Zombie Companies In The Context Of State- Owned Enterprises In Indonesia

Zombie Companies In The Context Of State- Owned Enterprises In Indonesia

Elazhari^a,1*, Khairuddin Tampubolon^a,Barham Siregar^a, Ramadha Yanti Parinduri^a,Boby Indra Prayoga^a

aUniversitas Pembinaan Masyarakat Indonesia

1elazhari12345@gmail.com

*corresponding author

ARTICLE INFO ABSTRACT

Article history:

Received 31 Ags 2022 Revised 6 Sept 2022 Accepted 13 Sept 2022

This paper discusses “zombie” companies in the context of state- owned companies in Indonesia. Specifically, we will examine the factors that determine them to become a “zombie” company. In addition, we will examine the impact of their existence on the economy. Using a sample of 159 Indonesian state-owned companies from 2010 to 2020, we find that Indonesian state-owned companies are indicated to have zombie companies.

Their existence is significantly determined by internal factors rather than external factors. Dominant external factors are significant when tested simultaneously with internal factors. In addition, we also find that their presence has a significant negative impact on economic growth and national productivity. Therefore, the government, as well as controlling the company, is expected to be able to immediately overcome their existence, which can be done by restructuring the company or if possible liquidating them. Their existence not only harms themselves, but also harms other companies, and can even harm the national economy..

Copyright © 2023 International Journal of Artificial Intelegence Research.

All rights reserved.

Keywords:

State-Owned Enterprises Firm Performance Panel Regression Probit/Logit Regression

I. Introduction

Zombie companies are companies that have negative equity, but continue their business activities [1], These companies actually no longer have the ability to compete and most of them are unfit to live [2], They still survive because of the protection of creditors, otherwise they will die. They have the potential to pose a major threat to the economy, not only because of the threat to their own bankruptcy, but also the risk they pass to other firms, undermining competitiveness and reducing the capacity of other firms to create value [3]; [4], Unfortunately, their existence often goes unnoticed or may be noticed, but ignored about the seriousness of the problem.

[5], stated that zombie companies have increased since the late 1980s, with a tendency to increase over time. Using global data from Compustat from 1996 to 2018, they provide evidence that zombie companies are spread all over the world, including in ASEAN countries, such as Indonesia. Several other studies also stated that their concentration tends to increase over time, which is triggered by lower interest rates [6] and weak credit analysis [7]; [8]; [9], [10], [11] add that firm age, size, and industry are important factors in explaining their increase.

So far, studies on zombie companies are dominantly conducted on public companies, for example [12], and [13], in the UK, [14], and [2], in Spain, [15], in Ireland, [16], in [17], in Vietnam.

Meanwhile, state-owned companies are very rare. Whereas in developing countries, SOEs have a very important role. They are the main drivers of the economy, controlling national strategic fields and controlling the livelihoods of many people. Therefore, the existence of zombie SOEs will be more dangerous than zombie private companies.

This paper will study zombie companies in the context of state-owned companies in Indonesia.

Specifically, we will map their whereabouts and study the factors that cause them to become zombies.

In addition, we will also examine the impact of their existence on the economy. The results of this study are expected to provide valuable information for the government to consider and assess the

impact caused by zombie state-owned companies on the economic climate, both in micro and macro settings. With that, the government as the regulator and controller of state-owned companies can make appropriate and valuable policies related to this matter. Therefore, we hope that this paper can make a valuable contribution, both to the development of literature and to policy recommendations.

The second part of this paper describes the related literature and the formulation of hypotheses. The third part describes the research method. The fourth section presents the results of data analysis and discussion. The fifth part contains conclusions and suggestions, which is also the closing part of this paper.

II. Method

A. Data

The data includes all Indonesian state-owned companies from 2010 to 2020. During that year, there were 159 companies, consisting of 16 companies (10.06%) of which were of the Public Company (Perum) type, and 143 companies (89.94%) of the Limited Liability Company (Persero) type. . By industry sector, 22 companies (13.84%) are financial companies, and 137 companies (86.16%) are non-financial companies.

