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<p>As a core component of digital governance, public data openness, specifically operationalized here as the municipal rollout of Open Government Data (OGD) platforms providing structured, machine-readable datasets, has been reshaping fiscal expenditures and public service systems. Although prior studies have emphasized its role in fostering economic growth and governance efficiency, systematic evidence concerning its impact on health care financing—particularly regarding the dual burden shared by governments and individuals—remains limited. This study aims to evaluate the causal effects of municipal open data platform policies on both government and individual healthcare expenditures and to identify the mechanisms through which these effects occur. Exploiting the staggered rollout of municipal open data platforms across Chinese cities, this study combines city-level data covering 2012–2022 with individual-level data from the China Health and Retirement Longitudinal Study (CHARLS) covering 2011–2020. A multi-period difference-in-differences design and mediation analysis are used to estimate the macro-level fiscal effects and examine changes in individual healthcare expenditures. The final outpatient-expenditure models included 12,591 person-wave observations from 11,164 unique participants, whereas the inpatient-expenditure model included 1,597 person-wave observations from 1,440 unique participants. Public data openness was associated with an increase in government healthcare expenditure, with 13.2% of the total effect mediated through the expansion of the licensed and assistant physician workforce. The outpatient-visit and preventive-checkup pathways generated negative indirect effects accounting for − 2.2% and − 1.5% of the total effect, respectively, thereby partially offsetting the overall increase in government healthcare expenditure. At the individual level, public data openness was associated with lower annual inpatient expenditure at the 10% significance level. For outpatient expenditure, the log specification showed a statistically significant negative association, whereas the absolute-level estimate was not statistically significant. Public data openness appears to reconfigure healthcare financing through supply expansion, demand optimization, and prevention strengthening. It increases government expenditure on healthcare capacity, while the demand-side and preventive-care pathways partially offset this increase. The individual-level findings suggest a potential reduction in inpatient financial burden, although the outpatient-expenditure estimates vary across model specifications. Fiscal sustainability in this setting may therefore arise from structural reallocation and efficiency gains rather than absolute cost containment.</p>

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Public data openness and health expenditure: evidence from macro–micro analyses in China

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年7月31日

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  • Ying Liu,
  • Shanna Li,
  • Qin Sun,
  • Jie Hao,
  • Lin Guo

摘要

As a core component of digital governance, public data openness, specifically operationalized here as the municipal rollout of Open Government Data (OGD) platforms providing structured, machine-readable datasets, has been reshaping fiscal expenditures and public service systems. Although prior studies have emphasized its role in fostering economic growth and governance efficiency, systematic evidence concerning its impact on health care financing—particularly regarding the dual burden shared by governments and individuals—remains limited. This study aims to evaluate the causal effects of municipal open data platform policies on both government and individual healthcare expenditures and to identify the mechanisms through which these effects occur. Exploiting the staggered rollout of municipal open data platforms across Chinese cities, this study combines city-level data covering 2012–2022 with individual-level data from the China Health and Retirement Longitudinal Study (CHARLS) covering 2011–2020. A multi-period difference-in-differences design and mediation analysis are used to estimate the macro-level fiscal effects and examine changes in individual healthcare expenditures. The final outpatient-expenditure models included 12,591 person-wave observations from 11,164 unique participants, whereas the inpatient-expenditure model included 1,597 person-wave observations from 1,440 unique participants. Public data openness was associated with an increase in government healthcare expenditure, with 13.2% of the total effect mediated through the expansion of the licensed and assistant physician workforce. The outpatient-visit and preventive-checkup pathways generated negative indirect effects accounting for − 2.2% and − 1.5% of the total effect, respectively, thereby partially offsetting the overall increase in government healthcare expenditure. At the individual level, public data openness was associated with lower annual inpatient expenditure at the 10% significance level. For outpatient expenditure, the log specification showed a statistically significant negative association, whereas the absolute-level estimate was not statistically significant. Public data openness appears to reconfigure healthcare financing through supply expansion, demand optimization, and prevention strengthening. It increases government expenditure on healthcare capacity, while the demand-side and preventive-care pathways partially offset this increase. The individual-level findings suggest a potential reduction in inpatient financial burden, although the outpatient-expenditure estimates vary across model specifications. Fiscal sustainability in this setting may therefore arise from structural reallocation and efficiency gains rather than absolute cost containment.