Decoding Policy Signals: Heterogeneous Effects of Pronatalist Policies on Fertility Decision in China

China is navigating a profound demographic crisis, with its total fertility rate (TFR) plummeting to a record low of 1.01 in 2023(Source: China Population and Employment Statistical Yearbook, 2024). In response, sub-national governments have enacted a suite of pronatalist policies, encompassing financial incentives, extended parental leave, and improved childcare services. Despite this significant policy effort, a conspicuous paradox persists: high policy intensity has yielded disappointingly low fertility responses. This study posits that a primary reason for this efficacy gap lies in the homogeneous, ‘one-size-fits-all’ design of current policies, which fails to account for substantial heterogeneity in the needs and preferences of different demographic subgroups and households. To address this, our research interrogates two pivotal questions: (1) Laterally, what are the differential effects of the three core policy signals—financial subsidies, leave extensions, and childcare support—in fertility decisions? How do different types of policies affect the various dimensions of fertility decisions (Readiness, Willingness, and Ability)? (2) Longitudinally, how does the effect of a given policy signal vary across different household and individual characteristics? Moving beyond conventional economic cost-benefit models (e.g., Becker, 1960), we develop a novel theoretical framework integrating Policy Feedback Theory and the Readiness, Willingness, and Ability (RWA) framework. We introduce policy signaling theory to argue that pronatalist policies are not merely instrumental tools but also function as communicative signals that shape citizens?perceptions of governmental support and social norms, thereby influencing their cognitive readiness, emotional willingness, and assessed ability to fertility decision-making. To disentangle these complex causal relationships, we employ a factorial vignette experiment. This methodological approach allows us to present a nationally diverse sample of Chinese adults of reproductive age (N ? 3,000) with randomized combinations of policy attributes. Participants evaluate their fertility intentions across multiple scenarios, enabling precise quantification of the marginal causal effects of each policy type and their interactions with respondent characteristics. The findings will deliver robust causal evidence on the mechanistic pathways through which policy signals influence fertility decisions. Theoretically, the study contributes by pioneering the application of policy feedback and signaling lenses to low fertility research. Its methodological innovation lies in its experimental design, which isolates the effects of multifaceted policies. The practical and comparative policy implications are substantial: the results will provide a clear evidence base for designing targeted, efficient, and equitable pronatalist policies in China. By identifying policies that effectively reduce the disproportionate care burden on women and enhance their social well-being, this study aims to contribute to the design of pronatalist measures that simultaneously promote gender equity, offering critical insights for other nations grappling with the global challenge of ultralow fertility.