The relationship between inflation and the unemployment rate depicted by the Phillips curve becomes more complex in the face of economic uncertainty than predicted by traditional models. As global uncertainty increases, expected inflation becomes more difficult to control, leading to changes in the traditional Phillips curve model. This study examines the applicability of the Phillips curve in Indonesia by analyzing regional data from 34 provinces from 2010–2023. Using static and dynamic estimation methods, this study observes a set of variables— including unemployment rate, lagged inflation, expected inflation, output gap, growth of nominal exchange rates, trade openness, and the uncertainty caused by the COVID-19 pandemic.

The findings show that inflation is significantly affected by lagged inflation, unemployment, expected inflation, growth of nominal exchange rate, and COVID 19 dummies. Unemployment, lagged inflation, expected inflation, and growth of the nominal exchange rate consistently show a positive impact on inflation, with a larger magnitude in the long run. An insignificant impact is shown between trade openness and the output gap. While the COVID-19 dummy shows a negative impact both in the short and long run. By employing the regional data level, this research contributes to understanding inflation dynamics in Indonesia's diverse regional environments. With this approach, this study is expected to provide a more comprehensive picture of the relationship between inflation and variables studied under conditions of uncertainty and thereby appropriate policy implications for maintaining macroeconomic stability can be applied.