Rice is one of the staple foods in the Benin Republic. Annual rice consumption is increasing faster than annual rice production. That is why Benin is not yet self-sufficient in rice production. To meet the local demand, huge quantities of rice are imported. For country planning, forecasting is the main tool for predicting rice variables. This paper describes an empirical study that used a time series modeling approach (Box-Jenkins' ARIMA model) to forecast rice production, rice consumption, rice importation, rice exportation and finally rice self-sufficiency in Benin. Based on ARIMA model, the rice self-sufficiency rate in Benin is forecasted to be 47%, 56%, 58%, 59% and 68% respectively in 2019, 2020, 2021, 2022 and 2023. The forecasts would be helpful for the policy makers to foresee ahead of time the future requirements of rice production, adopt appropriate measures to develop rice sector for effective rice self-sufficiency and to reduce rice importation.

The development of many African countries' economy and life of the rural population in the south of the Sahara depends on the agricultural sector. Seventy to 80% of the active population was employed in the agricultural sector. The contribution of the agricultural sector to the Gross Domestic Product (GDP) of these countries ranged from 30% to 50%. The rural population in these countries has lived under low life standards and in economically unfavourable conditions (Diallo, 2004). In Benin Republic, economic activities were predominantly based on agriculture, and the agricultural sector contributes about 32.5% to GDP, 75% to exports, 15% to tax revenues and about 70% to employment (FAO, 2018). Agriculture is then seen as a sector with many potentials that should be seriously exploited to support national economic growth and thus contribute to the effective fight against poverty.

This research aimed to assess the efficiency of beef cattle markets in the Republic of Benin. Primary data were collected from face-to-face surveys of a random sample of 600 respondents consisting of 300 beef cattle farmers and 300 beef cattle traders participating in self-managed beef cattle markets (MBA) and traditional beef cattle markets (MT). Different marketing channels were identified in the selected beef cattle markets: Channel I, Farmer-Slaughterhouse/Butchery; Channel II, Farmer-Collector-Wholesaler-Slaughterhouse/Butchery; Channel III, Farmer-Collector-Slaughterhouse/Butchery; and Channel IV, Farmer-Wholesaler- Slaughterhouse/Butchery. Channel I appears to be the most efficient in both markets with a marketing efficiency of 2.57 in MBA markets and 1.23 in MT markets. The average marketing efficiencies are 1.25 and 0.97 in MBA and MT markets, respectively. The marketing efficiency analysis showed that MBA markets are more efficient than MT markets. To increase the marketing efficiency of farmers, MT markets should be converted into MBA markets. Facilitating transportation and access to market information are critical factors for increasing farmers' marketing efficiency.

Livestock in West Africa is an example of regional value chain development. It is essentially based on the trade in livestock between production areas and consumption centers. The livestock trade is an important economic activity in pastoral and agro-pastoral communities as it is their source of income. The livestock trade in these regions takes place at several sites, the best known of which are the livestock markets. Two different types of livestock market are investigated in this study. Self-managed livestock markets (Marché à Bétail Autogéré: MBA), are new models for marketing livestock in the Republic of Benin. Unlike traditional livestock markets (Marché à Bétail traditionnel: MT), MBAs offer several advantages to its participants by creating a platform where sellers and buyers can meet to trade without intermediaries. The absence of the intermediary system in the operation of MBA markets makes them different from MT markets. Because of their important role in rural development, MBAs have become the focus of policy makers and international development organizations. The purpose of this study was to analyse the factors that affect farmers' participation in MBA markets. The study used primary data collected from face-to-face surveys of a random sample of 300 livestock farmers consisting of 150 respondents from the MBA and 150 respondents from the MT. Descriptive statistics and Binary Logistic Regression were used to analyze the data. The results of the Logistic Regression Analysis revealed that access to market information, payment type, cooperative partnership, beef cattle herd size, sheep herd size, goat herd size and farmland ownership have significant positive effects on MBA market participation, while distance to market has significant negative effects on MBA market participation. Improving these factors could increase the participation of livestock farmers in the MBAs in the Republic of Benin. This would increase their income and improve their living conditions. Knowledge of the factors influencing participation in MBA markets would also help stakeholders and policy makers in their decision making.