The impact of armed conflict on agricultural production the case of Libya: 1970-2017

Bdawi, Elbahlul, author
Hoag, Dana, advisor
Graff, Gregory, committee member
Kling, Robert, committee member
Boone, Randall, committee member
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Colorado State University. Libraries
I examine the long-term impacts of a recent civil war on the agricultural sector within Libya. Due to the associated destruction and market disruption, armed conflict affects the agricultural sector in complex ways including reducing future growth potential by eroding physical and environmental capital. Libya, with its arid climate, low soil fertility and low agricultural productivity, represents an underdeveloped sector that minimizes the inherent complexity to investigate this impact. However, governmental interest in the agricultural sector has been inconsistent as the dominant oil revenue compensates for agricultural deficits through large subsidies. This absence of attention and oversight has resulted in a lack of quality agricultural data, making it difficult to develop beneficial policies to improve sector growth. Based on its simplicity and ease of interpretation, a Cobb-Douglas style production function with Solow-Swan modification is used to characterize the agricultural sector. Though limited, data was collected from FAO and ILO on land, irrigation, fertilizer, machinery, and labor in Libya spanning from 1970 to 2017 covering periods of stability and conflict in order to estimate agricultural sector growth compared to the status quo. To account for the long-term impacts of conflict on growth, inputs are divided into environmental capital, physical capital, and labor. Next, elasticity parameters are estimated through an OLS regression of the Cobb-Douglas production function before and after conflict. A Chow/QLR test is used to confirm the existence and timing of the structural break in the production function arising at the onset of the 2011 conflict. Finally, the impact of post-conflict growth rates are compared using the pre-conflict and conflict regression parameters. Changes in the estimated parameters from the start of the conflict were significant at the 5% level for both the labor and physical inputs, while the environmental elasticity parameter change was not significant. The conflict elasticity estimates were -0.518, -0.803, and -18.9 for the Physical, Environmental and Labor inputs, compared to their pre-con ict values of 0.107, 0.146, and 1.315, respectively. The two key questions are whether the growth path can recover to pre-conflict levels and the associated production losses resulting over the period the sector takes to return to those pre-conflict rates. A preliminary cost-analysis was applied to estimate the required investment to generate an increase in agricultural GDP. The most cost-efficient way to increase the production after conflict (under the assumption of a return to pre-conflict elasticities) is to increase the quantity/quality of fertilizer used. Increasing machinery is the least efficient way to grow the sector GDP. This may reflect two realities in Libya: weak soil quality and inefficient use of machinery, due to diseconomies of size with smaller plots. Lessons from conflicts in other post-conflict countries suggest that a necessary but insufficient condition is the application of good agricultural policies to rebuild the sector. New policies could improve agricultural returns to surpass losses due to conflict if post-conflict productivity is improved. These policies must be combined with good management and reliable data to effect positive changes within the sector. In Libya's case, the primary post-conflict policies should include improving data collection and focusing on increased education and training to enhance the agricultural sector's rehabilitation. I estimated 3 specific scenarios of the post-conflict future consisting of business-as-usual (BAU), a scenario with convergence between the pre-conflict and post-conflict growth paths within 50 years, and another with a convergence of 20 years. Based on the experiences of other post-conflict countries, Libya's agricultural production will likely converge back to the pre-conflict agricultural GDP trajectory within 10-15 years, so long as there is a minimal transition period and agricultural policies are consistent and well managed. The expected cost to the economy is measured by the discounted difference between the pre-conflict trajectory GDP and the estimated post-conflict GDP until the convergence point. For the likely 20 year convergence, there is an estimated opportunity cost of USD2010 25.0 billion. Should the sector return to business-as-usual, the present discounted value of the conflict is USD2010 49.0 billion. The impact of the conflict is lessened by poor productivity before the conflict. It appears that the conflict slowed business-as-usual, but did not significantly erode environmental capital, which would further cripple the recovery.
2022 Spring.
Includes bibliographical references.