The domestic price data come from Nigeria’s National Bureau of Statistics (NBS), which collect monthly data for 143 food and nonfood items by state in both rural and urban areas. The price data we use cover 2000 to 2010.<sup>14</sup> Our analysis relies on the urban data, assuming that rural prices will be a markup / discounted value of the urban prices. The rural data are not used because the Nigerian classification of the areas into urban and rural has not been updated since 1991, and thus they are not representative of the current division in urban and rural. We use two approaches to determine which price index from the NBS data is matched to which production or consumption item from the household survey. The first is a narrow price match, where the good is matched to price data with exactly the same name. However, the limited number of items in the price data means that relying on a narrow price match alone could exclude potentially important consumption items that have no exact match in the price data. The second approach is a broad price match, where the price of a food crop is also applied to products which are complements of or derived from that food crop (e.g., the price of cassava is used for its extract gari).<sup>15</sup> Appendix Table A2 reports the value of the scaling factor for both consumption and production indices by state for the narrow and broad matches.

We construct the production price index in a similar fashion to the consumption price index with the difference that we use the underlying bundle of produced goods to weigh the prices: where _Prodshr_ is the share of good _j_ in the total value of households’ sales of own produced goods in state s. We consider here only the products between 1 and K for which price data are available in state _s_ (thus the shares sum to 1). Finally _TotInc_ is the total household income from all sources in the state. Similarly to the consumption price index, the latter term scales the index by the importance of those items produced and sold by the households ( _Prodtot_ ) in total household income in the state _TotInc_ .

Because the prices may refer to different units of measurement of the commodities, in order to standardize them, we normalize the price of every commodity to 100 in 2003 and then construct the price index on the basis of the normalized series.

The variation in these price indices across states comes from both the different changes in state-level prices over time and the initial difference in consumption and production baskets. While we focus on the former below, figures A1 and A2 in the Appendix illustrate the latter, by focusing on the two most important consumption items in Nigeria, beans and rice. The variation in production and consumption is large. For example in Benue and Ebonyi rice accounts for over

> 14 Though another batch of data is available for 2010 to 2013, there are a number of inconsistencies in the data that makes it difficult to use at this point. The NBS changed methodology of data collection for the prices in those periods and some of the prices were totally different when compared to the 2000 – 2010 data set. Also the items in the 2010 to 2013 data sets were different with more items included and disaggregated.

> 15 The broad matching procedure relies on subjective judgments, based on our understanding of the country and the consumption items.

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