Abstract
A country’s total fertility rate (TFR) depends on many factors. Attributing changes in TFR to changes of policy is difficult, as they could easily be correlated with changes in the unmeasured drivers of TFR. A case in point is Australia where both pronatalist effort and TFR increased in lock step from 2001 to 2008 and then decreased. The global financial crisis or other unobserved confounders might explain both the reducing TFR and pronatalist incentives after 2008. Therefore, it is difficult to estimate causal effects of policy using econometric techniques. The aim of this study is to instead look at the structure of the population to identify which subgroups most influence TFR. Specifically, we build a stochastic model relating TFR to the fertility rates of various subgroups and calculate elasticity of TFR with respect to each rate. For each subgroup, the ratio of its elasticity to its group size is used to evaluate the subgroup’s potential cost effectiveness as a pronatalist target. In addition, we measure the historical stability of group fertility rates, which measures propensity to change. Groups with a high effectiveness ratio and also high propensity to change are natural policy targets. We applied this new method to Australian data on fertility rates broken down by parity, age and marital status. The results show that targeting parity 3+ is more cost-effective than lower parities. This study contributes to the literature on pronatalist policies by investigating the targeting of policies, and generates important implications for formulating cost-effective policies.
Highlights
After a prolonged post-war fertility decline, many developed countries saw a recovery of fertility in the 1990s to early 2000s
How can we identify groups whose targeting will influence total fertility rate (TFR) in a cost effective way i.e. groups that give the largest “bang per buck” [27]? In the current context, “buck” is the cost of targeting that group which will be proportional to the size of that group, and “bang” is the change in TFR obtained from a likely change in group fertility rates
Estimating the causal effects of pronatalist policy on TFR is difficult because policy changes are often endogenous
Summary
After a prolonged post-war fertility decline, many developed countries saw a recovery of fertility in the 1990s to early 2000s. Some of these countries introduced pronatalist incentives over the same period. Various alternative explanations of fertility recovery have been identified in the literature, including: tempo distortion [1,2]; delayed birth recuperation [3]; economic prosperity prior to the 2008 global financial crisis [2]; a possible reversal of the relationship between socioeconomic development and fertility trends in highly developed countries [4].
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