How does government intervention affect the formation of zombie firms?

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How does government intervention affect the formation of zombie firms? Qingqing Chang a, Yisihong Zhou b, Guangqiang Liu b, Di Wang b, *, Xiaojie Zhang b a b

School of Information Management & Engineering, Shanghai University of Finance and Economics, Guoding Road, Yangpu District, Shanghai, 200433, China School of Accounting, Zhongnan University of Economics and Law, Nanhu Road, Hongshan District, Wuhan, Hubei Province, 430073, China

A R T I C L E I N F O

A B S T R A C T

Keywords: Zombie firms Government intervention Supporting hand Grabbing hand China

Zombie firms cause serious, widespread harm to the economy. It is thus important to clarify the reasons for their formation. This paper empirically investigates the effects of government intervention on the formation of zombie firms. It suggests that a greater degree of government intervention can increase the risk that a firm will become a zombie firm. Robustness tests and endogeneity tests confirm this finding. Further, we undertake a preliminary exploration of the mechanism of government intervention on the formation of zombie firms, and study how government behaviors affect the formation of such firms from various perspectives. Analysis reveals that government induces the formation of zombie firms by means of subsidies, resource support, financial support, and tax. To a certain extent, the conclusions of this paper could guide the formulation and revision of government policies, which would be conducive to adjusting the direction and intensity of government intervention and providing new ideas for supply-side structural reforms in China. The Chinese government should further increase the role of market force in its reforms.

1. Introduction The “new normal” of the Chinese economy1 will require high-quality development. Overcapacity impedes such development. Thus, in the process of supply-side structural reforms, China has undertaken a project of “cutting overcapacity, reducing excess inventory, deleveraging, lowering costs, and strengthening areas of weakness,” a process that includes eliminating so-called “zombie firms.” As a primary task, “cutting overcapacity” not only reflects the seriousness of China's current overcapacity problem, but also highlights its determination to solve it. However, zombie firms are responsible for a large amount of overcapacity. This overcapacity has not been eliminated by falling demand, which hinders capacity reduction through normal market mechanisms. Therefore, the key to cutting overcapacity is to eliminate zombie firms. The term “zombie firm” is not only frequently used in official documents, but has also become a hot topic in academic research. It was first proposed by Kane (1987). The existence of zombie firms causes great social harm (Kwon et al., 2015). Zombie firms are the “pain points” of economic development. They make use of valuable social resources such as human resources, material resources and financial resources, which leads to great waste. Due to the limitation of resources, this inevitably

leads to crowding out effects on normal firms and reduces the efficiency of resource allocation in an industry (Ahearne and Shinada, 2005). It is difficult for emerging firms to enter an industry, and can even lead to a situation where it is better to be eliminates from the industry than to succeed. When an industry is in a downturn, according to the normal market rules, inefficient firms with low production technology should be eliminated, but these firms are able to withstand losses with the help of the government and banks, and can push high-quality firms out of the market. Zombie firms seriously affect social innovation and technological progress, and are a major hidden danger to economic development. Zombie firms cause serious, widespread harm to the economy (Imai, 2016), and there is an urgent need to find ways to eliminate them. However, we must consider what causes the deterioration and proliferation of zombie firms. Listed firms are an important force in local economic development. Since the advent of fiscal decentralization reform, local government officials have focused on supporting listed firms to help them win promotions. Thus, as long as the cost of supporting zombie firms is less than their contribution to local GDP and tax revenue, local governments will be willing to help them survive. In recent years, studies have found that government intervention is a major cause of the formation of zombie firms. There are several types of

* Corresponding author. E-mail address: [email protected] (D. Wang). 1 The “new normal” means that the economy has entered a stage of high efficiency, low cost, strong structure, and sustainable development, which indicates that the economic growth rate has shifted from high-speed to medium-high-speed growth. https://doi.org/10.1016/j.econmod.2020.02.017 Received 1 December 2019; Received in revised form 7 February 2020; Accepted 9 February 2020 Available online xxxx 0264-9993/© 2020 Elsevier B.V. All rights reserved.

Please cite this article as: Chang, Q. et al., How does government intervention affect the formation of zombie firms?, Economic Modelling, https:// doi.org/10.1016/j.econmod.2020.02.017

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government intervention. The first is macro-control, which is mainly manifested in macro-economic policies such as monetary, fiscal, and exchange rate policies, which to regulate and control the market. The second is micro-management, which is mainly manifested in direct or indirect government participation in state-owned firms in the name of shareholders. The third is government regulation, also known as “government supervision,” which is mainly manifested by the government regulating society and the market by legal authorization such as enacting laws and regulations that aim to achieve economic and social supervision. To sum up, this paper discusses the ways in which local government uses economic and legal means to intervene in firms in China, thus affecting their operation. This paper empirically investigates the effects of government intervention on the formation of zombie firms. It presents evidence that the higher the degree of government intervention, the greater the probability that a firm will become a zombie firm. Further, we make a preliminary exploration of the mechanism by which government intervention leads to the formation of zombie firms, from four different perspectives. Further analysis reveals that the government causes the formation of zombie firms by means of subsidies, resource support, financial support, and taxation. The contributions of this paper are as follows. First, it provides more direct evidence of the causes of the formation of zombie firms. Most of the literature focusing on Chinese firms remains at the level of qualitative analysis. Our paper takes zombie firms as the starting point and systematically reveals the mechanism through which government intervention causes the formation of zombie firms. It is a useful supplement to the theory of zombie firms and provides incremental empirical evidence for research on zombie firms. Second, our paper relates to and complements prior researches on government intervention. Although the literature on government intervention in China is relatively rich, it has not yet focused on the impact of government intervention on zombie firms. Our article fills in the gap. Thus, our paper can enrich the literature on the economic consequences of government intervention and provides a more complete assessment of the impact of government intervention on zombie firms. Third, our paper provides strong practical guidance for preventing the emergence of zombie firms in addition to making general academic contributions. Also, our findings provide policy implications for other emerging countries fight zombie firms. The remainder of this paper proceeds as follows. Section 2 discusses relevant previous studies and develops the research hypothesis. Section 3 describes the data collection method. Section 4 presents the empirical results. Section 5 concludes the paper.

Japan's economic development stagnated (Hoshi and Kashyap, 2004; Peek, 2008). The second cause is banks. Numerous studies have found that the emergence of zombie firms is tightly linked to banks' incentive to cover up bad debts (Peek and Rosengren, 2005; Hoshi, 2006; Hoshi and Kashyap, 2010; Watanabe, 2011; Ueda, 2012). From the banks' perspective, if they stop lending to zombie firms, it is very likely that previous loans will not be recovered; a large number of defaulted loans will lead to a reduction in the banks' own capital, affecting their normal operation. This mentality among banks is good news for debt-ridden firms, which can obtain loan renewals and become zombie firms rather than exit the market. Wilcox (2008) found that after the financial crisis in the United States, there were not as many zombie firms as in Japan. This was because U.S. banks quickly publicized the issue of defaulted loans after the financial crisis, thus inhibiting some banks’ attempts to cover up bad debts. The third cause is firms themselves. In addition to external macrofactors, some scholars have explored the micro-factors that lead to the formation of zombie firms. Cheng and Hu (2016) used propensity-score matching and found that low product quality, low technological innovation, and lack of entrepreneurship are important micro-factors leading to zombie firms. An empirical study by Han and Tian (2017) found that poor quality of internal control makes it more likely that a firm will become a zombie firm. In addition to these factors, some scholars have found that the legacy of the large-scale stimulus in 2008, the impact of external demand (Nie et al., 2016), imperfect social security mechanisms (Wang and Gao, 2014), and the regional preference of government officials (Chen and Huang, 2017) are important factors in the formation of zombie firms. Although there is a large literature on zombie firms, its quality is uneven. Early research in this field was almost exclusively based on qualitative analysis, rather than empirical data. In addition, their conclusions were based on firms in Japan, the United States, and South Korea. There is a lack of in-depth studies of the characteristics and causes of domestic zombie firms in China. Only a few papers have empirically studied the causes of the formation of zombie firms in China (Cheng and Hu, 2016; Han and Tian, 2017; Jiang and Lu, 2017; Rao and Wan, 2018; Song et al., 2019). Research has been relatively scattered, and has not yet established a systematic view. 2.2. Government intervention and zombie firms At present, China's resource allocation is not yet fully driven by the market, and it still frequently relies on an administrative-led resource allocation management model. To achieve economic, political, and social goals (Lin and Li, 2008; Pan et al., 2008), the government will take direct or indirect measures to prevent firms from exiting the market, including providing direct financial support, directly controlling the operations of state-owned firms, and deregulation (Brown and Dinc, 2011; Hoshi and Kashyap, 2010; Kawai and Morgan, 2013; Chernobai and Yasuda, 2013; Willam, 2014; Jaskowski, 2015). The government will also indirectly intervene by compelling banks to continue lending to firms, which means that many firms that should have been eliminated by the market will continue “stiff but deathless” (Wang and Gao, 2014; Nie et al., 2016). To win promotions, which primarily requires strong contributions to GDP, local government officials often support key national industries beyond actual need, resulting in redundant construction and overcapacity (Liu and Yu, 2017). After firms become zombie firms, the government continues to give them assistance to crowd out firms in other regions. Rao and Wan (2018) found that large government subsidies increase the risk of formation of zombie firms. Luan et al. (2018) took small and medium-sized firms in Shanghai as a research sample, and found that R&D subsidies reduced the risk of normal firms becoming zombie firms in the short term, but could make zombie firms worse in the long term. Some scholars also believe that the bankruptcy of zombie firms leads to financial risks, which affect economic and social stability. This in turn will damage the government's image and indirectly affect performance evaluation. For this reason, the government will intervene

