outcomes 13 to 30 months prior to childbirth. We exclude the last three months before birth because sick leave is prevalent, and it is also possible to claim maternity benefits four weeks before giving birth.

Panel (a) of Figure 1 displays the event study coefficients _βj_ from equation (1) separately for 2012-2014 and 2015-2017 and for smaller (1 to 50 employees) and larger (more than 50 employees) firms. The earnings of mothers and non-mothers evolve similarly before pregnancy, both before and after the change of the reference period and in smaller and larger firms as well. Starting around the time when women become pregnant, the earnings of expectant mothers in smaller and larger firms start to diverge. In the 2012-2014 period, in smaller firms, expectant mothers’ reported earnings were 2.1% higher 4 months before giving birth (and on average 1.8% higher between the second and sixth months of pregnancy) than those of women in the control group. This effect was even larger at 6.8% (and 5.3% on average) after the reporting incentive became much stronger in the 2015-2017 period. In larger firms, the earnings of expectant mothers declined by 2.9% relative to the control group over the same period. This decrease could be driven by women’s partial withdrawal from the labor market, health concerns, or discrimination. While the increase in reported earnings in small firms is 3 times larger in the 2015-2017 period than in the 2012-2014 period, reflecting the stronger reporting incentives, the decrease in earnings in larger firms is very similar in the two periods.

Panel (b) of Figure 1 displays the estimated event study coefficients _βj_ from equation (1) using an indicator for top-percentile earnings increases as the outcome variable. This indicator captures large and rare earnings increases: it equals one if an earnings change is in the top percentile of the year-specific distribution of monthly earnings changes, excluding earnings increases where a large earnings increase already took place in the previous month or there is an earnings decrease in the subsequent month.<sup>9</sup> Conditional on experiencing such an increase, earnings jumped on average by around 40% among women who gave birth between 2012 and 2014 and by around 50% among women who gave birth between 2015 and 2017. This figure suggests that before pregnancy, the probability of receiving such a large earnings increase evolves similarly among women who give birth and those who do not, both in smaller and larger firms in both of the time periods. Then, in the first half of pregnancy, there is a divergence between smaller and larger firms. In larger firms, there is no change in the probability of top-percentile wage increases. In smaller firms, the probability of large wage increases was up to 1.5 percentage points higher among expectant mothers during pregnancy between 2012 and 2014 and up to 3.5 percentage points higher between 2015 and 2017.

Panel (c) of Figure 1 re-estimates equation (1) using an indicator for reporting earnings within 10% of twice the monthly minimum wage, the benefit-maximizing threshold. Compared to the control group, the probability of reporting at threshold increases by up to 6.5 percentage

> 9More precisely, for all women aged 20-45, we calculate the monthly wage growth rate, conditional on the wage one month earlier being between 90% and 110% of the wage two months earlier. We define a monthly wage increase as a top-percentile change if the rate of increase is in the top 1 percentile of the year-specific distribution of wage increases, and the nominal wage does not decrease in the next month. We cannot define this indicator before 2012 because our data source smoothed earnings within employment spells by employer-employee-year observations.

7