Amsterdam Business School
MSc Business Economics: Finance Track
Master Thesis
The trade credit and government
investment in China
Student Name: Ke Zhang
Student Number:10707522
Supervisor:J.E.Ligterink
State of originality
The work presented in this thesis is, to the best of my knowledge and belief, original, except as acknowledged in the text, and the material has not been submitted, either in
whole or in part, for a degree like this or any other university.1 The Faculty of
Economics and Business is responsible solely for the supervision of completion of the work, not for the contents.
Ke Zhang July 2015
1. I gratefully acknowledge my supervisor J.E.Ligterink who sheds light on the topic of this thesis, provides abundant wonderful papers to read or study and gives many helpful instructions and thoughts to me.
Catalog
Abstract
...1
1. Introduction
...2
2. Literature review
...5
3. Background information
...13
4. Methodology
...16
5. Data and descriptive statistics
...21
6. Results
...27
7. Robust check
...34
8. Conclusions
...35
Abstract
This paper tests external financing behavior of firms in China, and points out the causal relation between government investment and trade credit. We examine the differences on both supply and demand sides of trade credit between state owned firms and non state owned firms. We find that government investment can increase the supply of trade credit of the listed companies and state owned firms tend to extend more trade credits than private firms do. In China, trade credit is a redistribution channel of government investment from state owned, financial healthy firms to smaller, financial weaker firms. State owned firms play the role delivering government investment to smaller firms. Finally, firms with higher sales growth rate tend to provide more trade credit.
1. Introduction
Trade credit rises with the emergence and the thrive of people’s commercial activity , now has a long history, It has now formed a comprehensive system. Around the world, the key factor of firms’ operation and growth is funding, firms financing from a lot of different resources such as retained earnings, bank loans, outside investment and from their suppliers when purchasing inputs as well. There are many existing studies on the original and the mechanism of trade credits such as why firms using and offering trade credits, what kind of relationship between the trade credits and commercial loans and whether the relationship between supply and demand of commercial credit depends on the suppliers’ and the customers’ bargaining power and market power. Customers usually get trade credit by delaying their payments, although it is still be considered as an expensive source of financing. But when talking about emerging country, especially China, there are still a lot of work we can do. In this paper, we are trying to test several questions as follow: Whether government investments affect the supply of trade credits among the market? Do the state owned firms tend to supply more trade credits than non-state owned firm? Could transactions of trade credits be seen as an substitution of bank credit as well as a redistribution of bank credit loans from the financial stronger firms to the financial weaker firms? There is no such study link the government investment to trade credit, we hope this study could fill the gap. Government investment has long been the main pillar of the economic growth in China, due to the underdeveloped financial market and the backward industrial
structure, the central bank of China tend to use government invest often as a way of macro-control. After 2003, the Chinese government establishes a national economic status of real estate, increasing capital investment in new construction projects to solve the employment problem, the iron and steel, cement, glass and other industries bundled together with the real estate. The government took an economic stimulus plan that combined by the positive fiscal policy and the moderately loose monetary policy as an attempt to minimize the impact of the global financial crisis on theworld's second largest economy. The government invested 4 trillion yuan (equal to five hundred and eighty billion dollars at that time) in infrastructure and social welfar, which was aim at drive “internal demand” and achieve industrial restructuring according to the stimulate plan. As the consequence, the firms within industries such as the real estate, machinery, metal had a rapid expansion and the government successfully avoided a big decline of the economy. Investment behavior of the government and all of this expansion of the industry made me curious how they have an impact on the trade credit and whether they fuels the growth and usage of trade credit.
In China, state owned firms always have better accesses to bank credit than do
non-state owned firms, which means non-state owned firms would more rely on trade credit to run their businesses. In order to maintain a product market relationship, trade creditors that are more dependent on their customer’s business grant more credit to financially distressed customers than banks do (Wilner 2000). The government orders included in the stimulate plan provide huge incomes and liquidity to both state owned
and non-state owned firms, which leads to a redistribution of credit in the supply chains. Therefore, we suppose that the government invest would cause an increase in the trade credit due to the lager fund pools. we are interested in the relationship between government investment and the trade credit. In other word, does government invest helps trade credit develop in China and to what extend trade credits help firms grow? We intend to do this research by using the data of public traded companies from Shang Hai and Shen Zhen A-shares stock markets.
China has become an important role in world economy, the rising questions about the low efficiency of state owned companies and the unfair allocation of resources need us to do more research.It is of value to investigate the mechanism and actual results of government invest. It is good to know if the increasing budget for the government indeed helps the firms to expand their business. We intend to sum up the recent researches done by other scholars on trade credit, sort out the recent findings and agreements on this issue. Since there is no existing study on my topic, my research would provide a better understanding of China’s fiscal system from credit distribution perspective.
2.Literature review
Firms procure funds not only from specialized financial intermediaries but also from suppliers, generally by delaying payments.There is a lot of exist studies about trade credit, some focus on the origin and the develop of the trade credit, some focus on the relationship between the supplier and the receiver of the trade credit, also many papers test the role of trade credit during the crisis. Existing theories of trade credit provide several explanations of why companies provide trade credit: (1) alternative financing source for financial constrain firms in the imperfect market(Mian and Smith, 1992) (2) price discrimination by suppliers (Brennan et al., 1988) , (3) determined by powerful buyers(Fabbri and Menichini,2010) or warranty for product quality (Long et al., 1993) and (4) fosters long-term relationships with customers (Summers and Wilson, 2002). Since my study is mainly about test the impact of government invest on trade credit in the market and the tendency of state owned companies and non-state owned companies to be suppliers or receivers of trade credit, we would need the learn from a variety of theories, here we list the main contents of my literature.
2.1 Alternative Financing:
Academic study of trade credit began in the 1960s. Meltzer found that monetary tightening period, large enterprises increase in account receivable amount and expand the term of payment to provide trade credit to small firms.
The most traditional explanation about the existence of trade credit is that trade credit is the alternative of bank credit due to the imperfect and asymmetric information in product and capital markets( Mian and Smith, 1992). In such markets, both buyers
and sellers have to pay the costs when they investigating the information to analysis risks and benefits of the transaction.
