Working Capital Management and the Persistence of Corporate R&D Innovation: A Review from the Perspective of Fictitious-toward Economy
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摘要: 以2010—2019年中国A股非金融上市公司为研究样本，从内部平滑机制出发，实证考察营运资本管理与企业研发创新可持续性的关系，以及企业“脱实向虚”资产组合配置对营运资本管理平滑作用的影响。结果表明，在企业现金流大幅波动时，营运资本管理对企业研发创新具有平滑作用，而对固定资产投资的平滑效果并不突出。同时，企业金融资产配置主要发挥短期财富效应，弱化了营运资本管理对企业研发创新的平滑效果。分组检验发现，小规模企业和非国有企业的营运资本管理对研发创新的平滑作用更明显。进一步研究企业内部资产管理策略，发现在现金流剧烈波动时以积极的营运资本管理代替金融资产配置的企业的平均研发创新水平更高；企业的负债率及股权融资水平越低，其实施上述资产管理策略的概率越大。研究强调了“脱实向虚”背景下企业内部资产配置在维持企业研发创新可持续性中的不可或缺作用。Abstract: Starting from the internal smoothing mechanism, this pater takes China's A-share non-financial listed companies from 2010 to 2019 as the research sample, empirically examines the relationship between working capital management and the sustainability of corporate R&D innovation, and carefully investigates the impact of corporate financialized asset portfolio allocation on the smoothness of working capital management. The results show that when the cash flow fluctuates violently, working capital management can smooth their R&D innovation, but the smoothing effect on fixed asset investment is not significant; at the same time, the allocation of financial assets by companies mainly exerts short-term wealth effects, which weakens the smoothing effect of working capital management on corporate R&D innovation. Group tests found that the smoothing effect of working capital management on R&D innovation is more prominent in small-scale companies and non-state-owned companies. Furthermore, through the study on the internal asset management strategy of companies, it is also found that companies using active working capital management instead of allocating financial assets when cash flow fluctuates violently have a higher average level of R&D innovation; the lower the company's leverage and the level of equity financing, the more likely it is to implement active working capital management strategies. The conclusions emphasize the indispensable role of working capital management in maintaining the sustainability of R&D innovation under the fictitious-toward economy.
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表 1 变量的统计性描述
变量 观测值 均值 标准差 最小值 中位数 最大值 R&D 11 000 17.538 7 1.228 6 13.730 7 17.549 2 20.600 2 WKS 11 000 0.046 0 1.358 8 -1.510 1 0.001 7 5.083 3 Fa 1100 0 0.264 1 0.159 7 0.024 9 0.228 6 0.796 0 ΔFa 10 000 -0.025 8 0.107 3 -0.719 6 -0.017 9 0.754 0 Size 11 000 21.650 4 0.950 7 19.886 3 21.564 1 24.511 8 Lev 11 000 0.452 0 0.258 7 0.046 8 0.417 8 0.983 5 Growth 11 000 0.001 9 0.003 5 -0.004 5 0.001 3 0.020 0 Stk 11 000 0.039 6 0.099 1 0.000 0 0.000 1 0.612 0 Cf 11 000 0.048 1 0.067 1 -0.203 0 0.045 7 0.250 7 
