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Abstract:
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With the increase in the availability of data at the local level, community stakeholders are becoming more reliant on data analyses to identify and describe vulnerable populations, target and evaluate policy interventions, and estimate statistics for use in decision making for the public good, for example, program management and development, and federal funding allocations. Many communities use composite indicators, such as well-being, equity, sustainability, and social vulnerability, to describe and track the conditions of their community. However, these indices are typically presented without an estimate of variability. This paper takes a statistical look at the construction of composite indicators and proposes a method to estimate their variability. Examples will be provided using data from the American Community Survey integrated with local administrative data.
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