	57.1429
Istr	30,731	35.9009	24.6773	0.0000	85.7566
Pgdp	30,731	11.4927	0.7754	8.6088	13.0060
Fsiz	30,731	0.2484	0.2292	0.0079	1.0163

Table 4.

Robustness test for equation (1).

Variables	(1)	(2)	(3)	(4)	(5)
	LSHR	rLSHR	LSHR	LSHR	LSHR
LBRP	1.9794***	0.0666***		1.2085***	1.0717***
	(0.4187)	(0.0224)		(0.3660)	(0.3499)
rLBRP			2.2808***
			(0.3750)
IC				0.9586**
				(0.4482)
Crsk				−1.0875***
				(0.4221)
Control	YES	YES	YES	YES	YES
Individual	YES	YES	YES	YES	NO
Annual	YES	YES	YES	YES	YES
Industry	NO	NO	NO	NO	YES
observations	30,731	30,731	30,731	27,770	30,731
R2	0.1317	0.1321	0.1331	0.1126	0.1313
N	3384	3384	3384	3325	3384

3.3. Variables

The dependent, interpreted, mediating, and control variables of this study are reported, in accordance with the existing literature.

3.3.1. Independent variable

The variable being manipulated in this study is the proportion of an enterprise's income that comes from labor. Based on previous research [18,19,61], we define the labor-source revenue share (LSHR) as the ratio of employee compensation to the enterprise's value added. Employee compensation refers to the total amount of money disbursed to employees, as stated in the cash flow statement of the company. The value generated by the firm can be calculated by subtracting the operating costs from the operating income and then adding the employee remuneration and the depreciation of fixed assets. In addition, we cite Du et al. [61] and apply logarithmic transformation to the labor income share by taking the natural logarithm of (LSHR/[100 – LSHR]) in order to produce LSHR for the purpose of conducting robustness testing.

3.3.2. Dependent variable

The variable being measured in this study is the severity of the labor administrative penalties imposed on cities. The severity of labor administrative penalties in cities is a macro-level variable. In China, the Department of Human Resources and Social Security is responsible for imposing labor administrative penalties. Consequently, we gather annual data on the frequency of penalties imposed on businesses by human resources and social security departments in each city using the Enterprise Alert Pass to obtain Hradmin. The LBRP is derived from the ratio of Hradmin to the total population, which serves as a proxy variable for measuring the severity of labor administrative penalties in cities. Furthermore, the rLBRP is derived by normalizing the Hradmin variable using the formula (Max - Hradmin)/(Max - Min) for the purpose of conducting the robustness test.

3.3.3. Mediating variables

The factors being examined in this study are enterprise intellectual capital (IC) and credit risk level (Crsk). With regards to the literature cited as [37], we categorize the enterprise internal control disclosure index issued by Shenzhen Dibo Enterprise Risk Management Technology Co. Subtracting 100 from a certain value will get IC, which acts as a substitute variable indicating the level of quality in the internal control of the firm. To determine the enterprise's credit risk level, we calculate a proxy variable Crsk, by dividing the enterprise's Z-score by 100. This approach is based on the existing literature [62].

3.3.4. Control variables

In relation to the control variables in equation (1), we adhere to the previously published literature (e.g., Refs. [14,18,61]) and control for enterprise size, enterprise age, leverage, profitability, dividend and interest payments, financing constraints, equity concentration, board size, board independence, institutional investor shareholding, and economic development level. Li et al. [55] consider economic and financial-related variables as factors to be taken into account when analyzing the influence of macro variables on micro variables of firms. For this reason, we also control the level of credit resource allocation.

In reference to the control variables in equation (2), When considering the quality of enterprises' IC as the mediating variable, in accordance with the previous research [15], we account for enterprise size, profitability, growth, enterprise age, board size, board independence, two-job unity, and equity concentration. Among the variables, Growth symbolizes the rate at which the operating income increases, and two-job unity is a dummy variable, which takes a value of 1 if the chairperson of the board is also the general manager; otherwise, it is 0. Similarly, referring to Li et al. [55], In addition, we account for the influence of two macro factors: the levels of economic development and credit resource allocation.

