No abstract

Understanding to what extent and speed agricultural commodity price changes on international markets are transmitted to consumers is key in assessing the vulnerability of households to price shocks. The importance of these transmission indicators is compounded, in developing countries, by the fact that consumers tend to spend a higher proportion of their income on food items. Regional estimates of food inflation transmission can also be used to predict consumer-level impacts of international price shocks, contributing to improve the information basis on which to base policy mitigation actions and to focus on the areas likely to suffer the most. The aim of this paper is to provide estimates of the transmission of price changes from international commodity markets to consumers in different regions of the world, using monthly data from FAO's Food Price Indices and Regional Food Consumer Price Indices. This econometric analysis, which uses impulse response functions from error-correction models, is useful in establishing typologies of regions with respect to the extent and speed of price transmission processes.

This study utilized a Stochastic Frontier Analysis to determine the effect of irrigation modes on Technical Efficiency of rice farmers in Mali. The survey data have been collected from 552 farmers in three rice mainly production regions during the campaign 2014-2015. The translog model is used to fit data using frontier 4.1and Stata 14 software. The results indicate that coefficient of irrigation by immersion is significant and positive which imply it influences negatively the Technical Efficiency. Meanwhile the coefficient of irrigation with total water mastery by gravity which is significant and negative influences positively the Technical Efficiency. Variables such as ownership to Segou's region, chemical fertilizer also influence positively technical efficiency, but the use of organic fertilizer have a negative influence on technical efficiency which might be explained by the insufficient quantity and bad use of it. The average Technical Efficiency of 0.67 which suggesting potential production gains with available resources and existing technologies.

While there is growing awareness of the issue of food losses at the political level, official post-harvest loss data for informing policymaking and reporting on SDG Indicator 12.3.1. (a) Food Loss Index is scarce. Representative sample-based surveys are necessary to obtain information on on-farm losses at the country level, but due to the issue’s complexity, a loss module covering several key questions is needed. One main strategy proposed by the 50x2030 Initiative for optimizing data collection is sub-sampling for some of the survey modules. This paper examines whether modelling approaches can be combined with sub-sampling to improve harvest and post-harvest loss estimates and allow for further sample and cost reduction. The paper first presents the loss models generated on four selected surveys conducted in Malawi, Zimbabwe, and Nigeria, which were built using the Classification and Regression Tree (CART) method. The performance of each model is assessed for different sizes of sub-samples to improve the sample-based estimates, either by model-based estimates or by model-based imputation. The research concludes that the model-based estimates improve the loss estimates of the sub-samples due to post-stratification implied in the CART method, whereby they can constitute a cost-effective complement to sub-sampling strategies, while model-based imputations should only be used on a reduced number of missing observations. The models perform best when the survey invests in obtaining more detailed on-farm loss data and considers some key variables identified as relevant for on-farm loss models. Sub-sampling allows for investment in more detailed questionnaires and some considerations are derived for its design.