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表 2 基准回归
变量 因变量：R&D 因变量：Inv 因变量：R&D 因变量：R&D (1) (2) (3) (4) R&Dit-1 0.776 6*** 0.781 8*** 0.789 3*** (0.057 6) (0.045 6) (0.044 1) Invit-1 0.995 1*** (0.026 4) WKSi 0.005 2** 0.008 1 0.018 6*** (0.002 9) (0.005 1) (0.005 7) Fait-1 -0.331 7*** -0.308 8*** (0.089 6) (0.089 5) ΔFait 0.116 3* 0.101 9 (0.066 7) (0.066 7) W_Fit-1 -0.050 3*** (0.017 7) Levit-1 0.005 3 -0.131 3* -0.106 0* -0.088 7 (0.063 1) (0.069 7) (0.056 7) (0.055 7) Sizeit 0.216 6*** 0.058 4*** 0.220 4*** 0.212 8*** (0.047 8) (0.019 6) (0.038 9) (0.037 8) Growthit 29.296 1*** 9.996 7*** 32.975 4*** 33.342 3*** (3.489 1) (2.361 1) (3.487 6) (3.453 2) Stkit-1 0.114 3* -0.014 4 0.177 0*** 0.177 5*** (0.059 3) (0.070 2) (0.065 0) (0.065 3) Cons -0.849 0*** -1.041 2*** -0.892 8*** -0.868 0*** (0.222 4) (0.383 6) (0.213 4) (0.211 1) 行业效应 是 是 是 是 时间效应 是 是 是 是 AR(2) 0.185 0.201 0.164 0.159 Hansen 0.402 0.410 0.546 0.370 观测值 7 656 7 656 7 656 7 656 注：AR(2)检验和Hansen检验汇报对应p值；括号内为稳健标准误；*、**和***分别代表 10%、5%和1%的显著性水平。下表同。
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表 3 替换性检验
变量 因变量：R&D 因变量：Inv 因变量：R&D 因变量：R&D (1) (2) (3) (4) R&Dt-1 0.772 6*** 0.784 7*** 0.770 7*** (0.044 0) (0.039 9) (0.043 8) Invt-1 0.971 5*** (0.029 6) Iwkt-1 -0.000 5** -0.000 2 -0.000 8*** (0.000 2) (0.000 2) (0.000 3) Fa1t-1 -0.863 6*** -0.843 9*** (0.170 4) (0.175 5) ΔFa1it 0.331 3** 0.320 3* (0.164 8) (0.167 7) W_F1it-1 0.007 8** (0.003 3) Sizeit 0.218 6*** 0.070 6*** 0.225 6*** 0.234 1*** (0.036 9) (0.021 5) (0.035 4) (0.038 3) Levit-1 -0.016 3 -0.156 2** -0.071 8 -0.045 7 (0.057 1) (0.070 3) (0.055 2) (0.056 1) Cfit-1 0.101 5 0.306 4* 0.130 7 0.125 1 (0.120 7) (0.157 6) (0.152 0) (0.155 8) Growthit 32.813 8*** 10.063 5*** 33.041 4*** 32.120 7*** (3.317 2) (2.345 8) (3.219 6) (3.367 2) Stkit-1 0.149 2** -0.030 0 0.132 8** 0.130 5** (0.062 3) (0.069 8) (0.061 4) (0.061 4) Cons -0.851 1*** -1.289 9*** -1.121 8*** -1.074 0*** (0.218 0) (0.420 4) (0.223 5) (0.226 5) 行业效应 是 是 是 是 时间效应 是 是 是 是 AR(2) 0.161 0.193 0.140 0.159 Hansen 0.200 0.141 0.465 0.171 观测值 7 656 5 896 7 656 7 656
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表 4 渐进DID估计
变量 全样本 国有企业 非国有企业 大规模企业 中小规模企业 (1) (2) (3) (4) (5) St_WKSit 0.010 8** -0.064 4 0.012 4*** -0.093 7** 0.007 7*** (0.004 5) (0.045 1) (0.003 5) (0.043 5) (0.002 1) Levit-1 -0.006 1 0.315 3* -0.104 9 0.265 9** -0.134 0* (0.070 0) (0.183 0) (0.083 4) (0.105 8) (0.078 6) Sizeit 0.876 1*** 0.859 4*** 0.893 7*** 0.857 9*** 0.916 7*** (0.029 8) (0.053 4) (0.028 6) (0.058 8) (0.036 4) Growthit 6.252 0 18.462 0 2.955 4 1.948 0 6.406 9 (3.887 3) (11.166 8) (3.597 0) (6.005 4) (3.937 1) Stkit-1 -0.170 9* 0.207 9 -0.280 0*** -0.013 0 -0.261 5** (0.101 9) (0.294 0) (0.077 4) (0.202 3) (0.101 7) Cons -1.376 8** -1.471 0 -1.632 6** -1.234 2 -2.122 0*** (0.638 6) (1.164 4) (0.618 9) (1.305 5) (0.774 0) R2 0.553 2 0.630 8 0.552 9 0.532 6 0.479 0 观测值 7 652 1 650 5 999 2 544 5 102