When employing the amount of enterprise credit risk as the mediating variable, we adhere to the current body of research [15,62]. and control for enterprise size, leverage, growth, equity concentration, board size, board independence, two-job unity, and property rights attributes (a dummy variable where state-owned enterprises (SOEs) are assigned a value of 1; otherwise, they equal 0). We also control for profitability, share of fixed assets, enterprise age, board size, and board independence.

After completing the research design, Section 4 empirically tests the direct effect of cities' labor administrative penalties on enterprises’ labor income shares based on data on Chinese listed enterprises registered within cities and the labor administrative penalties in these cities.

4. Empirical analysis

4.1. Descriptive statistics

The descriptive statistics of the variables, showing the following. The average labor income share (LSHR) of Chinese firms is 19.7104 %, with a minimum value of 3.6991 %. The greatest value reaches 54.2621 %, indicating a significant disparity between the two values. This is in line with the overall national condition of uneven development. The average value of labor administrative penalties intensity (LBRP) for cities is 0.0712. The lowest value is 0.0000, and the highest value is 0.7842. The disparity between the two is also substantial, which aligns with China's fundamental national condition of uneven development. Furthermore, the observation value experiences a decline to 27,770 as a result of an increased number of IC quality faults.

4.2. Benchmark regression

Equation (1) can be approximated using the fixed-effects model (FE) and the random effects model (RE). This study conducts the Hausman test on the fixed effects (FE) and random effects (RE) estimate outcomes. The chi-square statistic for the Hausman test is 360.91, and the p-value is less than 0.0001. The fixed effects (FE) method is employed in this study to estimate equation (1), taking into account the steady growth of control variables. The findings of this estimation may be seen. The coefficients of cities' labor administrative penalties intensity (LBRP) in columns (1)–(5) of Table 3 are all significantly positive at the 1 % significance level. Moreover, the severity of cities' labor administrative fines might enhance the proportion of labor income that firms receive. The empirical findings corroborate hypothesis H1. Column (5) shows that for each additional unit of cities’ labor administrative penalties (for a one-time labor administrative penalty per 10,000 people), the proportion of labor income generated by businesses registered in the city has increased by 0.9707 %.

Table 3.

FE estimation results for equation (1).

Variables	(1)	(2)	(3)	(4)	(5)
	LSHR	LSHR	LSHR	LSHR	LSHR
LBRP	1.8094***	1.8956***	1.3978***	1.4049***	0.9707***
	(0.3278)	(0.3278)	(0.3107)	(0.3104)	(0.3383)
Size		−0.4384***	−0.4674***	−0.4631***	−0.4806***
		(0.0919)	(0.0959)	(0.0967)	(0.0969)
Age		0.3026	−2.1302***	−1.9276***	−1.8660***
		(0.4344)	(0.4170)	(0.4190)	(0.4179)
Lev			0.0097***	0.0092***	0.0090**
			(0.0035)	(0.0035)	(0.0035)
Roe			−0.1283***	−0.1290***	−0.1288***
			(0.0042)	(0.0043)	(0.0043)
Di			−0.0248	−0.0264	−0.0250
			(0.0197)	(0.0197)	(0.0197)
Sa			−1.6287***	−1.7589***	−1.8374***
			(0.5925)	(0.6007)	(0.6020)
First				0.0084	0.0084
				(0.0054)	(0.0054)
Bsiz				0.3765	0.3811
				(0.2532)	(0.2536)
Indr				−0.0012	−0.0016
				(0.0065)	(0.0065)
Istr				−0.0030*	−0.0030*
				(0.0016)	(0.0016)
Pgdp					1.1306***
					(0.3433)
Fsiz					2.7362***
					(0.5221)
Constant	18.0927***	22.5647***	23.9284***	21.9188***	9.0775**
	(0.1575)	(1.3947)	(2.0439)	(2.2610)	(4.2944)
Individual	Yes	Yes	Yes	Yes	Yes
Annual	Yes	Yes	Yes	Yes	Yes
observations	30,731	30,731	30,731	30,731	30,731
R2	0.0432	0.0448	0.1308	0.1311	0.1320
N	3384	3384	3384	3384	3384

Robust standard errors for double clustering in parentheses, ***p < 0.01, **p < 0.05, *p < 0.1, same.

