TIME SERIES FORECASTING AND PARAMETER ESTIMATION IN AGRICULTURAL COMMODITY PRICES: A BIBLIOMETRIC ANALYSIS
DOI:
https://doi.org/10.35631/IJIREV.825025Keywords:
Commodity Price, Forecasting, Long-memory, Parameter Estimation, Time SeriesAbstract
This study provides a detailed and comprehensive bibliometric analysis of the time series forecasting technique and parameter estimation methodologies in agricultural commodity price analysis, a field that has gained increasing attention due to the growing price volatility, market uncertainty and the demand for effective decision-support tools. Despite the substantial growth of publications, a systematic understanding of the intellectual structure, influential contributions and methodological evolution remain limited. Thus, to fill the gap, this study analyses 761 articles indexed in Scopus from 2000 to January 2026. Bibliographic data were standardized using Scopus Analyzer and OpenRefine to ensure consistency in author names, affiliations, and keywords. Bibliometric techniques, including citation analysis, keyword co-occurrence analysis, and country-level co-authorship network analysis, were conducted using VOSviewer. The results of the study show a steady growth in the number of research articles published in the domain, especially since 2010, suggesting that the research domain is mature. The citation analysis identifies a handful of research articles that have made a significant contribution to the advancement of the research field, especially with respect to long-memory processes, fractional integrations, volatility modelling and estimation techniques. The co-occurrence of keywords indicates that research articles published in the domain have been centred on long-memory processes, fractional integrations, ARFIMA models, volatility modelling, and estimation methodologies. The study also reveals a shift in research methodological approaches from traditional techniques to Bayesian estimation, state-space models, time-varying parameters and volatility modelling. Finally, the analysis also shows that research output and impact are concentrated in a limited number of countries, suggesting a strong degree of author collaboration.
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