BMC Public Health

Table 5 Natural resource and carbon concentration: baseline results

From: Mineral wealth paradox: health challenges and environmental risks in African resource-rich areas

	(1)	(2)	(3)	(4)
Mineral deposit	0.0585^a	0.0482^a	0.0287^b	0.0212^c
	[0.0131]	[0.0124]	[0.0118]	[0.0119]
Petroleum field	0.0700^a	0.0495^a	0.0340^b	0.0274^b
	[0.0135]	[0.0137]	[0.0138]	[0.0138]
Latitude		0.0004	0.0000	-0.0003
		[0.0018]	[0.0018]	[0.0018]
Longitude		0.0338^a	0.0451^a	0.0446^a
		[0.0020]	[0.0021]	[0.0021]
Mean elevation		0.0000	0.0002^a	0.0002^a
		[0.0000]	[0.0000]	[0.0000]
Ln(distance to coast)		-0.0038	-0.0597^a	-0.0567^a
		[0.0059]	[0.0087]	[0.0088]
Temperature			0.0573^a	0.0586^a
			[0.0053]	[0.0053]
Precipitation			0.0037^a	0.0037^a
			[0.0004]	[0.0004]
Vegetation			0.0001^a	0.0001^a
			[0.0000]	[0.0000]
Night luminosity				0.0460^a
				[0.0069]
Observations	12,529	12,428	12,356	12,356
R-squared	0.3387	0.3532	0.3858	0.3868
Country FE	Yes	Yes	Yes	Yes
Clustering var.	Grid Cell	Grid Cell	Grid Cell	Grid Cell

The table presents the coefficient estimates of the OLS regression with multiple fixed effects, which examines the association between natural resources and carbon concentration. We define all variables in Appendix A. In columns (1) to (4), we include country-fixed effects, and all variables are clustered at the grid level. Heteroscedasticity-robust standard errors are reported in parentheses. ^a, ^b, and ^c indicate statistical significance at the 1%, 5%, and 10% levels (two-tailed), respectively

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