In recent years, China has been plagued by overcapacity problem and zombie enterprises, which are seriously harmful to sustainable economic development and the stability of financial system. More importantly, it slows down the process of economic restructuring. But in fact, the problem of zombie enterprises is not a unique phenomenon to China and is also not a new word. The Japanese economy had experienced rapid growth of zombie firms in the last decade of the 1990s. This circumstance aroused widespread interest of scholars, leading to a growing number of researches. Caballero, Hoshi and Kashyap(2008)proposed " CHK” model by calculating a hypothetical " risk free interest payment”. Later, Fukuda and Nakamura(2011)developed a more accurate " FN-CHK” model by adding two indicators, namely " profitability criterion” and " evergreen lending criterion”. However, " FN-CHK” model has two defects if it is directly applied to China. On the one hand, it totally overlooks the significant role of government subsidies, which is especially serious in China. On the other hand, " FN-CHK” model regards the interest rate of convertible bonds as the unique criterion when calculating the hypothetical " risk free interest payment”. As a consequence, this model has a tendency to underestimate the number of zombie firms. This paper attempts to improve " FN-CHK” model in several aspects, for instance, improving calculation method of the " risk free interest payment”, and taking into account the dependence of government subsidies, and then identify zombie enterprises by using the data of Chinese listed companies from 2010 to 2016. This paper shows that, the rate of zombie companies was around 3.3% in 2011 and 2012, while it rose to 5% after 2013 and slowed down in 2016. This tendency could be related with different features of the early and late periods of the prolonged recessions. In the earlier stage(between 2011 and 2013), economy experienced an unexpected downturn and fewer companies could adjust their management tactics. As a result, the number of zombie enterprises was growing. In the later period(between 2013 and 2016), however, the economic decline was much more modest and more firms had adjusted their management strategies. Consequently, the number of zombie enterprises declined. Compared with our improved recognition model, " FN-CHK” model misses 16.59% of actual zombie firms. Using unique indicator when calculating the " risk free interest payment” and ignoring government subsidies have equal weighting in missing samples. It demonstrates that, our proposed model can improve the accuracy of recognition effectively, while directly using " FN-CHK” model might lead to error. We also find that, the proportion of zombie companies in western region is the highest, followed by central and eastern regions. The rates of zombie companies in traditional industries, like iron industry and papermaking industry, are the highest. It is remarkable that the rates of zombie companies in these traditional industries decreased the most in 2016. It might be attributed to a big rise in commodity prices and the success of dealing with zombie enterprise problem in iron industry in 2016. Previous studies show that the increasingly serious zombie problem might be blamed on the overcapacity caused by the " 4 trillion yuan stimulus plan”. Using statistical analysis and " DID” regression method, this paper confirms that, the over-rapid growth of investment in fixed assets caused by " 4 trillion yuan stimulus plan” might be responsible to the increasing rate of zombie enterprises after 2013. Besides, we also find that, the proportion of zombie state-owned companies is much higher than others. Moreover, this proportion is much higher in the areas where the state seriously intervenes the market. The most frequently used method of receiving financial assistance is evergreen lending, which is followed by interest discount and government subsidies. Because of the harmfulness of zombie firms, precise prediction is extremely important in prevention. We attempt to predict zombie enterprises by using Panel Logit model, the correct forecast rates in sample and out of sample are 88.57% and 96.58%. These results have significance to preventing and controlling zombie enterprises.
/ Journals / Journal of Finance and Economics
Journal of Finance and Economics
LiuYuanchun, Editor-in-Chief
ZhengChunrong, Vice Executive Editor-in-Chief
YaoLan BaoXiaohua HuangJun, Vice Editor-in-Chief
The Recognition and Warning of Zombie Enterprises: Evidence from Chinese Listed Companies
Journal of Finance and Economics Vol. 44, Issue 04, pp. 130 - 142 (2018) DOI:10.16538/j.cnki.jfe.2018.04.010
Summary
References
Summary
[1]Bai J, Lian L S. Why do state-owned enterprises over-invest? Government intervention or managerial entrenchment[J]. Accounting Research, 2014, (2): 41-48. (In Chinese)
[2]Cheng H, Hu D Z. The mystery of zombies: An empirical study from a microscopic perspective-Evidence from China Employee Survey(CEES)[J]. Journal of Macro-quality Research, 2016, (1): 7-25. (In Chinese)
[3]Du Y, Liu X. Research on recognition model of loss reversal of listed company based on logistic regression[J]. Technology Economics, 2009, (12): 58-65. (In Chinese)
[4]Liu K F, Mao N. A foreign literature review of zombie companies research[J]. Foreign Economics & Management, 2016, (10): 3-19. (In Chinese)
[5]Nie H H, Jiang T, Zhang Y X. The research of zombie companies in China[R]. National Academy of Development and Strategy, Renmin University of China, 2016. (In Chinese)
[6]Sun X H, Li M S. Over-investment and productivity loss of state-owned enterprises[J]. China Industrial Economics, 2016, (10): 109-125. (In Chinese)
[7]Wang H J, Li Q Y, Liu F. Government subsidies: Relief for the emergency or the poor? An empirical evidence from loss-making firms[J]. Nankai Business Review, 2015, (5): 42-53. (In Chinese)
[8]Zhang D, Xie Z H, Wang J W. China’s zombie companies and their detection: An exploratory research based on listed companies in iron and steel industry[J]. China Industrial Economics, 2016, (11): 90-107. (In Chinese)
[9]Zheng X Y, Wang H, Zhao Y Z. Can the reform of “County Directly Administrated by Province” promote economic growth?[J]. Management World, 2011, (8): 34-44. (In Chinese)
[10]Caballero R J, Hoshi T, Kashyap A K. Zombie lending and depressed restructuring in Japan[J]. The American Economic Review, 2008, 98(5): 1943-1977. DOI:10.1257/aer.98.5.1943
[11]Fukuda S I, Nakamura J I. Why did ‘zombie’ firms recover in Japan?[J]. The World Economy, 2011, 34(7): 1124-1137. DOI:10.1111/twec.2011.34.issue-7
[12]Kane E J. Dangers of capital forbearance: The case of the FSLIC and “zombie” S&Ls[J]. Contemporary Economic Policy, 1987, 5(1): 77-83. DOI:10.1111/coep.1987.5.issue-1
Cite this article
Zhou Jin, Xian Guoming, Ming Xiunan. The Recognition and Warning of Zombie Enterprises: Evidence from Chinese Listed Companies[J]. Journal of Finance and Economics, 2018, 44(4): 130-142.
Export Citations as:
For