Abstract
One important determinant of well-being is the environmental quality. Many countries apply environmental regulations, reforms and policies for its improvement. However, the question is how the people value the environment, including the air quality. This study examines the association between air pollution and life satisfaction using the Swiss Household Panel survey over the years 2000–2013. We follow a Bayesian network (BN) strategy to estimate the causal effect of the income and air pollution on life satisfaction. We look at five main air pollutants: the ground-level ozone (O3), sulphur dioxide (SO2), nitrogen dioxide (NO2), carbon monoxide (CO) and particulate matter of 10 micrometres (PM10). Then, we calculate the individuals’ marginal willingness to pay (MWTP) of reducing air pollution that aims to improve their life satisfaction. Beside the BN model, we take advantage of the panel structure of our data and we follow two approaches as robustness check. This includes the adapted probit fixed effects and the generalised methods of moments system. Our findings show that O3 and PM10 present the highest MWTP values ranging between $8000 and $12,000, followed by the remained air pollutants with MWTP extending between $2000 and $6500. Applying the BNs, we find that the causal effect of income on life satisfaction is substantially increased. We also show the causal effects of air pollutants remain almost the same, leading to lower values of willingness to pay.
Highlights
Local environmental amenities play a significant role in the quality of life
While structural equation modelling (SEM) is a promising approach for measuring the life satisfaction, the purpose of the current study is to explore the effect of the air pollution at the national level mapping the air quality on local area
For a variable to be a potential confounder the following criteria should be met: (a) it must have an association with the outcome variable; (b) it must be associated with the exposure or factor of interest; and (c) it must not be the effect of the exposure, meaning that it should not be a part of the causal pathway or a child according to the Bayesian network (BN) and directed acyclic graph (DAG) terminology we described in the previous section
Summary
Local environmental amenities play a significant role in the quality of life. Air pollution has a large influence on the health where both short-term exposure and long-term exposure to air pollution affect the cardiovascular and respiratory systems. Numerous research studies have strongly highlighted the extent of the air pollution adverse effects on health. These studies have widely recognised that air pollution is related to an increasing number of hospitalisations and deaths from heart and respiratory diseases (Pope et al 2006; Bhaskaran et al 2009; Lokken et al 2009; Giovanis and Ozdamar 2016a). Earlier research has emphasised on the importance of exposure to green and blue space (Pretty et al 2005; Takayama et al 2014), climate and biodiversity (Fuller et al 2007; Dallimer et al 2012; Feddersen et al 2016) and air quality (Welsch 2006; Luechinger 2009; Giovanis and Ozdamar 2016b; Ozdamar and Giovanis 2017) for the well-being
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