# The evolutionary logic of socialized older population care service demand in rural areas based on the HAPC model

## TL;DR

This study explores how aging in rural China is driving demand for socialized elder care services, using a model to analyze factors influencing this demand.

## Contribution

The paper introduces a novel theoretical framework and applies the HAPC model to analyze rural elder care service demand dynamics.

## Key findings

- Period effects show increasing demand for elder care services due to policy and economic changes.
- Cohort effects significantly influence demand for expanded care services but not basic ones.
- Demand for elder care services in rural China varies by region and gender.

## Abstract

Chinese rural areas have entered a stage of moderate population aging ahead of urban regions, where mismatches between the supply and demand of older population care services are particularly pronounced. Establishing a socialized older population care service system has therefore become a critical response to the challenges posed by rural aging. This study develops a theoretical framework to explain the demand generation mechanism for rural socialized older population care services, identifying key influencing factors under both policy-driven and individual choice scenarios. Using data from the China Longitudinal Healthy Longevity Survey (CLHLS) from 2005 to 2018, we employ a hierarchical age–period–cohort (HAPC) model to examine the effects of age, period, and cohort on service demand. The results show that period effects are characterized by fluctuating upward trends in demand for both basic and expanded care services, primarily driven by changes in policy environments and economic conditions. Cohort effects significantly shape demand for expanded care services, but not for basic care services, with notable heterogeneity across regions and gender groups. Overall, rural demand for socialized older population care services is jointly influenced by age, period, and cohort dynamics. These findings suggest that optimizing the supply of older population care services in rural areas requires better alignment with differentiated demand characteristics to improve service relevance and effectiveness.