Introduction:

The agricultural sector is central to the Moroccan economy as illustrated by the share of the sector in GDP (between 12.2% and 15.5%, depending on the year and climatic conditions). Furthermore, the sector is the largest employer in the country (around 40% of active work force) and employing around 75% of active population in rural areas; and 5% of GDP got from agribusiness, which contributes to 2% of Moroccan exports. However, a series of constraints undermine the central role of agricultural central. This includes economic, social, and sustainable development issues.

Economic issues   :

The Moroccan economy is heavily dependent on agriculture so that the GDP is volatile, especially with drought and climatic conditions being even more severe with climate changes. The overall negative food trade balance implies weaknesses on at least 3 levels: insufficient participation in the World agricultural trade, mainly with products with high added value and high productivity; poor distribution systems to meet changes in consumers’ preferences; and low capacity to adapt to international requirements in productivity and competitiveness. Compared with Mediterranean neighboring countries, Morocco experiences very high share of active population (40% vs. 19% in Tunisia and 6% in Spain) with the lowest agricultural productivity. Additionally, increase in agricultural production is due to overuse of lands rather than improvement of productivity, with predominance of sectors with low added value, low use of credits due to high transaction costs , weakness of subsidies (only 5% of farmers vs. over 30% in the EU and 20% in the U.S.); and low public and private investment.

Social and sustainable development issues:

18 million of rural people depends upon agriculture with more than 82% of their revenues are related to agriculture but poverty is the main factor since low average incomes represents the bulk of rural incomes (more than 80%), and over 80% of the land located in arid/semi-arid areas with rainfall variability and decline. In the medium term, about 63% of hydraulic basins in Morocco will be under stress or experiencing water deficit due to overexploitation of groundwater. Besides, water is inefficiently used as 80% to 90% of water is used by agriculture so that Morocco will be experiencing unsustainable water use in the long term, with the increased competition between different uses. Additionally, the agricultural sector has a complex land tenure system with the predominance of small land holdings (70% of farms with less than 2.1 ha) and land fragmentation.

The Argane tree (Arganeia spinosa) is an endemic plant in Morocco and the production of Argane oil has historically been one of the most important sectors in the Moroccan economy. Argane forest area, covers 867,000 ha, is second in coverage after cork oak tree. The usage of Argane is various, which includes firewood and charcoal for heating and cooking, wood for carpentry and construction, fodder for animals, oil for culinary, cosmetic and medicinal purposes. The production of Argane oil has a labor intensive aspect, which provide 800 thousand working days per year for collecting its fire-woods, and provide 20 million working days per year for extracting the oil. Argane oil is produced mostly by women’s cooperatives and 90% of rural economy of Argane forest region depends on Argane related products (Lybbert, Barrett and Narjisse, 2005).

Analytical framework   :

The development of Argane project is considered part of Pillar II, to upgrade poor & low value agriculture. This pillar is targeting 600 000 to 800 000 farmers, with initial investments of 15 to 20 billion DH and 300 to 400 projects. Even these figures will change after the declaration of the newly appointed government of Morocco, the Argane value chain is considered as part of the niche projects because of its high value among the value chain, social investment and agricultural poverty alleviation, especially among women in the Argane regions. Argane projects can be considered as part of pillar II Projects because they are agricultural projects that are area specific, integrating the whole value chain (upstream and downstream), economically viable, based primarily on direct intervention of the State in marginal areas with focus on the adherence and professional organization of the beneficiary population, especially women, and taking into consideration natural resource management and environmental dimension. This section presents the analytical framework employed in this study: technical efficiency of Argane oil production, Cost Benefit Analysis of Argane projects and sampling method and design of survey instruments.

Technical efficiency of Argane oil production:

The measurement of technical efficiency have become common framework with the development of the Stochastic Production Frontier (SPF) models by Aigner, Lovell and Schmidt (1977) and Meeusen and Van don Broeck (1977). Technical efficiency of ith firm is estimated by the difference between maximum possible output and observed output. A change in technical efficiency shows the movement of the firm’s actual output to its maximum possible output, given the technology. In this methodology, production frontier represents maximum possible output with the given technology and the quantity of inputs, and actual level of production is assumed to be less than the frontier due to technical inefficiency and a random shock on production. In this sense, the production of Argane oil is assumed to be stochastic phenomenon, depending on characteristics of the oil extraction process such as hand-pressing and mechanical technology.

Cost Benefit Analysis of Argane projects:

Cost-benefit analysis (CBA) is an approach used to evaluate the Argane project. This approach will ensures that the Argane project gives sufficient incentives to producers, and minimum costs are used to achieve the project objectives, and the project is the best sustainable and economically feasible alternative. The analysis will seek whether the distribution of costs and benefits is consistent with project objectives. CBA will be used at different decision making: production models, farm models, and project levels.