The effect of urban air pollutants in Germany: eco-efficiency analysis through fractional regression models applied after DEA and SFA efficiency predictions

• Autor(a) principal: Moutinho, Victor
• Data de Publicação: 2020
• Outros Autores: Madaleno, Mara, Macedo, Pedro
• Tipo de documento: Artigo
• Idioma: eng
• Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
• Texto Completo: http://hdl.handle.net/10773/37548
• topic: Air pollutants; Eco-Efficiency; German Cities; Data Envelopment Analysis (DEA); Stochastic Frontier Analysis (SFA); Fractional Regression Models (FRM)

Cities and living standards contribute intensively to air pollution, an environmental risk factor which causes diseases. Recently, in developed countries, the majority of cities has grown rapidly and has experienced increasing environmental problems. In this article we analyze the effect of urban air pollution considering the available data for the years 2007, 2010 and 2013 in 24 German cities. Proposing a new model, we start the analysis using data envelopment analysis (DEA) and stochastic frontier analysis (SFA) to predict eco-efficiency scores for the 24 German cities. Afterwards, it is applied fractional regression to infer about the influencing factors of the eco-efficiency scores, at the city level. Results suggest a significant impact over eco-efficiency due to the excess of PM10, the average temperature, the average of NO2 concentration and rainfall. The findings in this study hold important implications for policymakers and urban planners in Germany, especially those that coordinate environmental protection and economic development in cities. Therefore, interventions to reduce urban air pollution can be accomplished on different regulatory levels, leading to synergistic effects as the decrease of climate change effects and noise.