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Beside the mixed evidences on transmission of international food price volatility to local markets and the desirability or otherwise of reliance on stabilisation policy to cushion the effects, very little is known about the key drivers of price spikes and volatility in sub-Saharan Africa. This paper is an attempt to bridge this gap, by focusing on the patterns, drivers, and policy responses to food price spikes and volatility across in Nigeria. The study was based on 16 years panel data on average monthly prices (2001:1 - 2016:12) of major food commodities across local markets in the 36 States of Nigeria, supplemented with monthly series of relevant domestic policy variables, and international prices, among other factors. Data analysis was mainly within the framework of fixed effects models. Findings suggest that food price upsurges in an average Nigeria market is more strongly related to spikes than volatility. International factors such as crude oil price, international food prices, and global beginning stock to use of coarse grains, and domestic policy variables such as real exchange rates, monetary policy rates and narrow money are strong influencers of spikes in the price of one or more food commodities in Nigeria's local markets. Higher petrol price and food production variability may substantially advance price instability in local food markets. Government policy actions at addressing volatile food prices immediately after the 2007/2008 food crises appeared to enhance food price stability. These findings call for greater attention on management of monetary policy, including the exchange rates, ensuring stable petrol price, limiting food production instability, mitigating spill-over of price upsurges from international markets and building farmers and consumer's resilience against food price changes, among others, as important pathways to address short and medium-term food price upsurges.

This paper provides a general overview of the current status and key challenges of the Ethiopian wheat value chain. Wheat is an important staple food crop in Ethiopia. Improving wheat production and productivity is therefore a key part of the agenda in the Ethiopian government's food security policy programs. Policy interventions that aim at improving wheat production or agricultural production for that matter, however, require interventions beyond the farm-at the whole wheat value chain. Both domestic production and import-the two key sources of wheat grain supply to the Ethiopian wheat value chain-have shown a substantial increase since the mid-1990s. Yet, a steady increase in domestic wheat consumption has resulted in rising wheat and wheat product prices over the past two decades. For instance, wheat grain, wheat flour as well as wheat bread prices have all more than doubled between 2000 and 2013. Using a qualitative survey of selected wheat value chain actors and a review of existing literature, this study provides an overview of the wheat value chain, institutional and marketing arrangements, and trader behaviour of wheat value chain actors in Ethiopia. The wheat value chain consists of multiple actors that include several smallholder farmers and the Ethiopian grain trade enterprise (EGTE) at the upstream and urban and rural consumers at the other end. The study stresses the need for formulation of market-enhancing policies, such as quality control and dispute settlement mechanisms as well as better access to market information, to improve wheat productivity as well as marketing efficiency.

Forecasting food production is important to identify possible shortages in supply and, thus, food security risks. Such forecasts may improve input allocation decisions that affect agribusiness and the input supply industry. This paper explains methods and data used to forecast acreage of four crops that are particularly important staple commodities in the world, namely wheat, corn, rice, and soybeans for major global producer countries. It focuses on forecasting acreage-one of the two major determinants of grain production-3 months before planting starts with publicly available data. To this end, we use data from the period 1991 to 2013 and perform an out-of-sample forecast for the year 2014. A particular characteristic of this study is that the respective acreage determinants for each country and each crop are identified and used for forecasting separately. This allows accounting for the heterogeneity in the countries' agricultural, political, and economic systems through a country-specific model specification. The performance of the resulting forecasting tool is validated with ex-post prediction of acreage against historical data.