This paper uses life satisfaction data to help the design of climate mitigation policies in the United Kingdom. We assess the effects of the exposure to ambient pollutants on long-term life satisfaction and short-term mental health in the UK. We estimate augmented Cobb-Douglas utility functions using pooled and random effects ordinal logit models. Results show that increases in NO2, PM10 and PM2.5 significantly decrease the odds of longterm happiness and short-term mental health in the UK. The willingness to pay for clean air is also significant and increases with level of education. These measurements derived can be used as benchmarks for pollution abatement subsidies or pollution taxes and can help in projecting a more comprehensive assessment of costs and benefits.
This paper uses life satisfaction data to help the design of climate mitigation policies in the United Kingdom. We assess the effects of the exposure to ambient pollutants on long-term life satisfaction and short-term mental health in the UK. We estimate augmented Cobb-Douglas utility functions using pooled and random effects ordinal logit models. Results show that increases in NO2, PM10 and PM2.5 significantly decrease the odds of longterm happiness and short-term mental health in the UK. The willingness to pay for clean air is also significant and increases with level of education. These measurements derived can be used as benchmarks for pollution abatement subsidies or pollution taxes and can help in projecting a more comprehensive assessment of costs and benefits.
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