2. Literature review and hypothesis development 2.1. Causes of zombie firm formation Many factors cause the formation of zombie firms. Previous studies show that the main causes are the government, banks, and firms themselves. The first cause is the government. For the sake of its own interests (Pan et al., 2008; Tan et al., 2012), the government may take measures to prevent firms from withdrawing from the market, including providing direct financial assistance or deregulation (Brown and Dinc, 2011; Hoshi and Kashyap, 2010; Willam, 2014; Jaskowski, 2015). These are all inappropriate forms of government bailout. The government may also indirectly interfere with banks and require that they continue to lend money, which means that many firms that should be eliminated from the market continue “stiff but deathless” (Wang and Gao, 2014; Zhu and He, 2016; Nie et al., 2016). For example, during the economic recession of the 1990s, to maintain the financial market and social stability, the Japanese government chose to loosen its regulations. The government did not force firms with heavy losses to withdraw from the market, and allowed them to sustain serious bad debts with the banks. These actions acquiesced in or even encouraged “zombie lending.” In the long run, 2

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in firms, which leads to an increasing degree of firm rigidity.

However, government subsidy is different from credit. Firms often have great control over funds. They may distort the specified use and may decide not to use the funds for production and operation. Consequently, the government has become a “booster” to the formation of zombie firms. Furthermore, the hypothesis of “economic man” and the theory of “special interest groups,” as espoused by the school of public choice represented by Buchanan, support this paper's viewpoint. They believe that the government comprises various “rational persons,” and some local governments have degenerated into “self-interested organizations” whose actions run counter to the interests of the public. Government officials are also concerned about promotion, and thus naturally have their own interests to consider. Shleifer and Vishny (1994) held that government officials will use state-owned firms under their control to achieve their political goals. Boycko et al. (1996) found that the government has the same motivation to force private firms to employ more labor. To achieve the goal of stimulating economic growth and maintaining high employment levels, the government will actively intervene in firms that are on the verge of bankruptcy but contribute to GDP and local tax revenue. The government helps them survive, and zombie firms are born. In addition, excessive government intervention in firms and market has brought about rent-seeking behaviors. Not only has it led to unfair competition in the market, but firms use limited resources for rent-seeking rather than to improve productivity. The operating conditions are deteriorating day by day, resulting in firms that are “stiff but deathless.” Therefore, excessive government intervention is a major reason for the increase in the rigidity of firms, until they ultimately become zombie firms. In summary, we can see that government intervention will weaken the self-sufficiency of firms and increase the risk that they will become zombie firms. Accordingly, we propose the following hypothesis:

2.3. Hypothesis At present, China is in a period of transformation from a planned to a market economy. As China is a developing economy, firms will be affected to a certain extent by the institutional environment, especially government intervention. There are two different views of the role of government, as a “supporting hand” or a “grabbing hand” (Shleifer and Vishny, 1994). Whatever role the government plays, government intervention has a far-reaching impact on firms and society. The greater the degree of government intervention, the greater the impact on listed firms. Lee (1996) has found that more government intervention in trade is linked to lower productivity growth. Since China began its reform and opening up, it has pursued economic reform and decentralization. Encouraging economic development is an important task of government at all levels, and it is related to the promotion of officials. Local governments have strong motivation to intervene in economic development (Tan et al., 2012), especially due to fierce competition among regions; thus, government is more and more active in establishing links with firms and interfering in their operations. State-owned firms in China generally have two kinds of policy burden: strategic and social2 (Shen and Ni, 2014). The policy burden caused by government intervention will inevitably increase the operating costs of firms and lead to a failure to obtain normal profits in the market (Bai and Lian, 2014). These firms lack viability. To avoid the bankruptcy of state-owned firms, the government helps them out of “paternalism” (Kornai, 1980), which forms a soft budget constraint. This constraint distorts the real financing constraints of firms and induces excessive resource investment in the firms. Therefore, the managers of state-owned firms rely on government help because they know that the government will provide a backstop for the firm's debts regardless of its viability. Thus, they treat debts as unimportant and are less sensitive to changes in leverage, assets, and interest rates. Ultimately, firms lose their viability and become zombie firms. In addition, there is information asymmetry (Akerlof, 1970) between the government and firms. Zombie firms usually need to apply to the government for financial assistance to maintain their survival, and obtain subsidies if they successfully undergo an examination and approval process. Firms may consequently conceal the deterioration of their financial situation through earnings management and other means to meet government standards; past subsidies can also be used through earnings management to compensate for a deteriorating financial situation, to obtain sustained subsidies. In addition, it is difficult for the government to fully understand the actual operations, financial stability, and managerial ability of firms. As the government does not know whether the losses of firms are policy losses or operational losses, the government hopes that firms can extricate themselves from the predicament, and giving subsidies is almost the only way to do this. In addition, due to the expansion of the scale of zombie firms, healthy firms cannot obtain financing, and they may experience operating difficulties or even exit the market. The departure of non-zombie firms aggravates policy risk and leads to adverse selection. In the view of ex post information asymmetry, moral hazard may result from assistance to zombie firms. Zombie firms that depend on bank credit only need to pay interest regularly to obtain the right to use the funds, so banks will prevent firms from investing in high-risk projects to ensure the recovery of funds.

H. Government intervention will increase the likelihood of the formation of zombie firms. 3. Research design and method 3.1. Identification of zombie firms There are two generally used methods of identifying zombie firms in China: the CHK (or modified CHK) method and the continuous operating loss method. 3.1.1. CHK method and modified CHK method Caballero et al. (2008) jointly presented a methodology for identifying zombie firms, subsequently known as the “CHK method.” The core idea of this method is that if the actual interest expenditure of a firm is lower than the minimum required interest payment, then this firm is zombie firm. However, this method provides a noisy measure, with both type one and type two errors. It may identify relatively healthy firms as zombie firms and may not identify unhealthy firms as zombie firms. Some scholars have subsequently improved on this approach. In the FN-CHK method proposed by Fukuda and Nakamura (2011), zombie firms are identified according to what they call the evergreen lending criterion3 and profitability criterion.4 Nie et al. (2016) further refined this method as follows: if a firm has been categorized as a zombie firm by the FN-CHK method for two consecutive years, then the firm is a zombie firm.5

3

Firms that were unprofitable and highly leveraged and had increased their external borrowings were categorized as zombie firms. 4 Firms whose earnings before interest and taxes (EBIT) exceeded the hypothetical risk-free interest payments were excluded from being categorized as zombie firms. 5 Huihua Nie, Ting Jiang, Yuxiao Zhang et al. Research Report on Chinese Zombie Firms: Current Situation, Causes and Countermeasures[R]. Beijing: The National Academy of Development and Strategy (2016).

