Toward an empirical investigation of the long-term debt and financing deficit nexus: evidence from Chinese-listed firms

ABSTRACT

As the literature has studied the financing method of Chinese-listed firms for a long time, but with inconclusive indications, this research thus adopts non-financial Chinese-listed firms’ data from 2003 to 2015 to investigate the relationship between long-term debt financing and financing deficit. We pay particular attention to three channels (ownership concentration, market timing, and state ownership) that potentially affect the adoption of long-term debt financing when there is a financing deficit. The empirical analysis documents a positive relationship between financing deficit and changes in the long-term debt ratio in our sampled firms for both static and dynamic panel models. Moreover, among the three channels we show that state ownership has the strongest positive impact on the adoption of long-term debt financing, followed by ownership concentration, while the weakest channel is the market timing’s negative effect. In general, our empirical analysis finds that the important external financing method of long-term debt is most likely to be impacted by the state ownership aspect.

KEYWORDS:

• Pecking order theory
• financing deficit
• long-term debt ratio
• Chinese-listed firms

JEL CLASSIFICATION:

• G32
• C23
• C33

Acknowledgments

The authors are grateful to the insightful comments from the Editor and the anonymous referees on the earlier draft of this article. These authors contributed equally to this study and share joint first authorship.

Data Availability Statement

Data are available from the authors upon request.

Disclosure statement

All authors declare that they have no conflicts of interest.

Ethical approval

This article does not contain any studies with human participants or animals performed by any of the authors.

Notes

¹ The trade-off theory forms one of the basic determinants of capital structure empirical testing, however, the static trade-off theory fails to consider multi-period capital structure adjustments (Fischer, Heinkel, and Zechner 1989). Various studies support the dynamic capital structure concept (Fama and French 2002; Flannery and Rangan 2006; Huang and Ritter 2009; Kayhan and Titman 2007; Leary and Roberts 2005; Qian, Tian, and Wrijanto 2009).

² The pecking order theory traces back to Donaldson (1961), who describes firms’ determinants of debt capacity. Stiglitz and Weiss (1981) propose credit rationing in the credit market because of the information asymmetry between bank and lenders. Myers and Majluf (1984) develop the pecking order theory based on the assumption of asymmetry information between a firm’s insiders and outside investors.

³ According to Shyam-Sunder and Myers (1999), there is no optimal debt ratio in the pecking order theory. The debt ratio changes under an imbalance of internal funds when firms desire to finance a real investment or to meet dividend commitments. Debt financing changes are driven by how much the firm needs external financing, and that the need for external funding is the amount the firm is currently lacking. This amount of external financing needed is described as a financing deficit. Therefore, after their IPO, firms have no incentive to issue equity unless in extreme circumstances. A financing deficit should have a unitary coefficient in the regression of change in firm leverage; i.e. β_po should be 1 or extremely close to 1. Shyam-Sunder and Myers (1999) conduct research on 157 U.S. companies from 1971 to 1989 using the pooled OLS econometric methodology. They justify a strong correlation result and fitness, where β_po = 0.85 and R2 = 0.86. It is difficult to discern any correlation equalling exact unity. Although this result may not be strictly correct in supporting the pecking order theory, it is a competitive theory challenging other mainstream empirical models on capital structure (Frank and Goyal 2003). Frank and Goyal (2003) subsequently use a larger cross-section of 768 firms and a longer time series from 1971 to 1998, finding that β_po equals 0.75 and R2 equals 0.71.

⁴ Several studies in the literature related to the marketing timing hypothesis are worth mentioning. Zavertiaeva and Nechaeva (2017) indicate that market timing has a greater effect on the capital structure of companies in developing countries. Baker and Wurgler (2002) state that market timing is the primary determinant of a firm’s capital structure since firms choose the most valuable financing methods based on market performance. Researchers have empirically tested the market timing theory using the external finance weighted average market-to-book ratio (EFWAMB) and historical market-to-book (MB) ratios to represent market timing effects, finding significant explanatory power to determine the capital structure. Ma and Rath (2006) discover that market timing significantly affects capital structure through new equity offerings in Chinese-listed firms. In this case, investors are generally more opportunistic to issue equity finance when MB is high, instead of doing so for investment requirements. Dudley (2012) likewise suggests that firms issue equity financing before debt when there are large investment projects. The interaction term with an investment dummy multiplied by financing deficit for explaining changes in leverage is positive, but smaller for firms without large investments. The interaction term between financing deficit and market-to-book ratio is also negative and significant, which shows that firms continuously time the market to issue equity financing for investments.

⁵ It is noted that those sectors frequently appearing with the lowest HHI are real estate (K), pharmaceutical manufacturing (C27), raw chemical materials and chemical products manufacturing (C26), software and information technology service (I65), and retail (F52). These industries, for nearly the entire research period, have low HHI, which suggests a low industry concentration with high competition between participants and higher earnings volatilities. In contrast, firms from the mining industry (B), automobile manufacturing (C36), telecommunications, radio and television and satellite transmission service (I63), and ecological protection and environmental governance (N77) espouse a high HHI, supporting that these industries are more concentrated and have greater monopolized features and higher profitability. Some researchers confirm a significant positive relationship between industry concentration and firm leverage ratios, indicating that higher competition and earning volatilities prevent firms from increasing debt financing (MacKay and Phillips 2005).