Forecasting municipal waste accumulation rate and personal consumption expenditures using vector autoregressive (VAR) model

Abstract Accurate forecasting of municipal solid waste (MSW) generation is important for the planning, operation and optimization management system. However, it’s not easy task due to dynamic changes in volume, its composition or unpredictable factors. Initially, mainly conventional descriptive statistical models with demographic socioeconomic factors were used. Methods based on machine learning artificial intelligence have been widely used projection several years. This study investigates trend accumulation rate relation personal consumption expenditures yearly data achieved from Local Data Bank (LDB) driven by Polish Statistical Office. The effect was analysed using vector autoregressive model (VAR). results showed that such method can be successfully this purpose an approximate level 2.3% Root Mean Square Error (RMSE).