Quantitative Methods for
Studying Collective Action
and Property Rights
Ruth Meinzen-Dick and
Nancy McCarthy
IFPRI
© 2004 IFPRI
Presentation at the CAPRi training course on Natural Resource Management and Institutions: the links between
property rights, collective action and natural resource management, 7-11 February, ICRISAT, Hyderabad, India
Quantitative Methods
• Attempts to generalize across some
“population”
• Techniques for testing strength of
relationship, probability that it is “true”
• Tradeoffs between sample size (which
helps in generalizing, testing), depth,
skills, and cost of study
Sampling
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Essential for statistical testing, generalizing
Guard against biases
Need to identify “population”
Sampling methods
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Select randomly
Stratify by hypothesized key variables (H/M/T in irrigation)
Multi-stage: e.g. select communities then households
NOT “convenience sample”!!
• These principles are also useful for qualitative
studies!! (How representative are your findings?)
What Level of Analysis?
• Potential Levels of Interest
– Intra-household (do outcomes differ for
different members of the family)
– Household
– Particular group(s) within the community?
– Community-level outcomes
– Groups that function above level of
community?
What Level Data Collection?
• Even if level of analysis is household or
intra-household, often very important
to collect some data at the community
level:
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Agro-ecological Data
Distance to Market
Community Infrastructure
Social “Cohesion”
Cooperative Capacity
Alternatively, Even if Community, Might
Want Household-Level Data
• Heterogeneity within the community:
distribution of wealth (land or livestock
holdings), how many with higher education,
proportion of different ethnic groups etc.
– Potential Difficulty: If you are collecting
household and community-level data, some
people are tempted to use “household averages”
within a community, but… very few studies
include enough households per community so
that the sampled households are representative;
averages of sampled households can be very
misleading.
Data Collection Methods
• Individual or household survey
• Key informant interview
– NGOs, officials, local leaders, poor
women, etc.
• Focus groups
Consider what you can get from each
– Private or public knowledge
– Norm or exceptions
Mapping Data to Methods
Data
Water
scarcity
Castes
Landhold
Key
informant
Focus
group
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Income
WUA
particip
WUA
structure
Secondary HH Survey
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Complications
• Usually, we have “abstract” concepts (e.g.
social cohesiveness) that require
operationalization
– How will it be measured, concretely?
• Even if variable at first seems easy… may not
be! e.g.
– size of landholdings in areas without titles
– crop yield and how much of crops sold
– often different and/or non uniform
measures
What to Collect
• Preparation is key… Think through variables
you want to explain AND variables you think
are explanatory
• Draw out diagram—what is likely to cause or
influence other variables?
• Distinguish between:
– Exogenous: externally generated, not
influenced by other variables in the set
– Endogenous: those that are influenced by
other variables that you are studying
Exogenous and Endogenous
Resource
scarcity
Collective action
Group size
Market
development
Castes
Education
User group
Resource outcome
Exogenous and Endogenous
• Can’t use an endogenous variable as an
independent variable in a regression
– e.g. user association in regression on collective action
• Option 1: Instrumental variables
– Find a proxy for the endogenous variable, that is not
influenced by other variables in the system.
• Option 2: Multi-stage analysis
– User association as function of exogenous variables
– CA (work days) as function of predicted value of user
association & other exogenous variables (not same set of
independent variables)
What to Collect: Household Decisions
• Lists are excellent!
Endogenous:
Measure:
Exogenous:
Measure(s):
HH participation in Planting Trees on Common Land
Number of Hours Contributed (Actual)
Opportunity Cost of Adult Labor
Wage rates for Adult Males and Females (Actual), or
Dependency Ratio (Proxy, Adult Females), or
Total Number of Adults (Proxy, Family Labor, which
assumes that labor markets completely missing)
Education (Proxy, Household Data by Adult)
What to Collect, Household Instruments
• After going through the list, go back through the exogenous variables,
and critically assess: Is it really exogenous?
• If you have reason to believe that it is not, then must come up with
potential variables to use as instruments
• Example:
Endogenous: Household Participation in planting trees on common
lands/pastures
Exogenous: Number of livestock (often used as a measure of
“wealth”). Is it exogenous? Probably not. Why? Decision on
participation and livestock likely to be a joint – same variables will
affect both decisions.
Potential Instruments: Stock (number or value) of consumer
durables; whether household is from traditionally “livestock-owning”
ethnic group, total number of livestock held at formation of
household.
What to Collect, Community
Endogenous: Maintenance of Community Irrigation
Measure(s): Engineer/Other Expert Assessment – Quality Ranking (Actual,
outside expert), or
Number of Hours and/or Money Contributed (Actual,Survey of
Person In-Charge of Maintenance, perhaps corroborated with
household surveys?), or
Measure of number of months functioned in last 12 months
(Actual, Survey of Person In-Charge, or Focus Groups? What if
information differs across sources?)