The data were obtained from the financial statements and annual reports of each company, as well as from reports from the Ministry of Finance of the Republic of Indonesia. The data includes balance sheet and profit/loss statement information. In addition, data were also obtained from Bank Indonesia and the Central Statistics Agency. All data are annual data and are in million rupiah (unless otherwise stated).

B. Variables and Measurements 1) Zombie Company

As we explained earlier, that there is no consensus about zombie companies. Therefore, to define a zombie or non-zombie company, we first need to define it clearly. We define zombie companies with certain criteria, which we combine from various previous studies. The criteria in question include:

1. Companies that have negative equity;

2. Companies that have an interest coverage ratio below one;

3. Companies that have high debt, but low financial costs;

4. Companies that have an injection of funds from the government;

5. Companies that have a low tax ratio; and

6. Companies that have negative profits for at least three consecutive years.

Zombie or non-zombie companies are treated as dummy variables, where a score of 1 (one) is assigned to zombie companies, and a score of 0 (zero) to non-zombie companies. A company will be declared a zombie, if it meets the specified criteria (at least one of the 6 criteria).

2) Determinant, Impact, and Control Variables

The determinant variables include company age, size, profitability, corporate governance, bank soundness, interest rates, regulations, and industrial sector. The age of the company is calculated from the time the company was founded to the year of observation. Company size is measured by the natural logarithm of total assets. Profitability is measured by return on assets. Corporate governance is measured by the proportion of state share ownership. Bank health is measured by a z-score. Interest rates are proxied by the BI rate. Regulation is measured by the ease of doing business index. The industrial sector is treated as a dummy, which includes four sub-sectors. Impact variables include economic growth and productivity. The control variables include liquidity (current ratio), leverage (debt to assets ratio), and asset management (total assets turnover).

C. Data Analysis Model 1) Determinant Analysis

To examine the significant factors causing companies to become zombies using the pooled logit/probit model. Systematically, the models developed for this research are:

𝐷_𝑍𝑜𝑚𝑏i𝑒i𝑡=𝛼0+𝛽1𝐴𝑔𝑒i𝑡+𝛽2𝑆i𝑧𝑒i𝑡+𝛽3𝑃𝑟𝑜fi𝑡i𝑡+𝛽4𝐶𝐺i𝑡+𝛽5𝑍𝑏𝑎𝑛𝑘i𝑡

+𝛽6𝐼𝑛𝑡𝑒𝑟𝑒𝑠𝑡i𝑡+𝛽7𝑅𝑒𝑔i𝑡+𝛽8𝐷_𝐼𝑛𝑑𝑢𝑠𝑡𝑟𝑦i𝑡+𝛽9𝐿i𝑞i𝑡+𝛽10𝐿𝑒𝑣i𝑡

+𝛽11𝑀𝑔𝑡i𝑡+𝛿𝑒+ s_i𝑡 Model 1

where:𝐷_𝑍𝑜𝑚𝑏i𝑒i𝑡is a zombie company;𝛼0 is a constant;𝛽1−11 is slope;𝐴𝑔𝑒i𝑡is the age of the company i in the year of 𝑡; 𝑆i𝑧𝑒i𝑡 is company size i in the year 𝑡; 𝑃𝑟𝑜fi𝑡i𝑡 is the company's profitability i in the year𝑡;𝐶𝐺i𝑡is corporate governance i in the year 𝑡;𝑍𝑏𝑎𝑛𝑘i𝑡is the soundness of banking in the country i in the year 𝑡; 𝐼𝑛𝑡𝑒𝑟𝑒𝑠𝑡i𝑡is the interest rate in the country i in the year 𝑡;

𝑅𝑒𝑔i𝑡is the regulation for the company i in the year𝑡;𝐷_𝐼𝑛𝑑𝑢𝑠𝑡𝑟𝑦i𝑡is the industry dummy for the company i in the year𝑡;𝐿i𝑞i𝑡is company liquidity i in the year𝑡;𝐿𝑒𝑣i𝑡is the company's leverage i in the year 𝑡; 𝑀𝑔𝑡i𝑡 is the asset management of the company i in the year 𝑡; 𝛿𝑒 is the fixed effect specification for the year; si𝑡is the residual error.

