Economic policy uncertainty, the dynamic adjustment of enterprises’ capital structure and stabilizing leverage

WANG Chaoyang1 ZHANG Xuelan2 BAO Huina3

(1.National Academy of Economic Strategy, CASS)
(2.School of Finance, Zhongnan University of Economics and Law)
(3.China Nonferrous Metals Techno-Economic Research Institute)

【Abstract】The essence of stabilizing leverage is the dynamic adjustment process of capital structure. Starting from the financing demand and supply, which is critical to the capital structure dynamic adjustment, this paper establishes a logical framework to interpret the effect of economic policy uncertainty on the dynamic adjustment of enterprise capital structure through the uncertainty avoidance of both enterprises and financial intermediaries, and then empirically tested with the data of the manufacturing industry in the China Industrial Enterprise Database from1998 to 2013. Results show that economic policy uncertainty hinders the dynamic adjustment of capital structure through uncertainty avoidance; with the increase of economic policy uncertainty, in order to deal effectively with the decreasing income and increasing cost of capital structure adjustment, enterprises become more cautious in making investment decisions, and the financial intermediaries represented by banks would reduce the availability of financing by credit rationing, which ultimately leads to a slowdown in capital structure adjustment; moreover, the difference in sensitivity of policy changes in different industries does affect the capital structure dynamic adjustment of enterprises within the industry. This indicates that stable policy expectations are a prerequisite for stabilizing leverage. Therefore, under the new situation, in order to enterprisely promote the stabilizing leverage and reduce the friction of the dynamic adjustment of enterprise capital structure, we should not rely solely on monetary and financial policies, but should also focus on stabilizing market expectations in terms of the key points affecting enterprises’ confidence in long-term investment and financial intermediary financing, grasping the impact of macroeconomic policy adjustments and their overlap on enterprises of different industries to improve policy orientation, as well as strengthening the forward-looking, consistency and stability of policies.

【Keywords】 economic policy uncertainty; uncertainty avoidance; capital structure; adjustment speed;

【DOI】

【Funds】 The National Social Science Fund of China (15BJY161) The National Social Science Fund of China (14AJY026)

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    Footnote

    [1]. ① Take Tangshan iron and steel production restriction policy from July to August 2018 as an example. At the end of July, a document was issued demanding that the blast furnace production of the steel plant be restricted by 30% until the end of August. On August 10, a document was issued demanding that the production limit be increased from 30% to 50%. On August 17, it issued a document requesting that it should not be recovered at the end of August. In September, most of Tangshan’s steel mills would no longer be restricted and some would resume production. In just over a month, the policy of restricting production was adjusted four times. With each adjustment of the policy, the prices of steel futures and spot prices soared and plummeted. Enterprises were at a loss and did not dare to make long-term investments. See the survey on Tangshan iron and steel industry in Li, B. 经济能不能起来,就看能否破解这三大困局 (http://www.sohu.com/a/252143326_313480). [^Back]

    [2]. ① Tian and Lin (2016) used conditional Markov model to find that many peaks of the uncertainty sequence of economic policies correspond to the political and economic time points when a large number of economic policies are issued in China, proving that the index can capture the uncertainty of China’s economic policies to a large extent. [^Back]

    [3]. ② Since listed enterprises are all regulated equity financing, their capital structure cannot reflect the whole picture of domestic enterprises. The research on this subject based on this sample may have sample deviation. [^Back]

    [4]. ① For example, Ma (2010) pointed out that from the tax system reform in 1993 to 2010, China’s export tax rebate policy changed no less than dozens of times, resulting in enterprises investing in the production of certain products for export under the conditions of complete legality and compliance with the policy. However, due to the policy change, the products were listed as prohibited from export or restricted from export, leaving enterprises in a dilemma. According to the current market situation, the enterprise estimated and signed the export contract, which could have been profitable, but the change in the export tax rebate policy led to losses or made the contract impossible to perform. [^Back]

    [5]. ① The enterprise characteristic indicators represented by controli,there are panel data, and macroeconomic indicators are time series data. [^Back]

