How Strong Do Global Commodity Prices Influence Domestic Food Prices in Developing Countries? A Global Price Transmission and Vulnerability Mapping Analysis

This paper analyzes the transmission from global commodity to domestic food prices for a large set of countries. First, a theoretical model is developed to explain price transmission for different trade regimes. Drawing from the competitive storage model under rational expectations, it is shown that domestic prices can respond instantaneously to global prices even if no trade takes place but future trade is expected. Using a global database on food prices, we construct national and international grain price indices. With an autoregressive distributed lag model, we empirically detect countries in which food prices are influenced by global commodity prices, including futures prices. Mapping transmission elasticities with the size of the population below the poverty line which spends typically a large share of its income on food, we are able to estimate the size of vulnerable population. Our empirical analysis reveals that 90 percent of the global poor (income below 1.25$/day) live in countries where domestic food prices respond to international prices - but the extent of transmission varies substantially. For 360 million poor people, international prices transmit to their country at rates of 30 percent or higher within three months

Stimulating innovations for sustainable agricultural practices among smallholder farmers: persistence of intervention matters

Published online: 17 Apr 2022As part of the dissemination of sustainable intensification (SI) of agricultural practices in northern Ghana, farmers were conditionally induced with inputs to adopt the SI practices. We study the effects of the conditional inducement on maize yield and net income of farmers under a quasi-randomised phase-out design. We examine the effects of the inducement by comparing continuous induced farmers with past induced and non-induced farmers. Our results indicate that the conditional inducement led to an increase in the maize yield and the net income of continuously induced farmers, on average. Estimates also suggest that the continuously induced farmers would have had their maize yields and net incomes decreased by about 64 per cent and 54 per cent, respectively if the inducement had been discontinued. Distributional analysis reveals that the inducement effects are heterogeneous and that past inducement impacted more on the maize yield and the net income of farmers at the lower quantiles. We conclude that appropriate conditional inducement can stimulate farmers’ adoption. Besides, the duration of intervention matters and must not be overlooked in interventions that necessitate gaining experience and learning

Scaling-up agricultural technologies: Who should be targeted?

Open Access Article; Published Online: 18 December 2021The effects of agricultural technology adoption on farm performance have been studied extensively but with limited information on who should be targeted during scaling up. We adopt the newly defined marginal treatment effect approach in examining how farmers’ resource endowment and unobserved factors influence the marginal benefits of adopting sustainable intensification (SI) practices. We estimate both the marginal and average benefits of adopting SI practices and predict which marginal farm household entrants will benefit the most at scale. Findings indicate that farmers’ resource endowment and unobserved factors affect the marginal benefits of adopting SI practices, which also influence maize yield and net returns among adopters. Finally, results imply that scaling up SI practices will favour farm household entrants associated with the lowest probability of adoption based on observed socioeconomic characteristics