Abstract
We employ quantile regression fixed effects models to estimate the income-pollution relationship on NO x (nitrogen oxide) and SO 2 (sulfur dioxide) using U.S. data. Conditional median results suggest that conditional mean methods provide too optimistic estimates about emissions reduction for NO x , while the opposite is found for SO 2. Deleting outlier states reverses the absence of a turning point for SO 2 in the conditional mean model, while the conditional median model is robust to them. We also document the relationship's sensitivity to including additional covariates for NO x , and undertake simulations to shed light on some estimation issues of the methods employed.
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