# **Notes**

1 This section draws heavily on Aker (2010).

> 2 Aker (2008) shows that grain traders store an average of one week, with larger traders (wholesalers) storing for an average of one month. Storage duration data were not available by commodity. Farmer-level data collected by one of the authors suggests that farmers primarily produce cowpea as a cash crop and sell soon after the harvest, thus implying limited storage, and store millet and sorghum for longer periods.

> <sup>3</sup> In surveys with agricultural traders and producers between 2005 and 2007, an overwhelming majority stated that they did not access or use price information provided Agricultural Market Information System (AMIS), primarily because of the type of data (only consumer prices are provided) and the timing of the data diffusion (the data are provided weekly, in some cases six days after a market).

4 Based on one of the author’s interviews with mobile phone service providers in Niger. The primary priority borders were those in the southern areas of the country (Nigeria, Burkina Faso, and Mali) rather than the north (Libya, Algeria).

> <sup>5</sup> Figure 1 is similar to Figure A1 Aker (2010), but it extends the data until 2008 and adds data on road quality. 6 Since 2008, mobile phone coverage and adoption have expanded considerably into rural areas in Niger. The 2009 survey conducted by one of the authors revealed that mobile phone ownership had reached 29 percent in rural areas. 7 Jensen (2007, 2010) develops a model outlining the welfare implications of costly search under exogenous supply, focusing primarily on the producer’s perspective.

8 Agricultural traders in Niger also typically relied upon personal travel to obtain price information prior to the introduction of mobile phones.

9 In 2008, a two-minute call to a market located 10 km away cost US$.50, compared to US$1 for round-trip travel using a market truck or cart.

10 This scenario encompasses two possibilities. The first is that traders and markets are placed at regular intervals on a lattice or Taurus, and traders cover partially overlapping geographical areas. The second is that _n_ traders cover the same _n_ producer markets and sell in the same consumer market.

> 11 Systematic differences in _F_ ( _q_ ) across markets would generate systematic differences in average price. However, in the first approximation, this should not affect the spatial integration of prices.

12 We only consider symmetric equilibria (thus ruling out a situation whereby traders coordinate on a public randomization device), which implies that the only Nash equilibria is for each trader to randomize among each market with equal probability.

13 To illustrate our model, assume that traders receive no information about market prices, and imagine that the agricultural commodity can be stored by farmers. Consider farmers in market _m_ who are offered a low price because few traders happen to visit market _m_ on that day. Rather than selling at a low price, they can store and sell later, when more traders visit the market. In this case, intertemporal arbitrage will smooth prices in market _m_ across time (Williams and Wright 1991). As a result, prices in different markets cannot diverge simply because the number of traders who visit each market varies in a stochastic manner.

14 Because sorghum requires more rainfall than millet, it is grown in fewer geographic locations in Niger, primarily in the southern areas of the country. As a result, sorghum price data are available for fewer markets and during fewer periods and hence are subject to more missing observations than the cowpea or millet producer price data. 15 These data were obtained from the _Syndicat des Transporteurs Routiers_ , the _Direction de la Météo_ in Niger, and the trader survey. The data are the same as those used in Aker (2010), but are extended for an additional two years (from 2006 to 2008).

16 Various dependent variables have been used in the literature to measure price dispersion. The consumer search literature has used the sample variance of prices across markets over time (Pratt, Wise, and Zeckhauser 1979), the coefficient of variation (CV) across markets (Eckard 2004; Jensen 2007), or the maximum and minimum prices across markets (Pratt, Wise, and Zeckhauser 1979; Jensen 2007). The international trade literature has used the log of the price ratio between two markets or the standard deviation of price differences across markets (Engel and Rogers 1996; Parsley and Wei 2001; Ceglowski 2003; Aker 2010). We adopt the latter approach for our core specification, but we also use the CV and the max-min as alternative specifications.

17 In all specifications, “treatment” is defined as the presence of a mobile phone tower rather than mobile phone adoption (Aker 2010).

18 A market’s urban status did not change between 1999 and 2008, so this is controlled for by including market pair and market fixed effects. Road quality in Niger was fairly stagnant during the time period under consideration. In 1995, Niger had 3,526 km of paved roads, increasing to 3,761 km in 2008, with the primary improvement occurring 23