Measuring Interstate Variations in the Consequences of Illegal Drugs: A Composite Indicator Approach

Eric L. Sevigny () and Michaela Saisana
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Eric L. Sevigny: Georgia State University
Michaela Saisana: Joint Research Centre of the European Commission

Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, 2016, vol. 128, issue 2, No 4, 529 pages

Abstract: Abstract This study develops a series of Drug Consequences Indices (DCIs) measuring interstate variations in the harmful consequences of heroin, methamphetamine, cocaine, and marijuana in the US from 2000 to 2009. Indicators measuring drug-related health, social and economic, and crime and disorder consequences were selected from key drug data systems. Using weights derived from an Analytic Hierarchy Process conducted with addiction and drug policy experts, indicators were normalized by min–max scaling and aggregated using geometric means to produce each drug-specific DCI. Index scores were generated on a best–worst scale of 0–100 for all 50 states across 10 years. The Heroin Consequences Index reveals a general uptick in heroin-related problems, but the most severely impacted states fall in the Northeast. The Methamphetamine Consequences Index reveals that the worst affected states lay west of the Mississippi River and confirms the methamphetamine problem peaked about mid-decade. The Cocaine Consequences Index also shows a general decline beginning mid-decade, but in contrast to methamphetamine the most impacted states lay along the Gulf and East Coasts. The Marijuana Consequences Index in contrast is neither highly regionalized nor consistently trending. The DCIs provide a parsimonious yet comprehensive snapshot of geographic and temporal variations in the nature and extent of illicit drug problems. They have a number of practical applications, including the ability to succinctly communicate drug policy needs, objectives, and progress at the national, regional, and state levels. Other policy applications include aiding benchmarking, performance assessment, and resource allocation decisions.

Keywords: Drug-related consequences; Composite indicator; Interstate variations; Drug data systems (search for similar items in EconPapers)
Date: 2016
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DOI: 10.1007/s11205-015-1042-2

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