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The policy burden is the burden caused by the state's policy arrangements for the consideration of macroeconomic development rather than maximizing the profits of firms themselves. Among it, the strategic policy burden is the burden of investing in capital-intensive industries that do not have comparative advantages, under the influence of the traditional catch-up strategy. And the social policy burden is the burden caused by undertaking too many social functions, such as hiring redundant workers, providing for workers' welfare, etc. 3

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Wang et al. (2017), using the methods of Sun et al. (2005), Wang and Gao (2012). The values range from 0 to 10. However, the index is a negative index; that is, the larger the index value, the lower the degree of government intervention. We thus use the “10 – index of the relationship between government and market” to measure the degree of government intervention. The larger the value, the higher the degree of government intervention.

3.1.2. Continuous operating loss method CHK methods are based on research on Japanese zombie firms that survived on bank credit in the 1990s. The main problem of these methods is that they confuse the superficial characteristics with the conditions or channels for the creation of zombie firms. In the light of the current situation in China, we cannot directly copy these methods, because preferential loans are just one of the reasons for the formation of zombie firms in China (Rao and Wan, 2018). Therefore, we argue that zombie firms should be identified according to the actual situation in China. Zombie firms were first defined in a State Council executive meeting in 2015. Zombie firms refer to firms with overcapacity that do not meet national energy consumption, environmental protection, quality, and safety standards, and which have sustained losses for more than three years and do not meet the structural adjustment requirements.6 Therefore, considering the real situation of China, it is more appropriate to identify zombie firms with continuous operating losses. Moreover, domestic scholars have aWaldeady adopted this method. For example, Cheng and Hu (2016) regarded firms whose profits or net profits aside from government subsidies are negative for two consecutive years as zombie firms; Zhu and Chen (2016) used the official criteria to identify zombie firms and analyzed the factors in the formation of zombie firms in China. Based on the official criteria, we use the identification methods of Zhu and He (2016), Rao and Wan (2018), and Song et al. (2019). We regard firms with negative net profits (except for non-recurring gains and losses) for three consecutive years as zombie firms.

3.3.3. Control variables To purge the effect of other fundamental drivers of the formation of zombie firms, we include a number of control variables that the literature has shown to associate with it (Chen and Huang, 2017; Rao and Wan, 2018; Song et al., 2019). Firm liquidity (Cr), using current assets/current liabilities to measure a firm's ability to convert current assets into cash to repay its liabilities. Relative profitability (Profit) equals the difference between the firm's profitability and the industry's annual average profitability, in which profitability is represented by net profits except for non-recurring gains and losses/sales revenue; thus the greater the value of relative profitability, the smaller the industry shock. The rate of overhead expenses (Expense) equals the rate of overhead expenses minus the average annual industry rate. The higher the value, the lower the management efficiency. The higher the management efficiency, the less likely it is to become a zombie firm (Rao and Wan, 2018). Firm growth ability (Growth), is represented by operating income growth rate. Listing time of the firm (Age) is represented by the cumulative years from the firm's listing date to the forecast year. Many studies have found that the listing time of the firm has an impact on business behavior. Size of the firm (Size) is represented by ln(total assets). Size may have two effects on the formation of zombie firms: On the one hand, the bigger the firm, the more scientific and standardized its internal management, and the stronger its ability to reduce risk. On the other hand, the bigger the firm, the greater the social impact of bankruptcy, and the more reluctant the government will be to let it go bankrupt. Financial leverage (Lev) equals total liabilities/total assets. The greater the value, the higher the likelihood that the firm is in financial distress. State ownership (SOE) equals 1 for state-owned firms and 0 for private firms. Moreover, we control for annual (Year) and industry (Ind) fixed effects. The main variables are defined in Table 1. To test the impact of government intervention on zombie firms (that is, to verify the research hypothesis of this paper), we make use of a Probit model. Due to government intervention is time-lagged, and there is a potential endogeneity problem between the dependent variable and control variables, thus we use one lag of independent variable and control variables.

3.2. Sample selection Our research sample consists of A-share listed firms from 2008 to 2016. Due to the region's special situation, listed firms in Tibet are excluded. Financial firms and firms with incomplete data are also excluded. The remainder (10,828 observations) are included in our study sample. The data used are from the WIND database, CSMAR database, and Juchao Information Network. Certain variables that cannot be extracted and calculated from the database are collected manually. In addition, to avoid the negative influence of extreme outliers on the results, the raw data of all continuous variables are winsorized at the 1% level. Stata 14 and Excel 2016 are used for data processing. 3.3. Variables and model 3.3.1. Dependent variable Based on the official criteria, we use the identification methods of Rao and Wan (2018), and Song et al. (2019). We set the zombie firm dummy variable (Zombie) as follows. If the net profits (except for non-recurring gains and losses) are negative for three consecutive years (t, t þ 1, t þ 2), the firm is identified as a zombie firm and given a value of 1; otherwise, the value is 0.

Zombiei;t ¼ β0 þ β1 Govi;t1 þ β2 Cri;t1 þ β3 Profiti;t1 þ β4 Expensei;t1 þ β5 Growthi;t1 þ β6 Agei;t1 þ β7 Sizei;t1 þ β8 Levi;t1 þ β9 SOEi;t1 X X þ βj Industry þ βk Year þ εi;t

3.3.2. Independent variable We use the index of the relationship between the government and the market7 in the “Report on marketization index by provinces in China” by

(1) 4. Results 4.1. Description

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http://www.gov.cn/zhengce/2015-12/10/content_5022115.htm. The index includes five secondary indicators: reducing government intervention in firms, market allocation of economic resources, reducing the scale of government, reducing the extra-tax burden of firms, and reducing the taxes and fees of rural residents. The first indicator represents direct interference in firms, while the other four indicators indirectly reflect the strength and policy environment of government intervention. For example, “reducing the burden of taxes and fees on rural residents” reflects the reality that part of the government's revenue comes from fund-raising, extra-tax charges, and so on. The transfer and distribution of economic resources remains opaque, distorting the rational allocation of resources by the market and reducing the transparency of the market environment. As a consequence, the government remains at the regulatory level and engages in rent-creating and rent-drawing, rather than becoming service-oriented. 7

4.1.1. Description of the main variables Table 2 reports descriptive statistics for the main variables. The mean of zombie is 0.111, meaning that the proportion of zombie firms is 11.1%, roughly the same as the 10% estimated by Zhu and He (2016) using data from listed firms, while slightly lower than 13% as estimated by Nie et al. (2016) using data from Chinese Industrial firms Database. The minimum and maximum of government intervention (Gov) are 0.880 and 8.150, which demonstrates the major difference in the degree of government intervention in different regions of China. The standard deviation of size (Size) is 1.286, which means that the volume gap of A-share listed firms in China is large. The mean and median of financial 4

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Table 1 Definitions of main variables. Variable type

Variable name

Symbol

Variable definition

Dependent variable

Zombie

Zombie

If the net profits except nonrecurring gains and losses are negative for three consecutive years (t, t þ1, t þ 2), the firm is identified as a zombie firm (value of 1); otherwise it has a value of 0.

Independent variable

Government intervention

Gov

10 – index of the relationship between government and market

Control variables

Firm liquidity Relative profitability

Cr Profit

Rate of overhead expenses

Expense

Firm growth capacity Listing time

Growth

Current assets/current liabilities The difference between the firm's profitability and its industry's annual average profitability The rate of overhead expenses minus that of the average annual industry Operating income growth rate

Firm size Financial leverage State ownership

Size Lev

Age

SOE

Fig. 1. Statistics on the number of zombie firms and degree of government intervention.

The current year – the listing year þ1 Ln(total assets) Total debts/total assets

Table 3 The distribution of zombie firms.

State-owned firms are assigned a value of 1 and private firms are assigned a value of 0.