This theory believes that suppliers have an financial advantage than banks. Since they work in the same field, suppliers have better understandings of the industry trend, technological advance, materials price, industry prospect and other information take time and experience to excavate and analysis. Besides, institutions spend time and money to do the credits evaluation of firms, to protect against the information asymmetries. Banks would reject applications for both risk management and
investigation cost purposes. While suppliers have more credit worthiness to get loans from banks and less information asymmetries to get private information from their customers at low costs, this private information and the awareness become their financial advantages compare to banks. Consequently, it is nature for suppliers to become the second layers of the bank loans to provide the credits to firms at downstream of the industry chain which are unable to be reached by financial institutions. Some big suppliers have more power to control the behavior of
customers , so they have better control for their costumers to monitor them. Suppliers also have lower liquidity costs when default.
Jain(2001) build a model to prove that suppliers would act as an intermediary between banks and borrowers due to less information asymmetric and lower information cost. Biais and Gollier(1997) find that trade credit can alleviate the problem of information asymmetric by incorporating in the lending relation which suppliers hold more private information about their customers. Our idea to test the redistribution of government
invests in line with this theory, since government investment funds also entry by larger enterprises through trade credit to financial weaker enterprises.
2.2Price discrimination:
According to this theory, the trade credit is a market tool adapted by suppliers to achieve price discrimination. Suppliers’ dominant market positions may allow them to give their different costumers trade credits at different price since they can’t charge different price of the same product to different costumers. To achieve the maximum of profits, a shorter credit term or a higher interest would be charged to the buyer which is less sensitive to the price. Brennan, Maksimovic, and Zezhner (1988) claim that low competition among suppliers in an input market may stimulate incentives to discriminate against cash and credit customers. This would happen if, first, the demand elasticity (or the reservation price) of credit customers is lower than that of cash customers, meaning that customers who take trade credit are less sensitive to the price of credit, and second, if there is adverse selection in the credit market, which means the creditworthy firms would find the trade credit expensive and pay back as soon as possible while the risky firms would use the trade credit because it is still cheaper than the bank loans they can get.
2.3Buyer Market Theory:
Study of alternative financing dilemma theory, some scholars (Fabbri and Menichini,2010) proposed a Buyer Market Theory, which points out that the existence of widespread trade credit may related to the balance of bargaining power within two counterparts. This theory points out that trade credit could be a tool used by big
buyers also. On the one hand, those financing unconstrained, good credit enterprises (especially large corporations) can make use of trade credit, low-cost access to suppliers for liquidity (Fabbri and Menichini2010); suppliers are happy to provide trade credit to such enterprises, in order to speed up its product sales. In some cases, they have to provide such trade credit to their biggest buyers.Important customers sometimes delay the payment terms and produce late payments. Also, weaker bargaining power suppliers offer lots of trade credit even when their pockets are constrained by banks. These findings suggest that suppliers use trade credit as a competitive tool in the product market, stronger buyers win a right to take and use more trade credit at a cheap price. State owned companies which have more market power would take favorable positions when negotiating trade credit.
2.4 Business Relation Theory:
Trade credit is also an important tool for relationship building and maintaining. On the supply side trade credit can be a effective and important competitive tool that plays a role in attracting new business, in building supplier customer relationships (developing an indirect equity stake in the customer), in signaling goods quality, `reputation' and deep pocket, and in price competition.
Small firms are more tend to be suppliers of trade credit, despite the consequences of doing so will cause. This finding in line with my idea of non-state owned firms would expand more trade credit than do state owned firms.
Peterson and Rajan (1997) in their paper find that buyers sometimes provide trade credit to their customers to save them. Suppliers provide trade credits to some customers even the customers are in trouble. Aiming at protect their future profits from such customers, sellers would earn a long-term interest in keeping their customers survival.
2.5 Other findings:
companies in order to occupy the dominant position in the industry or maintain their advantage or reach scale economies, often expand a lot of trade credit. In other words, this kind of enterprises “buy” sales from their customers by providing them trade credit (Peterson and Rajan 1997).
Raymond Fisman and Inessa Love(2003) in their paper highlight the relation between trade credit and the sales growth rate of the industry, they find that industries which more rely on trade credit have higher growth rate. This means trade credit plays an important role as a power of firm growth. Ying(2013) in his paper comes up with the finding that the reliance of business growth on trade credit financing will gradually weaken with the development of the financial system.
The paper written by Inessa Love, Lorenzo A. Preve and Virginia Sarria-Allende(2007) focus on how trade credits responses to the crisis in Asian countries. They find a sharp decline of trade credit provision after the crisis and attribute that to the contraction of bank credit. Because trade credit has long been thought a way to redistribute the bank credit from financial stronger firms to financial weaker firms. In the paper they test the redistribution of trade credit during and after the 1997 Asian crisis and find the result in line with the redistribution theory, some of their research methods can be adopted in my study.
Another paper related to our study is the study on Chinese government investment. Zhang, Ren and Hou (2010) in their paper study on the efficiency of government investment on economic growth. In this paper I find the data source and proxy of the government investment in China. Huang and Han(2014) find that the payment
of natural monopoly industries in China is significantly higher than others. I can adapt their finding to better examine the state owned firms in public service industry.
2.6 Hypotheses
Follows the idea of trade credit is the redistribution of external financing source from financial stronger firms to financial weaker ones. The government invests huge amount of money in the railway construction, health care, environmental management,
defense, finance, and tourism-related areas. With the funding support, firms in those industries are able to purchase equipment, hire more labor to expand production scale, improve technology and promote the development of related industries. Firms who directly benefit from such investments can supply trade credit to other customers. Firms can provide more trade credit to other firms who buy their products or provide services to them downstream. At the same time, the extend of such firms would lead to increase of raw materials and other nature resources, which will also introduce large sums of money to the provider of semi-manufactures and raw materials upstream. Therefore, upstream firms also have the ability to provide more trade credit the their buyers. Despite the channel of trade credit is a one way road from upstream to downstream, the path which government invest may increase the trade credit supply goes to both upstream and downstream from the invested firm.
Different from the redistribution of bank loans, which need the producer to apply for the credit and then provide to the customers, government order increases the company's own revenues, directly enhances the producer’s ability to offer trade credit. For example, railway construction would increase the demand of steel and cement, China Railway Construction Company(stock code 601186), the major one in charge with rail way industry, would buy more steel and resources from upstream sellers, which allows sellers to expand trade credit to CRCC and other construction companies. Meanwhile, the CRCC would also provide more trade credit to the producer of global buyers of their high-speed trains. We come up with the first hypothesis.
Hypothesis 1: The government investment helps companies to expand trade credits.
