Enflasyon hedeflemesinin parametrik olmayan eğilim skor eşleştirme yöntemleri ile analizi

This study employs the propensity score matching framework to examine the average treatment effect of inflation targeting approach to examine its economic performance on important economic variables. We use various nonparametric matching methods that have several advantages compared to the traditional regression models due to its properties that deal with potential bias problems. As a result of the evaluation framework, the results from the matching process are not flawed because of a self-selection bias. Moreover, the process does not need a specific functional form that may cause any omitted variable bias. Annual data for the period between 1990 and 2019 for different country groups are employed. Nearest-neighbor matching, propensity score matching, and kernel matching methods are utilized to examine the average treatment effect of inflation targeting framework on the inflation rate and inflation volatility, exchange rate stability, and foreign direct investment. Results document that the average treatment effects of inflation targeting on all outcome variables are statistically significant. The findings significantly document that inflation targeters perform better on the examined economic conditions compared to those non-inflation targeters to reach better macroeconomic conditions. To be more precise, the results of the propensity score matching analyses to examine the average treatment effect of inflation targeting conclude that if non-inflation targeting countries had adopted inflation targeting, their inflation rates, and inflation volatility would have been significantly lower, their exchange rate stability would have been significantly better, and their foreign direct investment inflows would have been significantly higher.