Type

Table 2 Descriptive statistics for the main variables. Variable

N

mean

sd

min

p50

max

Zombie Gov Size Lev Cr Growth Age Expense Profit SOE

10828 10828 10828 10828 10828 10828 10828 10828 10828 10828

0.111 3.149 22.310 0.513 1.604 0.177 12.080 0.144 0.141 0.542

0.314 1.493 1.286 0.194 1.104 0.446 5.841 0.380 0.390 0.498

0 0.880 19.690 0.113 0.220 0.522 3 1.569 1.151 0

0 2.880 22.140 0.510 1.329 0.101 12 0.046 0.012 1

1 8.150 26.140 0.979 6.857 2.896 24 0.316 0.191 1

The number of zombie firms

Panel A: distribution of zombie firms by industry Accommodation and catering (H) 9 Agriculture, forestry, animal 41 husbandry and fishery (A) Manufacturing (C) 895 Wholesale and retail (F) 75 Comprehensivea(S) 17 Water conservancy, environment, and 7 public facilities management (N) Real estate (K) 41 Mining (B) 22 23 Information transmission, software and information technology services (I) Electricity, thermal, gas and water 29 production and supply (D) Science and technology services (M) 2 Transport, storage, and post (G) 21 Culture, sports and entertainment (R) 3 Leasing and business services (L) 4 Construction (E) 10 Panel B: distribution of zombie firms by ownership State-owned 794 Private 405 Panel C: distribution of zombie firms by listing time 1–5 87 6–10 217 11–15 345 16–20 364 >20 108 Panel D: distribution of zombie firms by scale Large 864 Medium-sized 300 Small and micro 35

leverage (Lev) are very close, indicating an even distribution. However, different industries have different financial leverages. For example, the real estate industry and heavy industry have high leverage, and zombie firms are often found in these industries. The minimum and maximum of liquidity (Cr) are 0.220 and 6.857, which indicates a great difference in short-term solvency. The standard deviation of listing time (Age) is 5.841, indicating a major difference in the listing time of the firms. The mean of the rate of overhead expenses (Expense) is less than 0, indicating that the rate of overhead expenses of most listed firms is lower than the industry average, which indicates that the management efficiency of most firms is high. The mean of relative profitability (Profit) is 0.141, showing that the profitability of most listed firms is lower than the industry average; thus, the minority of firms contribute the majority of profits. Fig. 1 shows the trend of the number of zombie firms and degree of government intervention. According to it, we can know the trend of degree of government intervention is basically consistent with the number of zombie firms. Next, we show the distribution of zombie firms according to different classification standards. Table 3 shows the distribution of zombie firms. Panel A, Panel B, Panel C and Panel D represent the distribution of zombie firms by industry, by ownership, by listing time and by scale, respectively. Panel A shows the distribution of zombie firms by industry, which is almost the same as that measured by Zhu and He (2016). Zombie firms account for a large proportion of a number of

The number of normal firms

Proportion of zombie firms

31 179

22.50% 18.64%

5848 592 158 91

13.27% 11.24% 9.71% 7.14%

599 326 347

6.41% 6.32% 6.22%

464

5.88%

38 440 70 109 307

5.00% 4.56% 4.11% 3.54% 3.15%

5070 4559

13.54% 8.16%

1890 2343 2371 2416 687

4.40% 8.48% 12.70% 13.09% 13.58%

8182 1363 89

9.55% 18.04% 28.23%

Notes: This table reports distribution of zombie firms by different classification standards. Panel A, Panel B, Panel C and Panel D represent the distribution of zombie firms by industry, by ownership, by listing time and by scale, respectively. a If the industry ownership cannot be determined according to the above classification method, the industry ownership of the listed company shall be determined by the industry classification expert committee of the listed company according to the actual operating conditions of the company. And if the ownership is not clear, it shall be classified as a comprehensive category.

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industries, including agriculture, forestry, animal husbandry, fishery, manufacturing, accommodation and catering, wholesale, and retail. There are many zombie firms in the manufacturing industry with serious overcapacity. The wholesale industry, as a typical labor-intensive industry, has many zombie firms, which confirms that governments favor supporting these zombie firms to maintain local employment levels. The overcapacity problem of the transport industry has become more and more serious, and the number and proportion of zombie firms in the transport industry are high. Panel B shows the distribution of zombie firms according to state ownership. The proportion of state-owned zombie firms is significantly higher than that of private zombie firms. This is closely related to the fact that state-owned firms are more easily controlled by the government and subject to government paternalism. Panel C shows the distribution of zombie firms according to listing time. We divide the sample into five groups according to listing time: 1–5 years, 6–10 years, 11–15 years, 16–20 years, and more than 20 years. As can be seen, as listing time increases, the proportion of zombie firms becomes higher and higher. There are only about 4.40% zombie firms in the 1–5 years group, while there are about 13.58% zombie firms among firms aged more than 20 years. Panel D shows the distribution of zombie firms of different scales. We divide the sample into three categories according to the “Statistical dividing method for large, medium-sized and small and micro firms” from the National Bureau of Statistics. The results differ from those of Nie et al. (2016), which may be due to the impact of sample differences; in addition, Nie et al. (2016) used Chinese industrial firms. From the results, we can see that the proportion of large and medium-sized zombie firms is relatively low, which may be because such listed firms are mature, and often have more scientific and standardized management and stronger ability to reduce risk.

4.1.2. T-test Table 4 shows the mean difference between the samples of zombie firms and normal firms using the T-test. According to the results, we can see that the degree of government intervention in zombie firms is higher than in normal firms. The state ownership (SOE) of zombie firms is significantly higher than that of normal firms, indicating that stateowned firms more easily become zombie firms. The financial leverage of zombie firms is significantly higher than that of normal firms, indicating that the debt burden of zombie firms is heavier because the continuing operation of zombie firms is related to debt. The liquidity and growth capacity of zombie firms are worse than those of normal firms. 4.1.3. Correlation analysis Table 5 reports the correlation coefficients for the main variables. The correlation coefficient between government intervention (Gov) and zombie firm (Zombie) is significantly positive, which preliminarily confirms the hypothesis that government intervention is an important cause of the formation of zombie firms. Zombie firm (Zombie) is negatively correlated with size of the firm (Size), firm growth capacity (Growth), firm liquidity (Cr), and relative profitability (Profit), indicating that firm size, financial stability, and profitability may decrease the likelihood of the formation of zombie firms. However, higher financial leverage and longer listing time increase the chance that a firm will become a zombie firm. State ownership (SOE) is positively correlated with zombie firm (Zombie), indicating that state-owned firms are more likely to become zombie firms, which is due to the uniqueness of state-owned firms. In addition, the correlation coefficient among the variables is quite low, so there is no serious multicollinearity problem.

Table 4 Results of T-tests between the samples of zombie firms and normal firms. Variable

Variable type

Zombie ¼ 0

Zombie ¼ 1

0–1

T-values

Government intervention Firm size Financial leverage Firm liquidity Firm growth ability Rate of overhead expenses Relative profitability Listing time State ownership

Gov Size Lev Cr Growth Expense Profit Age SOE

3.086 22.361 0.500 1.652 0.197 0.145 0.136 11.831 0.527

3.654 21.873 0.618 1.215 0.018 0.134 0.176 14.090 0.662

0.568 0.488 0.117 0.437 0.179 0.011 0.039 2.259 0.136

12.512*** 12.490*** 20.110*** 13.029*** 13.189*** 0.985 3.298*** 12.721*** 8.924***

Notes: This table shows results of T-tests between the samples of zombie firms and normal firms. Zombie ¼ 0 represents normal firms. Zombie ¼ 1 represents zombie firms. 0–1 represents the difference between zombie ¼ 0 and zombie ¼ 1. ***, **, * represent the significance at the 1%, 5%, 10% levels, respectively. Table 5 Correlation coefficients for the main variables. Zombie

