Does financial deleveraging affect governments' desirability of privatization? Evidence from the Chinese listed local SOEs

Yang, Weiwei; Wang, He; Huobao, Xie Article Does financial deleveraging affect governments' desirability of privatization? Evidence from the Chinese listed local SOEs Journal of Applied Economics Provided in Cooperation with: University of CEMA, Buenos Aires Suggested Citation: Yang, Weiwei; Wang, He; Huobao, Xie (2023) : Does financial deleveraging affect governments' desirability of privatization? Evidence from the Chinese listed local SOEs, Journal of Applied Economics, ISSN 1667-6726, Taylor & Francis, Abingdon, Vol. 26, Iss. 1, pp. 1-20, https://doi.org/10.1080/15140326.2023.2220468 This Version is available at: https://hdl.handle.net/10419/314228 Standard-Nutzungsbedingungen: Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden. Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen. 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Evidence from the Chinese listed local SOEs Weiwei Yang, He Wang & Huobao Xie To cite this article: Weiwei Yang, He Wang & Huobao Xie (2023) Does financial deleveraging affect governments’ desirability of privatization? Evidence from the Chinese listed local SOEs, Journal of Applied Economics, 26:1, 2220468, DOI: 10.1080/15140326.2023.2220468 To link to this article: https://doi.org/10.1080/15140326.2023.2220468 © 2023 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group. Published online: 02 Jun 2023. Submit your article to this journal Article views: 711 View related articles View Crossmark data Citing articles: 1 View citing articles Full Terms & Conditions of access and use can be found at https://www.tandfonline.com/action/journalInformation?journalCode=recs20 FINANCE AND BANKING ECONOMICS Does financial deleveraging affect governments’ desirability of privatization? Evidence from the Chinese listed local SOEs Weiwei Yang a , He Wang b and Huobao Xie c a School of Business and Tourism Management, Yunnan University, Kunming, China; b The Geriatrics Hospital of Yunnan Province, Kunming, China; c Economics and Management School, Wuhan University, Wuhan, China ABSTRACT The rapid growth of local SOEs in China largely depends on high leverage, thus local governments and their SOEs will face harder budget constraints when the central bank implements tight credit policies. Using a sample of listed local SOEs in the Chinese A-share market, this paper attempts to investigate the relationship between financial deleveraging and privatization of local SOEs. We find that privatization of the Chinese local SOEs increases significantly during financial deleveraging, and this effect is more pronounced among SOEs with less tax contribution, fewer employees and that cause greater financial burden to the local governments. This paper broadens the research on environmental factors that drive politicians to privatize. ARTICLE HISTORY Received 10 January 2021 Accepted 28 May 2023 KEYWORDS Financial deleveraging; privatization; local state-owned enterprises 1. Introduction Although it has been nearly four decades since privatization was introduced into the world, privatization in China is still ongoing. Unlike other transition economies who implemented “shock therapies”, the Chinese government has adopted a gradual privatization strategy (G. M. Chen et al., 2006). China’s large-scale privatization took place during 1995 − 2002, which was sanctioned by the central government and actively responded by the local governments. However, relative to the previous period, privatization in China after 2002 continues on a smaller scale and is mainly a decision of local governments absent central government policy. Even so, China has been still one of the most active countries in privatization between 2009 and 2016, and its privatization trade volume has ranked first in the world for many years. 1 As the owners of state-owned enterprises (SOEs), the governments’ willingness to reform will ultimately determine whether privatization happens (K. Guo & Yao, 2005). Therefore, existing literature on the causes of the Chinese privatization primarily focuses on government motivations. There are three main points of view: The first line of CONTACT He Wang [email protected] The Geriatrics Hospital of Yunnan Province, Kunming, Yunnan, P. R. China 1 The data is from Privatization Barometer Database, www.privatizationbarometer.net. The amount of transactions in the database refers to the funds raised by share issue privatization (SIP) and private equity, including both partial and full privatization. JOURNAL OF APPLIED ECONOMICS 2023, VOL. 26, NO. 1, 2220468 https://doi.org/10.1080/15140326.2023.2220468 © 2023 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group. This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial License (http:// creativecommons.org/licenses/by-nc/4.0/), which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited. The terms on which this article