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By using the panel data of quoted company during 2005-2014 and the PVAR model, this paper aims to empirically examine the dynamic and interacting relationships among Debt, Growth of company, PB of company’s stock, the Effective income tax rate. The pvar model can estimate the dynamic relationship of all endogenous variables, and the empirical results show that the Growth, PB and ETR are the critical factors of Debt; The PB’s ability to explain changes in the capital structure has grown stronger over time, and “invalid periods” may occur in the short term. Enterprise Growth and Effective income tax rates both have positive effects in the short term. At the early stage, the enterprises show the debt financing preferences. With the expansion of the scale, the enterprises slowly show the equity financing preferences.

With the development of China’s financial securities market, especially the establishment of small and medium-sized boards and the GEM, more small and medium-sized companies have entered the capital market. Therefore, it is very necessary to analyze the debt financing structure of Chinese enterprises at this time. Debt financing is a corporate financial structure and performance of a very important aspect, MM theory, trade-off theory, agency theory and the pecking order theory is debt leverage of debt financing in different areas, tax shield benefit aspects, corporate finance costs of research.

For the debt financing and debt structure, the most important study on the classical capital structure theory, namely the MM theory proposed by American Modigliani and Miller [

As can be seen in previous studies, the research methods are mostly biased towards static one-way research, and there is no clear relationship between the two variables. Therefore, this paper mainly adopts the selection of China’s Shanghai and Shenzhen Stock Exchanges. The relevant data of the home manufacturing A-shares were constructed by constructing panel VAR model, impulse response analysis and variance decomposition method to study the relationship between variables.

When studying the corporate financing structure, the debt ratio (the ratio of liabilities to total assets) is used to represent the financing structure of the enterprise. In order to receive better regression effects, the scope of the model is also improved. The original data is divided into six groups of data with large meanings according to the meaning of the data (shown in

This paper uses the panel VAR model to estimate the dynamic interaction of each sample financing structure and various aspects of its economic activities. Method VAR panel presented by Holtz-Eakin (1988), this method can VAR time series of the panel data advantages binding, not only has the advantages of dynamic analysis of time series, but also through the panel data to resolve the heterogeneity between individuals. Similar to the general VAR model, in this model, all the variables involved are regarded as endogenous variables, and the regression relationship between the variables is obtained through the panel GMM estimation; then an endogenous variable is separated by the impulse response function. other endogenous variables to impact caused by the influence of a period; Finally, the use of the variance of the error term decomposition, to give each of the factors on the panel VAR model relative influence of each of the variables in size.

Based on the panel data, this paper sets up the third-order PVAR equation:

y t = α + β 1 y t − 1 + ⋯ + β n y t − n + Η x t + ε t t = 1 , 2 , 3

y t represents growth (Growth), PB, the effective income tax rate (Effective Tax Rate, referred ETR) and gearing (Debt/Asset, referred Debt Total). It is assumed that the random disturbance term ε_{t} obeys a normal distribution.

Descriptive statistics of variables are shown in

With a minimum of −996.5313, a maximum of 1671.184, an average of 2.169506, the largest is Magic Pharmaceutical (2006), and the smallest is Gong Shenbei (2006); the average price-to-book ratio is 3.747, the largest is 94.0304, which is Huasu Holdings (2014), the smallest is −290.0477, which is Huasu Holdings (2010). It’s book value appear relatively large in volatility, through access to relevant information, found that the company starting in 2006, continued to receive delisting police report, until 2014, the implementation of the split share reform program, The company was re-entered on the right track; the effective income tax rate was 220.3927, the minimum was −2.972461, the relative difference in debt ratio was small, the maximum was 1.47, which belonged to Huasu Holdings (2012); the minimum value was 0.044, which belonged to Shenzhou High Speed Rail (2011). The difference in debt ratio comes from both business operations and industry differences.

Conducting face plate before the VAR model estimation, we need to examine whether the samples to smooth the panel, so as to ensure that the model estimates are accurate and impulse response function and variance decomposition analysis of stability. This paper completes the panel unit root test by LLC criteria and Fisher-ADF test. The results show that (

In the study of the time series while, if the variable contains x1, x2 at the last condition information, the variable x2 predicted effect than solely by x2 past information x2 predicted effect of better. As long as the variables x1 explanatory

groups | variable | method of obtaining |
---|---|---|

First group | Tangible asset rate | Tangible assets/total assets |

Current asset ratio | Current assets/total assets | |

Operating cash flow ratio | Operating cash flow/total assets | |

Second Group | Growth | Total operating income for the previous year/total operating income for the current year |

