Effect of layoffs on fertility by business cycle
| . | Model C: LPM . | Model D: IPW . | Model E: Double IPW . | |||
|---|---|---|---|---|---|---|
| Year After Layoff . | Treated in Downturn . | Treated in Upturn . | Treated in Downturn . | Treated in Upturn . | Treated in Downturn . | Treated in Upturn . |
| 1 | −0.020* | −0.014 | −0.020* | −0.013 | −0.019* | −0.019* |
| (0.009) | (0.009) | (0.009) | (0.010) | (0.009) | (0.010) | |
| 2 | −0.027* | 0.003 | −0.027* | 0.003 | −0.027* | −0.005 |
| (0.012) | (0.015) | (0.012) | (0.015) | (0.012) | (0.016) | |
| 3 | −0.033* | 0.014 | −0.032* | 0.013 | −0.032* | 0.008 |
| (0.014) | (0.019) | (0.014) | (0.018) | (0.014) | (0.022) | |
| 4 | −0.033* | 0.024 | −0.032* | 0.021 | −0.032* | 0.032 |
| (0.015) | (0.022) | (0.016) | (0.023) | (0.016) | (0.031) | |
| 5 | −0.033* | 0.012 | −0.032† | 0.010 | −0.035* | 0.009 |
| (0.017) | (0.023) | (0.018) | (0.023) | (0.018) | (0.031) | |
| . | Model C: LPM . | Model D: IPW . | Model E: Double IPW . | |||
|---|---|---|---|---|---|---|
| Year After Layoff . | Treated in Downturn . | Treated in Upturn . | Treated in Downturn . | Treated in Upturn . | Treated in Downturn . | Treated in Upturn . |
| 1 | −0.020* | −0.014 | −0.020* | −0.013 | −0.019* | −0.019* |
| (0.009) | (0.009) | (0.009) | (0.010) | (0.009) | (0.010) | |
| 2 | −0.027* | 0.003 | −0.027* | 0.003 | −0.027* | −0.005 |
| (0.012) | (0.015) | (0.012) | (0.015) | (0.012) | (0.016) | |
| 3 | −0.033* | 0.014 | −0.032* | 0.013 | −0.032* | 0.008 |
| (0.014) | (0.019) | (0.014) | (0.018) | (0.014) | (0.022) | |
| 4 | −0.033* | 0.024 | −0.032* | 0.021 | −0.032* | 0.032 |
| (0.015) | (0.022) | (0.016) | (0.023) | (0.016) | (0.031) | |
| 5 | −0.033* | 0.012 | −0.032† | 0.010 | −0.035* | 0.009 |
| (0.017) | (0.023) | (0.018) | (0.023) | (0.018) | (0.031) | |
Notes: Dependent variable is cumulated first-birth probability. Model C: OLS regression of linear probability model for the pooled sample including interaction terms. The full model for year 1 after the layoff is reported in Table S6 in Online Resource 1; Model D: Inverse probability weighting (IPW) estimation for separate samples (upturn/downturn); Model E: Double IPW estimation for separate samples (upturn/downturn). In the double IPW, we cannot control for time trends because, by definition, the upturn and the downturn take place at different times. Therefore, the point estimates differ slightly from those reported in Model D. For the IPW estimators, the standard errors are bootstrapped (500 replications). See Table 3 for number of observations.
†p ≤ .10; *p ≤ .05