has been published allow the posting of the Accepted Manuscript in a repository by the author(s) or with their consent. thinking argues that increasing fiscal revenue or reducing financial burden is the main reason for local governments to privatize their SOEs (D. Li & Lui, 2004; Han & Oi, 2008; Zhu, 2004). The second line of thinking is that the purpose of governments privatizing SOEs is to improve enterprise efficiency (Gupta et al., 2008). The third line of thinking supports political motivation. For example, Xia and Chen (2007) and Yang et al. (2010) document that the local governments tend to control large-scale and regulated industry firms. Collectively, these studies merely concentrate on the relationship between government motivation and privatization without considering macro-environment that affects the governments’ willingness to privatize. Then, do environmental factors affect the governments’ willingness to privatize? Several studies have explored the impact of China’s institutional change on privatization. Cao et al. (1999) argue that reforms in tax, fiscal, monetary and banking systems in the 1990s have hardened the local governments’ budget constraints and triggered the privatization of local SOEs. S. Li et al. (2000) document that cross-regional competition played an important role in driving the local governments to privatize. Brandt et al. (2005) show that banking reform played an integral role in inducing the township and village enterprises to be privatized. H. Li (2003) and K. Guo and Yao (2005) also attribute the privatization to the hardened budget constraints and market competition. Surprisingly, however, there is scarce literature on what drives the Chinese local governments to privatize in the 21st century. Obviously, institutional change mentioned above cannot explain China’s privatization in recent ten years, thus it is of great academic interest to provide new explanation for this, especially in the case that China’s institutional and economic environment is rapidly changing. In this paper, we study the influence of financial deleveraging on privatization of local SOEs in the past decade. China’s credit supply has exhibited cyclical features since 1998. Typically, the People’s Bank of China (PBC) implements a credit expansion policy in bad times and a credit crunch policy in good times. Following Bezemer and Zhang (2014), we use the method of Hodrick-Prescott filter to identify financial deleveraging and financial leveraging in China. By employing a Logit model and using a sample of listed local SOEs in the Chinese A-share market from 2004 to 2017, we find that financial deleveraging can increase the probability of a local SOE being privatized. In particular, SOEs with less tax contribution, fewer employees and that cause greater financial burden to the local governments are more likely to be privatized during financial deleveraging. Overall, our results indicate that stabilizing tax revenue, minimizing unemployment and reducing financial burden are important considerations for local governments when selecting SOEs to privatize. Our paper has important theoretical contributions and policy implications. First, the current literature on factors that influence China’s privatization mainly focuses on the local government motivations. Even though several articles explored the impact of institutional changes on privatization, they mainly focus on privatization in the 1990s. By using more recent Chinese privatization data, this paper contributes to this strand of literature by showing that macro environment plays a key role in driving local governments to privatize, and provides a new explanation for privatization in China in the 21st century. Second, it enriches the literature on the consequences of financial deleveraging. The current literature mainly focuses on the macro-effects caused by financial deleveraging by using cross-country data, but our paper is an empirical study on its micro2W. YANG ET AL. consequences within one country. Third, our findings indicate that stabilizing finance and keeping employment are important considerations for local governments when making privatization decision. Therefore, the central government, in order to encourage local governments to abandon SOEs that are uncompetitive but pay more taxes, have more loss or redundancy, should deepen reform of fiscal and taxation system and formulate measures to compensate local governments’ loss caused by efficiencyenhancing privatization. The rest of our paper is organized as follows: Section 2 is the theoretical analysis and research hypothesis; Section 3 describes data sources and research design in detail; Section 4 is empirical analysis, testing the relationship between financial deleveraging and privatization, and which types of SOEs that the local governments are more likely to privatize during financial deleveraging. Robustness checks are presented in Section 5. Section 6 is the concluding remarks. 