# **3.1 Price Survey**

_Design of Study_

**A systematic difference in retail prices for identical goods in two markets is probably the most reliable indicator of barriers to trade between those markets.** Absent physical and regulatory barriers to trade, price differences will be arbitraged away. This is why we look at prices first.

**For a rigorous comparison of prices on both sides of the river we selected 57 precisely defined products that allowed us to collect and compare prices for “identical” products.** Even on Congolese markets, where the degree of product differentiation is considerably lower than in highincome economies, great care must be taken to compare like with like, i.e. to define meticulously the type and quantity of the good whose price is to be recorded. The 57 goods were chosen in close consultation with local experts so as to offer a representative sample of Congolese consumption baskets. The list of products and summary price statistics are given in Appendix 2.

**Price data were collected carefully from representative samples of retail markets in both Kinshasa and Brazzaville.** We relied on a local expert who recorded prices using a consistent methodology to make prices comparable among vendors, as prices are commonly determined through bargaining. Four large retail markets were selected in each city, two in the respective city center and two in the suburbs.<sup>13</sup> We obtained some complementary price data from the RC Planning Ministry, collected in Brazzaville over the same time period as our own price data, and we consider these data points as our “ninth sample market”. Where possible, prices were recorded for each product from up to three vendors per market.<sup>14</sup> Some of the Brazzaville prices were obtained from wholesalers, and are thus not directly comparable to the prices recorded at the retail level. All prices were recorded in local currency, between 26 August and 3 September 2010. We asked vendors for the origin of their goods, allowing us to classify the goods as locally produced, imported across the river, and imported from overseas. For our estimations, prices are converted into US dollars at the exchange rates prevailing locally in that period.<sup>15</sup> Finally, for goods sold in known weight units, we expressed all prices in terms of dollars per kilogram.

# _Results_

**We use panel data regression methods to estimate systematic price differentials for identical products across markets.** By using this technique, we can formally test the hypothesis that observed price differences across markets are systematic – i.e. “statistically significant” –, meaning that they cannot be explained by random price variation among individual vendors due to a myriad of reasons such as the time of day, the vendor’s available stock at the time of the transaction, the precise quality of the item(s) sold, the vendor’s location within a market, or the vagaries of the haggling process. Moreover, we can control for good-specific “fixed effects”, meaning that price differences across markets are estimated by using only differences within individual products, and thus by comparing like

> 13 Kinshasa center : Marché Central and Gambela; Kinshasa suburbs : Matadi-Kimbala and Liberté; Brazzaville center : Total and Poto-Poto; Brazzaville suburbs : Mikalou and Mongali.

> 14 We could not collect prices for each good in each market. While a balanced sample would comprise 1,539 observations (57 goods * 9 markets * 3 vendors), our maximum sample size is 970.

> 15 1 USD = 910 Congolese francs; 1 USD = 511 CFA francs.

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