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Analysis Of Factors Influencing Liquidity Risk Of Private Enterprises

Posted on:2024-08-03Degree:MasterType:Thesis
Country:ChinaCandidate:Z Y LinFull Text:PDF
GTID:2539307073959909Subject:Economic statistics
Abstract/Summary:PDF Full Text Request
Over the past 40 years of reform and opening up,the majority of private enterprises have become the "capillaries" of China’s economic muscle,an important subject of entrepreneurship and innovation and a major source of national tax revenue,and an important force indispensable for promoting the high-quality development of China’s socialist market economy and building a modern economic system.In recent years,the shortage of funds,financing difficulties and expensive financing have led to a significant increase in the liquidity risk of private enterprises,which has become a major bottleneck for the continued healthy development of the private enterprise economy,seriously inhibiting the sound development of the private enterprise economy,and may even affect the macroeconomic outbreak of systemic risk.The Party Central Committee and the State Council attach great importance to the development of private enterprises and have conducted several seminars on private enterprises to discuss solutions together.General Secretary Xi Jinping proposed six initiatives to ease the crisis of private enterprises by lowering corporate taxes and fees,easing the problem of difficult and expensive financing for private enterprises,creating a level playing field for private enterprises,improving policy implementation methods,establishing a new type of pro-clear governmentbusiness relationship and safeguarding the personal and property safety of entrepreneurs;Premier Li Keqiang proposed at the two sessions to encourage and guide the reform and innovation of private enterprises and further improve the private bond financing support system In addition,Premier Li Keqiang proposed at the two sessions to encourage and guide private enterprises to reform and innovate,and further improve the private bond financing support system.However,the financing problem of private enterprises is still not well relieved,and this problem is reflected in the risk of losses caused by the inability of private enterprises to obtain cash and cash equivalents,i.e.liquidity risk.Therefore,in order to solve the problem of difficult and expensive financing for private enterprises and to explore the causes of the financing problem,this paper uses various research methods such as literature analysis,questionnaire survey,panel quantile regression and complex networks to analyse the factors influencing the liquidity risk of private enterprises based on the triple perspective of leverage,information and credit from the perspective of private enterprises’ own business problems.This paper not only enriches the theoretical research on the private economy,but also plays an important role in helping the highquality development of the private economy and improving the effectiveness of government financing support policies.The research content and conclusions of this paper are mainly in the following areas.First,a survey and analysis of the current situation of liquidity risk of private enterprises.A questionnaire survey was conducted on private enterprises nationwide through an online survey platform.The survey was divided into two parts: one part was the basic information,current operating situation and financing situation of private enterprises,and the other part was a ten-level Likert scale with development capability,profitability,operating capability and solvency as the first-level indicators.After quality checking the questionnaire data,the current situation of private enterprises’ liquidity risk was analysed in four dimensions: basic situation,financing situation,internal management and external factors of private enterprises,and it was initially found that private enterprises have short term loans and long term investments,poor management,inability to meet the financing threshold and vulnerability to external shocks.Second,the analysis of the impact of leverage on the liquidity risk of private enterprises.Based on the data of private enterprises in China combined with trade-off theory,this paper proposes a leverage deviation index and uses panel quantile regression to analyse the impact of leverage on private enterprises’ liquidity risk.The results of the study found that the leverage deviation of private enterprises had a positive impact on liquidity risk,while profitability,solvency,operational capacity and development capacity had a negative impact on liquidity risk,and that enterprises at different liquidity levels were affected differently by the size of the enterprise and the level of financial development,with private enterprises being more affected by these factors than stateowned enterprises.The insight gained is that improving the internal management issues of enterprises,adopting an optimised debt structure,making leverage more in line with the actual operating conditions of enterprises,and getting bigger and stronger enterprises can reasonably address liquidity risk.Third,the analysis of the impact of information asymmetry on the liquidity risk of private enterprises.After analyzing the impact mechanism of liquidity risk caused by information asymmetry between private enterprises and the government,financial institutions and investors,information asymmetry indicators were selected and through a panel quantile regression model,the study found that the higher the degree of information asymmetry of private enterprises,the higher the liquidity risk,while compared to stateowned enterprises,private enterprises are more affected by information asymmetry.Therefore,private enterprises should pay attention to the issue of information disclosure,increase the transparency of corporate information,reduce information asymmetry with investors,financial institutions and government departments,which will help them increase financing,improve corporate liquidity and prevent corporate liquidity risk.Fourthly,the analysis of the contribution and contagion of credit risk to the liquidity risk of private enterprises.On the basis of using the KMV model to measure the credit risk of private enterprises,we examine whether there is a boosting effect of credit risk on liquidity risk;furthermore,from the new perspective of complex network analysis,using2018 as the time node of credit default outbreak,we adopt the minimum spanning tree algorithm to construct a complex network model of private enterprises’ liquidity from2012-2017 and 2018-2021 to study whether there is a contagion effect of credit risk on the liquidity risk of private enterprises.The results of the study found that the elevated credit risk of private enterprises will drive down the level of liquidity,the contagion path of liquidity risk of each private enterprise increases,and once the liquidity of large enterprises fluctuates,small private enterprises will also be affected,the cash flow between private enterprises slows down and the liquidity risk of each private enterprise increases.By analysing the impact of credit risk on the liquidity risk of private enterprises,it will help the government to introduce appropriate private enterprise financing support policies,improve policy effectiveness,promote the high-quality development of the private economy,and prevent and resolve the spread of credit risk among private enterprises resulting in the spread of liquidity risk.Fifthly,we summarise the findings of the study and propose countermeasures from the perspectives of both private enterprises and government departments.For private enterprises,they should improve their financing structure,enhance corporate information disclosure,optimise their credit rating and promote the overall improvement of their development level;for government departments,they should give private enterprises a favourable financing policy and should build a tripartite electronic information platform to help private enterprises resolve their credit risks.
Keywords/Search Tags:private enterprises, liquidity risk, influencing factor, panel quantile regression, complex network
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