2. Theory and hypotheses 2.1. Financial deleveraging and privatization of local SOEs Privatization in China is mainly prompted by local governments (Qian & Weingast, 1997). Therefore, financial deleveraging may promote privatization by affecting the governments’ willingness to privatize. In what follows we analyze how financial deleveraging influences local governments’ desirability of privatization. First, Financial deleveraging has side effects on GDP growth in the short term caused by a reduction of total credit supply in the society (Bernanke & Gertler, 1995; Devlin & McKay, 2008; International Monetary Fund, 2008; Ma et al., 2016), as reforms usually occur when external environment becomes unfavorable, so local governments will seek reform strategies to support economic growth. In particular, China’s unique fiscal decentralization that requires the local governments to share most of their tax revenue with the central government but take the main responsibility for local public expenditure makes the local governments face strong budget constraints. The local governments need to obtain more fiscal revenue through economic development in order to provide public services and maintain social stability. More importantly, the promotion of local officials in China is in the hands of the central government who usually uses economic indicators such as regional economic growth and fiscal revenue to evaluate the performance of local officials (H. Li & Zhou, 2005; Y. Chen et al., 2005). As a result, the local governments in China have a higher initiative to pursue economic growth. Developing private economy is conducive to enhancing economic growth (Barnett, 2000; Berkowitz & DeJong, 2003; Patrick, 1997) and improving local fiscal conditions (Zhu, 2004). Therefore, local governments have incentives to increase support for the private economy, and privatizing SOEs can make this support more credible. Second, Financial deleveraging will harden the budget constraints of local SOEs. The Chinese local governments’ implicit guarantee for local SOEs has induced soft budget constraints problems for a long time. Specifically, SOEs with lower profitability and even loss can still survive through bank loans and pay taxes to the local governments (K. Guo & Yao, 2005). Financial deleveraging in large part reflects the central government’s intentions who often exerts influence on the PBC’s decision-making (Chen and Zha, JOURNAL OF APPLIED ECONOMICS 3 2018). In order to avoid being punished, not only the banks quickly respond to the credit policies, but also the local governments reduce their intervention in the credit allocation. Then, banks strengthen their risk awareness and are motivated to allocate scarce credit resources to more profitable and efficient firms. This fact is supported by Cong et al. (2019), they show that more capital was allocated to firms with higher productivity during the credit crunch period, but stimulus-driven credit expansion reverses this allocation process. Hardened budget constraints make it difficult for the local governments to finance the inefficient SOEs and they have to use their own financial resources to keep the SOEs survive (Cao et al., 1999), which will cause a heavy financial burden to the local governments and hence reduce their willingness to control such SOEs. Third, Financial deleveraging can reduce social consumption and increase demand uncertainty in the short term. Less capital supply and higher costs of debt induce liquidity problems. As a response, firms may reduce investment, hold down wages and even lay off workers (Ma et al., 2016), which is followed by a decline in demand for consumer goods. According to the view of informational gains, private enterprises respond more quickly to consumer demand, input costs and other information compared with public-owned enterprises (Glaeser & Scheinkman, 1996; Gupta et al., 2008). Therefore, the local governments are more likely to privatize their SOEs to improve the flexibility of firms’ management when the SOEs are subject to demand shock, which is conducive to enhancing enterprise efficiency and increasing tax revenue. In summary, financial deleveraging puts the local governments into a disadvantaged position through slowing economic growth, hardening SOEs’ budget constraints and reducing social demand in the short run, which will discourage their willingness to control SOEs and thus privatization may take place. On the basis of arguments above, this paper proposes the following hypothesis: H1: Financial deleveraging has a positive effect on the probability of a local SOE being privatized. 