It is a common belief that state owned companies are much stronger in their financial and market power in China. Due to historical reason, private enterprises have been recognized by the reform and opening up, they are less supported by government policies, financial institutions and government investments. Although the private sector rely more on trade credit to run their businesses, the redistribution of government investment would still has a less impact on non state owned firms.
Since the reform and opening up policy took place, China's state-owned enterprises experienced a series of reform and innovation, by hardening budget constraints, so the performance of state-owned enterprises has been greatly improved, but these reforms focus more on the economic level, not on the system-level arrangements, thus failed to achieve a real sense of separation between government and enterprises. The SOEs are still playing part of the role as the invest channel for both central and local governments. There are two aspects for this fact, on the one hand, the state owned enterprises are easier to get the government orders and control the core industries such as electric power industry, oil industry, telecom industry, this gives them the right and responsibility to allocate resources(provide trade credit) in the supply chain. On the other hand, this makes the state owned enterprises safer to t get trade credit. There is a possibility that state owned firms transfer more government investment into trade credit than do non state owned firms. Therefore, we come up with our second hypothesis.
Hypothesis 2: The government invests would make SOEs provide more trade credit than do non-SOEs.
According to the price discrimination theory, enterprises which face less competition are more likely to achieve price discrimination through trade credit. With high margin of profits, sellers are willing to provide trade credit to increase sales, since the new one unit of goods won’t change the revenue of goods sold before. To test this theory, we suggest our third hypothesis.
Hypothesis 3: Firms with high profit would provide more trade credit.
Suppliers use trade credit as a competitive device to attract new customers, to compete with their peers, and maintain high speed growth. Sale growth rate is a measure for the potential, firms with higher sales growth often use trade credit to buy their sales. Therefore, we come up this hypothesis.
Hypothesis 4: Firms with high sales growth would provide more trade credit.
According to the bargaining power theory, the stronger buyer can force it supplier to expand trade credit. Because of the special nature of state-owned enterprises,
state-owned enterprises make decisions more representative of the will of the
government. Despite of chasing for profit, the state owned firms also take respond to serve the public. Once they have operating difficulties, the government has
responsibility for financial subsidies, tax breaks, and even financing guarantee. In this case, even if the state-owned enterprises insolvent, creditors do not have to worry about default, as the owner and the ultimate guarantor of the government will eventually take responsibility for the enterprise, thus reducing the possibility of state-owned enterprises business credit defaults, the state-owned therefore become safer than private enterprises and more likely to get financing (Faccio, 2006). Sellers know that they are doing business with the government behind the state owned enterprises. Here we come up with our fifth and sixth hypothesis on the demand side of trade credit.
Hypothesis 5: The government investment increases firm’s trade credits received from their suppliers.
Hypothesis 6: The SOEs would use more trade credit than do non-SOEs.
3.Background information
Contract theory proposed by Coase (1937) developed to emphasize the decisive roles of rule and property right. Therefore, when studying trade credit financing, we can not ignore China's unique institutional environment factor. Our thirty years of economic reform has made remarkable achievements, but also caused a highly uneven in market development, legal environment and the degree of government intervention among regions. Here we briefly introduce the history and the changing of the government investment, this can help us have a better understanding about the whole picture of the government invests and the basic point of trade credit in China.
Government investment is the main tool for Chinese government to achieve economic development, to promote public services, therefore it is of important macroeconomic policy means. Government investment policy is the management of the function positioning and the achievement of specific function for the government. Since the founding of China, the policy of government investment has changed several times to meet the different needs of country’s develop strategies. This progress have important influences on the economic growth, the economic structure adjustment and the implementation of the strategy plan of each period.
According to China’s modern history, there are three stages of economic development since 1949, including the planned economy period(1949-1978), the transformation period from planned economy to a market economy(1979-1997), and the market economy period(1998-).
In the first period, the government has all the power to allocate the resources for all industries, so it can focus on building the industrialized system for the country and establishing the major country owned companies in each industry such as machinery manufacturing industry, agriculture industry and chemical industry. There was no
room for private company and no market for product materials and normal commodities, all the resource were allocated by the government according to the plan. The construction plans were divided to three level according to their scales of construction, big and medium plan was proposed by the plan board of province level, examined and approved by the plan board of central level; the small size plan was examined and approved by the plan board of central level. The factories made products in accordance with the production plan, wages and the price of every kind of good was determined by the certain department in the central government. All profits must turned over to the government.
In the second period, the Chinese economic reform took place, which is a great plan aim at transform the Planed Economy to Socialist Market Economy. The whole project include several parts such as: the introduction of foreign capital, the establish of capital market, the allowance of private firms and invests, the shareholding system
reform of country-owned companies. The idea “divide revenue and expense by
central and local government, each level takes response for the appropriate level of construction project” began to implement, which expanded the power of local government from both funding side and prosecuting side. The mixed-ownership system appeared, which changed the situation of the economy public ownership as the only ownership, stimulated the vitality of the private sector and private capital. The market of raw materials and products came into being, the price mechanism replaced the plan supply and became the determinant of the allocation of resources. At the year of 1988, the Central Basic Construction Fund was established by the central government. In the same year, at the central level, the government established six national professional investment companies for energy, transportation, raw materials, and textile, agriculture, forestry industries, they are responsible for operation and management of the central investment in the business of fixed assets investment projects.With the results of reform even more significant, the leaders’ attitude toward market and private economy became more open. The legitimacy of the private firms was accepted for the first time and they began to be seemed as a ‘ necessary and helpful supplement of the public ownership economy ’. The
discussion about trade credit is meaningful after the market and private firms came into being, before that the plan board limited the supply and sale of every kind of product, all the businesses was run with the help of ‘government credit’.
4.Methodology
Figure 1 The diagrammatic sketch of the firm’s trade credit interactions
When we trying to test the amount of trade credit supplied by a firm, we take the firm as the supplier of the trade credit and the supplier of the products. When we focus on the trade credit received by the firm, we take the firm as the receiver of the trade credit and the customer of the inputs. We would test the firms firstly as the supplier of the trade credit then as the receiver.
The amount of trade credit firm provide to its customers would shows as the account receivable on the balance sheet, while the amount of trade credit firm receive from its suppliers would shows as the account payable on the balance sheet.