    [6]. ① The epu indicated by Ci,t here is time series data, and uoe and uof are panel data. [^Back]

    [7]. ① Some documents use two-step method to estimate the adjustment speed, which first calculate the enterprise’s optimal leverage ratio level, and then use the fitting value of the optimal leverage ratio level to estimate the adjustment speed of capital structure. This two-step method will not only cause large deviation of adjustment speed due to the low fitting degree of target capital structure, but also fail to consider the interaction between capital structure determining factors and adjustment factors (Huang, 2010), which may lead to variable error bias. [^Back]

    [8]. ② When Mi,t is enterprise uncertainty avoidance (uoe), the control variables are enterprise characteristic variables and the data form is panel data. When Mi,t is financial intermediary uncertainty avoidance, the control variables are macro variables and the data form is time series data. [^Back]

    [9]. ① For the regression results, please refer to the public annex of the website of China Industrial Economics (中国工业经济) (http://www.ciejournal.org). [^Back]

    [10]. ② In order to avoid multicollinearity, the correlation coefficient and variance expansion factor of independent and control variables are calculated. The results show that the correlation coefficients of almost all variables are relatively small. Even if there are some large correlation coefficients, the variance expansion factor is far less than 10, which basically can eliminate the influence of multicollinearity. For the results of descriptive statistics, correlation coefficient and variance expansion factor, please refer to the public annex of the website of China Industrial Economics (中国工业经济) (http://www.ciejournal.org). [^Back]

    [11]. ① For the test results and fitting results of this part, please refer to the public annex of the website of China Industrial Economics (中国工业经济) (http://www.ciejournal.org). [^Back]

    [12]. ② At the same time, this paper also considers that the model needs to control the annual effect and the industry effect, but there will be serious multicollinearity after adding the annual and industry dummy variables, because the macroeconomic data money supply (lnM2) and entrepreneur confidence index (eei) in this paper have the same values in each year, and adding these two variables in the fitting is equivalent to controlling the annual effect at the same time. Similarly, the median industry leverage (medlev) has the same value for each industry every year. Adding this variable is equivalent to controlling the industry effect at the same time. Therefore, the annual effect and industry effect in the existing model in this paper are controlled. [^Back]

    [13]. ① Since the financial intermediary uncertainty avoidance index is based on macro level, macro variables are selected as the control variables here. [^Back]

    [14]. ① Results of robustness test are omitted. Please refer to the public annex of the website of China Industrial Economics (中国工业经济). [^Back]

    References

    [1] An, N. & Zhong, B. Economic Information Daily (经济参考报), (2015-05-18).

    [2] Chen, D., Fan, R. & Tang, X. Journal of Shanxi University of Finance & Economics (山西财经大学学报), (5): 11–21 (2014).

    [3] Chen, G. & Wang, S. Finance & Trade Economics (财贸经济), (5): 5–21 (2016).

    [4] Chen, L. & Xu, P. 中银国际证券股份有限公司研究报告, (2018).

    [5] Gan, X. Social Scientist (社会科学家), (5): 61–66 (2014).

    [6] Gong, P. & Zhang, Z. Management Review (管理评论), (9): 11–21 (2014).

    [7] Gu, Y. & Zhou, Q. The Journal of World Economy (世界经济), (6): 102–126 (2018).

    [8] Huang, H. Economic Science (经济科学), (3): 96–106 (2010).

    [9] Huang, Y. http://news.hexun.com/2016-07-13/184911461.html

    [10] Jiang, F., Qu, Y., Lu, Z. et al. Economic Research Journal (经济研究), (4): 99–110 (2008).

    [11] Lian, J. People’s Daily (人民日报), (2017-03-29).

    [12] Ma, Y. China Customs (中国海关), (9): 161–161 (2010).

    [13] Rao, P. & Yue, H. The Journal of World Economy (世界经济), (2): 27–51 (2017).

    [14] People’s Daily. People’s Daily (人民日报), (2016-09-12).

