One-Size-Fits-All Remedy for Low Fertility Rates? : Fuzzy-Set Analysis of the Conditions Associated with High Fertility Rates Among OECD Countries

Background/Purpose: Over the past decades OECD countries have witnessed the total fertility rates fall far below 2.1 children per woman, which is the minimum requirement to secure the generational replacement. The consequences of these low fertility rates are considered having a wide range of unfavorable social and economic effects. In real world, diverse sets of political, social, and economic conditions within countries are so complexly intertwined in creating fertility changes that underlying causes of different childbirth rates can also vary. Therefore, different conditions can work toward the same outcome, while some similar factors can end up with very different results. In this regard, our study aims to provide a comprehensive overview of what different conjunctional sets of causal conditions might be at play in explaining high fertility rates among different OECD countries.

Methods: Using FsQCA, we try to compare various OECD countries with diverse combinations of factors related to high fertility rates under different contexts and at the same time come up with moderately generalized different sets of causal mechanisms leading to similar outcomes. FsQCA has some advantages in dealing with this since FsQCA not only offers a solution to this small N problem by allowing logical inferences to be drawn from comparing a limited set of just 33 OECD country cases but also establishes a moderate level of generalization by testing a sufficient and necessary condition between the causes and the outcome.

Results: For the study purpose, we present the parsimonious solution not only because logical remainders are those logical configurations of conditions that are not empirically present in relation to the outcome of interest but still would be empirically proven if the sample-N were expanded, but also because parsimonious solution is much more pragmatic of modeling more generalized causal configurations. According to our FsQCA analytical results, the raw coverage for the configurations ranges from 0.67 to 0.83, whereas the unique coverage ranges from 0.003 to 0.056. In the result of our FsQCA analysis with 33 OECD countries, one individual factor (the female educational level) and three combined conditions (the combined condition of the presence of family Allowances and the flexible part-time work schedule, and of a high level of female political empowerment along with the high public expenditure on leave entitlements or with highly secured job status) were found to be the causal conditions of high fertility rates among OECD countries.

Conclusions and Implications: Just relying on the “one size fits all” assumptions could lead to poor choices for the government intervention. The overall results address the possibility that there should be different paths leading to the same outcome. Therefore, to gain better insight into these different mechanisms related to fertility rates in each different setting, it is desirable to go beyond internationally aggregated solutions and complementing the problems of overgeneralizations by looking more carefully and in depth at conditions behind the outcome within a country context itself.