We need to collect the panel data of Chinese listed firms’ financial information. Our sample included 1,580 non-financial businesses listed companies. According to the CSRC industry classification standard, they were classified as public service, real estate, comprehensive, manufacturing and business industries. We chose the time period from the end of 2007 to the end of 2011, this is because after the financial crisis, the government began to increase the investment, this is perfect time period to examine the impact of state investment on trade credit. Also, within listed companies, state owned enterprises account for more than half of the composition, the private firms in the market are mostly solid and financially strong group companies or former state owned enterprises. At this point, we can test who is more willing to be the supplier of trade credit among this two kind of firms. We consider to test if non state owned firms rely more on trade credit to increase sales and whether state owned firms use more trade credit due to their strong bargaining power? What is the difference
situation in different industries, in which industry government invests increase the trade credit the most? In order to accomplish the above hypothesis, we need to collect government data, basic financial data, basic financial information and some financial indicators data.
First of all, we need the data of government investment every year, we find the data at the economic database of Chinese Academy of Social Sciences. Under the investment catalog, they classify investment by the source of funds, there are four items, national budget, domestic loan, foreign invest and self financing. We chose the national budget as the measure of government investment.
Secondly, We take the receivable divide sales (R/S ratio) as the measure of trade credit supply and take payable divide total assets as the measure of credit demand, this approach follows the methodology of Peterson and Rajan (1997). Besides those items, we also collect every year data of following items: net profits, firm’s cash holding by the end of the year, bank loans. We find detailed financial data from the annual report of the companies, but the information of bank loan is hard to collect. There are much less data about bank loans in the database, so it eliminates lots of observations when I run the regression using bank loans data.
Thirdly, we I have calculated some of the indicators. To test the relation between trade credit supply and sales growth, we add the sales of 2006 into the observations and
calculate the growth rate using the equation gi,t salesi,t /salesi,t1 1 . Also, we
need firm’s age as the control of firm’s own characteristics. I believe that firms which operating for longer time have a closer relation with government even they are not state owned firms. We use the date of the observation minus the date of the firm’s established to get the firms age and it is growing from 2007 to 2011 each year.
Finally, we need to judge whether the firm belong to state or private. We look up for the data about the real controller of the firm, to classify the ownership of the firms. According to CSMAR’s classifications, The actual controller entry contains central government, local government, related department, domestic natural persons, foreign natural person and public ownership. We concern the firm is state owned firm if the
controller of the firm belong to any kind of government institution. Thus the remain part of firms are concerned non state owned enterprises.
Table 1: Definition Of Different Variables
The table gives definition of different variables and the method of transferring the original data into the data we need for the regression.
I estimate the following model using ordinary least squares:
i t i t i t t i t
i Sales GI Stateown Assets
ceivable, / , 0 1log 2 , 3log ,
Re (1)
We would test my first hypothesis by using a regression model which include the amount of government investment as an independent variable and the trade credit supply as the dependent variable, then we would analyze the economic implications and significance of the coefficient. We use the total amount of budget invest from
Variable Definition Approach
Dependent variables
Trade credit supply The amount of trade credit supply to downstream firms.
Receivable/Sales
d
Tradedeman The amount of trade credit which
firm get from upstream sellers.
Payable/assets
Independent variables
t
GI The amount of investment each
year by government.
Got from government public info.
t i
Stateown, Whether the actual control of the
enterprise is the government.
1 if is, 0 otherwise
t i
Assets, Book value of the assets for firm
i at year t.
Got from balance sheets of listed firms.
t i
h
Salesgrowt , The growth rate of firm’s sales. Salesi,t/Salesi,t11
t i
ofit,
Pr The net profit of the firm i at year
t.
Got from balance sheets of listed firms.
t i
Cash, The amount of cash holding of
firm i at year t.
Got from balance sheets of listed firms.
t i
Loans, The amount of bank loan took by
firm i at year t.
Got from CSMAR database.
Control variables
i
Fix effect of firm, irrelevant with
time.
Age Firm age. The year of
both government as the measure of government investment. We suppose the government invest would increase the supply of trade credit since trade credit is a
redistribution process of government investment. We expect the coefficient 1
would be a positive value and significantly different from 0.
This regression can also help me to test the difference of trade credit supply between SOEe owned firms and private firms . We suppose SOEs would provide more trade credits after they get government investments because they have more important market position and easier to as and non-SOEs. The dummy variable Stateown
measures this difference between statccess to government investments. Therefore, 2
should be positive value which is significantly different from 0 according to my second hypothesis.
We consider that firms’ total assets could also be a factor that could have influence on the supply of trade credit because firms have more assets are less likely to face credit constrain from financial institutions, thus they may more likely to be supplier of trade
credit. I expect the coefficient 3 be positive and significantly different from 0.
We take control for the firm’s fix effect which is independent with time. We will use the total amount of budget invest from both government as the measure of government investment. Then we break down to industries to test my hypothesis in each industry. i t i t i t i t i t i t t i t i profit Stateown profit Assets Stateown GI Sales ceivable , , 5 , 4 , 3 , 2 1 0 , , * log log / Re (2)
Because SOEs are facing less competition than are non-SOEs, they are more likely to price discriminate through trade credit.To test my third hypothesis, we introduce a dummy variable profit above mean to the equation (1), we also add a cross term of two dummies. If the high profit margin is one of the reasons that makes firms to provide trade credit to achieve price discrimination, the coefficient should be positive and significantly different from 0. If the state owned firms with high profit margin provide more trade credit to others, the coefficient of cross term should also be
positive and significantly different from 0. i t i t i t i t t i t i h salesgrowt Stateown salesgroth Assets Stateown GI Sales ceivable * log log / Re 5 , 4 , 3 , 2 1 0 , , (3)
To test hypothesis 4th, we add another dummy variable salesgrowth and a cross term
of state owned and sales growth above mid to the equation(1) in order to test the relation between trade credit supply and the sales growth. We take the mid of sales growth, set the observations with sales growth rate higher than mid to 1 and set other s to 0. Because firms has low profit but high sales growth rate shows that the enterprises are rapidly expanding their business, this could also be the reason that firms are tend to provide more trade credit to buy additional sales. We expect the
coefficient 4 to be positive and significantly different from 0. Just like the cross
term in equation (2), this cross term stands for state owned firms with high sales growth rate. i t i t i t t i t
i Assets GI Stateown Assets
Payables, / , 01log 2 , 3log , (4)
The second part we will study the demand of trade credit, we are going to test my 5th
and 6thhypotheses by the equation (4). Instead of using payable to cost of good sold,
we use payable to assets ration as a measure of trade credit received by the firm. This proxy follows the methodology of Peterson and Rajan(1997). In this regression, we expect that the government invests would help firms to expand their usage of trade credit and the state owned firms would use more trade credit then do non SOEs. So
the coefficients 1 and 2 should be positive values and significantly different
from 0. i t i t i t t i t
i Assets GI Stateown cash loans
Payables, / , 01log 2 , 3 , 4 (5)
Then we add cash holding and bank loans as two independent variables to the regression (4) to test the influence on dependent variable. Since cash is the cheapest internal financing, it should decline with more payable dived assets. Bank loans is a substitution of self financing and trade credits, it should also have a negative
correlation with trade credit usages. Thus, we consider the coefficient 3 and 4 to be negative values and significantly different from 0.
