SYNOPSIS: Whiplash is a compensable injury in many jurisdictions, but there is considerable heterogeneity in the compensation arrangements that apply across jurisdictions, even within some countries. These compensation schemes have, however, been subject to a common set of interrelated concerns, chiefly concerning the incentives, behaviors, and outcomes that may arise when financial compensation for injuries is available to injured parties. This article provides a nontechnical overview of some of those concerns through the lens of economics: principally, insurance economics and health economics, including related subsets such as information economics and agency theory, as well as economics and the law. It notes that because it is generally infeasible to randomize the treatment (ie, compensation) via trials, analyses of observational data are necessary to discover more about the relationship between compensation and health outcomes. This poses the analytical challenge of discovering causal connections between phenomena from nonrandomized data sets. The present article calls for further research that would enable convincing causal interpretations of such relationships via the careful analysis of rich observational data sets using modern econometric methods.

The Nature of Whiplash in a compensable environment: Injury, disability, rehabilitation, and compensation systems

Connelly, Luke B.
2017

Abstract

SYNOPSIS: Whiplash is a compensable injury in many jurisdictions, but there is considerable heterogeneity in the compensation arrangements that apply across jurisdictions, even within some countries. These compensation schemes have, however, been subject to a common set of interrelated concerns, chiefly concerning the incentives, behaviors, and outcomes that may arise when financial compensation for injuries is available to injured parties. This article provides a nontechnical overview of some of those concerns through the lens of economics: principally, insurance economics and health economics, including related subsets such as information economics and agency theory, as well as economics and the law. It notes that because it is generally infeasible to randomize the treatment (ie, compensation) via trials, analyses of observational data are necessary to discover more about the relationship between compensation and health outcomes. This poses the analytical challenge of discovering causal connections between phenomena from nonrandomized data sets. The present article calls for further research that would enable convincing causal interpretations of such relationships via the careful analysis of rich observational data sets using modern econometric methods.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11585/610385
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