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The Use of Social Surveys to Measure Drought and the Impact of Drought

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  • Boyd Hunter

    ()

  • Matthew Gray
  • Ben Edwards

Abstract

Although the term drought is widely used, defining it is conceptually and technically difficult and there is no generally accepted definition. This article uses data from an Australian social survey of people living in agricultural areas to test the validity of using general social surveys to ask respondents whether they are living in an area that is drought affected. Strong evidence is found that the survey based self-report measure of drought is both internally consistent and correlated with the standard Australian meteorological (rainfall deficit) measures of drought and thus provides a valid measure of whether individuals are experiencing the drought. The relationship between self-report drought and the standard meteorological measure of drought and financial hardship and changes in financial position is estimated. While a negative association between drought and financial position is found for both measures, the relationship is stronger for the self-report than the meteorological definition. The self-report measure is more closely linked to the economic, social and community impacts of low rainfall and provides greater flexibility in the geographic area over which drought is measured—thus survey data about drought allows respondents to define the area in way which is meteorologically, topographically or agriculturally meaningful. Copyright Springer Science+Business Media B.V. 2013

Suggested Citation

  • Boyd Hunter & Matthew Gray & Ben Edwards, 2013. "The Use of Social Surveys to Measure Drought and the Impact of Drought," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 113(1), pages 419-432, August.
  • Handle: RePEc:spr:soinre:v:113:y:2013:i:1:p:419-432
    DOI: 10.1007/s11205-012-0102-0
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    References listed on IDEAS

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    1. Andrew E. Clark & Paul Frijters & Michael A. Shields, 2008. "Relative Income, Happiness, and Utility: An Explanation for the Easterlin Paradox and Other Puzzles," Journal of Economic Literature, American Economic Association, vol. 46(1), pages 95-144, March.
    2. Crossley, Thomas F. & Kennedy, Steven, 2002. "The reliability of self-assessed health status," Journal of Health Economics, Elsevier, vol. 21(4), pages 643-658, July.
    3. German Rodriguez & Irma Elo, 2003. "Intra-class correlation in random-effects models for binary data," Stata Journal, StataCorp LP, vol. 3(1), pages 32-46, March.
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