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논문검색

Application of Data Mining in Fiscal Expenditure on the New Urbanization and Income Gap based on Network Big Data

원문정보

초록

영어

Network big data is an important driving force for the upgrading of information technology, and network data has brought great opportunities to the economic survey. The openness and freedom of the network also produced the possibility of private information and data to be destroyed or violated, and the security of the Internet is becoming more and more important. In this paper, the author analyzes the impact of fiscal expenditure on the new urbanization and income gap by using data mining technology. The result shows that the public expenditure increase 1% will lead urbanization rate increase 0.0462%; also, the effect of public finance expenditure on urbanization has a certain time lag, and the effect will be more obvious in the long term. At the same time, public expenditure will help to narrow the income gap in the long term, public expenditure at lag 2 increase 1% will lead income gap decrease 0.758%. So that, increasing public expenditure is an important way to promote the equalization of basic public services between urban and rural areas.

목차

Abstract
 1. Introduction
 2. Data Mining and Support Vector Machine
  2.1. Data Mining
  2.2. Support Vector Machine
  2.3. Network Data
 3. New Urbanization
  3.1. Land Urbanization
  3.2. The Connotation of New Urbanization
 4. Empirical Analysis
  4.1. ADF Stationarity Test
  4.2. VAR Model
  4.3. Granger Causality Test
 5. Conclusions
 References

저자정보

  • Yan Liu College of Urban, Rural Planning and Architectural Engineering, Shangluo University, Shangluo 726000, Shaanxi, China

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