Gov

Size

Lev

Cr

Growth

Age

Expense

Profit

SOE

Zombie

1.000

Gov

0.119 *** 0.119 *** 0.190 *** 0.124 *** 0.126 *** 0.121 *** 0.009

0.081 *** 1.000

0.125 *** 0.070 *** 1.000

0.172 *** 0.053 *** 0.380 *** 1.000

0.180 *** 0.073 *** 0.229 *** 0.644 *** 1.000

0.170 *** 0.067 *** 0.051 *** 0.002

0.098 *** 0.086 *** 0.231 *** 0.281 *** 0.224 *** 0.154 *** 1.000

0.039 *** 0.124 *** 0.158 *** 0.189 *** 0.059 *** 0.188 *** 0.012

0.100 *** 0.102 *** 0.174 *** 0.038 *** 0.056 *** 0.015

0.032 *** 0.043 *** 0.400 ***

1.000

0.087 *** 0.120 *** 0.295 *** 0.259 *** 0.277 *** 0.105 *** 0.400 *** 0.086 *** 0.056 *** 1.000

Size Lev Cr Growth Age Expense Profit SOE

0.032 *** 0.085 ***

0.067 *** 0.062 *** 0.047 *** 0.023 ** 0.088 *** 0.094 *** 0.120 *** 0.124 ***

0.349 *** 0.227 *** 0.034 *** 0.193 *** 0.028 *** 0.140 *** 0.305 ***

0.630 *** 0.021 ** 0.278 *** 0.059 *** 0.055 *** 0.255 ***

0.021 ** 0.198 *** 0.055 *** 0.039 *** 0.243 ***

0.080 *** 1.000 0.056 *** 0.069 *** 0.079 *** 0.084 ***

0.785 *** 0.041 ***

0.037 *** 0.538 *** 1.000 0.020 **

Notes: This table provides Correlation coefficients for the main variables. ***, **, * represent significance at the 1%, 5%, 10% levels, respectively. 6

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overhead expenses (Expense) has a significant positive correlation with zombie firm (Zombie), indicating that the higher the rate of overhead expenses, the lower the internal management efficiency, and the more likely that the firm will become a zombie firm. This is consistent with the conclusions of Han and Tian (2017). The rate of overhead expenses is also usually regarded by scholars as an agent variable of rent-seeking (Cheng and Tan, 2017), so this also shows that zombie firms have more rent-seeking behaviors. Listing time (Age) is positively correlated with zombie firm (Zombie) at a significance level of 1%, indicating that the longer a firm is listed, the more likely it is to become a zombie firm. This is consistent with the findings of Nie et al. (2016). There is a significant negative correlation between size of the firm (Size) and zombie firm (Zombie). This may be because the larger the firm, the more scientific and standardized its internal management, and the stronger its ability to mitigate risk; thus it is less likely to become a zombie firm. We also find that the greater the financial leverage (Lev), the higher the possibility of firms becoming zombie firms, which also confirms the “blood sucking” characteristic of zombie firms to some extent. State ownership (SOE) is positively correlated with zombie firm (Zombie) at a significance level of 1%. This shows that state-owned firms more easily become zombie firms, and the proportion of state-owned zombie firms is much higher than other firms in reality; in addition, regions and industries with a higher proportion of state-owned firms face more serious problems of misallocation of resources (Shen, 2016), because state-owned firms must follow government goals. Thus, the government will preferentially give state-owned firms resources, ensuring that the proportion of state-owned zombie firms is high.

4.2. Primary regression test To provide further support for the hypothesis, we carried out regression analysis to confirm the predictive accuracy of model (1). The correct predictive rate of the Probit model is 89.08%. In order to control potential heteroscedasticity and sequence-related problems, standard errors are clustered at the firm level, and the following tables are the same. Table 6 reports the regression results. Column (1) presents the regression results, which show a positive correlation at a significance level of 1% between government intervention (Gov) and zombie firm (Zombie); that is, the higher the degree of government intervention, the higher the possibility a firm will become a zombie firm. Because model (1) is a Probit model, column (2) presents the average marginal effects of variables. The marginal effect of government intervention (Gov) is 0.015, indicating that the probability of a firm becoming a zombie firm will increase by 1.5 percentage points for every additional unit of government intervention, which supports the hypothesis. To achieve the goal of stimulating economic growth and maintaining high employment levels, the government will actively intervene in firms that are on the verge of bankruptcy but contribute to GDP and local tax revenue. As for stateowned firms on the verge of bankruptcy, the government always helps them out of “paternalism”, which forms a soft budget constraint. In addition, there is information asymmetry between the government and firms. Firms may conceal the deterioration of their financial situation to obtain more resources. Moreover, firms use these limited resources for rent-seeking rather than to improve productivity. The operating conditions are deteriorating day by day, resulting in firms that are “stiff but deathless.” Relative profitability (Profit) is negatively correlated with zombie firm (Zombie) at a significance level of 1%, indicating that the higher the relative profitability, the smaller the impact of industrial shock, and the less likely the firm will become a zombie firm. The rate of

4.3. Robustness test 4.3.1. Changing the method of identifying zombie firms For a robustness test, we draw on Chen and Huang (2017) and Zhang (2019), by using the FN-CHK and actual profit methods. The actual profit method was developed by Zhu and He (2016) based on the operation of the firm. In this method, if the difference between the firm's net profit and non-recurring profit is less than zero, the firm is identified as a zombie firm. Fukuda and Nakamura (2011) improved on the CHK criterion, identifying zombie firms according to what they called the profitability criterion and evergreen lending criterion. The profitability criterion means that firms whose earnings before interest and taxes (EBIT) exceed hypothetical risk-free interest payments are excluded from being categorized as zombie firms. The evergreen lending criterion means that firms that are unprofitable and highly leveraged and have increased their external borrowings are categorized as zombie firms. In addition, we draw on the methods of Tan et al. (2017) and Zhou et al. (2018), by replacing the minimum observed rate on any convertible corporate bond (rcbminoverlast5years,t) with the interest rates of outstanding bonds (rbondi,j,t-1), in which bond collection J includes convertible bonds, private equity bonds, corporate bonds, directional tools, and so on. R*i,t represents the minimum required interest payment for each firm each year, and Ri,t represents the actual interest expenditure. We use the resulting variable to calculate interest rate gap X. If X is less than 0, the firm is a zombie firm.

Table 6 Regression results for the correlation between government intervention and the formation of zombie firms. Variables

Gov Cr Profit Expense Growth Age Size Lev SOE Constant Year Industry Log likelihood Wald chi2 P value N Pseudo R2

(1)

(2)

Zombie

Margin

0.094*** (4.420) 0.022 (-0.521) 0.295** (-2.381) 0.271** (2.341) 0.351*** (-5.563) 0.020*** (3.038) 0.216*** (-7.680) 1.792*** (8.768) 0.239*** (3.305) 1.932*** (3.058) Yes Yes 3209.127 434.510 0.000 10746 0.145

0.015*** (0.003) 0.004 (0.007) 0.048** (0.020) 0.044** (0.019) 0.057*** (0.010) 0.003*** (0.001) 0.035*** (0.005) 0.292*** (0.033) 0.039*** (0.012)

Yes Yes 3209.127 434.510 0.000 10746 0.145

Ri;t ¼ rst1  BSi;t1 þ

 X  X 1 5 rltj  BLi;t1 þ rbondi;j;t1  Bondsi;j;t1 5 j1 j (2)

Xi;t ¼

Notes: This table reports our main results of the impact of government intervention on the formation of zombie firms. Column (1) presents the regression coefficients and column (2) presents the average marginal effects of variables. The values in the column (1) are z values, and those in the column (2) are standard errors. ***, **, * represent significance at the 1%, 5%, 10% levels, respectively.