5. Data and descriptive statistics
We use the data from CSMAR database, which is an authoritative database containing financial information , macroeconomic data and other data of listed companies in China. I use the time period from 2007 to 2011and exclude the observations from financial industry. The variables I used contained: whether the actual controller of the firm is government, total assets, receivable, payable, firm age, sales, net profits, cash holdings and the amount of bank loans.
Firstly, we would prohibit the data of our first part of the study, which is about the supply side of the trade credit. According to table 2 and table 3, the average receivable to sales ratio is 15.8%, for only state owned firms is 13.75% and for non state owned firms is 19.06%. This data proves that non state owned firms rely more on the trade credit to sale their products. State owned firms have less receivable than payable while non state owned firms have more receivable than payable. This shows that non state owned firms give more trade credit than receive, the net trade credit for this sector is negative while the state owned firms receive more trade credit than they provide, the net trade credits for state owned firms are positive. Therefore, we can clearly say that state owned firms have stronger bargaining power than private firms, they can gain lots of trade credit from suppliers and use as much cheap financing source as possible. The net positive trade credit indicates that state owned firms are more tend being a receiver of trade credit while the non state firms are net provider of trade credit, non state own firms use trade credit as a competitive device at product markets.
The natural log of government invests varies from 27.096 to 28.026, the mean value is 27.869 with a standard deviation of 0.358. The natural log of total assets varies from
19.777 to 23.977, the mean value is 21.556, the standard deviation is 0.965. The max value of the natural log of profit is 22.448, the min value is 11.664, the average value is 18.317 and standard deviation is 1.366. The firm age is in range of 4 to 37, the average age of firms is around 17 years old. Some firms perform bad with a negative sales growth rate of -98.4% while the best performing firm achieves a 15 times sales growth. All the firms in my sample experience a 90.7% sales growth but the mid value goes to 16.4%, the standard deviation is as high as 21.678.
Summery statistic
Table 2: Descriptive statistics of six variables
The table 2 shows the largest, smallest, mean and median value for the six variables---receivable/sales, log(government investment), log(total assets), firm age, log (profit) and sales growth rate. Also, the table presents the standard deviation of each variable in the last column.
Variable Max Min Mean Mid Std Dev Receivable /sales .990 0 .158 .115 .157 Log(gover nment invest) 28.026 27.096 27.737 27.869 .358 Log(assets) 23.977 19.777 21.556 21.462 .965 Age 37 4 17.730 17 4.795 Log(profit) 22.448 11.664 18.317 18.326 1.366 Sales growth rate 1497.156 -.984 .907 .164 21.678
In table 3 , we divide the sample into two groups, state owned firms and non state owned firms, there are 4804 state owned observations and 3094 non state owned observations. Basically, state owned enterprises are greater both in receivable and payable than non state owned enterprises. The non state owned firms not only provide less trade credit than do state owned firms but also they receive less trade credit than state owned firms. At the same time, non state owned firms have a higher sales growth rate on average. Although non SOEs have a higher R/S ratio and sales growth rate, their profit is still lower than SOEs. According to this, we can assure that the
state owned firms have a stronger bargaining power. The state owned firms have better profit margin and more trade credit to use, the size of the state owned enterprises is greater than the non state owned enterprises.
Table 3: Descriptive statistics of seven variables in SOE and non SOE The table shows the mean and median value of the seven variables for two kinds of firms.
Mid value Mean value
State own Non state own State own Non state own
Number 4804 3094 4804 3904 log(receivable) 18.721 18.648 18.507 18.412 log(payable) 19.087 18.464 19.025 18.416 log(profit) 18.394 18.235 18.378 18.228 log(sales) 21.151 20.638 21.174 20.665 log(assets) 21.669 21.149 21.732 21.282 Sales grow .149 .188 .801 1.071 AR/S .0947 .1502 .1376 .1906
Then we provide the data in details for five industries in table 4. They are public service, real estate, comprehensive, manufacturing and business industries. The industry has the highest account receivable is manufacturing industry, followed by public service industry, the lowest account receivable industry goes to business industry. When we look at account payable, real estate industry wins the first place. Considering it has the second lowest account receivable, real estate industry has a net positive trade credit usage. The real estate industry also has the highest mid profit, followed by public service, the comprehensive industry which means its main business is difficult to classify the industry earns the lowest profit. The real estate industry is also the highest mid value of total assets industry, followed by public service industry.
Table 4: Descriptive statistics of median value of variables in the five industries
The table shows the median value of some variables in the five selected industries---public service, real estate, comprehensive, manufacturing and business.
Public service Real estate Comprehensive Manufactur ing Business Mid log(receivable) 18.418 17.698 18.338 18.866 17.661 Mid log(payable) 18.207 19.291 18.331 18.841 19.200 Mid log(profit) 18.460 18.822 18.017 18.275 18.256 Mid log(sales) 20.559 20.903 20.645 20.955 21.464 Mid log(assets) 21.421 21.973 21.323 21.405 21.463
Mid Sales grow .168 .154 .143 .166 .145
Figure 2: Descriptive statistics of median value of variables in the five industries
Then we start to describe the statistic about our second part of regressions. Since we did not get every data of bank loans, we only keep a part of the observations comparing with the first part. We collect the data of bank loans for each year, merge this item with our first sample and rule out all the observations which can not find the loan data to matched up.
We can see in table 5, average payable to assets ratio is 9.19%. The natural log of cash holding varies from 14.383 to 22.608 with a standard deviation of 1.169. The natural log of bank loans varies from 13.459 to 23.753 with a standard deviation of 1.501. This sample don’t have big difference from our first sample although it has ruled out a lot of observations from the first sample.