Enterprise Scale Assets (LN) | Take the natural logarithm of the total assets of the enterprise | |

The shareholding ratio of the largest shareholder | The largest shareholder’s shareholding value/total corporate capital | |

The third group | Accounts receivable turnover | Business operating income/average balance of accounts receivable |

Current asset turnover | Business operating income/average balance of current assets | |

Total asset turnover | Business operating income/average balance of total assets | |

Fourth group | Return on equity (ROE) | After-tax profit/owner’s equity |

Operating profit margin | Marginal profit/sales revenue | |

Operating asset return | After-tax profit/total assets | |

Fifth group | Dividend payout ratio | Dividend per share/net income per share |

P/B ratio | Stock price/net assets per share | |

The sixth group | Income tax effective tax rate | Total tax paid divided by taxable income |

Non-debt tax shield (LN) | Depreciation of fixed assets, amortization of intangible assets and amortization of long-term deferred expenses |

variables x2 future changes helpful then the variable x1 is caused by the variable x2 Granger reasons. Through the Granger test, the causal relationship between variables can be inferred.

In this paper, some cross-section data were randomly selected, and the Granger causality test was carried out for the four key variables included in this paper. Since the Granger causality test is only for partial cross-section data, the data for a single cross-section cannot represent the nature of the entire panel data. After data analysis, it was found that each variable showed a dependent variable for other variables in different cross-section samples:

According to the previous unit root test results (

variable | observations | average value | Standard deviation | Minimum value | Maximum |
---|---|---|---|---|---|

Growth | 750 | 2.169506 | 75.72267 | −996.5313 | 1671.184 |

PB | 750 | 3.746762 | 12.88728 | −290.0477 | 94.0304 |

ETR | 750 | 0.4896696 | 8.046966 | −2.972461 | 220.3927 |

Debt | 750 | 0.504091 | 0.1930965 | 0.0437055 | 1.469336 |

Data Sources: Wind database.

LLC test | Fisher-ADF test | |||
---|---|---|---|---|

Statistics | p-value | Statistics | p-value | |

Growth | −251.926 | 0.0000 | 522.352 | 0.0000 |

PB | −19.9687 | 0.0000 | 366.341 | 0.0000 |

ETR | −70.3577 | 0.0000 | 402.649 | 0.0000 |

Debt | −9.66832 | 0.0000 | 225.642 | 0.0001 |

Chi-square statistic | Independent variable | ||||
---|---|---|---|---|---|

growth | PB | ETR | Debt | ||

Dependent variable | growth | 8.71*** | 9.88*** | 5.25*** | |

PB | 0.17 | 0.09*** | 0.01*** | ||

ETR | 1.22 | 3.97*** | 0 | ||

Debt | 8.42*** | 0.18 | 0.28 |

relationship between the results shown in the following

According to the estimation results in

h_Grouth | ||||
---|---|---|---|---|

β | Se | t | ||

L.h_Growth | 0.01808502 | 0.02249688 | 0.80388986 | |

L.h_PB | −0.04555587 | 0.04155192 | −1.0963601 | |

L2.h_ETR | 0.02204854 | 0.01386053 | 1.5907434* | |

h_PB | ||||

β | Se | t | ||

L.h_Growth | 0.00719002 | 0.0127164 | 0.56541302 | |

L.h_PB | 0.49585893 | 0.33741845 | 1.4695668* | |

L2.h_ETR | −0.01361687 | 0.00776021 | −1.7547033** | |

h_Debt | ||||

β | Se | t | ||

L.h_Growth | −0.00034601 | 0.000129 | −2.6821906*** | |

L.h_ETR | −0.00060461 | 0.00014408 | −4.1964994*** | |

L.h_Debt | 0.72094056 | 0.184597 | 3.9054836*** | |

L2.h_Growth | −0.00007161 | 0.00002051 | −3.4913674*** | |

L2.h_PB | −0.00134341 | 0.00016001 | −8.3959867*** | |

L2.h_ETR | 0.00010335 | 0.00002938 | 3.5177591*** | |

L3.h_PB | 0.00144887 | 0.00031559 | 4.5910384*** | |

L3.h_Debt | 0.02901699 | 0.05185795 | 0.55954755 |

its good reputation to obtain more debt financing. Over time, companies will use equity financing to replace debt financing in order to protect their good reputation; the effective tax rate of income tax lags behind the impact of the debt ratio is negative, and the lag of the second period is positive. This shows that enterprises will raise debts in the early stage of raising the income tax rate to form a tax shield. In the later stage of the increase in the income tax rate, the company may have a positive expectation of the tax rate, and this behavior will be weakened.