2.2. Heterogeneous effects of financial deleveraging on privatization of local SOEs In China, fiscal revenue of local governments mainly comes from taxes and government funds——income from auction of state-owned land (Q. Guo, 2019). The slowdown of economic growth and the decline of social demand reduce the sales and profits of firms when financial deleveraging occurs. In addition, the capital investment of the firms will also decline due to the reduction of credit loans, leading to lower wages and higher unemployment (Cuerpo et al., 2015). As a result, the local governments’ revenue from value added taxes related to sales activity and income taxes related to business or personal income can fall significantly. Bernanke and Gertler (1995) document that the impact of tight monetary policy on household demand is first reflected in housing investment of a family, causing a sharp decline in housing demand. In China, financial deleveraging is always accompanied by tight monetary policy, so it can be reasonably inferred that 4W. YANG ET AL. financial deleveraging will lead to a decline in housing demand and affect the local governments’ revenue stemming from government funds. Therefore, the local governments have a strong incentive to try their best to stabilize the taxes from SOEs because they are easier to be controlled. So, how to reduce tax loss as much as possible while promoting privatization? As the information asymmetry between SOEs and the local governments is lower relative to private firms, it is difficult for SOEs to evade taxes by hiding income (Liu & Li, 2012). From this point of view, a rational local government will choose to control the SOEs that make more tax contribution. Therefore, we propose the following hypothesis: H2: Relative to the SOEs with more tax contribution, the SOEs with less tax contribution are more likely to be privatized by local governments during financial deleveraging. High regional unemployment rate may hinder the political promotion of local officials. Therefore, how to minimize unemployment is usually a key issue for local governments in the process of privatization. Hu et al. (2006) document that privatization in China is not accompanied by higher unemployment, which probably implies that local governments in China considered employment problem in advance (D. Li & Lui, 2004) and choose to privatize SOEs first with fewer employees. D. Li and Lui (2004), Hu et al. (2006), Xia and Chen (2007) and Yang et al. (2010) find that governments tend to retain the large SOEs and privatize the small ones. Given the rise in unemployment during financial deleveraging, the Chinese local governments’ preference for this kind of privatization sequencing should be more prominent. In view of this, we propose our third hypothesis: H3: Relative to the SOEs with more employees, the SOEs with fewer employees are more likely to be privatized by local governments during financial deleveraging. In addition to increase revenue, saving expenditure can also help alleviate the fiscal pressure faced by the Chinese local governments during financial deleveraging. Therefore, the SOEs that create high fiscal pressure for the local governments are likely to be privatized first. Bai et al. (2006) find that privatizing unsustainable SOEs can reduce the financial burden of local governments. D. Li and Lui (2004) indicate that the local governments would like to privatize SOEs only when the huge debts and losses of the SOEs needed to be borne by the government. Huang (2019) shows that the purpose of local governments privatizing SOEs is not to improve the performance of SOEs but to reduce subsidies to them. Combining the views of these literature, we think that only the loss itself does not necessarily lead to privatization of local SOEs. Profit-losing SOEs may have higher sales income and still be able to pay value added taxes (K. Guo & Yao, 2005), or profit-losing SOEs are still able to access to bank loans and do not need the assistance of local governments. Therefore, if the profit-losing SOEs rely on the assistance of local governments to operate, with the fiscal pressure increasing during financial deleveraging, the local governments are likely to privatize them to get rid of the burden. Based on the arguments above, this paper proposes the following hypothesis: JOURNAL OF APPLIED ECONOMICS 5 H4: The SOEs with more losses and more government subsidies are more likely to be privatized by the local governments during financial deleveraging. 3. Research design 3.1. Sample selection and data sources The initial sample of this paper includes all the listed SOEs in the Chinese A-share market from 2004 to 2017. The China Securities Regulatory Commission (CSRC) has required all listed companies to disclose the information of controlling shareholders and ultimate owners since 2003, so we choose 2004 as the starting point of our sample period in order to observe the annual change of the ultimate owners of firms. Ultimate owners and financial data of sample firms mainly come from the China Stock Market and Accounting Research (CSMAR) database, which provides comprehensive data on China’s capital market. The data of regional GDP, value of the secondary industry, value of import and export trade, and unemployment rate come from the Economic Statistical Yearbook of each