大数据税收征管与股价同步性——基于金税三期工程的准自然实验证据

Big Data in Tax Enforcement and Stock Price Synchronicity——Evidence from a Quasi-natural Experiment on the Third Phase of Golden Tax Project

本文基于金税三期工程在全国分批试点推广行为的准自然实验,运用多期双重差分法,研究引入大数据技术后税收征管对资本市场股价同步性的影响及其作用机制。研究发现:大数据税收征管有助于降低股价同步性,提高资本市场效率。机制研究表明,金税三期工程的实施,一方面可以通过缓解代理冲突减少市场噪音交易,从而降低股价同步性;另一方面可以通过提高公司信息质量增进公司特质信息纳入股价的程度,从而降低股价同步性。异质性检验表明,在公司信息透明度低、税收征管力度弱的地区,大数据税收征管政策对股价同步性的降低效果更显著。本文拓展了大数据税收征管的经济后果研究,为大数据税收征管降低股价同步性提供了经验证据支持。

Based on the quasi-natural experiment of implementing the Third Phase of Golden Tax Project in batches nationwide,this paper applies the multi-period difference-in-difference method to study the impact of introducing big data into the tax enforcement on the capital market stock price synchronicity and its mechanism of action.It is found that big data in tax enforcement helps reduce stock price synchronicity and improve capital market efficiency.Mechanistic studies have shown that,on the one hand the implementation of the Third Phase of Golden Tax Project can reduce market noise trading by mitigating agency conflicts and on the other hand enhance the degree to which company-specific information is incorporated into the stock price by improving the quality of company information thus reducing stock price synchronicity.Heterogeneity tests show that the utility of big data tax enforcement policies in reducing stock price synchronicity is more significant in regions with lower transparency of company information and weaker tax enforcement.This paper extends the study of the economic consequences of big data in tax enforcement and provides direct empirical evidence to support that big data in tax enforcement reduce stockpricesynchronicity.