This paper uses comprehensive and long time series monthly food price data and a panel dyadic regression framework to evaluate the impact of the COVID-19 pandemic and associated policy responses on spatial market integration across a diverse set of food items in Nigeria. The empirical results reveal several important insights. First, we show that a significant slowdown in the speed of adjustment and price transmission occurred during the pandemic. For some food items, the speed of adjustment and, by implication, spatial market integration weakened by two- to-threefold after the pandemic outbreak. The effect was specially pronounced for perishable food items. Second, lockdown measures and the spread of the pandemic triggered additional dispersion in market prices across markets. For example, lockdown measures were associated with a 5–10 percent reduction in the speed of readjustment toward long-term equilibrium. Third, additional underlying attributes of markets, including lack of access to digital infrastructure and distance between markets, exacerbated impacts associated with the pandemic. For instance, access to Internet service reduced the slowdown in the speed of adjustment caused by the pandemic, but longer distances between market pairs induced greater slowdown in the speed of price transmission. Our findings offer important insights for revitalizing the efficiency of food markets affected by the pandemic. The heterogenous impacts of the pandemic across value chains and markets reinforce the need to properly target post-pandemic recovery interventions and investments. Finally, we offer some insights to reduce the vulnerability of food and market systems to disruptions in future pandemics or similar phenomena that inhibit food marketing and trade.

This study focused on measuring spatial market integration between urban and rural food markets in South Africa. The study was influenced by continual debate on the issue of high food price increases among the basic agricultural foods which have impact on food price differentials that exists in market locations. Higher food price differentials between market locations can have negative implications for households’ livelihoods. In South Africa the majority of lower-income earners live in rural areas, which implies that the disposable incomes of those households are affected differently by higher price differentials. To ensure that there are lower price differentials between market locations, spatial market integration is required. The main objective of this study was to measure spatial market integration between urban and rural food markets. This objective was achieved through the modelling of secondary price data of the 2.5 kg package of super maize meal. Data used in the study was collected by the NAMC and Stats SA during the period of November 2006 to July 2012. The study used a co-integration model, together with the Vector Error Correction Model (VECM) and the Autoregressive Distributive Lag (ADL) model. The study revealed that out of the nine markets which were measured for spatial integration, six of the rural food markets were co-integrated with urban markets. Estimation of the six co-integrated markets with the VECM revealed a long-run equilibrium relationship between urban and rural food markets. The VECM results further showed different speeds of price adjustments to the long-run equilibrium which was faster (65% on average) in five markets and slower (40 %) in one market. The fast speed of price adjustment to long-run equilibrium relationships suggests that transaction costs have significant effects on markets linkages. Markets also showed different time of adjustments which was between three and five months. Short-run dynamic effects were found in only three markets and could not be established in the other six rural food markets. Price information flow, transportation costs and transaction costs are seen as bottlenecks that prohibit integration of markets in the short run. With regard to price relationships, the study found statistically significant differences between urban and all rural food market mean prices. This suggested that the price of 2.5 kg maize meal was generally high in all rural markets, as compared with urban markets. Markets with very high price increases were those located in the lower production potential areas of the maize commodity. The Impulse Response Function (IRF) was employed to establish the effects of negative and positive price transmission shocks from the urban to the rural food markets. One standard deviation was put into the model to establish the response of markets to shocks. The markets tested revealed a period of between two and eleven months for the negative and positive impulses to be cleared in all the markets. A high degree of spatial market integration was found when negative and positive shocks did not exhibit price diversion from the long-run equilibrium relationship.

This paper combines pre-pandemic face-to-face survey data with follow up phone surveys collected in April-May 2020 to quantify the overall and differential impacts of COVID-19 on household food security, labor market participation and local food prices in Nigeria. We exploit spatial variation in exposure to COVID-19 related infections and lockdown measures along with temporal differences in our outcomes of interest using a difference-in-difference approach. We find that those households exposed to higher COVID-19 cases or mobility lockdowns experience a significant increase in measures of food insecurity. Examining possible transmission channels for this effect, we find that COVID-19 significantly reduces labor market participation and increases food prices. We find that impacts differ by economic activities and households. For instance, lockdown measures increased households' experience of food insecurity by 12 percentage points and reduced the probability of participation in non-farm business activities by 13 percentage points. These lockdown measures have smaller impacts on wage-related activities and farming activities. In terms of food security, households relying on non-farm businesses, poorer households, those with school-aged children, and those living in remote and conflicted-affected zones have experienced relatively larger deteriorations in food insecurity. These findings can help inform immediate and medium-term policy responses, including social protection policies aiming at ameliorating the impacts of the pandemic, as well as guide targeting strategies of governments and international donor agencies by identifying the most impacted sub-populations.

This book provides fresh insights into concepts, methods and new research findings on the causes of excessive food price volatility. It also discusses the implications for food security and policy responses to mitigate excessive volatility. The approaches applied by the contributors range from on-the-ground surveys, to panel econometrics and innovative high-frequency time series analysis as well as computational economics methods. It offers policy analysts and decision-makers guidance on dealing with extreme volatility.

Small farmers and traders often lack the market information they need to earn the most from their crop sales. This paper analyzes the effects of an action research experiment in central Malawi, in which four groups of smallholder farmers were provided with maize and soybean price information from a local commodity exchange during the 2019 marketing season, while four other groups of smallholder farmers did not receive this information. Using data from a panel survey of 399 farmers and 78 traders conducted before and after the main marketing season and using kernel propensity score matching approach to account for possible differences between the treated and non-treated farmers, we estimate the effects of the intervention on a number of outcome indicators. A before versus after analysis was also employed to evaluate changes in traders’ marketing outcomes. We find positive but statistically insignificant effects on maize and soybean selling prices, sales through structured markets and levels of commercialization after the intervention. We also find a negative and statistically significant effect on the quantity of maize sold by farmers, suggesting paradoxically that providing farmers with price information reduced their sales volumes. The proportion of traders aware of structured markets and their share of sales through structured markets also increased significantly after the intervention. The quantity of maize sold by traders as well as the selling prices for maize and soy-bean also increased significantly, although this may be due to factors other than the intervention. The study concludes that provision of price information alone is not enough to facilitate small farmers’ and traders’ use of structured markets. Greater effort is needed to sensitize farmers and traders on the quality and quantity requirements as well as the operations of structured markets.

This work details grain production, distribution, and marketing statistics from the United States Department of Agriculture.