4.3. Robustness tests

• 1)Endogeneity treatment: Previous theoretical analysis and empirical tests have demonstrated that cities' labor administrative penalties have a significant impact on the percentage of enterprise labor income. On the other hand, the proportion of labor revenue in enterprises has little impact on the overall severity of labor administrative penalties in cities. Nevertheless, there is a chance that the severity of labor administration fines in cities is influenced by endogenous factors such as measurement mistakes or unobservable variables. To get an instrumental variable, we calculate the mean value of cities' labor administrative penalty intensity in the same year, based on the findings of Li et al. [69]. The magnitude of labor administrative fines in different cities and within this city is influenced by measurement errors or unobservable factors. Thus, ivLBRP is associated with LBRP, and ivLBRP fulfills the “correlation” requirement. On the other hand, the impact of labor penalties in other cities on the labor income share of firms in this city is unlikely to be significant, thus the variable ivLBRP meets the criteria of exogeneity. By employing ivLBRP as an instrumental variable, we recalibrate equation (1) through the instrumental variable approach (IV). The Cragg-Donald F-statistic for the weak instrumental variable test is 120,000. The observed result exceeds the threshold value of 16.38 for a 10 % bias, indicating that the hypothesis of a weak instrumental variable is rejected. Therefore, ivLBRP is considered a legitimate instrumental variable. Using ivLBRP as the instrumental variable, we employ the instrumental variable method (IV) to estimate equation (1), yielding column (1). The data in Column (1) demonstrates that when cities impose labor administrative fines, it leads to an increase in enterprises' labor revenue share. Therefore, we can confidently conclude that our study hypothesis H1 remains valid even when we exclude the influence of endogeneity.

• 2)Alter the measurement of the independent variable:equation (1) is recalculated using fixed effects (FE) using rLSHR as the independent variable, and the outcomes are presented in column (2). The conclusion that research hypothesis H1 holds is robust, based on the findings in column (2).

• 3)Substitute the dependent variable: By substituting the dependent variable with rLBRP and recalculating equation (1) using fixed effects, the results are shown in column (3). The conclusion that research hypothesis H1 holds is robust, based on the findings from column (3).
• 4)Control for the type of mediating variable: The preceding section established that the caliber of enterprises' intellectual capital (IC) and the extent of enterprises' credit risk have an impact on the proportion of enterprises' labor income. This proportion is considered a mediating variable rather than a control variable. We manipulate the two intermediary factors and recalculate equation (1) using fixed effects. The outcomes can be found in column (4). The study hypothesis H1 is strongly supported based on the findings from column (4).
• 5)Control for industry fixed effects: When investigating the labor income shares of enterprises, existing literature (e.g., Ref. [61]) accounts for industry and year fixed effects. Therefore, we account for the fixed effects of industry and year and re-estimate equation (1), as illustrated in column (5). The data in column (5) demonstrates that research hypothesis H1 is strong and resistant to change or variation.

The results of the tests in Section 4 indicate that the city's labor administrative penalties increase enterprises' labor income shares. Section 5 tests the indirect effect of the city's labor administrative penalties on enterprises' labor income shares.

5. Mechanism testing

5.1. Internal control quality channel of enterprises

We estimate equation (2) using FE with IC as the mediating variable and LBRP as the dependent variable. The findings are shown in column (1). Using ivLBRP as the instrumental variable, we employ IV to estimate equation (2). The outcomes are presented in Table 5 Panel A, specifically in column (2). By substituting the dependent variable with rLBRP, we employ fixed effects (FE) to estimate equation (2). The outcomes are presented in column (3) of Table 5 Panel A. In order to manage credit risk, firms can enhance their internal controls (ICs) to enhance the overall quality of ICs. Consequently, the credit risk level of enterprises can also impact the quality of ICs. Therefore, we account for the enterprise's credit risk level by recalculating equation (2) using fixed effects (FE). The outcomes are displayed in column (4) of Table 5 Panel A. Table 5 Panel A demonstrates that the severity of labor administrative penalties in cities enhances the level of internal control in companies.