The table 5 shows the largest, smallest, mean and median value for the six variables---payable/assets, log(government investment), log(total assets), firm age, log (cash) and log (bank loans). Also, the table presents the standard deviation of each variable in the last column.
variable Max Min Mean Mid Std Dev
Payable/assets .522 0 .0919 .073 .071 Log(government invests) 28.015 27.096 27.606 27.869 .361 Log(assets) 23.969 19.813 21.742 21.688 .946 Age 37 6 18.538 18 4.414 Log(cash) 22.608 14.383 19.340 19.342 1.169 Log(bank loans) 23.753 13.459 18.755 18.792 1.501
We would only emphasize the data of bank loans and cash holding in this part. Just as before, we divide the data into two groups: state owned firms and non state owned firms to check the different characteristics. For state owned firms, the mid value and mean value of the natural log of cash holding are 19.435 and 19.458 while for the non state owned firms the statistics are 19.142 and 19.108. The mid value and mean value of state owned firms’ natural log of bank loans are 18.826 and 18.818 while for the non state owned firms the statistics are 18.713 and 18.633. State owned firms have more cash holding and more bank loans, which shows state owned firms have better abilities of self funding and got a better financing support from financial institutions.
Table 6: Descriptive statistics of seven variables in SOE and non SOE The table shows the mean and median value of the seven variables for two kinds of firms.
Mid value Mean value
State own Non state own State own Non state own
Number 1028 527 1028 527 log(receivable) 18.844 18.830 18.615 18.594 log(payable) 19.242 18.964 19.127 18.834 log(profit) 18.336 18.266 18.341 18.284 log(sales) 21.256 20.913 21.253 20.938 log(assets) 21.786 21.509 21.842 21.547 Sales grow .160 .1751 .456 3.670 AP/A .075 .071 .092 .092
Log(cash) 19.435 19.142 19.458 19.108
Log(bank loans)
18.826 18.713 18.818 18.633
Next we analyze each variable by industry classification. Just like our first sample, real estate industry also the most outstanding industry. It supply the least trade credit but receive the most, it has the highest sales growth, the highest cash holding and the highest bank loan taken and the most book value of total assets. It also wins the second place on profit. Manufacturing industry still the one who supply the most trade credit to its customers. The business industry supplies the second most of trade credit and receive the second most trade credit as well, it holds the least cash and takes the least bank loans. Public service industry is the only net provider of trade credit in our samples. Since the firms in public industry are mainly oil firms, water conservancy enterprises, electric power enterprises and other resource-based enterprises, which at the top of the supply chain. It is easy to understand why they are provide more trade credit than they take.
Table 7: Descriptive statistics of median value of variables in the five industries
The table shows the median value of some variables in the five selected industries---public service, real estate, comprehensive, manufacturing and business.
Public service
Real estate Comprehensi ve industry Manufacturin g Business Mid log(receivable) 18.797 17.518 18.756 19.040 19.039 Mid log(payable) 18.393 19.582 18.893 19.148 19.139 Mid log(profit) 18.457 18.813 18.191 18.236 18.133 Mid log(sales) 20.946 21.074 21.025 21.205 21.358 Mid log(assets) 21.559 22.354 21.810 21.645 21.502
Mid Sales grow .142 .197 .133 .168 .145
Mid log(cash holding) 19.356 19.734 19.291 19.306 19.280
6. Results
In this chapter, we would exhibit and explain our results for each regression model. Firstly we focus on the supply side of the trade credit, taking firms as the suppliers of trade credit and testing different factors which can impact on receivable to sales ratio. Then, to test the last two hypotheses, we take firms as receivers of trade credit, using payable to assets ratio as proxy of trade credit received by firms.
Table 8 The regressions of R/S ratio and different factors .
This table looks at the determinants of the receivable to sales ratio in different models. In column I, we test the basic mode; in column II, we introduce fix effect to control for the causal effects; in column III to VII, we test different factors including firm age, profit ability and sales growth. All column give the impact of different factors on the dependent variable. The table also reports the standard errors in parentheses and all the standard errors are clustered. The regressions use annual data after some manipulation from 2007to 2011. And for the significance level, *, ** and *** denote significance at 10%, 5%, and 1%, respectively.
Table 8 presents the results of the regressions that analyze the factors influencing trade credit supplies of firms in China. The dependent variable is receivable to sales ratio in all seven regressions, with different independent variables to test different factors.
As expected, the variable Government Investment has positive coefficients in all regressions and bears statistical significance in three, suggesting that in general, compared with firms receiving little government investment, firms receiving much investment of government tend to offer more trade credit.According to regression III,
Model Independent variable I II III IV V VI VII Government Investment .014 (.021) .009 (.014) .046*** (.017) .016 (.022) .048*** (.017) .047*** (.017) state owned (1 if is, 0 otherwise) .043*** (.009) .010*** (.028) .111*** (.028) .0001 (.004) -.013 (.009) .115*** ( .031) .110*** (.303) Log(book value of assets) .077*** (.019) -.147*** (.0497) .041*** (.005) .086*** (.019) .069*** (.019) Log(1+ firm age) -.032 (.249) Log(1+ firm age)2 -.008 (.047) Sales growth above mid(1 if above, o otherwise) .044** (.020) state owned Sales growth above mid -.006 ( .024) Profit above mean(1 if above, 0 otherwise) .029 (.031) state owned * Profit above mean .003 (.037) Firm fix effect
no yes yes yes no yes yes
Number of observations
the government increases one percent investment would lead to a 0.0046% increase in firms receivable to sales ratio. We can deduct that government investment can positively stimulate firms to expand trade credit. We can accept the hypothesis 1. For the variable Stateown, the results show that it is significantly positive in six of the seven regressions. The exception is Model V, when the factor of firm age is considered. However, when we include variables about sales growth (or profit) in the regression and replace the variables of age with a more comprehensive variable, firm fix effect, as presented in Model VI and VII, variable Stateown exhibits significance. Therefore, it is reasonable to say that the results are consistent to our hypothesis that than non-SOEs, SOEs provide more trade credit.
Total assets variable in all the 5 models shows significant. Except for model IV, which mainly aims at controlling and comparing with model III, all other coefficients are positive. Firms having more total assets tend to extend more trade credit to their customers. According to model III, a 1% increase in firm’s total assets would lead to a 0.0077% increase in trade credit supply.
By comparing model III and model IV, we expect to test the influence of government invests on state owned firms. We calculate the difference of two coefficients between two state own dummies, and the difference is significantly positive, meaning that the government investments indeed make the state owned firms to provide more trade credit.
