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3D impact analysis
A new tool to approach impact evaluations
April 23, 2015
CDI is a joint initiative between:
1
and and
For more information: www.ids.ac/cdi or email: cdi@ids.ac.uk
Rob D. van den Berg
Visiting Fellow, IDS
Overview
• What is impact?
• What is evidence?
• What is causality?
• What is attribution/contribution?
• Time
• Space
• Scale
2
Impact
• Impact is an ordinary word in the English
language
– “the effective action of one thing or person on
another; the effect of such action; influence;
impression”
• Its meaning cannot be scientifically claimed
• Demand for impact evidence can refer to a
wide variety of effects, influences and
impressions
3
Evidence
• Evidence is an ordinary word in the English
language
– “the quality or condition of being evident;
clearness; evidentness”
• Its meaning cannot be scientifically claimed
• Demand for impact evidence can refer to a
wide variety of qualities or conditions
4
Causality
• The word “cause” is an ordinary word in the
English language
– “A person or thing that gives rise to an action,
phenomenon, or condition”
• Its meaning cannot be scientifically claimed
• Demand for evidence of cause and effect can
refer to a wide variety of actions, phenomena
and conditions
5
Attribution / Contribution
• Both words are ordinary words in the English
language, with great variety in meaning
– Attribution: in copyright law, requiring an author
to be credited; in marketing, assigning a value to a
marketing activity based on desired outcome;
journalism, practice of attributing information to
its source
– Contribution: donation, sharing, payment,
publication, a song by Mica Paris
6
Impact Evaluation
• Focus of Impact Evaluations:
– Impact = evidence of causality between an
intervention and the desired effect by establishing
a counterfactual through controlled
experimentation, which attributes part of the
effect to the intervention
• This partially meets the demand for impact
evidence in politics, the media and society
• So what to do with other demands?
7
Meeting impact demand
• Broaden the concepts of impact and causality
• Broaden the range of scientific methods and
tools
• Develop a framework for understanding
demand for impact evidence
• Incorporate issues of time, space and scale
• This is urgent, given the adoption of the
Sustainable Development Goals in September
2015
8
Understanding causality
• Schaffer (2013) proposes two kinds of causality:
“difference” and “production”
– Difference: with/without (counterfactual) analysis
– Production: A “produces” B (natural systems, physics &
technology)
• Concepts that include causality:
– Catalytic roles (the change agent speeds up change but is
not involved in the change itself)
– Dynamic and chaotic systems (feedback loops, iterative
processes, Fibonacci sequences)
• Terry Pratchett: “hardly anything important has a single
cause”
9
Issues of time, space and scale
• Some changes can be observed immediately – others take
decades
– Short-term results: vaccinations, technology transfer, new
livelihood approaches etc.
– Either short- or long-term: market transformations, societal
change
– Long-term results: health trends, ecosystem services, ozone
layer
• Some changes are local, other regional, national or even
global
• Some changes concern one actor, intervention or
institution, others involve multiple actors or institutions,
and multiple sectors
• Sustainable development involves longer time horizons,
overlapping locations and many scales
Matrix of evaluable impact
• Impact can be evaluated at different moments in time: ex
ante, in real time and ex post
– These can be refined: ex ante tends to be done once, but real
time and ex post have many possibilities
– Different processes tend to have different time horizons
• Geographical space runs from local to global
– These can also be refined: the boundaries of societies,
economies and natural systems are different from each other
and may overlap
• Scales of involvement can go from one actor to a
multiplicity, from one market to a full economic system,
from one governance level (or sector) to many
– Actors, markets and governance may not fully overlap
12
Appraisal
Inception
Implementation
End-of-project
2 years ex-post
5-8 years ex-post
13
Local Regional National Global
One
Multi-
actor
Multi-
sector
Matrix dimensions space and time
14
Ex ante Inception Mid-term End of
project
Ex post <
2 years
Ex post 5-
8 years
Local
National
Regional
Global
Ecosystem
(overlap with
other rows)
Experimentation
Mixed methods /
theory of change
approaches
Monitoring and data
analysis (including “big
data”)
Matrix dimensions space and scale
15
One inter-
vention
Multiple
inter-
ventions
Enabling
environ-
ment
Market
change
Market
transform
-ation
Climate
change
Local
National
Regional
Global
Ecosystem
(overlap with
other rows)
RCTs
Data
analysis
Monitoring
Mixed methods / theory of change
Double evaluand evaluations
Matrix dimensions scale and time
1616
One inter-
vention
Multiple
inter-
ventions
Enabling
environ-
ment
Market
change
Market
transform
-ation
Climate
change
Ex-ante
Inception
Real-time
End-of-
project
Ex-post
RCTs and
quasi-
experimental
Data
analysis
Monitoring
Mixed methods / theory of change
Counterfactual analysis
17
One inter-
vention
Multiple
inter-
ventions
Enabling
environ-
ment
Market
change
Market
transform
-ation
Climate
change
Local
National
Regional
Global
Ecosystem
(overlap with
other rows)
RCTs
Modelling of data
and
experimentation
(quasi- and natural)
Quasi-
experimental
and QCA
Social
Network
analysis
Delphi
Production causality
18
One inter-
vention
Multiple
inter-
ventions
Enabling
environ-
ment
Market
change
Market
transform
-ation
Climate
change
Local
National
Regional
Global
Ecosystem
(overlap with
other rows)
Inspection, validation
before/after data
Verification of data, trend analysis
Systems evaluation
Thank you!
