When to Implement Pharmaceutics Policies: Deductions from the Periodically Integrated Average Cost per Prescription Data

Introduction: Pharmaceutics are integral to the healthcare; therefore dynamics of their prices affects not only firms but the wellbeing of the public as well. Consequently this study aims to investigate the dynamics of the pharmaceutical prices as well as the effect of shocks on the series for the purpose of policy implementation, exploiting the periodic structure of the series. Materials and Methods: The study focuses on the end user prices hence the price data is taken as average price of prescriptions. The data is a time series obtained from Social Security Institution’s Monthly Statistical Bulletins and includes the period 2008m12 - 2020m02. The series is investigated using periodic models. Results: The series depicts strong periodicity, moreover it is found out to be periodically integrated. Consequently the monthly average price of prescriptions is modeled using periodically integrated autoregressive models. The time varying accumulations of shocks of the models indicate the shocks on spring and summer months have the most severe effect such that it may change the stochastic trend of the series. Additionally shocks on winter have large long-run impacts. Conclusion: The shocks can occur intentionally as government policies on pharmaceutics or unintentionally such as pandemics, unexpected fluctuations in exchange rates. On one hand intentional shocks in winter have larger long run effects, but such shocks are less likely to change the dynamics of the series. On the other hand unintentional shocks at winter should be dealt carefully since their effect is going to be long lasting. Finally the models agree that policy shocks in spring and summer seasons are more likely to be successful whereas policy makers must take swift action when an unintentional shock occurs in these seasons.