Self-Reported Health Status: Difference-In-Differences Analysis Term Paper

Table of Contents
  1. Introduction
  2. Difference-in-Differences Application
  3. Conclusion
  4. Reference

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Introduction

When measuring the outcomes of a program, it could be helpful to plot the information earlier than and after the intervention to eyeball the distinction an intervention has made. The current mission estimates two variables which may be affected by the intervention, together with common doctor visits by quarter and common self-reported well being standing by quarter. Figure 1 beneath demonstrates the modifications within the variety of doctor visits by quarter in each teams. The plot demonstrates that, after the intervention, Group A elevated its utilization of medical companies, whereas Group B barely decreased it.

Figure 1. Changes within the variety of doctor visits

Figure 2 beneath demonstrates the modifications within the common self-reported well being standing by quarters in each teams. The plot demonstrates that Group A began to report the next well being standing after the intervention.

Figure 2. Changes within the self-reported well being standing

Difference-in-Differences Application

In order to quantify the impact of the intervention on each outcomes, the difference-in-differences (DD) was used. The method is without doubt one of the mostly used and the oldest quasi-experimental analysis designs (Goodman-Bacon, 2018). The outcomes of the DD evaluation are offered in Table 1 beneath.

Table 1. The difference-in-differences evaluation

Physician Visits Health Status
Before After Difference Before After Difference
Group A 4.5 9.5 5 Group A 76.25 90.5 14.25
Group B 6.5 6 -0.5 Group B 76.25 82.5 6.25
Difference-in-Differences 5.5 Difference-in-Differences 8

The outcomes of the DD evaluation display that, assuming the frequent development in Groups A and B. The outcomes display that the intervention had an impact on each the variety of doctor visits and self-reported well being standing. In specific, the coverage elevated the variety of doctor visits in Group A by 5.5 visits 1 / 4 on common after controlling for the frequent development. At the identical time, the intervention elevated the self-reported well being standing by 8 out of 100 factors after controlling for the frequent development.

Conclusion

The DD evaluation demonstrated that the coverage was profitable, because the insurance coverage enlargement had a optimistic impact on the self-reported well being standing of Group A. Thus, the central objective of this system was achieved. However, earlier than implementing the coverage universally, it’s essential to note that the coverage can improve the demand for healthcare companies. In specific, the variety of doctor visits virtually doubled in Group A, the enactment of the coverage. Thus, the coverage ought to be carried out provided that the realm can fulfill the elevated want for healthcare companies within the age group.

Reference

Goodman-Bacon, A. (2018). Difference-in-differences with variation in therapy timing (No. w25018). National Bureau of Economic Research.

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