Journal of Agricultural Big Data ›› 2023, Vol. 5 ›› Issue (3): 19-25.doi: 10.19788/j.issn.2096-6369.230304

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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

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