Information and communication technology (ICT) and agricultural sector productivity: empirical evidence from Somalia

Agriculture is the backbone of Somalia’s economy, contributing more than 75% of GDP and 93% of total revenue. Using an Autoregressive Distributed Lag (ARDL) model covering the period from 1990 through 2019, this study examines the relationship between ICT adoption and agricultural productivity in Somalia. The results show that ICT has a positive and significant relationship with agricultural productivity, indicating that ICT adoption contributes to higher production efficiency, greater land productivity, and improved labour productivity. Conversely, environmental degradation and population growth adversely affect agricultural productivity, suggesting that increased emissions and growing populations negatively impact the sector. The short-term results of the error correction model (ECM) indicate that ICT and population growth show a statistically significant positive correlation with agricultural productivity in the short term. In contrast, environmental degradation shows a positive and statistically significant relationship with agricultural productivity. This might be due to short-term adaptation strategies or increased input use. The study suggests important policy implications for stimulating agricultural development in Somalia. The government should promote investment in ICT-related infrastructure in Somalia, as this has the potential to enhance the performance of the country’s agricultural sector.

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Publication Details

Journal
Cogent Food & Agriculture
Published
2025-11-24
DOI
https://doi.org/10.1080/23311932.2025.2592351
Citations
2
Primary Topic
Economic Growth and Development
Type
article
Field-Weighted Citation Impact
6.49
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article

Information and communication technology (ICT) and agricultural sector productivity: empirical evidence from Somalia

Murni Mahmud, Husein Osman Abdullahi, Bile Abdisalan Nor
2 citations
Cogent Food & Agriculture
Economic Growth and Development
6.49
article

Information and communication technology (ICT) and agricultural sector productivity: empirical evidence from Somalia

Murni Mahmud, Husein Osman Abdullahi, Bile Abdisalan Nor
article en
2 citations

Abstract

Agriculture is the backbone of Somalia’s economy, contributing more than 75% of GDP and 93% of total revenue. Using an Autoregressive Distributed Lag (ARDL) model covering the period from 1990 through 2019, this study examines the relationship between ICT adoption and agricultural productivity in Somalia. The results show that ICT has a positive and significant relationship with agricultural productivity, indicating that ICT adoption contributes to higher production efficiency, greater land productivity, and improved labour productivity. Conversely, environmental degradation and population growth adversely affect agricultural productivity, suggesting that increased emissions and growing populations negatively impact the sector. The short-term results of the error correction model (ECM) indicate that ICT and population growth show a statistically significant positive correlation with agricultural productivity in the short term. In contrast, environmental degradation shows a positive and statistically significant relationship with agricultural productivity. This might be due to short-term adaptation strategies or increased input use. The study suggests important policy implications for stimulating agricultural development in Somalia. The government should promote investment in ICT-related infrastructure in Somalia, as this has the potential to enhance the performance of the country’s agricultural sector.

Cogent Food & AgricultureVol. 11(1)
International Islamic University Malaysia (MY), SIMAD University (SO), Institute of Finance and Banking (CN)
Openalex Percentile: Top 3%
Economic Growth and Development
6.49
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Information and communication technology (ICT) and agricultural sector productivity: empirical evidence from Somalia — Murni Mahmud, Husein Osman Abdullahi, et al. · Cogent Food & Agriculture (2025) | TGRS Research Map | TGRS