Conventional tests for food market integration ask, often misleadingly, whether prices in different markets move together. In this paper an alternative methodology, the parity bounds model (PBM) is developed which uses information on transfer costs in addition to food prices to access the efficiency of spatial arbitrage. Monte Carlo experiments using data generated by a point-space spatial price equilibrium model show the PBM to be statistically reliable. An application to Philippine rice markets demonstrates that the PBM detects efficient arbitrage when other tests do not.

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 research examines the extent of market integration among different bean markets across Malawi. Market integration is an indicator that efficiency exists within the flow of information between markets. The study focused on beans as they are a cheap source of protein affordable by the majority of rural smallholder farmers. Market price data for beans was obtained from the Ministry of Agriculture and Food Security and covered the period 1995 to 2011. The markets included in the study are Chitipa, Rumphi, Mzuzu, Lilongwe, Mitundu, Lizulu, Lunzu, Luchenza, and Bangula. Like prices of other agricultural crops, bean prices follow a general seasonal pattern, rising with increasing time since the last harvest and decreasing during the harvest period. Bean prices typically peak in December when bean supply to the market is low. The research results show that beans prices in different markets move in the same direction, meaning that the markets are co-integrated. However, price information is not fully transmitted between markets. Transaction costs were found to be higher in markets which are far away from major cities and in those markets serviced by poor roads. Based on the results, the study recommends the need to improve infrastructure and market information systems to enhance bean market efficiency in Malawi.

Spatial interactions are essential drivers of price transmission mechanisms and may significantly affect any food’s policy outcomes. However, spatial aspects seem to be generally overlooked when analyzing price transmission. This paper attempts to fill this gap by highlighting the usefulness of spatial interaction and models for market integration analysis. A spatial dynamic panel datamodel is presented and applied to Niger’s millet market. Empirical results show that (1) the millet market is partly integrated, (2) locally traded commodities (millet and sorghum) are linked by a cross-commodity price transmission, (3) most imported cereals prices, which for Niger is maize and rice, did not affect the millet market, and (4) no cross-regions price transmissionoccurred for the millet market.