duced primarily by thermal (oil, gas, or coal) plants (World Bank, 2010). If expensive oil is increasing the price of electricity within countries, it should do so less where hydro is the most likely source. World Bank (2010) also reports the location of power plants, by type. Column 3 of Table 5 restricts attention to the 251 cities in those countries that have both hydro and thermal power plants and adds to the baseline specification a term interacting _distance_ ( _Primate_ ) _∗Poil_ with an indicator that the closest plant to the city is a hydro plant. The coefficient on the triple interaction is small and insignificant and has very little effect on the coefficient on _distance_ ( _Primate_ ) _∗ Poil_ .<sup>43</sup> Proximity to a hydro plant has no effect on the relationship between transport costs and lights.

A related concern is that cities far from the primate might not be on the power grid, and therefore might be more likely to rely on non-grid electric lights fueled by diesel generators. High oil prices could reduce diesel generator use, lowering lights more in faraway cities than near ones. Data on the location of electrical transmission lines are available from World Bank (2010) for 13 of 15 sample countries. Transmission lines pass through 184 of 260 cities (71%) in these 13 countries. In column 4, when the sample is restricted to these 184 cities least likely to rely on diesel generators, the results are very similar to the baseline. This suggests that diesel generators are not driving my results.<sup>44</sup> As noted above motorists use gasoline and diesel, not oil, so as a further check on my result, I can use the price of diesel instead of the price of oil for the subset of countries and years for which it is available. However, countries often subsidize diesel, and this introduces potential reverse causality because countries may subsidize in part to prevent the isolation of hinterland cities. The oil price is a valid instrument for the diesel price, because it is a very strongly predictor and is set on world markets in which no sample country holds sway.<sup>45</sup> In column 5, results for the main specification

> 43This analysis excludes three plants, one in Nigeria and two in Tanzania, characterized as neither thermal nor hydro. All three are part of sugar or paper mills.

> 44Kerosene lamps are even less likely to be driving my results. Data on household electricity are available in 24 Demographic and Health Surveys for nine sample countries during the sample period. Weighting by urban population within and then across countries using data and projections from United Nations (2008), 75 percent of urban households have electricity. A simple unweighted average of the 24 surveys and a compound average of the nine countries after averaging across surveys in each country give 62 and 63 percent, respectively. According to Mills (2002), locally made kerosene lamps produce 5 to 10 lumens, while store-bought models produce 40 to 50 lumens. Electrical light tends to be cheaper than kerosene, so households with electrical connections are unlikely to use kerosene for lighting. A 60-watt incandescent light bulb produces 800 lumens. So even if all households without electricity had the most advanced kerosene lamp and other households had a single 60-watt bulb, only 2 percent of household light would be from kerosene. This is almost certainly a substantial overstatement, because outdoor light is more likely to come from public or commercial establishments that are less likely to use kerosene.

> 45Of course, the oil price also affects the gasoline price, in a very similar way, so the diesel price is

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