The Dickey Fuller test is effective in detecting breaks in mean stationary data, like controlled inflation rates. It accurately identifies unit root presence in trend-stationary processes with breaks and level/trend breaks in unit root processes. The test's reliability is confirmed through Monte Carlo simulations for practical sample sizes. This study enhances existing knowledge on the subject, showing that the test performs well in scenarios where inflation rates should be stable due to effective monetary policies.