    [15] Tan, X. & Zhang, W. The Journal of World Economy (世界经济), (12): 3–26 (2017).

    [16] Tian, L. & Lin, J. Nankai Economic Studies (南开经济研究) (2): 3–24 (2016).

    [17] Wang, G. Economic Perspectives (经济学动态), (7): 16–25 (2017).

    [18] Wu, Z., Zhang, Y. & Zhang, W. Accounting Research (会计研究), (3): 51–58 (2013).

    [19] Wen, Z. & Ye, B. Advances in Psychological Science (心理科学进展), (5): 731–745 (2014).

    [20] Xu, Z., Wu, Q., Ouyang, J. et al. People’s Daily (人民日报), (2016-08-29).

    [21] Xu, Z. Journal of Financial Research (金融研究), (1): 1–14 (2017).

    [22] Yu, M., Fan, R. & Zhong, H. China Industrial Economics (中国工业经济), (12): 5–22 (2016).

    [23] Zhang, T., Xie, C. & Gao, F. Journal of Financial Research (金融研究), (12): 179–185 (2007).

    [24] Zhang, X., Chang, X. & Liu, L. The Economic Observer (经济观察报), (2017-11-04).

    [25] Chinese Entrepreneurs Survey System. Management World (管理世界), (12): 55–67 (2016).

    [26] Aisen, A., and F. J. Veiga. How does Political Instability Affect Economic Growth. European Journal of Political Economy, 2013, 29 (568): 151–167.

    [27] Akey, P., and S. Lewellen. Policy Uncertainty, Political Capital, and Firm Risk-Taking. Working Paper, University of Toronto and London Business School, 2016.

    [28] Alessandri, P., and M. Bottero. Bank Lending in Uncertain Times. Banca D’Italia Working Paper 1109, April, 2017.

    [29] Baker, S. R., N. Bloom, and S. J. Davis. Measuring Economic Policy Uncertainty. Center for Economic Performance Discussion Paper, London School of Economics and Political Science, 2013.

    [30] Bloom, N. The Impact of Uncertainty Shocks. Econometrica, 2009, 77 (3): 623–685.

    [31] Bloom N., S. Bond, and J. V. Reenen. Uncertainty and Investment Dynamics. Review of Economic Studies, 2007, 74 (2): 391–415.

    [32] Bonciani, D., and B. von Roye. Uncertainty Shocks, Banking Frictions and Economic Activity. Journal of Economic Dynamics and Control, 2016, (73): 200–219.

    [33] Bordo, M. D., J. V. Duca, and C. Koch. Economic Policy Uncertainty and the Credit Channel: Aggregate and Bank Level U.S. Evidence over Several Decades. Journal of Financial Stability, 2016, (26): 90–106.

    [34] Bradley, D., C. Pantzalis, and X. Yuan. Policy Risk, Corporate Political Strategies, and the Cost of Debt. Journal of Corporate Finance, 2016, (40): 254–275.

    [35] Cesa-Bianchi, A., and E. Fernandezcorugedo. Uncertainty in a Model with Credit Friction. Bank of England Working Papers, 2014.

    [36] Cook, D. O., and T. Tang. Macroeconomic Conditions and Adjustment speed of capital structure. Journal of Corporate Finance, 2010, 16 (1): 73–87.

    [37] Drobetz W., and G. Wanzenried. What Determines the Speed of Adjustment to the Target Capital Structure. Applied Financial Economics, 2006, 16 (13): 941–958.

    [38] Flannery, M. J., and K. P. Rangan. Partial Adjustment Toward Target Capital Structures. Journal of Financial Economics, 2006, 79 (3): 469–506.

    [39] Francis, B. B., I. Hasan, and Y. Zhu. Political Uncertainty and Bank Loan Contracting. Journal of Empirical Finance, 2014, (29): 281–286.

    [40] Frijns, B., A. Gilbert, T. Lehnert, and A. Tourani-Rad. Uncertainty avoidance, Risk Tolerance and Corporate Takeover Decisions. Journal of Banking and Finance, 2013, 37 (7): 2457–2471.

