Table 5 breaks our sample down even further in order to study how the effects of salt iodization may have differed over the course of these individuals' careers. In particular, we are interested in comparing effects in young adulthood and prime ages to effects in later adulthood. Focusing on women, the only ones significantly affected by salt iodization, we run our labor market outcome regressions using only the 1950 and 1960 Censuses (during which our sample individuals were aged 19 to 40) and then using only the 1970 and 1980 Censuses (when they were 39 to 60 years old). Sample sizes are substantially larger in panel B because we are using a 1% sample for all census waves except 1980 (which shows up in panel B), for which we use the 5% sample. Table 5 reports these regressions in panels A and B, respectively, and reveals a clear pattern. The effects of salt iodization on labor supply seem to be entirely driven by the large impact salt iodization had on women early in their careers. For all outcomes, the early census coefficients are larger in magnitude than the late census coefficients. With the exception of income, for which we see a 6% increase even in later census waves, none of the late census coefficients are significantly different from 0. It is worth noting that for three of the four outcomes of interest in panel A, there appear to be significant effects on the during cohort, emphasizing that the effects of iodization do appear to show up quite rapidly (as was the case in Feyrer et al., 2017).

Table 5.
Effects of Salt Iodization on Female Labor and Income Outcomes in Early and Late Censuses
(1)(2)(3)(4)
1(Employed)1(Participated in the Labor Force)1(Worked at least 40 weeks)sinh$-1$(Income)
A. 1950–1960 Censuses (ages 19 to 40)
After $×$ Goiter Rate 0.0185*** 0.0221*** 0.0288*** 0.241**
(0.00593) (0.00657) (0.0106) (0.100)
During $×$ Goiter Rate 0.0133** 0.0135* 0.0426*** 0.0309
(0.00631) (0.00695) (0.0111) (0.0761)
Observations 306,087 306,087 80,777 180,375
Mean of dependent variable 0.357 0.374 0.568 4.534
B. 1970–1980 Censuses (ages 39 to 60)
After $×$ Goiter Rate 0.00266 0.00152 0.00286 0.0604*
(0.00330) (0.00329) (0.00405) (0.0327)
During $×$ Goiter Rate −0.00346 −0.00254 0.00218 0.00762
(0.00265) (0.00278) (0.00457) (0.0337)
Observations 930,333 930,333 525,927 928,275
Mean of dependent variable 0.505 0.526 0.736 6.701
(1)(2)(3)(4)
1(Employed)1(Participated in the Labor Force)1(Worked at least 40 weeks)sinh$-1$(Income)
A. 1950–1960 Censuses (ages 19 to 40)
After $×$ Goiter Rate 0.0185*** 0.0221*** 0.0288*** 0.241**
(0.00593) (0.00657) (0.0106) (0.100)
During $×$ Goiter Rate 0.0133** 0.0135* 0.0426*** 0.0309
(0.00631) (0.00695) (0.0111) (0.0761)
Observations 306,087 306,087 80,777 180,375
Mean of dependent variable 0.357 0.374 0.568 4.534
B. 1970–1980 Censuses (ages 39 to 60)
After $×$ Goiter Rate 0.00266 0.00152 0.00286 0.0604*
(0.00330) (0.00329) (0.00405) (0.0327)
During $×$ Goiter Rate −0.00346 −0.00254 0.00218 0.00762
(0.00265) (0.00278) (0.00457) (0.0337)
Observations 930,333 930,333 525,927 928,275
Mean of dependent variable 0.505 0.526 0.736 6.701

Standard errors, clustered by state of birth, in parentheses ***p < 0.01, **p < 0.05, and *p < 0.1. “Goiter Rate” is the goiter rate in the individual's state of birth from Love and Davenport (1920), scaled by the difference between the 75th and 25th percentile of the goiter distribution (0.71). “After” is a dummy equal to 1 for those born 1928 to 1931. “During” is a dummy equal to 1 for those born 1924 to 1927. These regressions restrict to women born from 1920 to 1931. All regressions include state of birth fixed effects; year of birth $×$ census year dummies; census division of birth $×$ birth year dummies; gender; race; and during and after dummies interacted with average state latitude and 1920 state-level female and black proportions. “1(Worked at least 40 weeks)” is conditional on having worked in the past year. “sinh$-1$(Income)” takes the inverse hyperbolic sine of total income, including zeros for those not working.

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