Research on influence of safety investment and technological innovation to economic benefits of extractive industry: threshold effect model

doi:10.16265/j.cnki.issn1003-3033.2022.08.1389

Abstract

Abstract:

In order to strengthen enterprise safety management, improve economic benefits and optimize the safety investment structure, based on the perspective of safety accounting, taking the listed enterprises of mining industry from 2012 to 2019 as samples, a multiple regression model was applied to analyze of the impact of safety investment and technological innovation on economic benefits of mining enterprises. Then, the panel threshold regression model was constructed with technological innovation as the threshold value to further explore the relationships among them. The results show that there is a significant positive correlation between safety investment and economic benefits of enterprises, and technological innovation has a significant positive role in promoting economic benefits of enterprises. With technological innovation as the threshold value, there is a single threshold effect on the impact of safety investment on economic benefits. On both sides of the threshold, technological innovation positively promotes the positive impact of safety investment on economic benefits of enterprises, but the promotion intensity on the left side of the threshold is significantly greater than that on the right side.

Key words: safety investment, technological innovation, extractive industry, economic benefits, threshold effect

SHI Gonglong, ZHANG Yaoyi, LI Hongxia, TIAN Shuicheng, WANG Qian. Research on influence of safety investment and technological innovation to economic benefits of extractive industry: threshold effect model[J]. China Safety Science Journal, 2022, 32(8): 9-15.

Figures/Tables 7

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变量类型	变量名称及符号	变量定义与说明
被解释变量	经济效益Y	总资产净利润率=净利润/总资产平均余额
解释变量	安全投入X₁	本期维简费和安全生产费减少额之和的自然对数值
解释变量	技术创新X₂	技术创新=研发费用/营业收入
控制变量	企业规模Z₁	年末总资产的自然对数值
	资本结构Z₂	资产负债率=负债总额/资产总额
	营运能力Z₃	总资产周转率=销售收入/资产平均总额
	发展能力Z₄	销售增长率=本年营业收入增长额/上年营业收入总额

变量	观测值	平均值	标准差	最小值	最大值
Y	480	0.034	0.091	-1.052	0.79
X₁	480	9.361	2.052	3.586	13.355
X₂	480	0.012	0.044	0.000	0.895
Z₁	480	14.224	1.699	6.906	19.426
Z₂	480	0.494	0.476	0.026	10.082
Z₃	480	0.644	0.472	0.100	3.34
Z₄	480	0.052	0.853	-0.01	18.192

变量	Y	X₁	X₂	Z₁	Z₂	Z₃	Z₄
Y	1	—	—	—	—	—	—
X₁	0.067^*	1	—	—	—	—	—
X₂	0.017^*	-0.070^*	1	—	—	—	—
Z₁	0.017	0.536^***	-0.092^**	1	—	—	—
Z₂	-0.622^***	0.138^***	-0.050	-0.066	1	—	—
Z₃	0.140^***	-0.012	-0.076^*	0.166^***	0.072	1	—
Z₄	0.025	0.001	-0.016	0.144^***	0.005	0.179^***	1

变量	模型1	模型2
X₁	0.007^**(2.269)	—
X₂	—	0.440^*(1.674)
Z₁	0.004(0.674)	-0.090^***(-3.043)
Z₂	-0.133^***(-20.456)	-0.327^***(-3.159)
Z₃	0.059^***(6.081)	0.214^**(1.973)
Z₄	-0.003(-0.798)	-0.022(-0.760)
常数项	-0.051(-0.653)	2.568^***(5.659)
企业固定效应	是	是
年份固定效应	是	是
样本量	480	480
R²	0.679	0.156

门槛变量	模型	F值	P值	临界值/%
门槛变量	模型	F值	P值	10	5	1
X₂	单一门槛	11.92	0.090 0	11.260 8	14.556 7	19.494 6
X₂	双门槛	10.25	0.183 3	12.760 4	16.013 3	21.048 3