rdwinterberg@gmail.com
19
For more information: www.ids.ac/cdi or email: cdi@ids.ac.uk

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CDI Seminar: 3d impact analysis

  • 1. 3D impact analysis A new tool to approach impact evaluations April 23, 2015 CDI is a joint initiative between: 1 and and For more information: www.ids.ac/cdi or email: cdi@ids.ac.uk Rob D. van den Berg Visiting Fellow, IDS
  • 2. Overview • What is impact? • What is evidence? • What is causality? • What is attribution/contribution? • Time • Space • Scale 2
  • 3. Impact • Impact is an ordinary word in the English language – “the effective action of one thing or person on another; the effect of such action; influence; impression” • Its meaning cannot be scientifically claimed • Demand for impact evidence can refer to a wide variety of effects, influences and impressions 3
  • 4. Evidence • Evidence is an ordinary word in the English language – “the quality or condition of being evident; clearness; evidentness” • Its meaning cannot be scientifically claimed • Demand for impact evidence can refer to a wide variety of qualities or conditions 4
  • 5. Causality • The word “cause” is an ordinary word in the English language – “A person or thing that gives rise to an action, phenomenon, or condition” • Its meaning cannot be scientifically claimed • Demand for evidence of cause and effect can refer to a wide variety of actions, phenomena and conditions 5
  • 6. Attribution / Contribution • Both words are ordinary words in the English language, with great variety in meaning – Attribution: in copyright law, requiring an author to be credited; in marketing, assigning a value to a marketing activity based on desired outcome; journalism, practice of attributing information to its source – Contribution: donation, sharing, payment, publication, a song by Mica Paris 6
  • 7. Impact Evaluation • Focus of Impact Evaluations: – Impact = evidence of causality between an intervention and the desired effect by establishing a counterfactual through controlled experimentation, which attributes part of the effect to the intervention • This partially meets the demand for impact evidence in politics, the media and society • So what to do with other demands? 7
  • 8. Meeting impact demand • Broaden the concepts of impact and causality • Broaden the range of scientific methods and tools • Develop a framework for understanding demand for impact evidence • Incorporate issues of time, space and scale • This is urgent, given the adoption of the Sustainable Development Goals in September 2015 8
  • 9. Understanding causality • Schaffer (2013) proposes two kinds of causality: “difference” and “production” – Difference: with/without (counterfactual) analysis – Production: A “produces” B (natural systems, physics & technology) • Concepts that include causality: – Catalytic roles (the change agent speeds up change but is not involved in the change itself) – Dynamic and chaotic systems (feedback loops, iterative processes, Fibonacci sequences) • Terry Pratchett: “hardly anything important has a single cause” 9
  • 10. Issues of time, space and scale • Some changes can be observed immediately – others take decades – Short-term results: vaccinations, technology transfer, new livelihood approaches etc. – Either short- or long-term: market transformations, societal change – Long-term results: health trends, ecosystem services, ozone layer • Some changes are local, other regional, national or even global • Some changes concern one actor, intervention or institution, others involve multiple actors or institutions, and multiple sectors • Sustainable development involves longer time horizons, overlapping locations and many scales
  • 11. Matrix of evaluable impact • Impact can be evaluated at different moments in time: ex ante, in real time and ex post – These can be refined: ex ante tends to be done once, but real time and ex post have many possibilities – Different processes tend to have different time horizons • Geographical space runs from local to global – These can also be refined: the boundaries of societies, economies and natural systems are different from each other and may overlap • Scales of involvement can go from one actor to a multiplicity, from one market to a full economic system, from one governance level (or sector) to many – Actors, markets and governance may not fully overlap
  • 13. 13 Local Regional National Global One Multi- actor Multi- sector
  • 14. Matrix dimensions space and time 14 Ex ante Inception Mid-term End of project Ex post < 2 years Ex post 5- 8 years Local National Regional Global Ecosystem (overlap with other rows) Experimentation Mixed methods / theory of change approaches Monitoring and data analysis (including “big data”)
  • 15. Matrix dimensions space and scale 15 One inter- vention Multiple inter- ventions Enabling environ- ment Market change Market transform -ation Climate change Local National Regional Global Ecosystem (overlap with other rows) RCTs Data analysis Monitoring Mixed methods / theory of change Double evaluand evaluations
  • 16. Matrix dimensions scale and time 1616 One inter- vention Multiple inter- ventions Enabling environ- ment Market change Market transform -ation Climate change Ex-ante Inception Real-time End-of- project Ex-post RCTs and quasi- experimental Data analysis Monitoring Mixed methods / theory of change
  • 17. Counterfactual analysis 17 One inter- vention Multiple inter- ventions Enabling environ- ment Market change Market transform -ation Climate change Local National Regional Global Ecosystem (overlap with other rows) RCTs Modelling of data and experimentation (quasi- and natural) Quasi- experimental and QCA Social Network analysis Delphi
  • 19. Thank you! rdwinterberg@gmail.com 19 For more information: www.ids.ac/cdi or email: cdi@ids.ac.uk