Forecasting carbon dioxide emissions based on a hybrid of mixed data sampling regression model and back propagation neural network in the USA

• Published in: Environmental science and pollution research international 2018, Vol.25 (3), p.2899-2910
• Main Authors: Zhao, Xin, Han, Meng, Ding, Lili, Calin, Adrian Cantemir
• Format: Article
• Language: English
• Subjects: Aquatic Pollution; Atmospheric Protection/Air Quality Control/Air Pollution; Autoregressive moving-average models; Back propagation; Back propagation networks; Carbon dioxide; Carbon dioxide emissions; Data sampling; Earth and Environmental Science; Economic development; Economic forecasting; Economic growth; Economic models; Economics; Ecotoxicology; Emissions; Empirical analysis; Energy policy; Environment; Environmental Chemistry; Environmental Health; Environmental science; Forecasting; Neural networks; Regression analysis; Regression models; Research Article; Sampling; Sulfuric acid; Waste Water Technology; Water Management; Water Pollution Control
• ISSN: 0944-1344; 1614-7499
• DOI: 10.1007/s11356-017-0642-6

The accurate forecast of carbon dioxide emissions is critical for policy makers to take proper measures to establish a low carbon society. This paper discusses a hybrid of the mixed data sampling (MIDAS) regression model and BP (back propagation) neural network (MIDAS-BP model) to forecast carbon dioxide emissions. Such analysis uses mixed frequency data to study the effects of quarterly economic growth on annual carbon dioxide emissions. The forecasting ability of MIDAS-BP is remarkably better than MIDAS, ordinary least square (OLS), polynomial distributed lags (PDL), autoregressive distributed lags (ADL), and auto-regressive moving average (ARMA) models. The MIDAS-BP model is suitable for forecasting carbon dioxide emissions for both the short and longer term. This research is expected to influence the methodology for forecasting carbon dioxide emissions by improving the forecast accuracy. Empirical results show that economic growth has both negative and positive effects on carbon dioxide emissions that last 15 quarters. Carbon dioxide emissions are also affected by their own change within 3 years. Therefore, there is a need for policy makers to explore an alternative way to develop the economy, especially applying new energy policies to establish a low carbon society.