Imrecon

Incentive analysis & design E-mail

Incentives lie at the heart of incentive regulation and at the heart of Imrecon's practice, and Imrecon exists to help policy makers incentivise better outcomes.  The analysis and design of incentives is thus an underpinning theme behind much of Imrecon's work.

Ian Rowson realised early in his work with regulators that:
  • like risk, incentives are about what happens when outturns are different from expectations
  • analysing incentives requires analysing the effects of uncertain outturns

This led him to recognise that incentive analysis and risk analysis are closely related, and that the techniques of risk analysis can help inform incentive policy.

Basic incentive analysis

However, Imrecon only uses explicit risk analysis techniques when they add serious value to the analysis.  Most of the time, high quality analysis can be carried out just as rigorously using simple logical illustration, requiring little in the way of formal modelling, simulation or other advanced techniques.  Academic literature and regulatory precedents can sometimes also be helpful.

However, Imrecon believes the experience of incentive modelling informs any incentive analysis through a better understanding of how the following might interact:

  • incentive objectives
  • the motivation dynamics of participants
  • uncontrollable aspects of the environment
  • the potential scope of regulatory tools and levers
  • features of mechanism design

to support such analysis, Imrecon uses a framework known as PAACTS.  PAACTS takes into account not only the first order effects of a proposed mechanism but also aspects of the wider policy environment that impact on the effectiveness of incentives.

Systematic incentive analysis

Imrecon believes that the technique of policy simulation modelling is ideally suited for times when the analysis and design of incentives must take account of relatively complex interactions, when the effects of incentives need to be explained or illustrated or when a policy body must demonstrate formally that it has reached an optimal decision.  The following chart shows an output of a simulation of 100 scenarios for a rolling incentive mechanism operated by a UK regulator.

 policy1graphtight440

 

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