    [41] Ganley, J., and C. Salmon. The Industrial Impact of Monetary Policy Shocks: Some Styled Facts. Bank of England Working Papers, 1997.

    [42] Georgopoulos, G., and W. Hejazi. Financial Structure and the Heterogeneous Impact of Monetary Policy across Industries. Journal of Economics and Business, 2009, 61 (1): 0–33.

    [43] Graham J. R., and C. R. Harvey. Expectations of Equity Risk Premia, Volatility and Asymmetry from a Corporate Finance Perspective. NBER Working Paper, 2001.

    [44] Gulen, H., and M. Ion. Editor’s Choice: Policy Uncertainty and Corporate Investment. Review of Financial Studies, 2015, 29 (3): 523–564.

    [45] Harford, J., S. Klasa, and N. Walcott. Do Firms Have Leverage Targets? Evidence from Acquisitions. Journal of Financial Economics, 2009, 93 (1): 1–14.

    [46] Hofstede, G. Culture and Organizations. International Studies of Management and Organization, 1980, 10 (4): 15–41.

    [47] Huang, R., and J. R. Ritter. Testing Theories of Capital Structure and Estimating the Speed of Adjustment. Journal of Financial and Quantitative Analysis, 2009, 44 (2): 237–271.

    [48] Ilut, C. L., and M. Schneider. Ambiguous Business Cycles. American Economic Review, 2014, 104 (8): 2368–2399.

    [49] Jens, C. E. Political Uncertainty and Investment: Causal Evidence from U.S. Gubernatorial Elections. Journal of Financial Economics, 2017, 124 (3): 563–579.

    [50] Kim, H., and H. Kung. The Asset Redeployability Channel: How Uncertainty Affects Corporate Investment. Review of Financial Studies, 2017, 30 (1) :245–280.

    [51] McMullen J. S., and A. S. Kier. Trapped by the Entrepreneurial Mindset: Opportunity Seeking and Escalation of Commitment in the Mount Everest Disaster. Journal of Business Venturing, 2016, 31 (6): 663–686.

    [52] Pástor L., and P. Veronesi. Political Uncertainty and Risk Premia. Journal of Financial Economics, 2013, 110 (3): 520–545.

    [53] Popp, A., and F. Zhang. The Macroeconomic Effects of Uncertainty Shocks: The Role of the Financial Channel. Journal of Economic Dynamics and Control, 2016, (69): 319–349.

    [54] Pricewaterhouse Coopers. 2013 U.S. CEO Survey: Creating Value in Uncertain Times. Pricewaterhouse Coopers 16th Annual Global CEO Survey, 2013.

    [55] Quagliariello, M. Macroeconomic Uncertainty and Banks’ Lending Decisions: The Case of Italy. Applied Economics, 2009, 41 (3): 323–336.

    [56] Ramirez A., and S. Tadesse. Corporate Cash Holdings, Uncertainty Avoidance, and the Multinationality of Firms. International Business Review, 2009, 18 (4): 387–403.

    [57] Stokey, N. L. The Economics of Inaction: Stochastic Control Models with Fixed Costs. New Jersey: Princeton University Press, 2008.

    [58] Talavera, O., A. Tsapin, and O. Zholud. Macroeconomic Uncertainty and Bank Lending: The Case of Ukraine. Economic Systems, 2012, 36 (2): 279–293.

    [59] Zhang, G., J. Han, and Z. Pan, H. Huang. Economic Policy Uncertainty and Capital Structure Choice: Evidence from China. Economic Systems, 2015, 39 (3): 439–457.

This Article

ISSN:1006-480X

CN: 11-3536/F

Vol , No. 12, Pages 134-151

December 2018

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Article Outline

Abstract

  • 1 Introduction
  • 2 Logical mechanism and research hypotheses
  • 3 Research design
  • 4 Empirical process and result analysis
  • 5 Conclusion and enlightenment
  • Footnote

    References