Weinstein, 2008).<sup>4</sup> However, compared to a large strand of this literature, we have the advantage of having data available for similar homogenous goods across markets instead of broad price indexes or prices of differentiated goods By providing accurate estimates of firms’ price changes and price stickiness at the product level, Imbs et al. (2003), Bils and Klenow (2004) and Nakamura and Steinsson (2008) have shown that pricing behavior can only be precisely studied by using price level data at the product level. Moreover, Broda and Weinstein (2008) underline that using prices at the product level leads to more accurate estimates of border effects and allows the level of market integration to be assessed through the absolute value of relative prices in level, which is a direct measure of deviations from the law of one price. That is why we use the absolute value of relative price to measure market integration. This indicator has been less popular in the literature because of the higher demands on the data, in particular with regard to highly disaggregated data. However, recently it has been used by Versailles (2012), Grafe et al. (2008) and Broda and Weinstein (2008), among others.

Despite their potential importance, border effects and regional market integration in low income countries have not been the subject of much research, in particular because of the requirement of high-frequency data on narrowly defined goods. In the Eastern and Southern Africa region, research efforts have focused on analyzing integration of agricultural markets at an intra-country level (Tostão and Brorsen, 2005; Atkin and Donaldson, 2013; Zant, 2013; Myers, 2013). Limited work has gone into evaluating how well integrated markets are at the regional level (Araujo and Brunelin, 2013; Mutambatsere, 2007; Versailles, 2012).

Among these papers, Versailles (2012) uses a similar approach to that adopted in this paper and measures the extent to which distance and border effects explain the lack of market integration between 39 cities located in Uganda, Rwanda, Burundi and Kenya for a large range of products. Araujo and Brunelin (2013) estimate the effect of distance and of border impediments on the standard deviation of relative prices in fourteen countries of West Africa for three to five staple foods between 2007 and 2011. Aker et al. (2012) estimate also the border effect between Niger and Nigeria for staple foods. As discussed below, compared to this literature, the magnitude of our estimated border effects on relative prices are similar to the findings of Versailles (2012) for staple foods and as in Aker et al. (2012) and Araujo and Brunelin (2013), we find also a strong effect of distance on market integration.

Gorodnichenko and Tesar (2009) make an important critique of the methodology used to assess border effects from price-data. They point out that if relative price variability across locations within the same country differs systematically country-by-country, the border effect measured by a regression comparing within-country and cross-country price dispersion will be confounded by the divergence between two countries' internal price distributions. This is particularly relevant when evaluating border effects between a wide range of African countries, which are particularly

> 4 This paper also builds on studies that estimate trade costs using price differences between cities (Atkin and Donaldson, 2013; Zant, 2013) and on the literature which measures market integration based on the spatial price equilibrium conditions using probability bounds models or threshold auto-regression models (Baulch, 1997; Zant, 2013; Myers, 2013).

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