运用双尺度分布最近邻估计对公司盈利能力作异质性因果推断

Heterogeneous causal inference of corporate profitability using two-scale distributional nearest neighbor estimation

异质性治疗效应是现代因果推断的一个重要内容,在金融领域也有非常广泛的应用.研究提高偿债水平对不同营运能力的上市公司盈利能力的异质性效应,以消除上市公司个体差异带来的影响,使得估计结果更加准确.在估计方法的选择上,选择了双尺度分布最近邻估计.它能够消除估计中的一阶有限样本偏差,并且它在正则化条件下是渐近无偏和渐近正态的.因此,应用双尺度分布最近邻估计对CSMAR中国上市公司财务报表数据库中的中国上市公司财务指标进行了实证分析,研究了不同经营能力下公司的偿债能力提高对于公司盈利能力是否存在异质性治疗效应.根据其研究结果,对优化上市公司财务结构,提高上市公司的盈利能力给出了相应的建议.

The heterogeneous treatment effect is the center of gravity in modern causal inference and is also widely used in the financial field.Studying the heterogeneous effect of improving solvency on the profitability of listed companies with different operational capabilities can eliminate the impact of individual differences in listed companies and make the estimation results more accurate.The two-scale distributional nearest neighbor(DNN)is able to eliminate the first-order finite sample bias in the estimate,and it is asymptotically unbiased and asymptotically normal under regularization conditions.Therefore,an empirical analysis was conducted of the financial indicators of Chinese listed companies in the CSMAR financial statement database by using the two-scale distributional nearest neighbor estimation.And a study was carried out on that whether there is heterogeneity in the impact of corporate solvency reduction on corporate profitability under different operating capabilities.Corresponding suggestions were given for optimizing the financial structure and improving the profitability of listed companies.