The main aim of the study is to investigate the impact of inflation targeting (IT) strategy in Turkey during 2002-2022, which was adopted in a three-year period of 2002-2004, on macroeconomic performance (actual inflation, exchange and interest rates) and economic growth of Turkey (in terms of the real GDP). The econometric and empirical investigation of this research focusing on the impact of inflation targeting on the selected macroeconomic variables were carried out by the linear squares method (LSM) regression taking the data of the period after implementation of the monetary policy. At this, the independent variable of inflation targeting was estimated against each chosen macroeconomic variable separately in four different models to catch its linear impact on the changes of these variables over the period after implementation of the strategy. The empirical outcomes demonstrated that inflation targeting monetary policy is strong enough to impact the macroeconomic performance of Turkey in terms of reducing inflation rates, boosting economy by pushing real GDP to grow, stabilize exchange rates and lower the nominal interest rates on deposits.

Purpose: This study aims to investigate the intricate relationship between the volume of exports (Y) and freight turnover on railways (X) through a paired linear regression model. The purpose is to discern the quantitative impact of railway freight turnover on a nation's export volumes and offer insights for policymakers and stakeholders in the transportation and trade sectors. Design/Methodology/Approach: A quantitative research design is employed, utilizing historical data spanning from 2000 to 2022. The chosen methodology involves the estimation of a paired linear regression model using the method of least squares. Statistical significance is tested through the coefficient of determination, Fisher's F-test, and an examination of heteroskedasticity. Elasticity analysis, rank correlation, and graphical assessments of residuals provide a comprehensive understanding of the relationship. Findings: The research reveals a strong and statistically significant positive correlation (r = 0.92) between export volumes and railway freight turnover. The regression model, validated through multiple tests, explains 84.72% of the variability in export volumes. Economic interpretation indicates that a one-unit increase in railway freight turnover leads to a substantial average increase of 1627720.728 units in export volumes. The absence of heteroskedasticity reinforces the robustness of the model.