Complex Comparison of Statistical and Econometrics Methods for Sales Forecasting

Sales forecasting holds substantial significance in shaping decision-making processes in the retail industry. This study investigates the contemporary landscape of sales forecasting methods, aiming to provide empirical insights into the performance of various statistical and econometric models. By rigorously evaluating these models across diverse datasets, we identify stable methods that consistently demonstrate reliable predictive capabilities. Our research contributes to the field by offering baseline models that can furnish trustworthy forecasts, guiding practical applications and future research efforts. The paper details the study’s methodology, results, and discussions, enabling a comprehensive understanding of the strengths, limitations, and implications of the evaluated forecasting methods.