Ri;t  Ri;t BSi;t1 þ BLi;t1 þ Bondsi;t1 þ CPi;t1

(3)

where BS, BL, and Bonds are the short-term bank loans, long-term bank loans, and total bonds outstanding of firm i at the end of year t-1. CP is the amount of commercial paper outstanding for firm i at the beginning of period t-1. rst1 and rltj are the average short-term prime rate in year t 7

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Table 7 Regression results after changing the method of identifying zombie firms. Variables

Gov Cr Profit Expense Growth Age Size Lev SOE Constant Year Industry Log likelihood Wald chi2 P value N Pseudo R2

(1) FN-CHK method

(2) Actual profit method

Zombie

Margin

Zombie

Margin

0.080*** (4.277) 0.108*** (3.102) 0.219* (-1.786) 0.168 (1.452) 0.379*** (-4.440) 0.013** (2.343) 0.055** (-2.425) 1.875*** (9.816) 0.198*** (3.242) 2.029*** (-3.950) Yes Yes 2226.756 349.220 0.000 10289 0.105

0.009*** (0.002) 0.012*** (0.004) 0.025* (0.014) 0.019 (0.013) 0.044*** (0.010) 0.002** (0.001) 0.006** (0.003) 0.216*** (0.023) 0.023*** (0.007)

0.070*** (4.236) 0.012 (-0.412) 0.457*** (-4.597) 0.404*** (4.390) 0.472*** (-8.028) 0.023*** (4.645) 0.240*** (-10.639) 2.157*** (13.186) 0.132** (2.352) 3.240*** (6.667) Yes Yes 4806.490 2324.770 0.000 10751 0.151

0.018*** (0.004) 0.003 (0.007) 0.115*** (0.025) 0.101*** (0.023) 0.119*** (0.015) 0.006*** (0.001) 0.060*** (0.005) 0.542*** (0.040) 0.033** (0.014)

Yes Yes 2226.756 349.220 0.000 10289 0.105

Table 8 Regression results after changing the model. Variables

Gov Cr Profit Expense Growth Age Size Lev SOE Constant Year Industry Log likelihood Wald chi2 P value N Pseudo R2

Yes Yes 4806.490 2324.770 0.000 10751 0.151

Notes: This table reports results after changing the method of identifying zombie firms. We use FN-CHK method and actual profit method to identify zombie. The zombie columns present the regression coefficients and the margin columns present the average marginal effects of variables. The values in the zombie column are z values, and those in the margin column are standard errors. ***, **, * represent significance at the 1%, 5%, 10% levels, respectively.

(1)

(2)

Zombie

Margin

0.176*** (4.462) 0.068 (-0.709) 0.551** (-2.131) 0.475** (2.036) 0.778*** (-5.056) 0.040*** (2.957) 0.389*** (-7.342) 3.151*** (7.944) 0.456*** (3.310) 3.618*** (2.997) Yes Yes 3204.793 436.880 0.000 10746 0.146

0.015*** (0.003) 0.006 (0.008) 0.048** (0.022) 0.041** (0.020) 0.067*** (0.013) 0.003*** (0.001) 0.034*** (0.005) 0.272*** (0.034) 0.039*** (0.012)

Yes Yes 3204.793 436.880 0.000 10746 0.146

Notes: This table reports results after changing the model. We use logit model instead of probit model. Column (1) presents the regression coefficients and column (2) presents the average marginal effects of variables. The values in the zombie column are z values, and those in the margin column are standard errors. ***, **, * represent the significance at the 1%, 5%, 10% levels, respectively.

show a significantly positive correlation between government intervention and the formation of zombie firms. This is consistent with the primary regression results, indicating that the research results are robust.

and the average long-term prime rate in year t. We measure rs and rl by the average one-year benchmark interest rate and 90% of the average five-year long-term benchmark interest rate,8 respectively. The regression model refers to model (1), and the regression results are shown in Table 7. Government intervention (Gov) is still positively correlated with zombie firm (Zombie) at a significance level of 1%; that is, the higher the degree of government intervention, the higher the likelihood that the firm will become a zombie firm. The result again supports the hypothesis, indicating that the previous conclusions are robust.

4.4. Endogeneity test Government intervention in firms is not entirely exogenous, because firms with a high degree of rigidity may be more likely to attract the attention and support of the government. Thus, there is an endogeneity problem. To solve it, we adopt the instrumental variable (IV) method. The instrumental variables need to satisfy the following conditions: (1) The instrumental variables are related to the endogenous independent variables; (2) The instrumental variables are exogenous to the dependent variables. We use “number of independent directors” as the instrumental variable for the endogenous independent variable (Gov), because the number of independent directors of listed firms is related to laws and regulations issued by the government, and the law makes specific provisions for this. The number of independent directors is influenced by government intervention, while there is no correlation between the number of independent directors (Dpd) and the dependent variable (Zombie). There is no need for an over-recognition test, because the number of endogenous independent variables in the model is the same as the number of instrumental variables. Next, we carry out the two-stage regression. The results of the first stage show that the instrumental variable (Dpd) is highly positively correlated with government intervention (Gov). The F-test value is 70.39, much higher than required by the empirical rule that the F-test value should exceed 10 in the first stage. This reveals that there is no weak instrumental variable problem, and the instrumental variable (Dpd) has a strong explanatory power for the endogenous variable (Gov). Table 10 shows the IVprobit regression results. There is still a positive correlation between government

4.3.2. Changing the model Our dependent variable is a binary classification variable, and Probit and Logit models can usually be used in place of each other. Thus, we use a Logit model instead of a Probit model to perform a robustness test. Table 8 shows the regression results after changing the model. These consistently suggest that government intervention has a positive effect on the formation of zombie firms. More importantly, our main conclusions do not change. 4.3.3. Changing the research sample The industry distribution shows that the top three industries in terms of proportion of zombie firms are (1) manufacturing, (2) accommodation and catering, and (3) agriculture, forestry, animal husbandry, and fisheries. Therefore, we select these industries for a robustness test. Table 9 shows the regression results after changing the research sample. These

8 According to the regulations of the People's Bank of China, the lowest limit of financial institutions' loan interest rate is 0.9 times the benchmark interest rate. Although the rate has changed since 2012, it is still not 10% lower than the benchmark interest rate (Yuyan Tan et al., 2017).

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intervention (Gov) and zombie firms (Zombie) after using the IV method to control for endogeneity. The main findings of this paper remain unchanged.

Table 9 Regression results after changing the research sample. Variables

Gov Cr Profit Expense Growth Age Size Lev SOE Constant Year Industry Log likelihood Wald chi2 P value N Pseudo R2

(1)

(2)

Zombie

Margin

0.089*** (3.718) 0.079* (-1.903) 1.227*** (-3.517) 1.086*** (3.897) 0.458*** (-5.168) 0.021*** (2.786) 0.187*** (-5.675) 1.577*** (6.368) 0.325*** (3.903) 1.380* (1.896) Yes Yes 2347.361 388.170 0.000 6980 0.152

0.017*** (0.004) 0.015* (0.008) 0.227*** (0.065) 0.201*** (0.052)

4.5. Further analysis We have tested the relationship between government intervention and the formation of zombie firms. What is the mechanism by which government intervention influences the formation of zombie firms? In this section, we address this question from four perspectives. 4.5.1. Government subsidies and the formation of zombie firms Subsidies are one of the most important policy tools by which governments intervene in the market, and have thus been researched by many scholars. They have mainly discussed the impact of government subsidies at the macro and micro levels. On the macro level, scholars mostly agree that government subsidies bring about negative effects. Kong et al. (2013) held that it is a waste of public resources to distribute government subsidies to uncompetitive, loss-making firms. At the same time, the abuse of government subsidies may reduce the efficient allocation of social resources, affecting the overall level of social welfare. At the micro level, there is no consensus about the impact of government subsidies on firms. Some scholars have found that government subsidies have positive effects, such as boost firms’ operating performance (Zhang et al., 2014; Howell, 2017) and increase R&D investment (Lee and Cin, 2010; Bronzini and Piselli, 2016; Yang et al., 2019), etc. Many scholars have found that there is a positive correlation between R&D subsidy and firm innovation (Guo et al., 2016; Sung, 2019). Other scholars have held that government subsidies bring about negative effects (Beason and Weinstein, 1996; Tzelepis and Skuras, 2004; Guan and Yam, 2015; Boeing, 2016; Guan and Pang, 2017). Lim et al. (2018) have found that firms with more subsidies tend to be overstaffed and they often have higher social performance but lower financial performance. Zhang et al. (2019) concluded that government subsidies are positively correlated with the overinvestment behavior of firms. The government subsidies granted to listed firms in distress can also contribute to earnings manipulation as these firms seek to avoid delisting (Chen et al., 2008). Lack of viability is one important characteristic of zombie firms. Therefore, it is difficult for zombie firms to survive in the market without external support. Because their promotions depend on improved GDP, local government officials often support key national industries beyond what is reasonable, resulting in redundant construction and overcapacity. As firm losses increase, the government continues to provide assistance to crowd out firms in other regions. Firms gradually lose their viability and become rigid. According to the normal rules of market development, these firms should withdraw from the market, but due to government subsidies, they do not, and eventually became “stiff but deathless” zombie firms. Apart from personal promotion goals, governments attempt to accomplish their social policy objectives (Lim et al., 2018), such as increased local GDP, tax revenue, or a lower unemployment rate. Because listed firms can make major contributions to local economic development and employment, government officials continue subsidizing listed firms on the verge of bankruptcy to help them survive during their terms of office. This is like satisfying thirst by drinking poison; such firms will eventually become zombie firms. On the other hand, due to information asymmetry, firms often provide false information to obtain more government subsidies and engage in rent-seeking, rather than investing major resources to improve operational efficiency. This “fast money” may reduce the motivation to improve operational performance, undermining the firm and weakening its viability. In this way, government subsidies provide fertile ground for the formation of zombie firms.

