How Do Zombie Firms Affect Innovation?
Evidence from China’s Industrial Firms
Yun Dai, Wei Li, Yongqin Wang
May 08, 2019
Zombie firms are insolvent firms that continue to operate due to continued
access to financing at extremely low costs. Nie et al. (2016) find that in the
year 2013 about 14 percent of Chinese-listed firms and 7.5 percent of Chinese
manufacturing firms are defined as zombie firms. The large amount of
financing subsidies distributed to insolvent zombie firms causes a great deal
of credit misallocation and impedes the availability of financing for normal
firms in China. Based on a Chinese patent application database and an
above-scale manufacturing firm database, we find that zombie firms
significantly reduce the number of patent applications and total productivity
factors (TFPs) of normal firms. For a 1 percent increase in the proportion of
zombie firms in the same industry, the total number of patent applications of
normal firms decreases by 1 percent, among which the number of inventiontype patent applications decreases by 0.5 percent and the TFPs of normal
firms decrease by 2.41 percent. The crowding-out effect of zombie firms on
innovation is both statistically and economically significant. In terms of the
mechanisms, empirical results show that the crowding-out effect is more
profound for industries highly dependent on external financing, highly
concentrated industries, and non-state-owned normal firms, which are more
financially constrained compared to state-owned normal firms. This implies
that the crowding-out effect of zombie firms works by distorting credit
allocation and harms fair industry competition. This paper highlights the
importance of solving the problems caused by zombie firms in order to boost
firm innovation and help achieve high-quality development in China.
Under the “new normal” of China’s economy, innovation has become
imperative for achieving high-quality development. The Chinese government
regards the dissolution of zombie firms as an important starting point for
improving the quality of the supply side of the economy. Based on the reform
background of deleveraging state-owned enterprises (SOEs), this paper
studies how “zombie firms” (insolvent firms that continue to operate due to
continued access to financing at extremely low costs) influence the innovation
outcomes of other firms, specifically by their distortion of credit allocation
and product market competition. It also provides empirical support for the
current focus in China of seeking “high-quality development.”
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Zombie firms account for a substantial part of the Chinese market. Nie et al.
(2016) find that in the year 2013 about 14 percent of Chinese-listed firms are
defined as zombie firms. Furthermore, the proportion of zombie firms are the
highest among SOE firms (about 16 percent for the period of 2005-2013)
compared to private firms and foreign firms (about 7 percent during 20052013). The prevalence of zombie firms consumes a large amount of financing
subsidies and causes a great deal of credit misallocation in China (Tan et al.,
2017). Previous studies show that financing accessibility is a key determinant
to corporate innovation (Chava et al., 2013; Cornaggia et al., 2015) and it is
important to find out how zombie firms affect corporate innovation in China.
Using firm-level data from the above-scale industrial firm dataset provided
by the National Bureau of Statistics, this paper empirically tests the impact of
zombie firms on the innovation outcomes of normal firms (i.e., non-zombie
firms). In particular, we use certain steps to identify the crowding-out effect
of zombie firms on the innovation of normal firms. First, in the baseline model,
we use firm-, industry-, and city-level control variables to control for the
impact of a firm’s own operating performance, industry development, and
local economic conditions on corporate innovation and TFP. Since the main
explanatory variable is the proportion of zombie firms at the industry level,
all regression models control for industry fixed effects and standard errors are
clustered at both the industry and year level. We also use year fixed effects to
control for time trends. The results of the baseline model show that the total
number of patent applications and the TFP of firms are significantly and
negatively correlated with the proportion of zombie firms in their industry.
Second, in order to deal with endogeneity problems such as omitted variables
and reverse causality, we follow Tan et al. (2017) and use instrumental
variable (IV) regressions to verify the empirical results of the benchmark
model. Third, we check for heterogeneous effects based on the ownership of
firms, the external financing dependence of the industry, and the degree of
industry competition. Subsample regressions show that the crowding-out
effect of zombie firms on the innovation of normal firms is more profound for
non-SOEs, firms in industries with high external financing dependence, and
firms in highly concentrated industries. This implies that zombie firms
influence the innovation outcomes and the TFP of normal firms by distorting
credit allocation and industry competition.