Table 5.

Estimated results of the internal control quality channel in firms.

Panel A
Variables	(1)	(2)	(3)	(4)
	IC	IC	IC	IC
LBRP	0.0099**	0.0209***		0.0103**
	(0.0041)	(0.0049)		(0.0041)
rLBRP			0.0215***
			(0.0045)
Crsk				0.0072***
				(0.0028)
Control	Yes	Yes	Yes	Yes
Individual	Yes	Yes	Yes	No
Annual	Yes	Yes	Yes	Yes
observations	27,770	27,583	27,770	27,770
R2	0.5557	0.5556	0.5560	0.5558
N	3325	3138	3325	3325
Panel B
Variables	(1)	(2)	(3)	(4)
	LSHR	LSHR	rLSHR	LSHR
LBRP	1.2592***	2.2205***	0.0856***
	(0.3657)	(0.4496)	(0.0241)
rLBRP				2.5835***
				(0.4024)
IC	0.9389**	0.8782*	0.0546*	0.8738*
	(0.4483)	(0.5125)	(0.0322)	(0.4480)
Control	Yes	Yes	Yes	Yes
Individual	Yes	Yes	Yes	Yes
Annual	Yes	Yes	Yes	Yes
observations	32,264	32,264	32,264	32,264
R2	0.1603	0.1601	0.1659	0.1606
N	3458	3458	3458	3458

Note: Instrumental variables all pass validity tests. When using IV in estimating equation (2), the number of observations is reduced to 27,583 because some single-observation firms are excluded by stata.

Column (1) is the result of the estimation of equation (3) using FE, with LSHR serving as the independent variable, IC as the mediator variable, and LBRP as the dependent variable. In accordance with Section 4.3, we utilize the average value of the quality of internal controls inside other enterprises in the same year (referred to as ivIC) as an instrumental variable, in conjunction with ivLBRP. Afterwards, we employ the instrumental variable (IV) method to estimate equation (3), as presented in Table 5 Panel B, specifically in column (2). The variable rLSHR replaces the independent variable, and equation (3) is estimated using fixed effects (FE), as demonstrated in column (3) of Table 5 Panel B. In this analysis, we substitute the dependent variable with rLBRP and employ the fixed effects (FE) method to estimate equation (3), which is presented in column (4) of Table 5 Panel B. Table 5 Panel B demonstrates a positive correlation between the effectiveness of firms' internal controls and the proportion of labor in their operations.

By merging, it is evident that the severity of labor administrative penalties in cities enhances the effectiveness of internal controls in companies, leading to an increase in the proportion of labor income for these enterprises.

5.2. Enterprises’ credit risk level channel

By utilizing the credit risk level (Crsk) of enterprises as the mediating variable, and with reference to Section 5.1, we calculate equations (2), (3). The outcomes are displayed. Table 6 shows that the intensity of cities' labor administrative penalties reduces enterprises' credit risk, increasing the share of enterprises’ labor income, and hypothesis H3 is valid and robust.

Table 6.

Estimation results of the channel of firms' credit risk level.

Panel A
Variables	(1)	(2)	(3)	(4)
	Crsk	Crsk	Crsk	Crsk
LBRP	−0.0381***	−0.0494***		−0.0446***
	(0.0090)	(0.0107)		(0.0094)
rLBRP			−0.0413***
			(0.0102)
Crsk				0.0322**
				(0.0133)
Control	Yes	Yes	Yes	Yes
Individual	Yes	Yes	Yes	No
Annual	Yes	Yes	Yes	Yes
observations	32,264	32,264	32,264	32,264
R2	0.1020	0.1020	0.1019	0.0888
N	3458	3458	3458	3458
Panel B
Variables	(1)	(2)	(3)	(4)
	LSHR	LSHR	rLSHR	LSHR
LBRP	0.9225***	1.8645***	0.0623***
	(0.3383)	(0.4193)	(0.0225)
rLBRP				2.2285***
				(0.3751)
Crsk	−1.2166***	−2.2378***	−0.1084***	−1.1990***
	(0.3798)	(0.6109)	(0.0281)	(0.3796)
Control	Yes	Yes	Yes	Yes
Individual	Yes	Yes	Yes	Yes
Annual	Yes	Yes	Yes	Yes
observations	30,731	30,731	30,731	30,731
R2	0.1333	0.1321	0.1342	0.1343
N	3384	3384	3384	3384

Note: Instrumental variables are tested for validity.

