TABLE 3.
Coffee Price Shocks and ln(Cohort Size) by Gender
| Male-Only Sample | Female-Only Sample | ||||||
|---|---|---|---|---|---|---|---|
| Sample/Specification | Sample/Specification | ||||||
| Ages 0–2 | Ages 0–3 | Ages 0–3 with Trends | Ages 0–2 | Ages 0–3 | Ages 0–3 with Trends | ||
| Panel A: 1975 Brazilian Frost | −0.17*** (0.04) | −0.04** (0.02) | −0.08*** (0.02) | Panel D: 1975 Brazilian Frost | −0.17*** (0.03) | −0.03** (0.01) | −0.08*** (0.02) |
| County Fixed Effects | Yes | Yes | Yes | County Fixed Effects | Yes | Yes | Yes |
| County-Specific Linear Trends | No | No | Yes | County-Specific Linear Trends | No | No | Yes |
| Implied Change | −2.09% | −0.48% | −1.01% | Implied Change | −2.15% | −0.38% | −0.97% |
| N | 2207 | 3305 | 3305 | N | 2205 | 3307 | 3307 |
| R2 | 0.99 | 0.99 | 0.99 | R2 | 0.99 | 0.99 | 0.99 |
|
| |||||||
| Panel B: 1985 Brazilian Drought | −0.16*** (0.05) | −0.15*** (0.05) | −0.20*** (0.11) | Panel E: 1985 Brazilian Drought | −0.17*** (0.06) | −0.13*** (0.05) | −0.25** (0.11) |
| County Fixed Effects | Yes | Yes | Yes | County Fixed Effects | Yes | Yes | Yes |
| County-Specific Linear Trends | No | No | Yes | County-Specific Linear Trends | No | No | Yes |
| Implied Change | −2.04% | −1.81% | −2.49% | Implied Change | −2.13% | −1.63% | −3.13% |
| N | 2199 | 3299 | 3299 | N | 2205 | 3305 | 3305 |
| R2 | 0.99 | 0.99 | 1.00 | R2 | 0.99 | 0.99 | 0.99 |
|
| |||||||
| Panel C: 1990 ICA Collapse | −0.09** (0.04) | −0.05** (0.01) | 0.03 (0.08) | Panel F: 1990 ICA Collapse | −0.10*** (0.04) | −0.04*** (0.01) | 0.11 (0.08) |
| County Fixed Effects | Yes | Yes | Yes | County Fixed Effects | Yes | Yes | Yes |
| County-Specific Linear Trends | No | No | Yes | County-Specific Linear Trends | No | No | Yes |
| Implied Change | −1.13% | −0.67% | --- | Implied Change | −1.23% | −0.46% | --- |
| N | 2199 | 3300 | 3300 | N | 2198 | 3298 | 3298 |
| R2 | 0.99 | 0.99 | 0.99 | R2 | 0.99 | 0.99 | 0.99 |
Notes: County-year cohort size data from the complete 1993 Colombian population census; coffee cultivation data from the National Federation of Coffee Grower’s early 1970s and early 1980s coffee censuses; annual internal coffee price data from the National Federation of Coffee Growers. Estimates and standard errors (in parentheses, clustered by county) shown for the interaction between coffee growing intensity and coffee price in the first year of life obtained by estimating equation 1 (controlling for county and year fixed effects and county-specific linear trends as shown above). Coffee area is in thousands of hectares and coffee prices are in thousands of pesos per kilogram. Implied changes are calculated for 250 hectares of coffee and a 500 peso per kilogram price change.
p<0.1,
p<0.05,
p<0.01.