计算机与现代化 ›› 2020, Vol. 0 ›› Issue (09): 25-31.doi: 10.3969/j.issn.1006-2475.2020.09.005

• 数据库与数据挖掘 • 上一篇    下一篇

面向宏观经济分析的多源多维政务共享数据分析系统

  

  1. (1.江西省信息中心,江西南昌330000;2.江西财经大学,江西南昌330000)
  • 收稿日期:2020-03-16 出版日期:2020-09-24 发布日期:2020-09-24
  • 作者简介:李新华(1982—),男,江西高安人,高级工程师,硕士,研究方向:信息化发展与应用,E-mail: lxh213wy@163.com; 王勇(1990—),男,讲师,博士,研究方向:经济计量模型及其应用。
  • 基金资助:
    江西省重点研发计划项目(20181ACE50032)

A Multi-source and Multi-dimensional Government Data Sharing Analysis System for Macroeconomic Analysis

  1. (1. Jiangxi Information Center, Nanchang 330000, China;
    2. Jiangxi University of Finance and Economics, Nanchang 330000, China)

  • Received:2020-03-16 Online:2020-09-24 Published:2020-09-24

摘要: 在“数字经济”的国家战略背景下,为了给政府部门、行业以及企业等不同类型用户提供及时、全面、准确的宏观经济信息,形成基于大数据分析的决策支撑体系,江西省信息中心汇聚多种不同业务领域、多种不同数据结构、多种不同数据源的政务共享数据,构建宏观经济大数据分析系统。结合传统的时间序列特征和影响社会经济关键指标的其他宏观经济特征,建设基于时序分析、回归模型的经济大数据监测预警方法库和模型库,应用双对数线性回归模型、ARIMA模型对社会经济进行实时监测和智能预测研究,为相关政府部门的宏观调控、精准施策提供可靠参考。

关键词: 宏观经济分析, 政务共享, 跨源多维数据

Abstract: In the context of the “digital economy” national strategy, to provide timely, comprehensive and accurate macroeconomic information for different types of users like government departments, industries and enterprises and form a big-data-analysis-based decision-making system, government shared data of many different business fields, data structures and data sources is gathered by Jiangxi provincial information center, and a macro-economic big data analysis system is built. Combined with the traditional time series characteristics and other macro-economic characteristics which affect key indicators of social economy, a method and model database about applying economic big data in monitoring and early warning macro-economy is built on the basis of time series analysis, regression model. Furthermore, double logarithm linear regression model and ARIMA model are adopted to carray out real-time monitoring and intelligent prediction research on social economy to provide a reliable reference for macro-control and precise implementation of relevant government departments.

Key words: macroeconomic analysis, government affairs sharing, cross-source multi-dimensional data

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