Does the audit quality affect the financing efficiency of photovoltaic enterprises? Evidence from listed companies in China

Figures & data

Table 1. Summary of audit quality research status.

Research contents	Focus
Influence factor	auditor independence (Olivia Furiady and Kurnia 2015), abnormal audit fees (Jung, Kim, and Chung 2016), firm size (Kim et al. 2017), auditor professionalism (Salehi, Fakhri Mahmoudi, and Daemi Gah 2019), auditor experience (Haeridistia and Agustin 2019), auditor motivation and objectivity (Zahmatkesh and Rezazadeh 2017), firm transparency (Johl et al. 2021) and the internal governance level of listed companies (Aiqadasi and Abidin 2018)
Economic consequences	investment efficiency (Boubaker et al. 2018), Internal governance level of the company (Beisland, Mersland, and Str?m 2015), Earnings management (Lin, Wan, and Chen 2019) and market value (Shubita 2021)
The relationship between audit quality and financing efficiency	The influence of audit quality on enterprise value (Taqi 2013), Debt financing costs (Coffie, Bedi, and Amidu 2018) and Equity financing cost (Luo, Peng, and Chen 2020)

Table 2. Analysis table of research status in China and other countries.

Content	Scholar	Focus point	Research depth
Current Situation of Financing of Photovoltaic Enterprises	Kabir et al. (2018), Feldman, Jones-Albertus, and Margolis (2020) and Zhao and Wang (2019)	Enterprise development status and financing problems	Study the challenges facing the Photovoltaic enterprise: technological uncertainty, low energy efficiency, high input costs, lack of financing mechanisms
Audit quality	Shubita (2021), Feldman, Jones-Albertus, and Margolis (2020) and Lin, Wan, and Chen (2019)	Audit Quality Influencing Factors, Measurement Methods, and Economic Consequences	The influencing factors extend from the auditor’s characteristic factor to the audited entity’s characteristic factor. The economic consequences continue to extend, focusing on the research on the value and earnings management of listed companies
Research on the relationship between audit quality and financing issues	Chen, Saffar, and Srinidhi (2017), Zijl, Ahmed, and van Zijl (2017) and Luo, Peng, and Chen (2020)	The impact of audit quality on different financing methods	Focus on the impact of audit quality on different financing methods. The research is continuously refined, focusing on the impact of the content of the audit report on the cost of capital of enterprises

Table 3. Descriptive statistical results.

Variable	N	Mean	Std. Dev.	Min	Max	P50
Re	540	0.37797	0.354853	0	1	0.252
Ae	540	0.57139	0.37665	0	1	0.587
Fe	540	0.47468	0.24509	0.0065	1	0.5
Da	540	−0.07699	0.08107	−0.66534	−0.00017	−0.05533
Fee	540	0.08858	0.07388	0.01374	0.75305	0.06887
Cs	540	22.54455	1.12785	20.09005	25.46001	22.4424
Lev	540	0.49402	0.21922	0.05159	2.86104	0.50569
Fc	540	0.03077	0.08166	−0.6563	1.00803	0.036222
Eg	540	0.34914	3.05891	−0.94661	58.84163	0.10353
Ep	540	0.03286	0.11381	−1.89476	0.91260	0.03996
At	540	0.52973	0.33882	0.01916	2.97077	0.49982
Fs	540	22.57609	0.98493	0.35066	23.5772	22.58041

Figure 1. Correlation coefficients.

Figure 2. Regression results of audit quality and photovoltaic enterprises’ fund-raising efficiency.

Table 4. Regression results of audit quality and photovoltaic enterprises’ fund-raising efficiency.

Variable	Coef.	Std. Err.	t	P>|t|
Da	0.17487**	0.07128	2.45	0.014
Cs	−0.04386***	0.00549	−7.98	0.000
Lev	−0.09589***	0.03202	−2.99	0.003
Fc	−0.08836	0.06988	−1.26	0.207
Eg	0.00529***	0.00181	2.92	0.004
Ep	−0.067	0.05653	−1.19	0.237
−cons	1.888951***	0.11889	15.89	0.000
YEAR	Control 540 22.03 0.1897
N
F value
Adj R^2

* p < .1, ** p < .05, *** p < .01 represent significance levels.

Figure 3. Regression results of audit quality and photovoltaic enterprises’ fund allocation efficiency.

Table 5. Regression results of audit quality and photovoltaic enterprises’ fund allocation efficiency.

Variable	Coef.	Std. Err.	t	P>|t|
Da	0.45471**	0.20391	2.23	0.026
Cs	−0.06759***	0.01707	−3.96	0.000
Lev	0.030339***	0.01095	2.77	0.006
At	0.150311***	0.0465	3.23	0.001
Eg	−0.00847*	0.00507	−1.67	0.095
Ep	−0.00256	0.01995	−0.13	0.898
Fs	0.00412	0.01570	0.26	0.793
−cons	1.905163***	0.54320	3.51	0.000
YEAR	Control 540 3.99 0.2846
N
F value
Adj R^2

* p < .1, ** p < .05, *** p < .01 represent significance levels.

Figure 4. Regression results of audit quality and financing efficiency of the photovoltaic enterprises.

