The study looked at different ways to predict inflation in Turkey using a method called Bayesian vector autoregression (BVAR). They found that using variables in log-difference form gave better forecasts than using log-levels. Smaller BVAR models with carefully chosen variables also performed well in predicting inflation up to two quarters ahead. Additionally, considering the future paths of some variables helped improve the accuracy of the forecasts. Overall, small to medium-sized BVAR models with selected variables in difference form and conditioning on future paths of some variables are effective for forecasting inflation in Turkey.