2) Impact Analysis

To examine the impact of the existence of zombie companies on the economy using a panel regression model. Systematically, the developed models are:

|𝐸𝑐𝑜_𝐺𝑟𝑜𝑤𝑡ℎ_i𝑡|, |𝑃𝑟𝑜𝑑𝑢𝑐𝑡i𝑣i𝑡𝑦_i𝑡|

=𝛽1𝐷_𝑍𝑜𝑚𝑏i𝑒_i𝑡+𝛽2∑𝐶𝑜𝑛𝑡𝑟𝑜𝑙_𝑉𝑎𝑟

+𝛼i𝑡+𝛾i𝑡+ si𝑡 Model 2

i𝑡

where: 𝐸𝑐𝑜_𝐺𝑟𝑜𝑤𝑡ℎi𝑡 is the economic growth of country i in year t; 𝑃𝑟𝑜𝑑𝑢𝑐𝑡i𝑣i𝑡𝑦i𝑡 is the productivity of country i in year 𝑡; 𝐷_𝑍𝑜𝑚𝑏i𝑒i𝑡 is a zombie dummy for company i in year 𝑡;

𝐶𝑜𝑛𝑡𝑟𝑜𝑙_𝑉𝑎𝑟i𝑡are control variables for company i in year i in year𝑡;𝛽is the slope;𝛼is a constant;

𝛾i𝑡is the sector and year effect for firm i in year𝑡; si𝑡is the residual error.

III. Results And Discussion

A. Statistics Highlights

The results showed that the number of zombie companies in state-owned companies in Indonesia reached 36 companies or about 22.64% of all existing companies. Most of them are manufacturing companies, while the majority of non-zombies are non-manufacturing companies. Their mean age was significantly higher than their non-zombie counterparts (39.94 years vs. 17.94 years). They are also significantly larger in size than non-zombies (1.27 vs. 1.11). Meanwhile, the profitability (return on assets) between zombies and non- zombies did not show a significant difference. The average profitability of zombies is - 0.14%, while non-zombies are only 0.39%. For governance, zombie companies are significantly worse than non-zombies, however, both have poor governance. The liquidity of zombie and non-zombie companies is quite under control, and there is no significant difference. However, their leverage and asset management are significantly lower than non-zombies.

Their average leverage reaches 83.23% with an asset turnover of only 0.61 per year. Meanwhile, the leverage of non-zombie companies is only 67.59%, with an asset turnover of 0.84 per year.

Table 1. Statistics and Different Test Results

Variables N Zombie Non-Zombie Differences

No of Companies 159 36 123 N/A

Determinant Factors

Age 1364 39.94 17.94 5.47 ***

Size 1364 1.27 1.11 2.97 *

Profit 1364 -0.14 0.39 -0.18

CG 1364 64.91 69.94 -3.022 **

Zbank 11 3.58 3.58 N/A

Interest 11 5.25 5.25 N/A

Reg 11 0.64 0.64 N/A

Industry 159 34 18 -4.453 ***

Impact Factors

Eco_Growth 1364 5.15 5.15 N/A

Productivity 1364 63.45 63.45 N/A

Control Variable

Liq 1364 1.79 1.72 -0.07

Lev 1364 83.23 67.59 5.44 ***

Mgt 1364 0.61 0.84 -4.87 ***

As far as we can see, the soundness of banks (z-score) is quite good (mean z = 3.58), with an average benchmark interest rate of 5.25%. However, the regulations reflected in the ease of doing business index are less profitable. The average is only 64 out of 100. Meanwhile, economic growth during the observation period was under control at the level of 5.15%, with a fairly good level of productivity (an average of 63.46%).