province. The data of credit to private sector (credit to households and credit to non-financial corporations) comes from the World Development Indicators (WDI) database of the world bank, in which we can get China’s credit data from 1977. In order to generate a more precise time trend and define financial deleveraging accurately, we use the Chinese credit data from 1977 to 2017. We exclude the following kinds of firms: (1) Firms in the financial industry; (2) Public utility firms; (3) Firms controlled by the central government; (4) ST, PT and insolvent firms 2 ; (5) Firms in industries and province (Tibet) that have never experienced privatization during the sample period; (6) Firms with missing data for major variables. Thus, 8,485 observations of 1,009 firms make up our final sample, and 208 observations of privatization are included. All continuous variables are winsorized at 1 percent in order to reduce the estimation errors caused by extreme values. 3.2. Regression model and variable measures In order to test the impact of financial deleveraging on the privatization of local SOEs, we estimate the following regression model at the firm-year level: 2 ST (special treatment) refers to firms that suffer losses for two consecutive years, and PT (particular transfer) refers to firms that suffer losses for three consecutive years. Insolvent refers to firms with total liabilities greater than total assets. 6W. YANG ET AL. Privatizationi;t¼αþβ1Deleveragei;tþβ2Strategyi;tþβ3PastROAi;tþβ4LnStaffi;t1 þβ5Growthi;t1þβ6Levi;t1þβ7Efficiencyi;t1þβ8Structurei;t þβ9Opennessi;tþβ10Unemploymenti;tþβ11V OLi;t þXIndustryþXProvinceþεi;t (1) Where Privatization is an indicator variable that equals one if the ownership of the local SOE i is transferred to private entities 3 in year t, and zero otherwise. Deleverage denotes financial deleveraging. Following Bezemer and Zhang (2014), we use the financial deleveraging year dummies (Del_Dum) generated by the extent to which credit to private sector/GDP (Debt/GDP) deviates from its long-term trend to measure Deleverage. Specifically, we first use the Hodrick-Prescott filter (HP) with a smoothing parameter of 400 to separate the trend and cyclical component in Debt/GDP. The cyclical component is the deviation of Debt/GDP from its trend and is denoted by Cycle. Cycle being positive means the credit is expanded, and otherwise the opposite. Then, we calculate the standard deviation of Cycle, namely σ(Cycle). When Cycle is negative and its absolute value is more than ασ (Cycle) with α = 1, we define the year as a local trough of the credit cycle. Finally, we define the local peaks of the credit cycle in which the cyclical component Cycle is higher than in both the previous and posterior year. Years between the peak and the trough (excluding the peak year) are defined as financial deleveraging years, for which the variable Del_Dum takes value one, and zero otherwise. 4 Since Del_Dum is a year-dummy variable, it may capture other time trend factors as well as financial deleveraging. In order to eliminate the proxy errors, we also use Debt/ GDP as the explanatory variable and observe whether there is a negative correlation between Debt/GDP and Privatization, so that Debt/GDP and Del_Dum can complement each other. Control variables. According to the literature on causes of privatization or privatization sequencing, we include control variables reflecting firm characteristics as follows: an indicator of strategic industry (Strategy), 5 average profitability over the past two years (PastROA), number of employees (LnStaff), sales growth rate (Growth), interest-bearing debt ratio (Lev) and employee productivity (Efficiency). Then, regional variables including industrial structure (Structure), openness (Openness) and unemployment (Unemployment) are controlled as well. Generally speaking, local governments are more open-minded and have greater support for private economy in areas with high industrialization and opening up, while they may oppose privatization in areas with high unemployment because employment issues affect their political promotion. In addition, financial leverage volatility (VOL) has a negative impact on economic growth and aggravates financial uncertainty (Ma et al., 2016), which may affect the privatization of local SOEs, so we also control for it. Finally, we control for industry and province effects 3 We define the ultimate owner as a local state entity if the code of its nature in the CSMAR database is 1100 (i.e., stateowned enterprises), 2000 (i.e., administrative organs and institutions) and 2120 (i.e., local institutions), and otherwise we define it as a private entity. 4 The unreported results show that 2004 − 2008, 2010, 2011 and 2017 are financial deleveraging years. 