Analysing the macroeconomic determinants of inflation under the explicit inflation targeting regime as a nominal anchor: A machine learning approach
Published 2025-12-25
Keywords
- Inflation Targeting, Nominal Anchor, Monetary Targeting, Exchange Rate Targeting, Machine Learning-Based Analysis
- Enflasyon Hedeflemesi, Nominal Çapa, Parasal Hedefleme, Döviz Kuru Hedeflemesi, Makine Öğrenmesi
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Copyright (c) 2025 Nuran Çakır Yıldız- Muzaffer Göztaş

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Abstract
To reduce inflation to a low, sustainable level, a clear target must be set within the framework of monetary policy. In this targeting process, a macroeconomic variable assumed to have a direct impact on inflation dynamics is selected and serves as a "nominal anchor," the reference point for monetary policy. The most common nominal anchors for achieving economic stability are the exchange rate anchor, monetary policy-based nominal anchors, and inflation-targeting regimes. Within the framework of its monetary policy strategy, Turkey implemented an implicit inflation-targeting regime during 2002–2005. The year 2005 was designated as a transition period toward the adoption of an explicit inflation targeting regime. During this process, the Central Bank of the Republic of Turkey (CBRT) emphasised the principles of independence, transparency, and accountability in its strategic plan. At the same time, price stability was formally established as the primary objective of monetary policy through legal amendments. As of January 1, 2006, Turkey officially adopted an explicit inflation-targeting framework. This study aims to identify the key macroeconomic indicators influencing Turkey's explicit inflation-targeting regime by employing a machine-learning–based empirical approach using data from 2006 to 2024. The analytical framework integrates multiple macroeconomic variables to evaluate their relative contributions to inflation dynamics under the nominal anchor perspective. The findings reveal that the combined use of the Consumer Price Index (CPI), real effective exchange rate (REER) indicators for both advanced and emerging economies, and the M2 money supply provides a practical and consistent predictive structure. In particular, the combination of REER indicators and the M2 aggregate captures inflation and CPI dynamics with high predictive power, underscoring their critical role in understanding the operational effectiveness of the explicit inflation-targeting framework in Turkey.
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