0.085*** (0.017) 0.004*** (0.001) 0.034*** (0.006) 0.292*** (0.045) 0.060*** (0.015)

Yes Yes 2347.361 388.170 0.000 6980 0.152

Notes: This table reports results after changing the research sample. we select the top three industries in terms of proportion of zombie firms as research samples. Column (1) presents the regression coefficients and column (2) presents the average marginal effects of variables. The values in the zombie column are z values, and those in the margin column are standard errors. ***, **, * represent significance at the 1%, 5%, 10% levels, respectively.

Table 10 IVprobit regression results. Variables

Dpd

The first stage

The second stage

Gov

Zombie

0.133*** (6.554)

Gov Cr Profit Expense Growth Age Size Lev SOE Constant Year Industry F-value N Adj-r2/Pseudo R2

0.035** (2.377) 0.263*** (3.471) 0.283*** (3.890) 0.071*** (2.767) 0.007*** (2.798) 0.068*** (-5.491) 0.858*** (8.849) 0.432*** (13.924) 3.366*** (12.644) Yes Yes 70.39 10746 0.162

0.435** (2.070) 0.034 (-1.318) 0.204* (-1.653) 0.171 (1.447) 0.374*** (-7.778) 0.018*** (4.513) 0.200*** (-10.222) 1.499*** (6.690) 0.084 (0.803) 0.797 (1.006) Yes Yes 10746 0.162

4.5.2. Resource support and the formation of zombie firms Resource support is one of the main means of government intervention, and involves benefits in the form of land, minerals, electricity, and

Notes: This table shows IVprobit regression results. ***, **, * represent significance at the 1%, 5%, 10% levels, respectively; t-values are given in parentheses. 9

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affecting the utilization efficiency of that capital; it places an invisible burden on firms, one which cannot be ignored. Moreover, the ability of zombie firms to pay taxes is poor because of their low profitability. However, to maintain stable fiscal revenue, local governments will inevitably fill this part of tax with other firms in the case of reduction in tax sources, which will increase the operating pressure on those microprofit firms. At this time, the tax burden may be the straw that breaks the camel's back, causing these firms to post periodic or even continuous losses. Nevertheless, the government will help these firms survive for the benefit of local GDP, employment levels, and social stability; the degree of rigidity will be raised again and again, and ultimately it will become a zombie firm. In short, the government plays both the roles of a “supporting hand” and “grabbing hand” in the market. We use government subsidy, resource support, financial support, and tax breaks as specific means of government intervention to test the mechanism by which government intervention influences the formation of zombie firms. We perform the test using model (1):

water. Land ownership is relatively vague in China. Local governments have a monopoly on land and have the power to provide firms with land below market value. The defects of the environmental protection system also mean that the government may favor firms by overlooking environmentally destructive activities. Due to paternalism, the government tends to favor state-owned firms in resource allocation. Private firms are also subject to government interference. According to resource dependence theory, if a firm wants to develop, it must obtain the necessary resources from the external environment. For private firms, although the government cannot make decisions directly, the government maintains control over key resources needed for the survival and development of private firms. Therefore, private firms are more likely to be threatened by local governments. They are keen to connect with the government and cater to its various needs. In addition, as China's market economy has developed, private firms have won increasing attention and recognition from all sectors of society. Local governments pay more attention to large-scale private firms, and regional development strategies and government work plans increasing aim to develop the private economy and enhance its competitiveness. Local governments and private firms depend on each other. Naturally, private firms will expand their size and scope to meet government needs, such as participating in local economic construction or investing in energy and transportation projects; they may benefit from the government's “compulsory arrangement” to help stateowned enterprises out of financial duress to reduce regional unemployment (Zhong et al., 2010). In short, inefficient and poorly managed state-owned firms can survive in the market by relying on resource support from the government, but these firms are not self-sustaining, and eventually will become zombie firms. Private firms must be subservient to the government to acquire the critical resources needed for operation, which may reduce operational efficiency, resulting in these firms becoming rigid.

Zombiei;t ¼β0 þβ1 Aþβ2 Cri;t1 þβ3 Profiti;t1 þβ4 Expensei;t1 þβ5 Growthi;t1 þ X X βj Industryþ βk Yearþεi;t

β6 Agei;t1 þβ7 Sizei;t1 þβ8 Levi;t1 þβ9 SOEi;t1 þ

(4) where variable A represents government subsidy (Subi,t-1), political connection (Poli,t), interest deviation (Idi,t), financial cost deviation (Fdi,t), and taxi,t. Because the impact of government subsidies is timelagged, so we use government subsidies lagged in the first phase. For government subsidy (Sub) we use the ratio of government subsidies to total assets, following Kong et al. (2013). The larger the ratio, the greater the subsidies. Through political connections, firms are more likely to gain a variety of preferential treatments, such as cheap or free land, electricity, water, market access, etc. This connection can serve as a channel for political rent-seeking and corruption. Therefore, we use political connection (Pol) as a proxy variable of resource support (Bartels and Brady, 2003; Faccio and Masulis, 2006; Fisman, 2001). We refer to the studies of Yu and Pan (2008). If the chairman or general manager of a firm occupies the following positions, the firm is considered to have political connections: (1) current or former government official; (2) current or former deputy to the National People's Congress; (3) current or former member of the CPPCC (China People's Political Consultative Conference) National Committee. Degree of credit imbalance (Dci): we use interest deviation (Id) and financial cost deviation (Fd) as proxy variables of degree of credit imbalance (Dci), referring to the studies of Luo and Lv (2015) and Lv and Chen (2018). Interest deviation is equal to ln((interest of a firm minus average interest in the industry)2). Financial cost deviation is equal to ln((financial cost of a firm minus average financial cost in the industry)2). For tax, we use taxes payable divided by operating income. The control variables are the same as in model (1). Table 11 shows the regression results of the further analysis. Columns (1)–(5) represent the regression results between government subsidy and zombie firm, resource support and zombie firm, financial support and zombie firm, and tax and zombie firm, respectively. The correlation coefficients and average marginal effects of each variable are listed below each column. Government subsidy (Sub) is positively correlated with zombie firm (Zombie) at a significance level of 1%, which indicates that government subsidy is an important cause of the formation of zombie firms. To ensure the employment level and regional economic stability, local governments will exert employment and industrial expansion pressure on firms, and help firms maintain operations through subsidies, making firms that are not “zombies” gradually rigid. Political connection (Pol), as the proxy variable of resource support, is positively correlated with zombie firm (Zombie), indicating that the government distorts normal market competition by providing land or lowering the threshold of market access. Thus firms that should have quit the market rely on these resources and privileges to linger on. Interest deviation (Id) and financial cost deviation (Fd) are positively correlated with zombie firm