Section 4 shows that cities' labor administrative penalties increase an enterprise's share of labor income. Section 6 examines the variability of the boosting effect along two dimensions: enterprise ownership attributes and enterprise size.

6. Further analysis

6.1. Heterogeneity of property rights attributes

The preceding analysis demonstrates that the quality of enterprises' internal controls can be enhanced by the labor administrative penalties imposed by cities, thereby reducing principal-agent conflicts. SOEs typically benefit from their inherent affiliation with the government, which often results in them receiving additional tax or financial assistance in the event of losses. This connection gives rise to more severe issues of duplicated resources, lenient oversight, and flexible budget limitations in SOEs, resulting in more significant conflicts between principals and agents [63]. Due to their larger capacity for addressing agency disputes through improved internal control quality, SOEs may find that labor administrative penalties imposed by cities are particularly effective in lessening such conflicts. This scenario has the potential to decrease resource duplication and financial limitations in SOEs, raise their efficiency in utilizing resources, and increase their proportion of worker income. Concurrently, SOEs possess more leverage over workers due to their state ownership, resulting in a higher net surplus for the enterprises. Moreover, workers at SOEs have a relatively favorable position in determining their wages compared to workers in private companies [2]. SOEs exhibit a reduced propensity for risk-taking when compared to non-SOEs. Consequently, cities' labor administrative penalties have a more pronounced influence on SOEs due to the impacts of information disclosure and deterrence. The labor stations in SOEs have a greater ability to negotiate and exert influence compared to those in non-SOEs. Additionally, the labor administrative penalties imposed by cities are more likely to result in an increase in the proportion of labor income received by workers in SOEs. Thus, we hypothesize that the impact of cities' administrative labor fines on the increase of enterprises' share of labor income varies and is more significant for SOEs.

We employ LSHR and rLSHR as independent variables and LBRP as dependent variables to evaluate this conjecture. We employ a variable coefficient individual fixed effects model to estimate equation (1), which is presented in columns (1) and (2). Table 7's columns (3) and (4) show the results of substituting rLBRP for the dependent variable. Table 7 indicates that the intensity coefficients of labor administrative penalties for cities are positively significant at the 1 % or 10 % level for both SOEs and non-SOEs. Furthermore, the intensity of cities' labor administrative penalties increases enterprises' share of labor income. Second, the coefficients of the dependent variable for SOEs are stronger in magnitude compared to those of non-SOEs. Additionally, the impact of cities' labor administrative fines on boosting the labor income share is more pronounced for SOEs. The empirical findings validate the conjecture made in this study.

Table 7.

Estimated results of heterogeneity in property rights attributes.

	(1)	(2)	(3)	(4)
Variables	LSHR	rLSHR	LSHR	rLSHR
LBRP(Non-state-owned)	0.6970*	0.0445*
	(0.4138)	(0.0259)
LBRP(State-owned)	1.3773***	0.0995***
	(0.4388)	(0.0321)
rLBRP(Non-State-owned)			2.1289***	0.1348***
			(0.4984)	(0.0320)
rLBRP(State-owned)			2.4357***	0.1600***
			(0.4675)	(0.0326)
Control	Yes	Yes	Yes	Yes
Individual	Yes	Yes	Yes	Yes
Annual	Yes	Yes	Yes	Yes
observations	30,731	30,731	30,731	30,731
R2	0.1321	0.1322	0.1331	0.1330
N	3384	3384	3384	3384

