Modeling structure of inflation in Türkiye: DCC-GARCH and Markov switching model

Purpose Recent surges in inflation have posed significant challenges for Türkiye, with the annualinflation rate culminating at 83.45% by the close of 2022. The purpose of the study is to take a closer look at the details behind the rising inflation trend in Türkiye. Design/methodology/approach Due to the time-varying nature of the relationship of the variables, dynamic conditional correlation-generalized autoregressive conditionally heteroscedastic (DCC-GARCH) models and the Markov switching model are used as analytical tools. Leveraging the DCC methodology proposed by Tse and Tsui (2002), this study examined time-varying correlations, while the effect of the weighted sum of past correlations was captured using the DCC-GARCH approach introduced by Engle (2002). Findings The findings from the DCC models highlight that the exchange rate plays the most pivotal role in influencing inflation, closely followed by the money supply. In addition, the Markov switching analysis, rooted in the Phillips curve concept, identified two statistically significant regimes. The results emphasize that components of the money supply and the exchange rate stand out as primary drivers of Türkiye’s heightened inflation rates. To promote sustainable development in Turkey, the Central Bank should focus on inflation targeting, managing the money supply to align with GDP growth and adopting adaptive inflation responses. Originality/value To the best of the authors’ knowledge, this paper is the first attempt to use a combination of the DCC and Markov switching models to examine Turkish inflation from December 2005 to October 2022, according to a thorough review of previous research. Such an innovative method provides a new perspective on inflationary patterns throughout this time. In addition, this study departs from traditional approaches by including money supply measures in the analysis.