Response to: Health Poverty Alleviation Project in Rural China: Impact on Poverty Vulnerability, Health Status, Healthcare Utilization, Health Expenditures [Response to Letter]

Dear editor

We are grateful to the readers’ interest in our article, “Health Poverty Alleviation Project in Rural China: Impact on Poverty Vulnerability, Health Status, Healthcare Utilization, Health Expenditures”¹ and we also appreciate the readers for recognizing our academic research contributions in five ways, as well as for giving insightful comments. The fact that we have just published the research article noticed by the academic community is very encouraging for our endeavor. It is true that the reform of health policy systems aims to promote equity and protect vulnerable groups. Health equity remains an important and frontier research topic in the field of health public policy evaluation. We have an ongoing commitment to health equity research, as evidenced by our most recent article on health insurance equity published recently.²

Although we understand the academic position of our readers, we remain confident that our findings are robust and rigorous, both in terms of methodology and policy-practice implications. These views were confirmed by the anonymous reviewers participated in the review process of our article. As noted in the letter by M. Zaenul Muttaqin, we respond to each of the readers’ comments in the light of academic impartiality and scientific rigor.

First, we use a consistently valid estimation of the Difference-In-Differences (DID) method based on large-sample analysis for policy evaluation, and this methodology is widely used in the empirical research literature.³ The DID method provides a more robust assurance of the internal validity of policy evaluations. The use of mediation effect model in mechanism analysis is an even more widely used empirical analytical paradigm in policy evaluation.^4,5 We follow the reliable assessment methodology and the credible analytical framework that are heavily used in academic research. This is a reflection of the consistency of methodology in our article. In analyzing the results of policy evaluations, our article consistently implements two important guidelines for effective policy analysis. One is based on public policy fundamental theory. The other one is the basic facts of the formation policy practices with regional differences in the context of policy institutions.

Second, we explicitly states that the target group of the policy does not only include the disability groups, and the groups catered also for by the HPAP policy include registered poor population, Dibao families. Registered poor population and Dibao families in particular are dedicated to the care of rural minorities groups and elderly groups. All of information is clearly articulated in our article. Our study focuses on evaluating the public policy effectiveness for government implementation of HPAP, and we take a cautious attitude towards the content that goes beyond empirical results in our article. This is important for empirical studies of policy evaluation. Our aim is to provide a valid policy rationale for government policy action in HPAP, not to expand on other aspects. It is clear that the topic of research on multi-party participation in HPAP policy infrastructure development is not at the core of our study. We believe that scientifically credible research should be focused, not overly decentralized.

Third, if we are to discuss moral hazard, it is important to clarify ex ante moral hazard and ex post moral hazard. Ex post moral hazard must be distinguished between supply-side moral hazard and demand-side moral hazard.^6–9 Failure to distinguish between these will leads to confusion in the outcome of the discussion. The central issue of our discussion in the article is ex post moral hazard for demand-side as the policy cost of HPAP in the analytical framework developed by us. Clearly, induced demand is the supply-side moral hazard. Discussions of induced demand must have data information on physician behavior. Otherwise, it is difficult to guarantee the scientific accuracy of the discussion results. But this greatly deviates from the research topic we wanted to discuss in our article.

The readers also provided visions of further research in the future, and we think that these visions are positive for health policy research. From the perspective of the research foundation that we have done, it will be even more important to employ large-sample analyses to ensure the internal and external validity of policy analyses in the future. Such studies based on rigorous research designs can provide a robust policy evidence. The final policy experience will have positive implications for developing countries that are preparing to reform their health policy systems. It would be appropriate to select research methods based on the health policy issues that research team focus on and a rigorous study design. Moral hazard can provide an important theoretical perspective for understanding the costs of health policy. New policy evaluation methods, such as machine learning, can help academics in future policy evaluations to make further more accurate assessments of enrollees’ risk preferences, health insurance coverage levels, and satisfaction. This can greatly enhance the level of health policy evaluations we conduct, as well as provide important policy factual evidence.