According to column V, a firm’s age seems not a factor that affect the amount of trade credit supplied by the firm. Younger firms supply no different trade credit in contrast to elder firms. This may be because all the Chinese listed firms are dominators in their fields. The younger ones are sub-companies which were stripping listed from parent firms, and therefore their ability and motivation of supplying trade credit have no relation with their age. This finding is in line with the result in Fabrri and Klapper (2013)’s empirical paper.
When we testing the price discrimination, according to the model VII, neither the profit dummy nor the cross term is significant. The firms earn higher profit don’t extend more trade credit to other firms. Thus, we can not accept our third hypothesis.
Besides, we introduce the sales growth rate dummy into our regressions to explore this issue from another angle. In line with our expectation, the coefficient of firms having sales growth rate above the mid value is significant. It indicates that the firms experiencing high expanding periods tend to supply 4.4% more on their R/S ratio. While in the high-speed growing firms, there is no significant difference between state owned firms and private firms.
Table 9 The regressions of different factors on R/S ratio in different industries.
This table looks at the determinants of the receivable to sales ratio in different models. From column I, to column V, we test the different factors including book value of firm’s assets, sales growth in public service, real estate, comprehensive, manufacturing and business industries. All column give the impact of different factors on the dependent variable. The table also reports the standard errors in parentheses and all the standard errors are clustered. The regressions use annual data after some manipulation from 2007to 2011. And for the significance level, *, ** and *** denote significance at 10%, 5%, and 1%, respectively.
In table 9, we examine the model VII by industries. Manufacturing industry contains 5437 observations, comprehensive industry contains only 270 observations, public service industry contains 853 observations, real estate has 693 observations, and
Industries Independent variable Public
service Real estate Comprehensive industry Manufacturing Business Government Investment -.010 (.007) .011 (.010) .013 (.015) .048*** ( .011) .003 (.005) state-owned (1 if is, 0 otherwise) .210*** (.014) .010 (.017) .019 (.025) .004 ( .005) .019* (.011) Log(book value of assets) .028 (.008) -.008 (.008) .071*** ( .022) .039*** (.004) -.017** (.007) Profit above mean(1 if
above, 0 otherwise) .041 ( .016) .007 (.016) -.040* (.024) -.011*** (.005) -.006 (.011) state-owned x Profit above mean -.064 (.018) -.022 ( .018) -.034 ( .033) -.005 (.006) -.004 (.013)
Fix effect yes yes yes yes yes
Number of observations
business industry has 645 observations. Among five industries, government invest shows significance only in manufacturing industry. This means that the redistribution of government investment through trade credit happens in the manufacturing industry. Government investment increased by 1% would lead the firms in manufacturing industry to supply 0.00048% more in their receivable to sales ratio. For other industries, there is no clear evidence of such effect.
For state owned firms dummy, public service and business industries have significantly positive coefficients, while other industries don’t. State owned firms in those two industries tend to extend more trade credit to their customers when they receive the government invests. State owned firms in the public service industry tend to extend 21% more R/S ratio than do non state owned firms. This may be because most of oil and electricity firms, often owned by the government, are in a natural monopoly industry. It is their responsibility to redistribute the government investment to their downstream customers since the industry stays at the top of the supply chain and supplies resources to other industries.
Also, firm’s total assets proved to be a factor that can influence the firm’s trade credit supply decision in three of five industries. One percentage increase in the total assets would lead to a 0.00071% increase in R/S ratio in comprehensive industry, a 0.00039% increase in R/S ratio in manufacturing industry, and a 0.00017% decrease in business industry.
Price discrimination does not exist, suggested by the result that the dummy of firms above mean profit is significantly negative for firms in manufacturing industry and in comprehensive industry, while it is not significant for other industries. This shows firms with different profitability don’t have different tendencies to provide trade credit.
Table 10 The regressions of AP/A ratio and different factors.
This table exhibit six models testing the relation before trade credit demand and other factors. Here the independent variable is payable divide assets, P/A ratio. All column give the impact of different factors on the dependent variable. The table also reports the standard errors in parentheses and all the standard errors are clustered. The regressions use annual data after some manipulation from 2007to 2011. And for the significance level, *, ** and *** denote significance at 10%, 5%, and 1%, respectively.
Table 10 shows the results of the regressions that analyze the factors influencing trade credit receives of firms in China. The dependent variable is payable to assets ratio in
Model Independent variable I II III IV V VI Government Investment .002 (.003) .003 (.003) .005 (.003) .004 (.003) .005* (.003) .005* (.003) state owned (1 if is, 0 otherwise) .004 (.004) 0 (.006) 0 (.006) 0 (.006) -.004 (.006) -.004 (.006) Log(book value of assets) -.005 (.004) -.002 (.002) Log(cash holding) -.003 (.002) -.003 (.002) Log(bank loans) 0 (.001) 0 (.001) -.003 (.005) Profit above mean(1 if above, 0 otherwise) -.011* (.006) -.011* (.006) state owned * Profit above mean .011 (.007) .011 (.007) Firm fix effect no yes yes yes yes yes
Number of observations
all seven regressions, with different independent variables to test different factors. Instead of using payable to cost of good sold, we use payable to assets ratio as a measure of trade credit received by a firm. This proxy follows the methodology of Peterson and Rajan(1997). For government invest subject, there are two regressions having significant coefficient for this term. The result means that a 1% increase in government investment would lead to a 0.00005% increase in P/A ratio. We should be aware that only two in the five regressions support Hypothesis 4, which means that the relation between government invest and trade credits receives is affected by other factors, mainly the firm’s profitability and business expansion speed.
For the variable Stateown, the results show no significant in any regression. Therefore, we can say there is no difference between state owned firms and private firms in receiving trade credit from suppliers. One possible explanation is that all the listed firms are better firms in each industry and they can make use of trade credit from financial weaker suppliers. Their stronger bargaining power and their tendencies to use trade credit are indifferent. Therefore, we cannot accept our last hypothesis.
For bank loan variable, in none of regressions it shows significance. It indicates that there is no substitution effect between bank credit and trade credit among Chinese listed enterprises. This finding is against the theory of Smith(1987), saying that suppliers have a financial advantage to be providers of credit to customers. The cash holding tells the same story since there isn’t any significant value for these variables. Big firms can surely get support by banks in China, but they are not the only ones who can rely on trade credit as the financing sources. To explain the fact, we consider it may be because all the listed firms keep chasing trade credit from their suppliers to achieve profit maximization though getting bank loans and having some cash by hands.
