Quantitative, Econometric, and Forecasting Methods for Agricultural and Agribusiness Markets

Dear Colleagues,

Agricultural and agribusiness markets operate in an increasingly complex and uncertain environment, shaped by price volatility, changing demand and supply conditions, climate-related risks, energy and input costs, global market integration, and disruptions across supply chains. These factors affect producers, agribusiness firms, consumers, investors, and policymakers, increasing the need for reliable quantitative tools to understand market dynamics and support informed decision-making.

Quantitative methods, econometric modeling, and forecasting play an important role in analyzing these markets. Established statistical and econometric approaches remain essential for identifying relationships, measuring market responses, and modeling dynamic behavior, while advances in time-series methods, data-driven techniques, machine learning, and artificial intelligence have expanded the range of tools available for prediction and decision support. At the same time, agricultural and agribusiness applications present particular challenges, including seasonality, structural changes, nonlinearities, volatility, limited or heterogeneous data, and uncertainty.

The continued development and evaluation of quantitative, econometric, and forecasting approaches is therefore important not only from a methodological perspective but also for their practical contribution to agricultural production, market analysis, risk management, supply-chain planning, and business and policy decisions.

The goal of this Special Issue is to bring together theoretical, methodological, and empirical research that applies quantitative, econometric, and forecasting methods to agricultural and agribusiness markets. Contributions may include established and emerging approaches, such as econometric and time-series models, machine learning, artificial intelligence, and other data-driven methods, with particular emphasis on their applications to market analysis, forecasting, risk assessment, and decision-making. As such, this Special Issue contributes to a better understanding of agricultural markets, agribusiness management, commodity-price dynamics, supply chains, and related economic challenges

Potential topics include, but are not limited to:

• Quantitative and econometric modeling of agricultural and agribusiness markets;
• Time-series analysis and forecasting of agricultural prices, production, demand, and supply;
• Agricultural commodity markets, price dynamics, volatility, and market linkages;
• Statistical and econometric forecasting methods;
• Machine learning, artificial intelligence, and data-driven forecasting approaches;
• Forecast evaluation, model comparison, benchmark models, and forecast combinations;
• Risk, uncertainty, and probabilistic forecasting;
• Nonlinear, dynamic, and adaptive modeling approaches;
• Energy–agriculture linkages and the effects of energy and input prices on agricultural markets;
• Climate-related risks and their effects on agricultural markets and agribusiness;
• Demand forecasting, supply-chain modeling, and inventory-related applications;
• Quantitative methods for business, investment, and policy decision-making in agriculture and agribusiness.

The Special Issue welcomes original research articles, review articles, and methodological contributions, as well as empirical studies and case-based research that provide new insights into agricultural and agribusiness markets.

We look forward to receiving your original research articles and reviews.

Dr. Foteini Kyriazi
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 250 words) can be sent to the Editorial Office for assessment.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-anonymized peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Agriculture is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

• agricultural markets
• agribusiness
• quantitative methods
• econometric modeling
• time-series forecasting
• agricultural commodity markets
• price forecasting
• demand forecasting
• forecast evaluation
• machine learning
• decision-making
• risk and uncertainty