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An investigation of thresholds in air pollution-mortality effects

Koop, G.M. and Tole, L.A. (2004) An investigation of thresholds in air pollution-mortality effects. Environmental Modelling and Software, 21 (12). pp. 1662-1673. ISSN 1364-8152

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    Abstract

    In this paper we introduce and implement new techniques to investigate threshold effects in air pollution-mortality relationships. Our key interest is in measuring the dose-response relationship above and below a given threshold level where we allow for a large number of potential explanatory variables to trigger the threshold effect. This is in contrast to existing approaches that usually focus on a single threshold trigger. We allow for a myriad of threshold effects within a Bayesian statistical framework that accounts for model uncertainty (i.e. uncertainty about which threshold trigger and explanatory variables are appropriate). We apply these techniques in an empirical exercise using daily data from Toronto for 1992-1997. We investigate the existence and nature of threshold effects in the relationship between mortality and ozone (O3), total particulate matter (PM) and an index of other conventionally occurring air pollutants. In general, we find the effects of the pollutants we consider on mortality to be statistically indistinguishable from zero with no evidence of thresholds. The one exception is ozone, for which results present an ambiguous picture. Ozone has no significant effect on mortality when we exclude threshold effects from the analysis. Allowing for thresholds we find a positive and significant effect for this pollutant when the threshold trigger is the average change in ozone two days ago. However, this significant effect is not observed after controlling for PM.

    Item type: Article
    ID code: 7752
    Notes: Working paper version
    Keywords: threshold air pollution–mortality effects, Bayesian model averaging, air pollution, econometrics, environmental economics, Economic Theory, Statistics, Environmental Science(all), Ecological Modelling
    Subjects: Social Sciences > Economic Theory
    Social Sciences > Statistics
    Department: Strathclyde Business School > Economics
    Related URLs:
    Depositing user: Strathprints Administrator
    Date Deposited: 20 Mar 2009 15:11
    Last modified: 05 Sep 2014 13:37
    URI: http://strathprints.strath.ac.uk/id/eprint/7752

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