Future Prospects of Labour Productivity in Algerian Agriculture: A 2030 Outlook

Summary The primary objective of this study was to forecast the labour productivity in Algeria's agricultural sector by the year 2030 using the seasonal autoregressive integrated moving average (SARIMA) model. Quarterly data spanning from the first quarter of 1991 to the fourth quarter of 2021 were analyzed, identifying the SARIMA model (1, 1, 1) x (1, 1, 1, 4) as the most suitable for capturing seasonal variations and accurately fitting the historical data. The methodology utilized Python 3.11.5 for data processing and modelling, thus enabling a comprehensive analysis of the trends and patterns in Algerian agricultural labour productivity. The results obtained demonstrate robust and steady growth in the Algerian agricultural labour productivity attributable to advancements in farming techniques, technological innovations, and evolving market conditions. These findings highlight the critical role of accurate forecasting in effective policy-making and resource allocation. By providing insights into future productivity trends, the research supports the development of strategies aimed at enhancing the resilience and sustainability of the agricultural sector, particularly in the face of challenges posed by climate change and geopolitical tensions. The conclusion underscores the importance of leveraging predictive models such as SARIMA in informing agricultural policies and ensuring the long-term food security and economic stability in Algeria.