5 We define the military, power grid, petroleum and petrochemical, telecommunications, coal, civil aviation and shipping industry as strategic industries. JOURNAL OF APPLIED ECONOMICS 7 decision of privatization when it becomes a major financial burden to the government. In addition to separately run models (2)−(4), we also run a general model that includes all the variables (LowTax, LowStaff, Loss and Subsidy) together to see if these variables have some kind of interaction among themselves. The results are reported in Table 6. As shown in Columns (1) and (3), our main conclusions do not change when we run a general model. That is, local SOEs with less tax contribution, fewer employees and more losses and subsidies have a higher privatization probability during financial deleveraging. However, the coefficients of Del_Dum*LowTax (Debt/GDP*LowTax) and Del_Dum*LowStaff (Debt/ GDP*LowStaff) are smaller than that in Table 4 while the coefficient of Del_Dum*Loss*Subsidy (Debt/GDP*Loss*Subsidy) is similar to that in Table 5. Such results indicate that the variables of taxes and employees may have some kind of interaction, but which does not affect the estimate of the correlation among financial deleveraging, tax contribution (scale of employees) and privatization of local SOEs. Columns (2) and (4) report the relative importance (RI)——calculated as the share in explaining dependent variable variance——of each variable, which show that financial burden caused by SOEs is the most important factor that local governments consider when deciding to privatize what types of SOEs. However, The RIs of LowTax and LowStaff have no significant difference, indicating that taxes and employees are equally important to the governments. 5. Robustness tests 5.1. Substitution of financial deleveraging First, although credit to private sector scaled by GDP is widely used to measure financial leverage ratio, some literature also adopts M2/GDP as a proxy variable for financial leverage ratio in robust tests. Therefore, we use the HP with a smoothing parameter of 400 to separate the trend and cyclical component in M2/GDP and regenerate the financial deleveraging year dummies, denoted by Table 7. Regression results based on substitution of financial deleveraging, Placebo test and IV estimation. Variable Privatization (1) (2) (3) (4) (5) Del_Dum2 0.570*** (3.057) M2/GDP −0.022** (−2.540) Del_Dum false −0.396** (−2.293) Del_Dum 1.712*** (5.145) Debt/GDP −0.103*** (−24.229) Constant 3.261 6.815*** 6.037** −6.470*** −1.891** (1.210) (2.758) (2.369) (−2.926) (−2.249) Control Variables YES YES YES YES YES Industry FE YES YES YES YES YES Province FE YES YES YES YES YES Pseudo R 2 0.128 0.127 0.126 — — Observations 8,485 8,485 8,485 8,485 8,485 14 W. YANG ET AL. Del_Dum2. Then, we re-estimate model (1), the result is shown in Table 7 Column (1), we note that the coefficient of Del_Dum2 is positive and significant at the 1% level. Second, we substitute M2/GDP for Debt/GDP. The result in Table 7 Column (2) shows that M2/GDP correlates negatively with Privatization, suggesting an increase in the privatization when the money supply decreases, which is consistent with our main results. 5.2. Placebo test Because financial deleveraging influences all listed local SOEs, thus we cannot observe the counterfactual situation——privatization of the local SOEs that are not affected by financial deleveraging. To further confirm the robustness of our main results, we perform a placebo test with defining a set of false financial deleveraging years. Specifically, we define 2009 and 2012 − 2016 (they are actually financial leveraging years) as the financial deleveraging years, denoted by Del_Dum false . If the coefficient of Del_Dum false is consistent with that of Del_Dum in Table 3 in terms of direction and significance, then we can say that our main results are not robust, and robust otherwise. Table 7 Column (3) indicates that the coefficient of Del_Dum false is −0.396, which is contrast to the results in Table 3. Therefore, our main results hold. 5.3. Endogeneity Some unobservable factors may influence China’s financial deleveraging and privatization of local SOEs at the same time. For example, the capital supply is usually insufficient in bad times, resulting in a decline in the credit to private sector. Meanwhile, the local governments are usually under higher fiscal pressure in bad times, and their willingness to privatize SOEs may increase. To address our concern for endogeneity issue, we employ an instrumental variable probit (IV Probit) approach. We designate the annual average shadow interest rate (SSR) in the United States as the instrumental variable for the Chinese financial deleveraging. There are two reasons: First, global factors such as federal shadow interest rate have spillover effects on the monetary policies of emerging market countries (He & McCauley, 2013). It will lead to capital outflow from emerging markets when the US Federal Reserve raises interest rates, and hence financial deleveraging may Table 8. Regression results that remove the effects of control variables on deleveraging. Variable (1) (2) (3) (4) Privatization Privatization