农业大数据学报 ›› 2023, Vol. 5 ›› Issue (3): 49-55.doi: 10.19788/j.issn.2096-6369.230309

• 农业农村社会经济数据:资源与方法 • 上一篇    下一篇

全国2021-2022年农机购置与应用补贴信息数据集

杨文君(), 辜香群(), 杨志海*()   

  1. 华中农业大学经济管理学院,武汉 430070,中国
  • 收稿日期:2023-08-16 接受日期:2023-09-02 出版日期:2023-09-26 发布日期:2023-11-14
  • 通讯作者: 杨志海,E-mail:zhyang@mail.hzau.edu.cn
  • 作者简介:杨文君,E-mail:yang_wj@yeah.net;辜香群,E-mail:xq_gu@foxmail.com
  • 基金资助:
    教育部哲学社会科学重大课题攻关项目(20JZD015);国家自然科学基金面上项目(72303076);国家级大学生创新创业训练计划项目(202310504074)

A Dataset of National Agricultural Machinery Purchase and Application Subsidy Information from 2021 to 2022

YANG WenJun(), GU XiangQun(), YANG ZhiHai*()   

  1. College of Economics and Management, Huazhong Agricultural University, Wuhan 430070, China
  • Received:2023-08-16 Accepted:2023-09-02 Online:2023-09-26 Published:2023-11-14

摘要:

农机购置补贴政策作为一项重要的强农惠农政策,对小农户及新型农业经营主体生产决策、农业生产以及农机行业发展等多方有深刻影响。通过搜集农机补贴政策背景下全国性农机购置与补贴数据,掌握各省市县农机购置差异、变动特征与趋势,才能合理评估政策所带来的影响,进而调整农机购置补贴政策目标与内容,从而推动农机市场健康发展,更好助力农业强国建设。目前,我国各省农业农村厅的农机购置补贴信息公开专栏实时发布农机购置相关数据。通过网络爬取、数据处理,得到涵盖2021—2022年北京、天津、山西等23个省(自治区、直辖市)农机购置与应用补贴信息、共计2226229条数据的数据集。该数据集可用于分析各地农机购置特征、差异以及补贴发放情况,为相关科学研究和管理决策提供数据基础。

数据摘要:

项目 描述
数据库(集)名称 全国2021-2022年农机购置与应用补贴信息数据集
所属学科 农业经济
研究主题 农机具购置补贴
数据时间范围 2021—2022年
数据地理空间覆盖 北京、天津、山西等23个省(自治区、直辖市)
数据类型与技术格式 预处理后数据(EXCEL格式)
数据库(集)组成 按省份分为3个文件,分别是重庆山西浙江陕西2021—2022数据集、河南湖北江西新疆黑龙江西藏2021—2022数据集和河北甘肃安徽福建广西辽宁贵州海南宁夏青海天津北京上海2021—2022数据集
数据量 259.49 MB
主要数据指标 省份、县、所在乡(镇)、购机者姓名对应字符、购机者姓名、机具品目等19个指标
数据可用性 CSTR:31253.11.sciencedb.12793
DOI:10.57760/sciencedb.12793
经费支持 教育部哲学社会科学重大课题攻关项目(编号:20JZD015);国家自然科学基金面上项目(编号:72303076);国家级大学生创新创业训练计划项目(编号:202310504074)

关键词: 农机购置, 农机购置补贴, 网络爬取, 政策评估

Abstract:

As an important policy to strengthen and benefit agriculture, the agricultural machinery purchase subsidy policy has a profound impact on many parties, such as new agricultural business entities, agricultural production, and the agricultural machinery industry. Through the collection of national agricultural machinery purchase and subsidy data, we can grasp the differences and trends in the purchase of agricultural machinery in various regions. We can then reasonably assess the impact of the policy, adjust the policy objectives and content, promote the healthy development of the agricultural machinery market, and better assist the construction of a strong agricultural country. At present, the Department of Agriculture and Rural Affairs of each province in China, through the information disclosure column of agricultural machinery purchase subsidies, releases data related to agricultural machinery purchase in real time. Through network crawling and processing, this dataset covers the subsidy data on the purchase and application of agricultural machinery in 23 provinces (autonomous regions and municipalities directly under the central government) such as Beijing, Tianjin, Shanxi, etc. in 2021-2022, totaling 222,6229 items. This dataset can be used to analyze the characteristics and differences of the purchase of agricultural machinery and the subsidy distribution in different regions, and provide a data basis for related scientific research and management decision-making.

Data summary:

Items Description
Dataset name A Dataset of National Agricultural Machinery Purchase and Application Subsidy Information from 2021 to 2022
Specific subject area Agriculture economics
Research topic Subsidies for the purchase of agricultural machinery
Time range 2021-2022
Geographical scope Beijing, Tianjin, Shanxi and other 23 provinces (autonomous regions and municipalities directly under the central government)
Data types and technical formats Preprocessed data (EXCEL format)
Dataset structure It is divided into 3 files by province. The first one is Chongqing, Shanxi, Zhejiang, Shaanxi 2021-2022 dataset. The second is Henan, Hubei, Jiangxi, Xinjiang, Heilongjiang, Xizang 2021-2022 dataset. The third is Hebei, Gansu, Anhui, Fujian, Guangxi, Liaoning, Guizhou, Hainan, Ningxia, Qinghai, Tianjin, Beijing, Shanghai 2021-2022 dataset
Volume of data 259.49 MB
Key index in dataset 19 indicators, including province, county, township (town), corresponding character of the purchaser's name, purchaser's name, and item of the machin
Data accessibility CSTR:31253.11.sciencedb.12793
DOI:10.57760/sciencedb.12793
Financial support Ministry of Education, Philosophy and Social Science Major Project (No. 20JZD015); National Natural Science Foundation of China (No. 72303076); National Innovation and Entrepreneurship Training Programme for College Students (No. 202310504074)

Key words: agricultural machinery purchase, subsidy disbursement, web crawling, policy evaluation