use these differential mining sites attributes for estimating the heterogeneous effects of post-WTO accession on local economic development. Ultimately, the constructed dataset contains over 40 mineral types matched across 2339 districts in 37 countries in Africa.

One key feature of the USGS data is the presence of historical mineral prices data (measured at 1998 constant US dollars and average US prices) available since 1900 for the United States. We employ<sup>10</sup> these data to control for the volatility in world mineral prices as we later detail in the empirical specification. Two facts guide the choice of US historical prices data. First, the US has a large economy whose mineral prices are good proxies for world mineral prices. Second, compared to the commonly used World Bank Global Economic Monitor (GEM) price data, the USGS price data covers a wider range of mineral commodities. The overall (unreported) price correlations between GEM and USGS, when matched across minerals, is 0.93, which suggests that the use of US minerals’ prices is not unreasonable. However, we use the GEM price data for robustness checks of our main regression estimates.

The third data source is the Satellite Assessment of Rainfall for Agriculture in Tropical Africa (TAMSAT),<sup>11</sup> which provides monthly rainfall data in Africa since 1983. We use this data source to construct a measure of rainfall (mean and standard deviations) and later use them as proxies for climatic shocks and agricultural productivity variations; this is similar in spirit to Miguel et al. (2004).

The fourth data source is the Gridded Population of the World (GPW. V4).<sup>12</sup> At a grid cell resolution of 30 arc-seconds (approximately 1 km at the equator), this source contains two main sub-sources: population count grids for the years 1990, 1995, and 2000, and population count grid future estimates for the years 2005, 2010, 2015 and 2020 and the data are adjusted to reflect the historical, current, and future projections of the United Nations World Population estimates. Following Holder and Rascky (2014), we extracted these data at the district level and linearly interpolated them to estimate population counts for the missing years. Thus, we were able to construct a dataset with population count estimates over the period from 1990 to 2015.

The Armed Conflict Location and Event Data (ACLED)<sup>13</sup> is our fifth source, providing disaggregated spatial conflict data that identifies the locations in which conflicts have taken place around the world since 1997. We exploit the spatial nature of the ACLED data to identify places where conflicts occurred in Africa between 1997 and 2007 before pairing them (at the district

> 10 Note, however, that the key limitation of using the USGS dataset is the lack of information on the levels of mineral productions at the mining site, and opening and closure of such sites.

> 11 The data are available at: <u>http://www.met.reading.ac.uk/~tamsat/cgi-bin/data/rfe.cgi</u>

> 12 From the Socio-Economic Data and Application Centre (SEDAC) hosted by the Centre for International Earth Science Information Network (CIESIN) at Columbia University which are available at: <u>http://beta.sedac.ciesin.columbia.edu/data/collection/gpw-v4</u>

> 13 Available at: <u>www.acleddata.com/</u>

9