农业大数据学报 ›› 2023, Vol. 5 ›› Issue (3): 19-25.doi: 10.19788/j.issn.2096-6369.230304

• 农业农村社会经济数据:资源与方法 • 上一篇    下一篇

国内金融市场变化对农产品价格横向传导机制分析数据集(2017-2021)

魏同洋1(), 徐珂2, 徐磊1,*()   

  1. 1.中国农业科学院农业信息研究所,北京 10081,中国
    2.中国农业科学院农业资源与农业区划研究所,北京 100081,中国
  • 收稿日期:2023-07-21 接受日期:2023-08-16 出版日期:2023-09-26 发布日期:2023-11-14
  • 通讯作者: 徐磊,E-mail:xulei02@caas.cn
  • 作者简介:魏同洋,E-mail:weitongyang@caas.cn
  • 基金资助:
    中国农业科学院科技创新工程(CAAS-ASTIP-2023-AII)

Dataset for Analyzing the Horizontal Transmission Mechanism of Domestic Financial Markets to Agricultural Commodity Prices, 2017-2021

WEI TongYang1(), XU Ke2, XU Lei1,*()   

  1. 1. Institute of Agricultural Information, Chinese Academy of Agricultural Sciences, Beijing 10081, China
    2. Institute of Agricultural Resources and Regional Planning, Chinese Academy of Agricultural Sciences, Beijing 100081, China
  • Received:2023-07-21 Accepted:2023-08-16 Online:2023-09-26 Published:2023-11-14

摘要:

农产品价格波动传导机制是备受关注的研究议题。农产品价格影响因素逐渐呈现多元化、复杂化,包括金融市场影响在内的非传统因素逐渐凸显,因此采集金融市场对农产品价格横向传导数据,揭示其传导机制,具有十分重要的价值。在本研究中农产品价格横向传导机制分析数据集包含原始数据集和预处理数据集,数据通过公开途径获取,均包括农产品价格以及国内总需求、货币市场、股票市场、房地产市场四类国内金融市场数据,数据为月度数据,时间范围为2017年1月至2021年2月,共计50个月。数据集构建包括数据集变量确定、数据权威来源确定与收集、数据预处理三个步骤。本数据集共享,可为国内金融市场对农产品价格横向传导机制的研究提供数据支持,同时可为相关企业决策和政府宏观调整提供数据支撑。

数据摘要:

项目 描述
数据库(集)名称 国内金融市场变化对农产品价格横向传导机制分析数据集(2017-2021)
所属学科 农业经济
研究主题 农产品价格传导
数据时间范围 2017年1月—2021年2月
数据地理空间覆盖 中国
数据类型与技术格式 *.XLSX
数据库(集)组成 包括原始数据集和预处理数据集两个excel文档。原始数据集文档包含时间(年月)、农产品批发价格200指数、工业增加值增长速度、广义货币供给量、7天银行间拆借利率、上证综指、商品房销售面积、商品房销售额、房屋销售价格等9个变量,共计459条记录。预处理数据集文档是在原始数据集基础上进行的定基折算、减少序列波动等预处理后的数据文档,包含时间(年月)、农产品批发价格200指数取对数、工业增加值同比增长率取对数、广义货币供给量取对数、7天银行间拆借利率取对数、上证综指取对数、房屋销售价格取对数等7个变量,共计357条记录。
数据量 29.94 KB
主要数据指标 国内金融市场主要月度指标与同期农产品价格指数
数据可用性 CSTR:17058.11.sciencedb.agriculture.00031
DOI: 10.57760/sciencedb.agriculture.00031
https://agri.scidb.cn/preview?dataSetId=877bab09989f4e319afdb0fe2d0702ff&version=V1
经费支持 本文得到中国农业科学院科技创新工程(CAAS-ASTIP-2023-AII)资助

关键词: 金融市场, 农产品价格, 横向传导, 数据集

Abstract:

