• Erasmus Kabu Aduteye Department of Agriculture, Food, and Resource Sciences. University of Maryland Eastern Shore.
  • Tseganesh Tegegne Sete Department of Agriculture, Food, and Resource Sciences. University of Maryland Eastern Shore.
  • Yeong Nain Chi Department of Agriculture, Food, and Resource Sciences. University of Maryland Eastern Shore.




coffee, model, time series, supply, demand, pandemic, stakeholders.


The global coffee market is a complex and dynamic system influenced by a multitude of factors, resulting in continuous fluctuations in coffee prices. This study utilized time series analysis to examine the historical trends and dynamics of the monthly global price of coffee, Arabica, from January 1990 to July 2023. The data were transformed to achieve stationarity using a methodical process, and an ARIMA (0,1,2) model was found to be the best-fit model for forecasting. The analysis' findings show how complex the coffee market is. Coffee prices are influenced by factors like supply and demand, climate change, currency exchange rates, economic conditions, and trade policies. Since 2001, unstable markets have affected producers and consumers. The COVID-19 pandemic brought unprecedented challenges to the coffee sector, disrupting consumption patterns and supply chains. Economic variables like GDP growth and exchange rates influence coffee prices and producer welfare. While the coffee industry is experiencing recovery, price fluctuations remain a concern. Understanding these factors is crucial for stakeholders, and time series analysis can help inform decision-making in this dynamic market.


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How to Cite

Erasmus Kabu Aduteye, Tseganesh Tegegne Sete, & Yeong Nain Chi. (2023). TIME SERIES ANALYSIS OF GLOBAL PRICES OF COFFEE: INSIGHTS INTO A COMPLEX MARKET. International Journal of Business & Economics (IJBE), 8(2), 138–151. https://doi.org/10.58885/ijbe.v08i2.138.ea