We analyse the impact of land tenure security on the technical efficiency of a sample of smallholder farmers in Benin, based on an output‐oriented stochastic distance function. We use propensity score matching to correct for selection bias from observed variables. The Greene () sample selection model is used to correct for selection bias due to unobserved variables. We estimate meta‐frontiers to analyse agricultural productivity and efficiency differences between landowners and non‐owners. Our results show that non‐owners have consistently higher levels of technical efficiency and productivity.

The reference model that we used in this article is the multinomial endogenous treatment effects model developed by Deb and Trivedi (2006). We hypothesize that farmers seek to maximize their utility 𝑉 𝑖𝑗 by comparing it with the utility provided by the alternative land tenure arrangement. Thus, a farmer i chooses a land tenure arrangement j as opposed to all other land tenure arrangements k if and only if 𝑉 𝑖𝑗 > 𝑉 𝑖𝑘 , 𝑗 ≠ 𝑘.Following Deb and Trivedi (2006), let EV* denote the indirect utility associated with the j th land tenure arrangement j= 0, 1, 2,…., j with j being a positive integer and:

In this study, we analysed factors that influence crop output commercialisation among smallholder farmers in Cote d'Ivoire. Unlike previous studies, we correct for sample selection bias by using the Heckman maximum likelihood sample selection model with village fixed effects. We rely on a unique and detailed dataset that covers 3,393 smallholder farmers. The dataset was gathered from the 2014 National employment survey collected by the National Institute of Statistics (INS) Côte d'Ivoire. Results from the study suggest that cooperative membership and land tenure security raise the level of marketed outputs of Ivorian farmers. Female headed households sold lower proportions of their outputs than their male counterparts. Labour shortage is a major constraint to crop output commercialisation. From a policy perspective, the Government should revive its interest in collective actions such as cooperatives, facilitate farmer's access to credit, improve food crop productivity and enhance mechanization.

The Policy Research Working Paper Series disseminates the findings of work in progress to encourage the exchange of ideas about development issues. An objective of the series is to get the findings out quickly, even if the presentations are less than fully polished. The papers carry the names of the authors and should be cited accordingly. The findings, interpretations, and conclusions expressed in this paper are entirely those of the authors. They do not necessarily represent the views of the International Bank for Reconstruction and Development/World Bank and its affiliated organizations, or those of the Executive Directors of the World Bank or the governments they represent.

The 2014-15 Ebola epidemic took a devastating human and economic toll on three West African countries, of which Liberia was perhaps the hardest hit. The pathways through which the crisis affected economic activity in these largely agrarian societies remain poorly understood. To study these mechanisms in the context of rural Liberia, we link a geographically disaggregated indicator of Ebola disease mortality to nationally representative household survey data on agricultural production and consumption. We find that higher Ebola prevalence (as proxied by local mortality) led to greater disruption of group-labor mobilization for planting and harvest, thereby reducing rice area planted as well as rice yields. Household welfare, measured by per capita expenditures spanning two points before and after the crisis, fell by more in Ebola prevalent areas with more intensive rice-farming, precisely those areas more adversely affected by agricultural labor shortages.

The Farm Income Stabilization Insurance Program (ASRA) is an agricultural program implemented in several agricultural sectors in Quebec, including the pork sector. This article aims to empirically assess the effects of this program on production decisions in the pork industry in Quebec using a Vector Error Correction Model (VEC). As variables we used the pig supply, the price of pork, and stabilized income. The dataset contains information about the pork sector which cover the period 1981-2014. The annual average growth rate of the quantity offered in this period is 5.24%. The results suggest that the supply of pork is strongly correlated with lagged values of stabilized income. The results also show that there is only one long-term relationship between the three variables above-mentioned. By contrast, in the short term, an increase of one percentage point of the stabilized income leads to an increase of 0.80 percentage point of pork supply in the next period while an increase of one percentage point of pork price will result to a decrease of 0.47 percentage point of the production. Pork production decisions are dominated in short-term by the presence of ASRA program. This shows evidence that without the ASRA program, pork production would be less. These results confirm some of the criticisms of this program. Thus, through this article we suggest a compensation indicator which internalizes market signals in order to improve pork industry efficiency. Simulations of the compensation indicator were also performed. The adoption of this indicator as a measure of compensation for the ASRA program will generate an efficient production system, reduce the deficit of the program, and improve the competitiveness of pork industry. This indicator can be applied to other agricultural sectors covered by the ASRA program.

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Irregular and low rainfall levels and drought have become important sources of low agricultural yields and agricultural incomes in sub-Saharan Africa. Weather index insurance is a financial product for climate risk management aimed at securing farmers' incomes. This paper aims to evaluate the impact of a weather index insurance project piloted with groundnut farmers in Senegal in 2015-2016 agricultural season on farmer's technical efficiency (TE). A Stochastic Production Frontier model was used to estimate the TE scores. A matched group of beneficiaries and control farmers was determined using propensity score matching techniques to mitigate biases stemming from observed variables. The results showed that average TE is consistently higher for control farmers than the beneficiary group. Age, gender and education were found to be significantly related to technical efficiency, while membership in farmers' association, credit, improved seeds and extension contact were not significantly related to technical efficiency. From a policy perspective, we suggest that weather index insurance programs targeting smallholder farmers in developing countries, and particularly in sub-Saharan Africa, be accompanied with education services, provision of new technologies such as high yield seeds and other best farm management practices and credit to help farmers better adapt to weather shocks and secure their production and income.