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Morbidity and pollution: model specification analysis for time-series data on hospital admissions


  • Krumm, Ronald J.
  • Graves, Philip E.


Time-series analysis of effects of pollutants on emergency hospital admissions indicates important synergistic interactions among pollutants and to a lesser degree nonlinearities in effects of single pollutants. Comparisons of alternative econometric specifications are made to determine the appropriateness of incorporating nonuniform pollution impacts. The data substantially support the existence of synergisms among pollutants with high levels of sulfur dioxide, SO, (particulates), increasing the impact of particulates (SO,) on emergency hospital admissions. Marginal effects of either pollutant are, however, small at current ambient air quality levels. These results indicate that damage estimates were likely to be understated during the 1960’s when pollution levels were high, while, at current levels of those pollutants considered here, marginal damages are lower than would be estimated in studies failing to incorporate synergistic and nonlinear impacts.

Suggested Citation

  • Krumm, Ronald J. & Graves, Philip E., 1982. "Morbidity and pollution: model specification analysis for time-series data on hospital admissions," MPRA Paper 19906, University Library of Munich, Germany.
  • Handle: RePEc:pra:mprapa:19906

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    Cited by:

    1. McCubbin, Donald R. & Delucchi, Mark A., 1996. "The Social Cost of the Health Effects of Motor-Vehicle Air Pollution," University of California Transportation Center, Working Papers qt5jm6d2tc, University of California Transportation Center.

    More about this item


    time series; hospital admissions; pollution and human health; synergisms; nonlinearities; econometric model specification;

    JEL classification:

    • D6 - Microeconomics - - Welfare Economics
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
    • N5 - Economic History - - Agriculture, Natural Resources, Environment and Extractive Industries
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C1 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General


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