1. Data source: Wind database
2. Time span: 2000-2020
3. Regional scope: Shanghai and Shenzhen A-shares (excluding the financial industry, excluding samples with total pre-tax profits less than or equal to 0, excluding samples with abnormal corporate actual income tax rates (actual income tax rates are less than 0 and greater than 1))
4. Indicator description:
Calculation ideas for key indicators:
1. The difference between the nominal income tax rate and the actual income tax rate (RATE_diff)
The difference between the nominal income tax rate and the actual income tax rate (RATE_diff) is used to reflect the degree of corporate tax avoidance.
2. The five-year average of the difference between the nominal income tax rate and the actual tax rate (from year t-4 to year t) (LRATE_diff)
The five-year average (from year t-4 to year t) (LRATE_diff) of the "difference between the nominal income tax rate and the actual tax rate" is used to measure the degree of corporate tax avoidance.
3. Accounting-tax difference (BTD)
BTD is equal to (pre-tax accounting profit-taxable income)/end-of-period total assets. Taxable income = current income tax expense / nominal income tax rate = (income tax expense - deferred income tax expense) / nominal income tax rate. 4. Accounting-tax difference (DDBTD) after deducting the impact of accrued profits.
DDBTD is calculated by the model: 
TACC is the total accrued profits, which is equal to (net profit - net cash flow generated from operating activities)/total assets. u represents the average residual of company i during the sample period
and ε represents the deviation of the residual in year t from the company’s average residual u.
Represents the portion of BTD that cannot be explained by accruals.
For more detailed calculation process, please refer to the literature in the shared file and the STATA do file.
References: Ye Kangtao, Liu Xing. Corporate tax avoidance activities and internal agency costs [J]. Financial Research, 2014, 000(009):158-176.
Related research:
[1] Deng Yingxiang, Zhu Guilong. Research on China's industry-university-research cooperation based on patent data [J]. Science and Science and Technology Management, 2009, 30(012):16-19.
[2] Zhuang Tao, Wu Hong. Research on the triple helix measurement of my country’s government-industry-university-research institute based on patent data—also on the role of government in industry-university-research cooperation [J]. Management World, 2013(08):175-176.
[3] Wang Banban, Qi Shaozhou. The effect of energy-saving and emission-reduction technological innovation of market-based and command-based policy tools - Empirical evidence based on patent data of China's industrial industries [J]. China Industrial Economics, 2016(6):91-108.
[4] Huang Lucheng, Gao Shan, Wu Feifei, et al. Analysis of global high-speed railway technology competition situation based on patent data [J]. Intelligence Magazine, 2014(12):41-47.
Basic data :
| stkcd | year | Securities code | Securities abbreviation | Listing date | Securities Regulatory Commission industry code | Securities Regulatory Commission industry name | net profit | Total profit before tax | income tax | Net cash flow from operating activities | total assets | Increase in deferred tax liabilities | Decrease in deferred tax assets | Year-end income tax rate % |
Tax avoidance activity indicators
| stkcd | year | Securities code | net profit | Total profit before tax | income tax | Net cash flow from operating activities | total assets | Increase in deferred tax liabilities | Decrease in deferred tax assets | Year-end income tax rate | effective income tax rate | RATE_diff | LRATE_diff | BTD | TACC | DDBTD |
All data :
Download link : Tax avoidance activity indicator data set.zip-Dataset document resources-CSDN download