Table 5.

Omitted variables: timing

	(1) ln Yict	(2) ln Yict	(3) ln Yict	(4) ln $\hat{Y_{\mathit{\text{ict}}}}$	(5) ln Yict
distance(Primate) * Poil	0.393 [0.255]	−0.875** [0.400]	0.492** [0.214]	−0.549*** [0.165]	−0.459** [0.181]
distance(Primate)*lagged Poil					−0.151 [0.215]
Observations	4,913	2,601	2,312	4,913	4,624
model	tobit	tobit	tobit	OLS	tobit
city trends	quadratic	linear	linear	split linear	linear
sample	1992–2008	1992–2000	2001–2008	1992–2008	1993–2008
left censored cases	263	186	77		211

Each column is a separate regression that includes country-year and city fixed effects. The unit of analysis is the city-year for a balanced annual panel of 289 cities in 15 coastal primate countries. Distance(Primate) is the road network distance to the largest city in the country, in thousands of kilometers. P_oil is the price of oil (specifically the annual average Europe Brent Spot Price FOB) in hundreds of dollars per barrel. Robust standard errors, clustered by city, are in brackets. Column 1, 2, 3 and 5 are tobit regressions that include the city-specific time trends shown. The dependent variable is the log of the lights digital number, summed across all pixels in the city, and averaged across satellite-years within a year when applicable. Column 4 is a two-step least squares regression that additionally includes two city-specific linear time trends per city, with the break point between the two periods estimated separately for each city. In column 4, the dependent variable is replaced by ln(5.5) when a city-year has no lights, and standard errors are boostrapped with 100 replications.

*, **, *** mean significance at the ten, five, and one percent level, respectively.