Privatization Privatization Residual Del_Dum 0.068** 0.065** (2.224) (2.158) Residual Debt/GDP −0.016** −0.019** (−2.077) (−2.232) Constant −3.687*** 7.685*** −3.688*** 7.834*** (−47.931) (3.032) (−47.770) (3.105) Control Variables NO YES NO YES Industry FE NO YES NO YES Province FE NO YES NO YES Pseudo R 2 0.001 0.125 0.001 0.127 Observations 8,485 8,485 8,485 8,485 JOURNAL OF APPLIED ECONOMICS 15 happen in these economies. Therefore, the US shadow interest rate meets the correlation requirements of IV. Second, the US shadow interest rate will not directly affect the privatization of local SOEs in China, meeting the exogenous requirements of IV. Table 7 Columns (4) and (5) present the results of IV Probit. As shown, the relationship between Del_Dum (Debt/GDP) and Privatization still exists. 8 Another endogeneity may be caused by the control variables. That is, the same control variables that have influence on the probability of privatization may also have some effects on the value of the deleveraging decisions taken by China’s Central Bank concerning the individual firms. To address such endogeneity issue, we first regress financial deleveraging variables (Del_Dum and Debt/GDP) on the control variables used in the baseline model, and obtain the residual terms——denoted by Residual Del_Dum and Residual Debt/GDP , respectively. Then, we regress Privatization on the residual terms (Residual Del_Dum and Residual Debt/GDP ). Doing so enables us to obtain the net effects of financial deleveraging on privatization because the residual term represents the portion of the deleveraging variable that is not affected by the control variables. Table 8 reports such net effects. As shown, the coefficients of Residual Del_Dum in Columns (1) and (2) are significantly positive, and the coefficients of Residual Debt/GDP in Columns (3) and (4) are significantly negative, indicating that the endogeneity issue caused by the control variables does not change our conclusions. 5.4. Sample selection bias Given that the local SOEs with certain characteristics may have a high probability of being privatized, which can cause estimation bias, we match the SOEs that are privatized with the SOEs that are not privatized employing the propensity score matching method (PSM). The variables used for matching include strategic industry dummy, ROA over the past two years, number of employees, sales growth, interest-bearing debt ratio and employee productivity. We use one-tofour nearest neighbor matching and the difference between the propensity scores of treatment firms and control firms is no more than 0.005. The results are Table 9. Regression results based on propensity score and MD matched sample. Variable Privatization (1) (2) (3) (4) Del_Dum 0.744*** 0.507** (2.991) (2.084) Debt/GDP −0.020* −0.016* (−1.959) (−1.817) Constant 3.877 7.900*** 1.491 4.030 (1.227) (2.803) (0.519) (1.564) Control Variables YES YES YES YES Industry FE YES YES YES YES Province FE YES YES YES YES Pseudo R 2 0.120 0.117 0.095 0.094 Observations 930 930 968 968 8 The Wald test shows that Del_Dum and Debt/GDP are endogenous. In addition, SSR has strong explanatory power for both Del_Dum and Debt/GDP. We also conduct a two-stage estimation and find that the F value of the first stage is far more than 10, so there is no weak IV problem. 16 W. YANG ET AL. presented in Table 9 Columns (1) and (2). In addition, we also employ Mahalanobis distance (MD) method to match firms, and the results are reported in Table 9 Columns (3) and (4). As shown, with either matching method, our main results still hold. 5.5. Other robustness tests China has been confronted with the complex and changeable environment during the long period from 2004 to 2017, our main results may be driven by external shocks or other domestic reforms. Therefore, we attempt to eliminate the impact of some special events. For example, we remove the observations in 2007 and 2008 from our sample to exclude the possible influence of the global financial crisis. In addition, the central government proposed to actively develop a mixed ownership economy at the Eighteen Third Plenary Session in 2013, which may affect the subsequent transfer of state-owned equity. To address this concern, we add the dummy variable after2013 (1 for the years after 2013, and 0 for other years) in the model (1). The unreported results show that the relationship between Del_Dum (Debt/GDP) and Privatization still exists. 