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Social Impacts Measurement in Government and Academia

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Social Impacts Measurement in Government and Academia Daniel Fujiwara d.f.fujiwara_at_lse.ac.uk Cabinet Office & London School of Economics I. Social impacts in public ... – PowerPoint PPT presentation

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Title: Social Impacts Measurement in Government and Academia


1
Social Impacts Measurement in Government and
Academia
  • Daniel Fujiwara
  • d.f.fujiwara_at_lse.ac.uk
  • Cabinet Office London School of Economics

2
I. Social impacts in public policy
  • Economists in government have a long tradition of
    measuring social impact Cost-Benefit Analysis
    (CBA).

3
The Green Book (1)
  • CBA enters at the Appraisal stage
  • Appraise policy interventions in terms of their
    social costs and benefits.
  • Further supported through the Social Value Act
    (2012)
  • ROAMEF cycle

4
The Green Book (2)
  • Supplementary Green Book guidance provides
    guidelines on how to value social impacts

5
The Magenta Book
  • Assessing whether the policy had a causal
    effect/impact

6
II. Social impacts research (1)
  • Valuation and Evaluation (causality) are key to
    understanding social impacts.
  • Valuation
  • Theory to find the monetary equivalent of the
    change in welfare or wellbeing associated with
    experiencing or consuming the good.
  • We could look at peoples preferences or their
    wellbeing
  • Wellbeing valuation recent research is looking
    at assessing value in terms of changes in
    subjective wellbeing (Fujiwara Campbell, 2011)
    with lots of potential for housing issues.

7
Social impacts research (2)
  • Evaluation (causality)
  • Evaluation scale (Dolan Fujiwara
    (2012) BIS technical report)
  • Theory Identifying
  • and measuring the
  • counterfactual
  • Many public sector
  • organisations moving
  • to the Maryland
  • Evaluation scale.
  • This scale ranks how
  • well counterfactuals have
  • been measured in the
  • analysis.

Level Design Statistical method
5 Randomised trials Evaluations with well implemented random assignment of treatment to subjects in treatment and control groups.
4 Quasi- Experiments Evaluations that use a naturally occurring event (that makes the treatment assignment as good as random)
3 Matching techniques Regression analysis Non-experimental evaluations where treatment and comparison groups are matched on observable characteristics
2 Simple comparisons Studies with a treated and comparison group, but with no attempt made to control for differences among the groups.
1 Pre- and post analysis Studies where no comparison group is used. Outcomes are measured pre and post-treatment.
8
III. Housing and social impact
  • Example Attaching values to aspects of housing
    through
  • the Wellbeing Valuation approach
  • Preliminary findings (not for citation)
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