B. Results for Determinant Analysis

Table 2 presents probit/logit regression estimates to examine the factors that significantly determine a company to become a zombie. Panel A displays the estimation results of the probit regression. From there it can be seen that partially, age, size, profitability, and governance are significant factors that determine companies to become zombies. While the health of banks, interest rates, regulations, and industry are not significant. However, simultaneously, only regulation and industry do not show a significant effect. The main contributors that determine companies to become zombies are age, size, and corporate governance.

Table 2. Probit/Logit Regression Models

I II III IV V VI VII VIII IX

Panel A. Probit

Age 0.03^** 0.81^***

Size 1.23^*** 0.33^***

Profit -0.24^*** -0.06^***

CG -1.12^*** -0.30^***

Zbank -0.01 -0.27^*

Interest -0.03 -0.21^*

Reg 0.02 0.14

Industry 0.02 0.00

Memo Item

R^{2 0.45 0.52 0.49 0.64 0.13 0.24 0.29 0.31 0.81}

Adj. R² 0.20 0.27 0.24 0.41 0.02 0.06 0.08 0.10 0.65

F-stat. 4.37 4.44 4.41 4.56 2.45^* 2.46^* 3.51^** 4.47^*** 120.4^***

Year FE Yes Yes Yes Yes Yes Yes Yes Yes Yes

Con. Var. Yes Yes Yes Yes Yes Yes Yes Yes Yes

Panel B. Logit

Age 0.24^*** -0.54^***

Size -0.96^*** -0.06^*

Profit 0.03^* 0.21^***

CG -0.85^*** -0.03^*

Zbank 0.26^*** -0.22^*

Interest 0.24^*** 0.06^*

Reg 0.29^*** 0.41^***

Industry 0.09^* 0.27^***

Memo Item

R^{2 0.72 0.79 0.76 0.91 0.80 0.81 0.86 0.82 0.88}

Adj. R² 0.52 0.62 0.58 0.83 0.64 0.66 0.74 0.67 0.77

F-stat. 11.64^*** 11.71^*** 11.68^*** 11.83^*** 11.72^*** 11.73^*** 11.78^*** 11.74^*** 127.6^***

Year FE Yes Yes Yes Yes Yes Yes Yes Yes Yes

Con. Var. Yes Yes Yes Yes Yes Yes Yes Yes Yes

Specifically, age and company size were negatively correlated with zombie companies. This shows that the older the age and the larger the size of the company, the greater their tendency to become zombies. Old companies tend to be less productive, innovative, and creative. They tend to maintain the

“status quo” and hence will affect their profitability. This is in line with the findings of [18], [19], and [20], Meanwhile, the size of the company can affect the company's financial policy and capital structure. In addition, company size is also positively correlated with bank credit and the government prefers to save the bankruptcy of large companies than small companies [10]; [21], On the other hand, large companies tend to have more business portfolios, which can lead to a more complex debt portfolio. They also have a lower level of information asymmetry, so their credit rating is better maintained.

In addition to age and size, governance also has a significant role in determining companies to become zombies. The relationship between the two is negative, where the worse the governance, the greater the chance for them to become zombies. This finding supports the findings of [22], who also found a negative correlation between governance and zombie companies.

Panel B presents the results of the logit regression estimation. This is only to control and strengthen the results of the previous probit estimation. From there, it can be seen that the variable coefficient is consistent with the probit estimation results, even the contribution and level of significance is better.

This shows the excellent durability of the model. Thus, these findings support our first hypothesis.

C. Results for Impact Analysis

The results also found that the existence of zombie companies in state-owned companies had a significant negative impact on economic growth and productivity, even after being controlled by age, size, profitability, governance, liquidity, leverage, asset management, and industry and also controlled by bank health. interest rates, and regulations. This is because they are the main drivers of the economy, who control strategic areas of development and control the livelihoods of many people.

