Agriculture constitutes the core sector of Rwandan economy. One decade ago, the contribution of
Agricultural Sector to the Gross Domestic Product of Rwanda oscillated between 39 and 33 percent
(NISR, 2013). The agricultural sector, also, accounts 85 percent of employment and 80 percent of the
foreign earning from the export of primary products. About 48.8 percent of households in the country earn
income as farm wage and income from agricultural accounts 45.7 percent of the total household income
(NISR, 2011). Agricultural development, however, has provided a crucial foundation for economic growth
in both agricultural and non-agricultural sectors.
Recent changes and reforms in Rwandan agricultural policies, formulated since 2000, have emphasized
on transforming agriculture sector from subsistence level into a modernized and more industrial and
market oriented agricultural sector. The Vision 2020 launched in 2000, considers the agricultural sector
as the principal source of economic growth of the country with an anticipated growth of between 5 - 6
percent each year to reach an overall economic growth of 7 – 8 percent projected in 2020, it has therefore
placed greater emphasis on improving agriculture productivity (MINAGRI, 2009).
As widely documented in the economic literature, policy changes and reforms adoption should improve
the functioning of agricultural markets and enhance commodity market performance. Therefore,
agricultural policy changes and reforms in the country have contributed to the decline of yield and crop
production instability, improvement in food distribution system, investing in new products that can
generate more revenues and has facilitated households to access foodstuff at fair prices. Nonetheless,
food prices from 1998 to 2014 show sudden and sometimes tremendous food price variations. Hence,
uncertainty surrounding the prediction of food prices represents a vital opportunity for commodity
modelers to analyze and provide information on food price volatility and inform policymakers and decision
takers on food market dynamics and their causes.
Using monthly data of food prices, this paper employs ARCH and GARCH models to analyze food price
volatility in the domestic markets. Vector Auto regression (VAR) and Vector Error-Correction Models
(VEC) are used to appreciate food price transmission and to characterize the joint dynamic behaviour of
different time series of selected food commodities. Traditionally, food market analysis is oriented in terms
of analyzing food price transmission from the world market to the domestic ones. Trying to evaluate the
impact of different reforms and policies undertaken by the government of Rwanda, domestic market
functioning and analysis of domestic food price volatility levels constitute an originality and a value added
of this paper.