6.2. The moderating role of enterprise size

Baseline regressions show that the larger the enterprise size, the smaller the enterprise's labor income share. This situation occurs for several reasons. First, the bargaining power of enterprises in the labor market affects employee compensation [31]. In China, labor unions play a small role in employee wages, and the country has a large employed population; therefore, the larger the size of the enterprise, the more bargaining power it has in the labor market. This situation means that the larger the enterprise, the lower the share of enterprise labor income is likely to be. Second, China is a bank-dominated financial system [64], and bank loans are the main source of external financing for enterprises because their profitability and risk resistance tend to increase as enterprises increase in size. As a result, banks prefer larger enterprises. Thus, as an enterprise grows, the more external financing it receives (such as bank loans) and the more likely it is to substitute capital (such as machinery and equipment) for labor, thereby reducing its share of labor income. Thus, in the face of the city's administrative labor penalties, as the enterprise's size increases, its response to the adverse effects of the penalties will gradually increase, and thus, the impact of the city's administrative labor penalties on the enterprise's labor income share can be weakened. Therefore, we hypothesize that the effect of the city's administrative labor penalties in increasing the enterprise's labor income share will gradually weaken as the enterprise grows.

To test this speculation, we add the interaction term between enterprise size and labor administrative penalties in the city to equation (1). Subsequently, we estimate equation (1) using FE with LSHR and rLSHR as the explanatory variables and LBRP as the dependent variable, respectively, and the results are in columns (1) and (2). Replacing the dependent variable with rLBRP results in columns (3) and (4). Table 8 shows that the coefficient on labor administrative penalties in cities is considerably positive at the 1 % significance level, and the coefficient on enterprise size is considerably negative at the 1 % significance level. Furthermore, the interaction term between the city's labor administrative penalties and enterprise size is considerably negative at the 1 % significance level. In other words, as the size of the enterprise expands, the role of the city's labor administrative penalties in increasing the share of the enterprise's labor income is gradually weakening. The empirical results confirm this study's speculation.

Table 8.

Estimated results of the moderating effect of enterprise size.

Variables	(1)	(2)	(3)	(4)
	LSHR	rLSHR	LSHR	rLSHR
LBRP	9.7999***	0.6125***
	(1.9343)	(0.1319)
rLBRP			15.2208***	0.9695***
			(2.2783)	(0.1628)
Size	9.7999***	0.6125***	9.7999***	0.6125***
	(1.9343)	(0.1319)	(1.9343)	(0.1319)
LBRP × Size	−0.6545***	−0.0405***
	(0.1358)	(0.0095)
rLBRP × Size			−0.9437***	−0.0600***
			(0.1566)	(0.0114)
Control	Yes	Yes	Yes	Yes
Individual	Yes	Yes	Yes	Yes
Annual	Yes	Yes	Yes	Yes
observations	30,731	30,731	30,731	30,731
R2	0.1326	0.1325	0.1341	0.1338
N	3384	3384	3384	3384

7. Discussions

Labor regulation determines wage rates [4], and less stringent labor regulation allows enterprises to adjust their labor force in response to market fluctuations [9], enhancing the flexibility of enterprises to use labor and conversely decreasing the flexibility of enterprises to use labor [65]. Reduced labor flexibility distorts the effectiveness of labor resource allocation, which may reduce an enterprise's share of labor income. However, our study is not consistent with this finding. The reason for this is that China has a large population and many employed people, and often, the labor supply exceeds the demand in the labor market. In this way, the bargaining power of laborers tends to be weak. Strengthening labor-labor regulation can enhance the bargaining power of workers; thus, the share of labor income for enterprises. Conversely, China is a transition economy, and its legal system has yet to be perfected. Although the central government unifies laws such as labor and labor contract laws, they are enforced by local governments such as city governments, and the enforcement is not the same across local governments [66,67]. Urban governments may relax the enforcement of labor and contract laws for economic development reasons, thereby protecting employers more and thus reducing enterprises' share of labor income. Conversely, when city governments strengthen the enforcement of labor laws and labor contract laws to protect workers, they increase the share of labor income of enterprises.

The study utilizes Chinese city data and data from A-share listed firms to employ a combination of theoretical and empirical research methodologies. The findings suggest that labor regulation has the potential to enhance the proportion of worker income in enterprises. This conclusion differs from existing studies, which is the strength of this study; however, China has many enterprises, and data from the National Bureau of Statistics of China shows that the number of new enterprises in 2023 alone was 32.73 million. Because of the missing statistics, we were unable to perform an analysis using data from all Chinese firms, which is a limitation of our work and a suggestion for future research.