Thus, these findings support our second hypothesis.

Table 3. Regression

Eco_Growth Productivity

Model I Model II Model I Model II

Coef. t-stat. Coef. t-stat. Coef. t-stat. Coef. t-stat.

D_Zombie -2.258 -6.551^a -0.852 -4.327^a -0.237 -2.352^b -0.350 -6.026^a Control Variables

Age --- --- -2.103 -1.520 --- --- 0.078 5.217^a

Size --- --- 0.924 4.447^a --- --- -0.036 -5.829^a Profit --- --- 5.339 2.012^c --- --- 1.907 8.936^a CG --- --- -1.225 -2.353^b --- --- 0.973 5.738^a

Zbank --- --- 0.320 2.694^b --- --- 2.991 9.578^a

Interest --- --- -6.275 -8.156^a --- --- 1.086 5.043^a Reg --- --- -2.135 -6.215^a --- --- 0.952 6.554^a D_Industry --- --- -1.660 -6.087^a --- --- 1.663 7.313^a

Liq --- --- 0.854 2.166^b --- --- 1.231 7.537^a

Lev --- --- -1.061 -4.502^a --- --- -0.088 -2.164^b

Mgt --- --- 0.237 2.352^b --- --- 0.044 5.527^a

Memo Item

R-Squared 35.959 81.790 76.921 96.872

F-statistic 43.819 8.982 40.746 15.483

Their existence tends to limit the economic growth of a country. [3], state that they can prevent market entry and corporate consolidation, which can lead to antrophy in economic development. In addition, an increase in the number of zombie companies can worsen the investment climate and limit employment growth in other (non-zombie) companies, which will further widen the productivity gap between these two types of companies [2]

Zombie companies can also reduce the profitability of other healthy (non-zombie) companies, thereby hindering entrepreneurship and new investment. In the most extreme cases, a zombie company can result in a non-zombie company becoming a zombie company as well. [23], assert that zombie companies will automatically suck up economic life by consuming tax money, capital, and labor, which should all be better used by developing companies (non-zombies). [6], also found that zombie companies weigh on economic performance because they are less productive, and because their presence causes a decrease in investment in more productive (non-zombies) companies.

IV. Conclusions

Based on the results of data analysis and the previous discussion, it can be concluded that some of the state-owned companies in Indonesia are indicated as zombie companies. Their existence is significantly determined by internal factors, especially age, size, governance, and profitability.

Meanwhile, external factors such as bank soundness growth, interest rates, regulations, and industry also determine their existence, but this does not seem to happen directly, but through internal factors. Dominant external factors are significant when tested simultaneously with internal factors. In addition, we also find that their presence has a significant negative impact on economic

growth and national productivity. Therefore, the government, as well as controlling the company, is expected to be able to immediately overcome their existence, which can be done by restructuring the company or if possible liquidating them. Their existence not only harms themselves, but also harms other companies, and can even harm the national economy.

References

[1] P. S. Mohrman, M. B. and Stuerke, “‘Shareowners’’ Equity at Campbell Soup: How can Equity be Negative?”, Accounting Education:,’”An Int. Journal, 23(4), 386-405., 2014.

[2] J. Urionabarrenetxea, S., Garcia-Merino, J., San-Jose, L., & Retolaza, “Living With Zombie Companies: Do We Know Where the Threat Lies.,”Eur. Manag. Journal, 36(3), 408-420., 2018.

[3] N. Ahearne, A. G. and Shinada, “‘Zombie Firms and Economic Stagnation in apan’,”Int. Econ.

Econ. Policy, 2(4), 363-381., 2005.

[4] A. Caballero, R., Hoshi, T., & Kashyap, “Zombie Lending and Depressed Restructuring in Japan.,”

Am. Econ. Rev. 98(5), 1943-77., 2008.