Table 1 reports the IV regression results of firm-year observations of
innovation outcomes on the proportion of zombie firms in the same industry
as the concerned firms in the same year. Following Tan et al. (2017), we use
the product between the proportion of SOE firms at the beginning of the
sample and the average leverage ratio of the SOE in the last year as the
instrumental variable (IV). As zombie firms are most prevalent among SOEs
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and those firms consume a lot of credit resources, this IV can satisfy both the
relevance and exclusion conditions (Tan et al., 2017). All regressions control
for firm-, industry-, and city-level controls, include industry and year fixed
effects, and cluster the standard error estimation at the industry level. The
empirical results show that zombie firms significantly reduce the number of
patent applications and the total factor productivity (TFP) of normal firms in
the same industry. If the proportion of zombie firms in an industry increases
by 1 percent, then for normal firms in the same industry, the total number of
patent applications will decrease by 1 percent, the total number of invention
patent applications will decrease by 0.5 percent, and TFP will decrease by 2.4
percent. These effects are both statistically and economically significant.
Moreover, the crowding-out effect of zombie firms influences normal firms
through multiple channels. We investigate two of these potential channels.
The first is the credit misallocation channel. Since industry diversification is
a strategy adopted by banks to reduce excess exposure to industry risk, credit
distributed to zombie firms in an industry would crowd out the credit available
to normal firms in that same industry. A second potential channel is the
distorted market competition channel. Financing subsidies enable zombie
firms to finance their investment at a much lower cost, thus giving them an
unfair advantage when competing against normal firms. Such distorted
market competition forces normal firms to focus on short-term survival
objectives instead of a long-term investment in order to innovate. We use two
proxies to test the credit misallocation channel; namely, state ownership and
industry dependence on external financing and one proxy for industry
concentration (HHI). We use these proxies to test the distorted market
competition channel. Table 2 reports the subsample regression results based
on corporate ownership, industry dependence on external financing, and
industry concentration. All of the regressions are 2SLS IV regressions. As an
IV estimation has a larger size distortion than OLS (Young, 2017), we focus
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on the significance level of the subsample regressions instead of comparing
the coefficient magnitudes. Panels A and B show that more resourceconstrained firms (non-SOEs) face more significant distortions from zombie
firms, as do firms with more external financial dependence and firms in more
concentrated industries, thus supporting the credit misallocation channel.
Panel C shows that normal firms in more concentrated industries suffer
significant reductions in their innovation, while this effect is not significant
for firms in less concentrated industries, thus supporting the distorted market
competition channel.
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The paper makes the following contributions. First, by studying the structural
problems of resource misallocation caused by zombie firms, we show that the
dissolution of zombie firms is critical to promoting innovation in China.
Second, we propose a new industry perspective on how zombie firms affect
the performance of normal firms. The literature usually focuses on the
jurisdictional perspective and uses the proportion of zombie firms at the
provincial level to study the credit misallocation caused by zombie firms (Tan
et al., 2017). By employing a different angle, we find that the crowding-out
effects of zombie firms not only play a role through credit rationing at the
jurisdictional level, but also through product market competition at the
industry level. This finding implies that the dissolution of zombie firms is not
simply a jurisdictional issue, but rather has national policy implications in
regards to promoting innovation. This paper thus illustrates the policy
importance of the dissolution of zombie firms and sheds light on the current
reforms aimed at promoting high-quality development in China.
(Yun Dai, Lingnan College, Sun Yat-sen University; Wei Li, School of
Economics, Fudan University; Yongqin Wang, School of Economics, Fudan
University.)
References
Chava, S., A. Oettl, A. Subramanian, and K. V. Subramanian, (2013).
“Banking Deregulation and Innovation,” Journal of Financial
Economics 109(3): 759-774.
Cornaggia, J., Y. Mao, X. Tian, and B. Wolfe (2015). “Does Banking
Competition Affect Innovation?”, Journal of Financial Economics 115(1):
189-209.
Tan, Y., Z. Tan, Y. Huang, and W. T. Woo (2017). “The Crowding-out Effect
of Zombie Firms: Evidence from China’s Industrial Firms,” Economic
Research Journal 5: 175-188 (in Chinese).
Young, A. (2017). Consistency without Inference: Instrumental Variables in
Practical Application. Unpublished manuscript. London: London School of
Economics and Political Science. Retrieved
from:https://personal.lse.ac.uk/YoungA/ConsistencyWithoutInference.pdf.
Tags: Zombie Firms, Innovation
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