The effect of leave policies on increasing fertility: a systematic review

Abstract

AbstractLow fertility is set to worsen economic problems in many developed countries, and maternity, paternity, and parental leave have emerged as key pro-natal policies. Gender inequity in the balance of domestic and formal work has been identified as a key driver of low fertility, and leave can potentially equalise this balance and thereby promote fertility. However, the literature contends that evidence for the effect of leave on fertility is mixed. We conduct the first systematic review on this topic. By applying a rigorous search protocol, we identify and review empirical studies that quantify the impact of leave policies on fertility. We focus on experimental or quasi-experimental studies that can identify causal effects. We identify 11 papers published between 2009 and 2019, evaluating 23 policy changes across Europe and North America from 1977 to 2009. Results are a mixture of positive, negative, and null impacts on fertility. To explain these apparent inconsistencies, we extend the conceptual framework of Lalive and Zweimüller (2009), which decomposes the total effect of leave on fertility into the “current-child” and “future-child” effects. We decompose these into effects on women at different birth orders, and specify types of study design to identify each effect. We classify the 23 studies in terms of the type of effect identified, revealing that all the negative or null studies identify the current-child effect, and all the positive studies identify the future-child or total effect. Since the future-child and total effects are more important for promoting aggregate fertility, our findings show that leave does in fact increase fertility when benefit increases are generous. Furthermore, our extensions to Lalive and Zweimüller’s conceptual framework provide a more sophisticated way of understanding and classifying the effects of pro-natal policies on fertility. Additionally, we propose ways to adapt the ROBINS-I tool for evaluating risk of bias in pro-natal policy studies.