8. Conclusions and implications

8.1. Conclusion

This study examines the influence of labor administrative fines imposed by cities on the proportion of labor income received by firms. We conduct a theoretical analysis on the influence of labor administrative penalties imposed by cities on the labor income share of firms. We consider both direct and indirect effects and carry out empirical tests using enterprise and year two-way fixed effects. The sample consists of data from Chinese cities and samples of firms registered on the A-share market in Shanghai and Shenzhen, covering the period from 2008 to 2020. The findings of our study suggest the following. Initially, the imposition of labor administrative fines by cities can lead to an increase in the proportion of labor income received by firms. Moreover, the proportion of labor income that firms receive rises as the severity of labor administrative penalties in cities gradually increases. Furthermore, the labor administrative fines imposed by cities have an indirect impact on the labor income share of firms by altering the quality of IC (Industrial Classification) and the amount of credit risk. More precisely, when cities impose labor administrative fines, it has a positive impact on the quality of enterprise IC (Industrial Classification), leading to an increase in the proportion of enterprise labor income. By fostering entrepreneurial innovation and enhancing production efficiency, cities can decrease the credit risk of enterprises through labor administrative fines, so boosting the proportion of labor revenue earned by enterprises. Furthermore, the impact of labor administrative fines on the proportion of labor income varies and is more significant for SOEs. The position diminishes as the scale of the organization expands.

8.2. Implications

The results of this investigation have significant ramifications. Firstly, it is possible to consider the rule of law and the growing share of labor income at the same time. The report of the 20th Party Congress highlights the need of upholding the rule of law in order to safeguard and advance social justice. In accordance with the Regulations on Labor Security Supervision, labor security administrations have the legitimate responsibility to enhance labor supervision and enforce administrative penalties on companies that unlawfully violate labor regulations. Our research indicates that the imposition of labor administrative fines by cities can lead to an increase in the proportion of labor revenue received by firms. Consequently, the concepts of the rule of law and the rise in labor income share can be examined concurrently. Secondly, local labor security administrations have the authority to confidently implement labor administrative sanctions in accordance with the legislation. Prior study indicates that labor regulation diminishes the adaptability of businesses' workforce and amplifies the workload on businesses. For instance, Yu [10] discovered that enhancing labor regulations and implementing labor administrative penalties promote the growth of enterprises. Our research reveals that enhancing labor administrative penalties leads to a higher proportion of labor revenue for companies. Consequently, the situation in China diverges from that in other nations. Regional labor security authorities have the authority to confidently enforce labor fines in accordance with the law, which encourages the development of businesses and enhances the proportion of labor income. Finally, labor administrative fines carry a beneficial meaning for the shareholders of enterprises. The study's theoretical analysis and practical testing demonstrate that labor administrative fines can enhance the quality of internal control (IC) and decrease the amount of credit risk for firms. This scenario has the potential to enhance the enterprise's worth, which holds significant positive implications for the owners of the enterprise. Hence, while selecting investee enterprises, investors should take into account the severity of labor administrative penalties in the location of these enterprises as a favorable aspect. Our study additionally demonstrates that cities' enforcement of labor administrative penalties has a greater impact on increasing the proportion of labor income for firms with lower levels of real investment, particularly those involving fixed assets. This finding suggests that owners of companies with limited levels of actual investment can derive greater advantages from labor administrative fines. Investors can evaluate the actual investment level of a company and the severity of labor administrative fines in its location to choose a suitable investment opportunity.

Ethics approval

Our institution does not require ethics approval to report individual cases or case series.

Funding

This study received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors.

Data availability statement

Data associated with our Study hasn't been deposited into a publicly available repository, and our Data will be made available on request.

CRediT authorship contribution statement

Xuerui Qin: Writing – review & editing. Xiao Pan: Writing – review & editing. Libo Li: Supervision, Conceptualization.

Declaration of competing interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.