The impulse response function can measure the current and future effects of other variables generated by the variation of a standard deviation of the random disturbance term, and visually display the dynamic interaction between the variables, and obtain the empirical basis for determining the time-lag relationship between the variables.

The orthogonal impulse response function is used in this paper. The figure below shows the results of the impulse response function obtained by simulating 500 times based on the Monte Carlo method and the 95% confidence interval.

In the previous 0.5, Growth has a positive effect and quickly decreases to 0. In about 0.5 to 1.75, the Growth negative impact gradually reaches its maximum. Then, in the next three periods, it tends to 0 slowly, and in the long run, it will continue to have a small negative impact.

In order to more accurately describe business operations, shareholders’ equity, tax burden, financing structure interaction effects of the degree, this variance decomposition by this tool, it has been the contribution of the impact of different endogenous variables VAR equations fluctuations. ^{th}, 20^{th} and 30^{th} forecast periods.

Specifically, the financing structure is greatly affected by itself. The operating operations, shareholders’ equity, and tax burden contribute only about 10.5% to the variance contribution rate. The shareholder’s equity contribution to the variance is the largest of these three, and its share. The increase in the number of periods is still rising slightly.

This paper empirically analyzes the dynamic interaction effects of business operations, shareholders’ equity, tax burden, and financing structure. The results show that the impact of the P/B ratio, corporate growth rate and effective income tax rate on the capital structure of the enterprise is volatility. The impact of the P/B ratio on the capital structure may have an “invalid period” in the short term, and the response time is slow. However, the ability to explain changes in capital structure is becoming stronger and stronger in the later period; the growth rate of enterprises and the effective tax rate of income tax are positively affected in the short term and have a negative impact in the long run; the results of this paper reflect the development of enterprises in the process of enterprise development. Affected by the different nature of various aspects, the previous

Forecast period | Growth | PB | ETR | Debt | |
---|---|---|---|---|---|

Growth | 10 | 0.97772106 | 0.00203013 | 0.000001577 | 0.02024724 |

PB | 0.0047664 | 0.75355919 | 0.00014472 | 0.24152969 | |

ETR | 0.00098225 | 0.00609369 | 0.94812238 | 0.04480168 | |

Debt | 0.0169173 | 0.07442304 | 0.00289172 | 0.90576793 | |

Growth | 20 | 0.97770955 | 0.00203503 | 0.000001581 | 0.02025384 |

PB | 0.00477605 | 0.7535896 | 0.0001447 | 0.24148965 | |

ETR | 0.00098243 | 0.00610963 | 0.94809458 | 0.04481336 | |

Debt | 0.01691692 | 0.07481215 | 0.00289032 | 0.9053806 | |

Growth | 30 | 0.97770955 | 0.00203503 | 0.000001581 | 0.02025384 |

PB | 0.00477606 | 0.75358956 | 0.0001447 | 0.24148968 | |

ETR | 0.00098243 | 0.00610964 | 0.94809457 | 0.04481336 | |

Debt | 0.01691693 | 0.07481229 | 0.00289032 | 0.90538047 |

period was the debt financing preference, and the equity financing preference gradually appeared as the scale of the enterprise expanded.

The reasons for the above phenomenon may be: First of all, from the modified MM theory, the trade-off theory, it can be known that with the increase of the proportion of corporate debt in total assets, the risks faced by enterprises will also rise and they will easily fall into financial crisis. At the same time, this will increase the cost of additional capital and reduce the value of the business. Therefore, the optimal capital structure of an enterprise should be related to the operating conditions of the enterprise, tax burden, and shareholders’ interests.

Secondly, for a company with a high P/B ratio, investors can get more shares of listed companies with lower investment when purchasing the company’s stock. Therefore, it can reflect the investment value of the stock and the market’s evaluation of the company’s asset quality through the P/B ratio. A higher price-to-book ratio can lead to greater investment demand, that is, the company can raise equity at the same or lower cost of capital. In the long run, the impact of the rising P/B ratio will have a negative impact on the corporate debt ratio and reduce the proportion of corporate debt financing. However, equity financing requires a certain amount of preparation and review, so at the beginning of the shock, there appeared an “invalid period”.

The authors declare no conflicts of interest regarding the publication of this paper.

Zhang, Z.W. and Wang, Z. (2019) The Determinants of Enterprise Capital Structure and Its Dynamic Influence. Journal of Service Science and Management, 12, 899-908. https://doi.org/10.4236/jssm.2019.127061