[5] F. De Martiis, A., Heil, T., and Peter, “Are you a Zombie? A Supervised Learning Method to Classify Unviable Firms and Identify the Determinants.,”SSRN Electron. Journal, forthcoming, January., 2021.

[6] B. Banerjee, R., & Hofmann, “The Rise of Zombie Firms: Causes and Consequences.,”BIS Q. Rev.

Sept. 23(3), 67-78., 2018.

[7] F. Calligaris, S., Del Gatto, M., Hassan, F., Ottaviano, G. I., & Schivardi, “CEP Discussion Paper No 1520 December 2017 The Productivity Puzzle and Misallocation:,”An Ital. Perspect., 2017.

[8] A. Storz, M., Koetter, M., Setzer, R., & Westphal, “Do we want these two to tango?,”zombie firms Stress. banks Eur., 2017.

[9] Z. Acharya, V., & Xu, “Financial dependence and innovation: The case of public versus private firms.,”J. Financ. Econ. 124(2), 223-243., 2017.

[10] F. Andrews, D., & Petroulakis, “Breaking the Shackles: Zombie Firms, Weak Banks, and Depressed Restructuring in Europe.,”ECB Work. Pap. No. 2240., 2019.

[11] F. J. De Martiis, A., & Peter, “When Companies Don’t Die: Analyzing Zombie and Distressed Firms in a Low Interest Rate Environment.,”SSRN Electron. Journal, forthcoming, July., 2021.

[12] T. Papworth, “The Trading Dead: The zombie firms plaguing Britain‟s economy, and what to do about them,”Engl. Adam Smith Res. Trust., 2013.

[13] P. Boers, M., Kirwan, J. R., Wells, G., Beaton, D., Gossec, L., d’Agostino, M. A., ... & Tugwell,

“Developing core outcome measurement sets for clinical trials: OMERACT filter 2.0.,”J. Clin.

Epidemiol. 67(7), 745-753., 2014.

[14] P. Prada, “‘Zombie Buildings Shadow Spain’s Economic Future’,”Wall Str. Journal, Sept. 16., 2010.

[15] Bloomberg, “‘Zombie Hotels Arise in Ireland as Recession Empties Rooms’,”August 30, [available www.bloomberg.com; see 20th January 2017]., 2010.

[16]. T. Tan, ., Huang, . and oo, “‘Zombie Firms and the rowding-Out of Private Investment in China’,”

Asian Econ. Pap. 15(3), 32-55., 2016.

[17] N. Binh, T., Huong, V., & Loan, “Zombie Companies: Experimental Research from Real Estate Listed Sectors.,”Rev. Argentina Clínica Psicológica, 29(5), 1360- 1369., 2020.

[18] V. Adalet McGowan, M, Andrews, D., & Millot, “The Walking Dead: Zombie Firms and Productivity Performance in OECD Countries,”Econ. Policy, 33(96), 685-736., 2018.

[19] S. Hallak, I., Harasztosi, P., & Schich, “Fear the Walking Dead? Incidence and Effects of Zombie Firms in Europe.,”J. Econ. Sci. Res. 1(1)., 2018.

[20] O. Blažková, I., & Dvouletý, “Zombies: Who Are They and How Do Firms Become Zombies?,”J.

Small Bus. Manag. forthcoming, 1-27., 2020.

[21] V. Adalet McGowan, M., Andrews, D., & Millot, “Insolvency Regimes, Zombie Firms and Capital Reallocation.,”OECD Econ. Dep. Work. Pap. No. 1399., 2017.

[22] J. San-Jose, L., Urionabarrenetxea, S. & García-Merino, “Zombie firms and corporate governance:

What room for maneuver do companies have to avoid becoming zombies?.,”Rev Manag Sci https//doi.org/10.1007/s11846-021-00462-z, 2021.

[23] C. Golub, A., and Lane, “Zombie Companies and Corporate Survivors.,”Anthropol. Now, 7(2), 47-54, http//dx.doi.org/10.1080/19428200.2015.1058124., 2015.