table 3

OLS Estimates of the Impact of Prenatal Pollution Exposure on TLI Test Performance

	(1)	(2)	(3)	(4)	(5)	(6)	(7)
	79–85	79–81	81–83	83–85	81–83	81–83	81–83
TSP	−0.0006	0.0092	−0.0323**	−0.0272	−0.0287**	−0.0243	−0.0010*
	(0.0074)	(0.0113)	(0.0146)	(0.0193)	(0.0135)	(0.0170)	(0.0005)
TSP_{t + 1}					−0.0175*	−0.0144
					(0.0096)	(0.0138)
TSP_{t + 1}					0.0188	0.0215
					(0.0127)	(0.0149)
TSP_{t + 2}						0.0022
						(0.0119)
TSP_{t + 2}						0.0087
						(0.0136)
Impact of one Standard Deviation Δ in TSP
Δ in TLI score	0.00	0.07	−0.24	−0.20	−0.21	−0.18	−0.01
% s.d. in TLI	−0.04	0.58	−2.04	−1.72	−1.82	−1.54	−0.06
Observations	73,950	31,895	34,669	30,075	34,669	34,669	34,669
Total students	757,507	322,464	334,956	320,932	334,956	334,956	334,956

Notes: Regressions are based on the 30 counties used in the primary analysis with standard errors clustered on county. Years listed in column labels identify the year of birth range used in each regression. All include school and year of birth by year of test fixed effects, as well as all economic, demographic, and weather covariates discussed in Section III. Observations refers to the number of cells used in each regression, while Total Students is the number of raw observations represented by the use of cell weights. Impacts are (1) change in the TLI score resulting from a within-county standard deviation increase in TSPs, and (2) percentage of a TLI withincounty standard deviation resulting from a within-county standard deviation increase in TSPs. Column 5 controls for one-year lag and one-year lead in annual TSP levels. Column 6 adds two-year lags and leads. Column 7 repeats Column 6 using the binary test-passage indicator as the outcome variable. * significant at 10 percent; ** significant at 5 percent; *** significant at 1 percent.