6. Conclusions Privatization is an effective means for China to reform SOEs and establish a market-oriented economy. However, mass and rapid privatization supported by economic liberals is not applicable for transition economies. The success of privatization in large part depends on the perfection of law and the effectiveness of regulation (Estrin et al., 2009). Given that China’s legal system is imperfect and protection of investors is weak, it is reasonable for the Chinese government to adopt the gradual privatization strategy. However, with the improvement of China’s legal system, the privatization of SOEs in China will continue. In particular, the central government has put forward guidance on the reform of SOEs by classification since 2015, which implies that most of the state-owned capital will be invested in the areas related to the public service, strategic security and vitals of the national economy. Meanwhile, the SOEs will follow the market rules of survival of the fittest and withdraw from the competitive field. Therefore, we need to deeply understand what and how environmental factors affect the local governments’ desirability of privatization and the local governments’ key concerns in the privatization decision in order to promote the local governments to withdraw their SOEs from the fields that lack competitive advantages. Using a sample of listed local SOEs in the Chinese A-share market from 2004 to 2017, our paper investigates the influence of financial deleveraging on privatization of local SOEs in China. Our results show that the probability of privatization of local SOEs increases significantly in financial deleveraging years, and the lower the financial leverage ratio, the greater is the possibility of privatization of local SOEs. Therefore, our paper is consistent with the notion that privatization is influenced by environmental factors. In addition, financial deleveraging has heterogeneous effects on privatization across firms. Specifically, the local SOEs with less tax contribution, fewer employees, and that cause greater financial burden to the local governments are more likely to be privatized during JOURNAL OF APPLIED ECONOMICS 17 financial deleveraging, suggesting that stabilizing tax revenue, minimizing unemployment and reducing financial burden are important concerns of local governments in the privatization decision. Our results have two important implications. First, previous literature has explored the impact of environmental factors——such as intensified market competition, tax sharing and banking reform and interregional competition——on Chinese privatization. Consistent with these literatures, we find that macro environment is an important factor affecting the privatization of Chinese local SOEs from the perspective of financial deleveraging. As a result, the willingness of the Chinese local governments to privatize varies in different macro-environments, and the researchers should not only focus on the local government motivations of privatization but also the environmental factors that affect the local government motivations of privatization when they study the causes of Chinese privatization in the future. Second, the Chinese central government can force their local governments to withdraw from fields that lack competitive advantages through appropriate macro policies, and hence promote the reform of local SOEs. However, our results indicate that the Chinese local governments may selectively retain large SOEs that contribute a lot to taxation but are inefficient or even suffer heavy losses to obtain fiscal and political benefit. Therefore, in order to promote more efficient privatization, the Chinese central government should also deepen reform of the fiscal and taxation systems and formulate measures to compensate for the losses caused by efficient privatization to local governments. Acknowledgments The views expressed herein are the authors’ own and do not necessarily reflect those of Wuhan University. In addition, no potential conflict of interest was reported by the authors. Disclosure statement No potential conflict of interest was reported by the author(s). Funding This paper was supported by the National Natural Science Foundation of China (No.71803146), Humanities and Social Sciences Research Project of the Ministry of Education of China (No. 19YJA630093), and the Fundamental Research Funds for the Central Universities in Wuhan University (No. 2019IVB004) Notes on contributors Weiwei Yang is a lecturer in the School of Business and Tourism Management at Yunnan University, China. Her research interests include corporate governance, capital market accounting, and effects of macroeconomic policies on firm behavior. Her works appear in journals including Annals of Economics and Finance, Emerging Markets Finance and Trade. He Wang is a senior economist. He has engaged in financial market related work at China Construction Bank from July 2013 to October 2022. At present, he engages in public utility related work at the Geriatrics Hospital of Yunnan Province. His research interests include financial 18 W. YANG ET AL. intermediation, and Chinese economy. His works appear in the Chinese journals including Chinese Public Administration, China Rural Survey. Huobao Xie is a professor in the Economics and Management School at Wuhan University, China. His research interests include corporate governance, capital market accounting, and Chinese economy. 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