Table 6. Regression results of audit quality and financing efficiency of the photovoltaic enterprises.

Variable	Coef.	Std. Err.	t	P>|t|
Da	0.1317**	0.06007	2.19	0.028
Cs	−0.08769***	0.00555	−15.78	0.000
Lev	0.003877	0.00336	1.15	0.25
At	0.045049***	0.01620	2.78	0.005
Eg	0.005272***	0.00139	3.79	0.000
Ep	0.039197	0.0389	1.01	0.314
−cons	2.763101***	0.13083	21.12	0.000
YEAR	Control 540 126.84 0.5835
N
F value
Adj R^2

* p < .1, ** p < .05, *** p < .01 represent significance levels.

Table 7. Test results of the intermediary effect of agency cost.

Variable	Fe	Fee	Fe
Da	0.1317** （2.19）	−0.0796*** （-2.78）	0.249191** （2.16）
Fee			−0.34356** （-2.25）
Cs	−0.08769*** （-15.78）	−0.0347*** （-6.68）	−0.06556*** （-6.71）
Le	0.003877 （1.15）	0.028903 （1.64）	0.045829*** （7.27）
At	0.045049*** （2.78）	−0.08051*** （-7.64）	0.05675* （1.95）
Eg	0.005272*** （3.79）	−0.0008 （-1.16）	0.004741 （1.62）
Ep	0.039197 （1.01）	−0.01986*** （-4.19）	−0.081 （-0.94）
−cons	2.763101*** （21.12）	0.882593*** （7.63）	1.764411*** （7.56）
N	540
Adj R^2	0.5835	0.4055	0.3080

* p < .1, ** p < .05, *** p < .01 represent significance levels.

Figure 5. Test results of the intermediary effect of agency cost.

Table 8. Robust regression results of audit quality and photovoltaic enterprises’ fund-raising efficiency.

Variable	Coef.	Std. Err.	t	P>|t|
Da	0.176592***	0.061031	2.89	0.004
Cs	−0.044287***	0.005486	−8.07	0.000
Le	−0.096624***	0.031725	−3.05	0.002
Fc	−0.081251	0.069796	−1.16	0.245
Eg	0.005424***	0.001811	2.99	0.003
Ep	−0.158424**	0.065908	−2.40	0.017
−cons	1.900391***	0.118671	16.01	0.000
N	540
R^2	0.2022
Adj R^2	0.1932

* p < .1, ** p < .05, *** p < .01 represent significance levels.

Table 9. Robust regression results of audit quality and photovoltaic enterprises’ fund allocation efficiency.

Variable	Coef.	Std. Err.	t	P>|t|
Da	0.003178**	0.001579	2.09	0.037
Cs	−0.175373***	0.006491	−27.02	0.000
Le	−0.000369	0.004471	−0.08	0.934
At	0.125187***	0.018364	6.82	0.000
Eg	0.000776***	0.000237	3.28	0.001
Ep	0.079291***	0.010741	7.38	0.000
Fs	−0.009575	0.006157	−1.56	0.121
−cons	4.809313***	0.200544	23.98	0.000
N	540
R^2	0.6666
Adj R^2	0.6622

* p < .1, ** p < .05, *** p < .01 represent significance levels.

Table 10. Robust regression results of audit quality and financing efficiency of the photovoltaic enterprises.

Variable	Coef.	Std. Err.	t	P>|t|
Da	0.007350***	0.001933	3.80	0.000
Cs	−0.115064***	0.004654	−24.72	0.000
Le	0.004007	0.003200	1.25	0.211
At	0.04597***	0.013171	3.49	0.001
Eg	0.000546***	0.00017	3.21	0.001
Ep	0.046366***	0.007698	6.02	0.000
−cons	3.262422***	0.106988	30.49	0.000
N	540
R^2	0.6140
Adj R^2	0.6097

* p < .1, ** p < .05, *** p < .01 represent significance levels.

Table 11. Robustness test results of the intermediary effect of agency cost (a).

	Coef.	Std. Err.	z	P>|z|	[95% Conf.Interval]
_bs_1 (r (ind eff))	0.000057	0.000170	0.34	0.736	−0.000276—0.000390
_bs_2 (r (dir eff))	0.006777	0.001196	5.72	0.000	0.004454—0.009101

Table

Indicator’s category	The index name	code	Indicators show
Explained variable	Fundraising efficiency	Re	Calculation using DEA
	Capital allocation efficiency	Ae	Calculation using DEA
	The financing efficiency	Fe	The arithmetic average of the efficiency of raising funds and the efficiency of allocating funds
Explanatory variables	Audit quality	Da	Using the Jones model, the result is negative
Intervening variable	Agency costs	Fee	Expressed using overhead/operating income ratio
Control variables	The cost of financing	Fc	Calculation using WACC
	Financing scale	Fs	Net cash inflow from financing activities
	profitability	Ep	In terms of return on assets
	The capital structure	Lev	It’s the asset-liability ratio
	Capital utilization capacity	At	In terms of asset turnover
	The enterprise scale	Cs	In terms of the logarithm of enterprise assets
	Enterprise growth	Eg	Expressed by the growth rate of operating income

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