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表 5 营运资本存量的影响及其他可能解释
变量 营运资本存量的影响 (3)其他可能解释 (1)低营运资本存量组 (2)高营运资本存量组 R&Dit-1 0.787 5*** 0.838 6*** 0.785 1*** (0.057 3) (0.045 5) (0.045 2) WKSi -0.002 5 0.011 7** 0.004 5* (0.012 7) (0.005 2) (0.002 7) ΔCashit 0.029 5 (0.067 4) Cfit-1 0.106 6 (0.154 0) Levit-1 0.056 0 -0.061 9 -0.008 4 (0.069 1) (0.110 8) (0.055 2) Sizeit 0.199 5*** 0.192 2*** 0.207 7*** (0.047 7) (0.051 1) (0.038 2) Growthit 30.741 7*** 39.117 4*** 33.462 7*** (3.845 0) (6.617 4) (3.314 1) Stkit-1 0.161 1** 0.201 6 0.180 2*** (0.073 8) (0.125 8) (0.063 4) Cons -0.762 6*** -1.020 9* -0.803 6*** (0.242 3) (0.598 6) (0.222 0) 行业效应 是 是 是 时间效应 是 是 是 AR(2) 0.146 0.754 0.146 Hansen 0.273 0.973 0.217 观测值 6 271 1 385 7 656
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表 6 异质性分析
变量 小规模企业 大规模企业 国有企业 非国有企业 (1) (2) (3) (4) R&Dit-1 0.809 0*** 0.749 4*** 0.771 2*** 0.786 2*** (0.051 0) (0.093 5) (0.064 6) (0.058 2) WKSi 0.017 9** -0.028 2 -0.017 2 0.004 7* (0.008 3) (0.021 8) (0.019 3) (0.002 5) Levit-1 -0.150 0* -0.010 7 0.137 8 -0.043 0 (0.087 9) (0.096 7) (0.161 0) (0.069 2) Sizeit 0.273 2*** 0.225 1*** 0.215 0*** 0.217 3*** (0.050 0) (0.079 5) (0.059 7) (0.048 2) Growthit 26.453 6*** 34.164 2*** 19.522 3** 33.805 5*** (3.863 3) (7.057 8) (9.692 8) (4.157 6) Stkit-1 0.064 4 0.113 8 0.256 7 0.176 3** (0.081 7) (0.105 0) (0.384 9) (0.068 9) Cons -2.274 9*** -1.150 3** -1.069 0** -0.872 4*** (0.439 2) (0.504 0) (0.543 6) (0.223 5) 行业效应 是 是 是 是 时间效应 是 是 是 是 AR(2) 0.644 0.768 0.215 0.471 Hansen 0.895 0.503 0.626 0.349 观测值 2 474 2 549 1 654 6 002
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表 7 分组均值描述性统计
组别 R&D Lev Size Stk Cf Growth Inv HH组 17.370 6 0.466 8 21.531 5 0.041 7 0.045 9 0.001 8 2.282 0 HL组 17.747 9 0.427 6 21.783 7 0.032 2 0.054 5 0.001 8 2.409 9 LH组 17.430 5 0.454 5 21.563 3 0.044 1 0.048 0 0.002 0 2.373 9 LL组 17.743 6 0.450 8 21.826 1 0.037 0 0.045 3 0.001 8 2.710 1
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表 8 以HL为因变量的logit回归结果
变量 全样本 HL组与LL组 HL组与LH组 HL组与HH组 (1) (2) (3) (4) Levit-1 -0.684 6*** -0.549 6*** -0.526 4*** -1.034 1*** (0.134 0) (0.168 1) (0.165 1) (0.169 5) Stkit-1 -1.632 8*** -1.026 8*** -1.790 5*** -2.048 8*** (0.310 2) (0.390 1) (0.357 3) (0.369 2) Controls 是 是 是 是 行业效应 是 是 是 是 时间效应 是 是 是 是 Pseudo-R2 0.054 7 0.038 8 0.093 6 0.101 5 观测值 7 656 3 323 3 766 3 749
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