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7.Robust check
In this chapter, we present the robust check for the results above. We alternatively use the account receivable to assets ratio to replace the receivable to sales ratio.
By changing the dependent variable, we can test if the models work well. The results are similar to the original models, as shown in table 10, so the models pass the robust check.
Table 10 The regressions of R/A ratio and different factors .
This table looks at the determinants of the receivable to sales ratio in different models. The regressions use annual data after some manipulation from 2007to 2011. And for the significance level, *, ** and *** denote significance at 10%, 5%, and 1%, respectively.
Independent variable I II III IV Government Investment .0019 (.0015) .001 (.001) .001* (.0006) .001** (.0005) state owned (1 if is, 0 otherwise) .009*** (.002) .005*** (.002) -.003 ( .002) .004** (.002) Log(book value of assets) .004** (.001) .005*** (.001) .005*** (.001) Log(1+ firm age) Log(1+ firm age)2 Sales growth above mid(1 if above, o otherwise) .008*** (.001) state owned Sales growth above mid -.005*** ( .002) Profit above mean(1 if above, 0 otherwise) .004** (.002) state owned * Profit above mean -.004 (.003) Firm fix effect
no yes yes yes
8. Conclusions
In this paper, we build several models to test the relation between government investment and the trade credit in China. Also, we examine the different tendencies of state owned firms and non stated owned firms. Our study tests the Chinese listed firms both as suppliers of the trade credit and as the receivers. We find that the investment projects taken by Chinese government indeed help the firms extend their trade credit supplies to their customers. Just like Love and Preve (2005) find in their study, trade credit plays a role of redistribution of bank loans from financial stronger firms to financial weaker firms, trade credit plays the same role as bridge to link the deep pocket firms with no so good firms, redistribute the government investment, and help the whole supply chain thrive. At the same time, the state owned firms in China have more power in product markets and capital markets than non state owned firms. Our findings reveal that under the government investments background, state owned firms are more likely to become trade credit providers than private firms. State owned enterprises in China help government investment pass to more firms on the supply chain. Our regression rejects the rice discrimination theory by Brennan, Maksimovic, and Zezhner (1988). Firms making more profit don’t tend to extend more trade credit to achieve price discrimination. Meanwhile the firms with high growth rate in sales also provide more trade credit to their customers, because they use trade credit to “buy” their sales and growing opportunities.
As for the demand side of trade credit, statistics support our hypothesis that government investment would extend the firms’ usage of trade credit. But this usage increasing effect is no difference between state owned enterprises and private enterprises. Besides, cash holding and bank loans don’t affect firms usage of trade credit.
According to our findings, we can come up with several implications. Firstly, The Chinese government's investment in the economy's strategy does help business development. Government should increase investment to make listed firms extend
more trade credit to others, since after listed firms get investments, they tend to extend the trade credit rather than take up it. Secondly, for firms who are customers of such listed firms, they should negotiate with listed firms to get more trade credit. With the increase in government investment, the listed companies could provide more liquidity to customers. Thirdly, for the policy makers, the order of redistribution of trade credit should be protected. The policy maker should strengthen supervision to prevent the use of trade credit for corruption and to prevent the excessive expansion of the redistribution process to cause systemic risk.
Although our study fills the gap between trade credit and government investment, due to the limitation of data, we still leave a lot of area for future study, we hope further studies can help to complement our research. Firstly, the shortage of bank loan data limits the convincing power of our regressions on the demand side of trade credit since we drop a lot of observations which we can not find bank loan information. Secondly, the samples we use for the large public traded firms may can not represent the majority of Chinese enterprises. The impact of government investment on the trade credit of the company outside of the listed companies is not clear. Thirdly, although we find that state owned firms redistribute more government invests to other firms than do private firms, we don’t know the efficiency and transaction costs of this redistribution. Therefore, more researches are needed to compare the efficiency of such redistribution process between SOE and non SOE. At last, we don’t know why state owned firms transfer more government investment into trade credit or how to improve the investment channel to benefit more enterprises through trade credit.
9. Reference
[1] Fabbri D, Menichini A M C. Trade credit, collateral liquidation, and borrowing constraints[J]. Journal of Financial Economics, 2010, 96(3): 413-432.
[2]Fabbri D, Klapper L. Bargaining power and trade credit[J]. 2013.
[3]Fan Gang et al. NERI Index of Marketization of China’s Provinces 2006 Report. [D]Economic Science Press, 2006.
[4]McGuinness G, Hogan T. Bank credit and trade credit: Evidence from SMEs over the financial crisis[J]. International Small Business Journal, 2014: 0266242614558314.
Brennan, Michael, Vojislav Maksimovic and Josef Zechner (1988), “Vendor Financing,” Journal of Finance, 43 (3), 1127-1141
[5] Huang Kai-di, Han Liang-zhi. Empirical Analysis on the income level of the natural monopoly industry in China[J]. China’s Economy and Trade, 2015, 8: 011.
[6]Fisman R, Love I. Trade credit, financial intermediary development, and industry growth[J]. The Journal of Finance, 2003, 58(1): 353-374.
[7] Brennan, M. J., MAKSIMOVICs, V. O. J. I. S. L. A. V., & Zechner, J. (1988). Vendor financing. The Journal of Finance, 43(5), 1127-1141
[8] Smith, J. K. (1987). Trade credit and informational asymmetry. Journal of Finance, 863-872.
[9] Faccio M, Masulis R W, McConnell J. Political connections and corporate bailouts[J]. The Journal of Finance, 2006, 61(6): 2597-2635.
[10] Long, M. S., Malitz, I. B., & Ravid, S. A. (1993). Trade credit, quality guarantees, and product marketability. Financial Management, 117-127.
[11] Ferris, J. Stephen (1981), “ A Transaction Theory of Trade Credit Use, ” Quarterly Journal of Economics, 96, 247-270.
[12] Wilner B S. The exploitation of relationships in financial distress: The case of trade credit[J]. The Journal of Finance, 2000, 55(1): 153-178.
[13] Zheng Jun et al．Can Higher Quality of Internal Control Increase Trade Credit Financing? ———Evidence from Monetary Policy Changes[J] Accounting Research, 2013,6:011.
[14]ZHANG Wei-guo, REN Yan-yan, HOU Yong-jian.The Local Government Investment Effects on Long-term Economic Growth — — — Evidence from China ’ s Economic Transformation[J].China Industrial Economics,2010, 8:23-33.
