volatility prevailing in one local market are very much correlated with the “central market price history”, while prices observed in the other local market are more related to “local price history”, the difference being explained by different transport costs. However, their analysis is based on two local markets ( <mark>one that is integrated and close to the central market and one that is less integrated and further located</mark> ) and does not <mark>allow to gauge the statistical effect of the degree of interdependence between local markets and the central market on price volatility. Furthermore, in</mark> their study, transport costs are not directly used as explanatory variables of price volatility in local markets, but are rather suggested through spatial price spreads between central and local markets.

Our study borrows from **Badiane and Shively (1998)** , but departs from their work in the sense that it measures interdependence between markets by using distance to major cities<sup>3</sup> (expressed in kilometers and hours) and road quality, both variables being proxies for transport costs. We explain spatial volatility differences across markets through the inclusion of explanatory variables that are directly related to transport costs.

The paper is organized as follows. In section two, we introduce a simple price-modeling framework that allows us to establish that high price volatility stems from changes in transport costs between rural and urban markets. In section three, we present the context of maize price and production in Burkina Faso. Maize is widely consumed throughout the country and maize production has significantly increased recently: it is the second source of income for farmers, after cotton. As volatility may hinder investments in agricultural production, understanding and analyzing maize price volatility is of strategic in Burkina Faso, for food security as well as for rural development more broadly. In section four, we present our empirical strategy to analyze the effect of market remoteness on price volatility, based on the estimation of an autoregressive conditional heteroskedasticity model adapted from **Shively, 1996** and **Maître d’Hôtel et al., 2013** . In section five, we finally deliver our empirical results by exploring a database of maize prices in Burkina Faso on 28 markets<sup>4</sup> over 2004-2013. We find robust evidence that maize price volatility is greater in remote markets. This result validates the empirical relevance of our conceptual model.

> 3 ‘central market’, ‘main cities’, ‘major cities’, ‘major consumption centers’, ‘urban consumption centers’ and ‘urban market are used synonymously in this paper, all referring to the leader market i.e. the capital city (Ouagadougou) and largest cities with a population of more than 100, 000 (Bobo-Dioulasso and Koudougou). 4 A market is defined as the meeting place between local farmers and traders, including intermediaries, wholesalers and semi-wholesalers who transport and deliver maize at consumption centers. It is worth noting that there also exist consumer and wholesaler markets where traders and consumers meet. Among traders, wholesalers are usually those who are responsible for inter- and intra-regional trade, by selling commodities to other wholesalers, retailers and consumers.

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