商业研究

商业研究

• 财税研究 • 上一篇    下一篇

大数据视角下的区域税收发展不平衡探析

孙存一1，谭荣华2   

  1. （1.北京物资学院 物流学院，北京101149；2.中国人民大学 财政金融学院，北京100872）
  • 收稿日期:2018-10-22 出版日期:2019-03-16
  • 作者简介:孙存一（1979-），男，山东青岛人，北京物资学院物流学院助理研究员，经济学博士，研究方向：大数据通用算法、金融财税行业算法；谭荣华（1946-），男，北京人，中国人民大学财政金融学院教授，博士生导师，研究方向：财政金融信息化。
  • 基金资助:
    国家税务总局“微观税收流失分析理论、测算和应用研究项目” （一期、二期）资助；国家税务总局“税法遵从风险评价指标体系与模型研究项目”（一期、二期）资助。

An Analysis of the Imbalance of Regional Tax Development under the Perspective of Big Data

SUN Cun-yi1,TANG Rong-hua2   

  1. (1.School of Logistics,Beijing Wuzi University,Beijing 101149,China;2.School of Finance, Renmin University of China,Beijing 100872,China)
  • Received:2018-10-22 Online:2019-03-16

摘要： 我国区域经济发展差距一定程度上体现在税收缺口的不平衡。本文选取中国31省份30多万规模以上工业数据，以适合大数据分析的机器学习作为核心算法，从税收流失的视角分析地区之间的税收差异。结果表明，在同等税收政策的前提下，省份之间的流失金额、流失率、流失户、流失户比差异明显。因此，税务机关应以“互联网+”以及大数据为契机，科学识别区域税收流失差异,促进区域税收征管平衡，保证经济税收的良性发展。 关键词：区域经济；大数据；机器学习；税收流失

关键词: regional economy, big data, machine learning, tax erosion

Abstract: The disparity of regional economic development in China is reflected in the imbalance of tax gap to a certain extent. This paper chooses more than 〖BF〗300,000〖BFQ〗 industrial data from 31 provinces in China, and takes machine learning for large data analysis as the core algorithm to analyze tax differences between regions from the perspective of tax loss. The results show that under the premise of the same tax policy, the loss amount, loss rate, loss of households, loss of household ratio between provinces are significantly different. Therefore, tax authorities should take the opportunity of “Internet +” and big data as a chance to scientifically identify the difference of regional tax revenue loss, in order to promote regional tax collection and management balance, and ensure the sound development of economic tax.

Key words: regional economy, big data, machine learning, tax erosion