4.5.3. Financial support and the formation of zombie firms Although firms on the verge of bankruptcy are inefficient, they can still obtain low-cost credit through various channels. The ultimate cause is the distortion of credit due to government intervention. Tax sharing reform has intensified government intervention in the lending decisionmaking and behavior of banks. Indirect government intervention has led banks to adopt non-market-oriented rationales for selecting prospective borrowers—that is, to provide low-interest loans to firms with poor operations that have special relations with the government. To some extent, the government's preference represents the implicit guarantee for banks, because the government is reluctant to allow the firms it supports go bankrupt and cause unemployment (Lim et al., 2018). The existence of the government's guarantee means that the financing structure does not match the economic structure in China, and there is a serious mismatch of resources. Far too many credit resources flow to inefficient state-owned firms and overcapacity firms. These firms lack viability, and maintain operations simply by borrowing new loans to repay old ones. However, banks continue to provide unconditional loans to such firms not only due to government intervention but also for their own reasons. The bad debt rate is an important indicator of the quality of bank credit, and an important basis for banks' internal performance evaluation and accountability. Therefore, to control and cover up the increasing scale of bad debts, banks continue to lend to poorly managed firms or zombie firms to ensure a high core capital adequacy rate, which increases the number of zombie firms. 4.5.4. Taxes and the formation of zombie firms Firms are not only promoters of economic growth and creators of employment opportunities, but also the providers of fiscal revenue such as taxes. In theory, value added tax is a turnover tax, and can be transferred along with the sale of products. It is consumers who ultimately bear the tax, and firms suffer no loss and only undertake the work of tax collection and remittance. In practice, however, value added tax will occupy a percentage of the firm's capital when goods are not sold, thus 10

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Table 11 Regression results of further analysis. Variables

Sub

(1)

(2)

Zombie

Margin

13.304*** (4.687)

2.154*** (0.465)

Pol

(3)

Zombie

Margin

0.146*** (2.937)

0.024*** (0.008)

Id

(4)

Zombie

Margin

0.021** (2.028)

0.003** (0.002)

Fd

(5)

Zombie

Margin

0.017* (1.750)

0.003* (0.002)

Tax Cr Profit Expense Growth Age Size Lev SOE Constant Year Industry Log likelihood Wald chi2 P value N Pseudo R2

0.036 (-0.900) 0.362*** (-2.721) 0.281** (2.316) 0.367*** (-5.094) 0.019*** (2.832) 0.202*** (-6.958) 1.864*** (8.721) 0.287*** (3.913) 2.105*** (3.171) Yes Yes 3056.088 429.450 0.000 10306 0.147

0.006 (0.006) 0.059*** (0.022) 0.046** (0.020) 0.059*** (0.012) 0.003*** (0.001) 0.033*** (0.005) 0.302*** (0.034) 0.046*** (0.012)

Yes Yes

0.012 (-0.286) 0.328*** (-2.613) 0.306*** (2.579) 0.349*** (-5.404) 0.022*** (3.255) 0.223*** (-7.949) 1.879*** (9.240) 0.277*** (3.884) 2.547*** (3.941) Yes Yes 3238.343 418.770 0.000 10752 0.139

0.002 (0.007) 0.054*** (0.021) 0.050*** (0.020) 0.057*** (0.011) 0.004*** (0.001) 0.037*** (0.005) 0.309*** (0.033) 0.046*** (0.012)

Yes Yes

0.094*** (-3.077) 0.323*** (-2.702) 0.305*** (2.850) 0.345*** (-5.204) 0.022*** (5.769) 0.228*** (-13.384) 1.673*** (13.133) 0.273*** (6.632) 2.305*** (4.646) Yes Yes 3235.217 797.120 0.000 10752 0.139

0.015*** (0.005) 0.053*** (0.020) 0.050*** (0.018) 0.057*** (0.011) 0.004*** (0.001) 0.038*** (0.003) 0.275*** (0.021) 0.045*** (0.007)

Yes Yes

0.009 (-0.358) 0.679*** (-5.266) 0.776*** (6.778) 0.556*** (-10.188) 0.022*** (5.976) 0.271*** (-15.780) 2.210*** (17.129) 0.274*** (6.513) 3.002*** (6.608) Yes Yes 3087.796 493.290 0.000 10752 0.179

0.001 (0.004) 0.107*** (0.020) 0.122*** (0.018) 0.087*** (0.009) 0.003*** (0.001) 0.043*** (0.003) 0.347*** (0.020) 0.043*** (0.007)

Yes Yes

Zombie

Margin

0.930* (1.714) 0.003 (-0.087) 0.478*** (-3.126) 0.732*** (5.059) 0.273*** (-5.125) 0.049*** (11.545) 0.432*** (-20.527) 2.891*** (18.906) 0.304*** (6.281) 6.238*** (13.278) Yes Yes 3077.852 419.610 0.000 10306 0.141

0.116* (0.067) 0.000 (0.004) 0.060*** (0.019) 0.091*** (0.018) 0.034*** (0.007) 0.006*** (0.001) 0.054*** (0.003) 0.360*** (0.019) 0.038*** (0.006)

Yes Yes

Notes: This table reports results between government subsidy and zombie firm, resource support and zombie firm, financial support and zombie firm, and tax and zombie firm, respectively. ***, **, * represent significance at the 1%, 5%, 10% levels, respectively. The zombie columns present the regression coefficients and the margin columns present the average marginal effects of variables. The values in the zombie column are z values, and those in the margin column are standard errors.

and the market, and to clarify the scope of local government intervention. At the same time, we should supervise of local governments’ non-market behaviors, thus bringing into full play the fundamental role of the market in the allocation of resources. For example, when seeking investors, the government or its departments often play a central role. This is abnormal in a market economy. In addition, local governments should be prohibited from distorting factor prices and resource prices by means of lax environmental standards, tax deductions, and low land prices, to transform the government from a promoter of economic development to a regulator and strive to create fair market competition. Secondly, the GDP-only performance appraisal system needs to be changed. We suggest reducing the weight of GDP in the performance appraisal system for officials, and taking livelihood improvement, social progress, ecological benefits and other indicators into consideration, to establish a comprehensive evaluation system to encourage local governments to consider the wider social good. Thirdly, it is necessary to reduce market entry and exit costs and improve the mechanism of market entry and exit. The central government should clean up and abolish local laws and regulations that maintain industry monopolies and continue improving the legal system to combat local protectionism. Moreover, unreasonable obstacles to market access for small and medium-sized firms should be removed, so that these firms can compete with incumbent firms in a fair environment. Burdens on firms should be reduced, through tax and fee reduction, to minimize the probability of market risk after the bankruptcy of firms. The disposal of zombie firms should also be carried out according to market-oriented law. Thoroughly rigid firms should be allowed to go bankrupt. Zombie firms that may only be undergoing temporary operational difficulties

(Zombie). The greater the deviation, the higher the degree of imbalance in the credit market; the higher the degree of government intervention in credit resources, the more likely the formation of zombie firms. Tax (Tax) and zombie firm (Zombie) are positively correlated at a significant level of 10%, which indicates that tax plays a role in exacerbating the formation of zombie firms. To sum up, in this section we have further verified the hypothesis from four perspectives: government subsidy, resource support, financial support and tax, and explored the mechanism by which government intervention influences the formation of zombie firms. 5. Conclusion This paper empirically investigates the effects of government intervention on the formation of zombie firms. It finds that the higher the degree of government intervention, the greater the probability that a firm will become a zombie firm. Robustness tests and endogeneity tests confirm this finding. Further, we make a preliminary exploration of the mechanism by which government intervention influences the formation of zombie firms from four different perspectives. Further analysis reveals that government causes the formation of zombie firms by means of government subsidies, resources support, financial support, and tax. To resolve the problem of zombie firms, we put forward the following suggestions: Firstly, we should maintain the spirit the Third Plenary Session of the 18th Central Committee of the Communist Party of China, and realize the transformation of the government from an unlimited to a limited role. It is necessary to establish an effective boundary between the government 11

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should be encouraged by the government to rescue themselves by means of re-organization and merger.

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