The transmission mechanism of agricultural commodity price volatility is a research topic that has attracted much attention. The factors influencing agricultural commodity prices are gradually diversified and complicated, and non-traditional factors including the influence of financial markets are gradually highlighted. Traditionally, it is believed that the price of agricultural products is mainly affected by supply and demand factors, but with the increasingly close connection between the price of agricultural products and financial markets such as currencies, stocks, futures and so on, the financial attributes of agricultural products have gradually come to the fore, and the influence of related non-traditional factors has become more and more obvious, and the factors affecting the price of agricultural products have gradually become diversified and complex. Comprehensively analyzing the various studies on the transmission of financial market fluctuations on agricultural commodity prices can reveal the collection of data from different perspectives, different periods and different variables, and reveal its transmission mechanism, which is of great value. However, the existing studies collect data and analyze the relationship and transmission mechanism of financial factors on the price volatility of agricultural products more from the perspective of derivatives and currency, and the financial factors considered are not comprehensive enough and the relevant data are not complete enough. Based on this, this dataset selects more diversified financial factors and collects the four most representative types of domestic financial market data. The dataset for the analysis of the horizontal transmission mechanism of agricultural commodity prices in this study contains the original data dataset and the preprocessed data dataset, which are obtained through public access, and both include agricultural commodity prices and the four types of domestic financial market data, namely, aggregate domestic demand, the money market, the stock market, and the real estate market, and the data are monthly data, with a time range of January 2017 to February 2021, for a total of 50 months. The dataset construction includes three steps of dataset variable determination, data authority source determination and collection, and data pre-processing. To ensure the dataset quality, the measures are taken as follows: first, in the data collection process, the financial factor variables that mainly affect the price fluctuation of agricultural products are selected, and no important variables are omitted. Second, in the data collection source link, the data are collected through authoritative data source channels. Third, in the data pre-processing process, professional methods are used to fill the empty data, and the logarithmic form is adopted to avoid heteroscedasticity and volatility caused by the data. This dataset is shared to provide data support for the study of the horizontal transmission mechanism of agricultural commodity prices in the domestic financial market, and at the same time, it can provide data support for the decision-making of the relevant enterprises and the macro-adjustment of the government.

Data summary:

Items Description
Dataset name Dataset for Analyzing the Horizontal Transmission Mechanism of Domestic Financial Markets to Agricultural Commodity Prices, 2017-2021
Specific subject area Agricultural economics
Research topic Transmission of agricultural commodity price
Time range January 2017 - February 2021
Geographical scope China
Data types and technical formats *.XLSX
Dataset structure Including the original data set and preprocessing data set two excel documents. The original dataset document contains time (month and year), wholesale price of agricultural products 200 index, industrial value-added growth rate, broad money supply, 7-day interbank lending rate, the Shanghai Composite Index, the area of sales of commercial properties, sales of commercial properties, housing sales prices and other 9 variables, totaling 459 records. The preprocessed data set document is the data document after preprocessing such as fixed-base conversion and reduction of serial fluctuation on the basis of the original data set, which contains 7 variables such as time (month and year), logarithm of wholesale price of agricultural products 200 index, logarithm of the year-on-year growth rate of value added of industry, logarithm of the supply of broad money, logarithm of 7-day interbank lending rate, logarithm of the Shanghai Composite Index, logarithm of the price of housing sales, etc., totaling 357 records.
Volume of data 29.94 KB
Key index in dataset Main monthly indicators of the domestic financial market and the agricultural price index for the same period
Data accessibility CSTR:17058.11.sciencedb.agriculture.00031
DOI: 10.57760/sciencedb.agriculture.00031
https://agri.scidb.cn/preview?dataSetId=877bab09989f4e319afdb0fe2d0702ff&version=V1
Financial support This work was supported by The Agricultural Science and Technology Innovation Program of the Chinese Academy of Agricultural Science (CAAS-ASTIP-2023-AII)

Key words: financial market, agricultural product price, horizontal transmission, dataset