Exogenous 1: Benefits of Maintenance
Measures(s): Might assume benefits same across all communities (water for
humans and/or animals, the same), so no variable, or
Alternative water sources (own tubewells? % of community
members, either from group interviews or key informant
interview); price of purchased water (either from group
interviews, or from shop that sells locally, etc.)
What to Collect
Endogenous:
Maintenance of Community Boreholes
Exogenous 2:
Heterogeneity within the community
Measure(s) Ethnic Differentiation (diversity index, or number of
groups) Actual, Key Informant and/or Focus Groups
Wealth Differentiation (diversity in landholdings, % community
members with vehicles or other expensive consumer durables)
Actual, Key Informant and/or Focus Groups, possible
corroboration with household level data (if enough
household data))
Difference in Education (proportion of households with at least
one member with primary, secondary schooling; Focus Groups
but still difficult to get if large community
Complications Specific to Property
Rights
• Property Rights…
– To a specific resource, or specific land/water
area?
– Of a specific person over certain resources
• If so, are the rights complete (to all resources, without
condition?) and/or unconditional (always have rights, or
does strength of right depend on other factors (e.g.
relative rainfall)
• If incomplete or conditional, can characterize in any
way that is “quantifiable” or easily comparable across
individuals, across communities and regions?
Complications Specific to Collective Action
• Measuring “Capacity” to Undertake Collective
Action at the group or community level:
Potential Measures: Trust, Social Cohesion, Agency,
History of Success and/or Failure
– How do you measure “trust” amongst members and get an
indicator of trust at the level required (the group or the
community). Some have tried the following:
Question at Household Level: Do you trust immediate
family members to watch your children? family friends?
Neighbors in the village?
Potential Problems: If not enough households sampled,
then may not be representative; what if a household has
no small children?
Complications Specific to Collective Action
Potential Measures: Trust, Social Cohesion, Agency,
History of Success and/or Failure
– How do you get a quantifiable, comparable (across
communities) measure social cohesion? Social
differentiation often used, but there can be tensions even
in communities where members all of same ethnic group
and speak same language
– Agency (A. Krishna): even when there is the “will” there is
often not the “way”. How do you measure the capacity to
transform “social capital” into collective action?
•Possibilities: Characteristics of Leadership and/or
Entreprenuership.
Complications Specific to Collective Action
Potential Measures: Trust, Social Cohesion, Agency,
History of Success and/or Failure
– How do you get a quantifiable, comparable (across
communities) measure of the historical experience with
collective action, particularly in large, heterogeneous
communities?
Potential Difficulties with simply “counting” successes and
failures:
1. Greater capacity may well lead a group to try more
things, and more difficult things – so number of failed (or
less successful) activities should be greater! Also, implies
endogeneity!
2. In practice, people prefer to speak of successes, so
data collected likely to be biased
Recall Data
• Subjective: Successes and failures; the
human tendency:
•The past was always better, generically, or
•Difficulty discussing negatives/failures
• Objective: Historical recall data on assets
(livestock), rainfall, climate, other shocks
•Nearly impossible to get good data for more than 5 years,
even 5 years is very difficult (e.g. livestock holdings),
•Rainfall, as with positive and negative subjective events,
people tend to forget how “bad” it was in past. Borana
“forgot” 1991-92 drought, which was quite devastating.
•Shocks (pest infestation, human disease, drought): Worst
shocks will be those most recently experienced,
irrespective of whether more likely to happen again.
• Possible Solution: Wherever possible, get secondary
corroborating data, or do very extensive job of
triangulating information from multiple sources
• Preferences and Subjective Assessments:
– Need to make sure that everyone has the
same “reference point”; e.g.
•Those in communities with generally bad soil might
rank their own plot as favorable… relative to the
generally poor soils in the area; if ask someone in
different area, might rank quality of his/her plot as
“average”, when in fact is much better because
soils generally more favorable
•Same with questions of leadership, for instance. If
community used to fairly poor leadership, current
leader may be relatively good, but in fact may still
be worse than in other community where
leadership ranked as poor – since that community
may have a different experience and expectations
• Open-Ended, Semi-Structured
Interviews:
– Enumerator Bias:
•In Burkina Faso, information on waterpoint
management perfectly correlated with 1 of 3
enumerators. Enumerator had previous water
project implementation experience; his 18
communities reflected his bias in how should be,
so no information on how is
•In India, information on individuals’ risk
preferences were nearly completely correlated
with the enumerator…
Final Thoughts
Some things simply not amenable to
quantification:
• Processes (how decisions are made, enforced)
• Variables with many “dimensions”; e.g. certain
tenure situations where many multiple,
overlapping claims over same resource
• Many subjective assessments – this does NOT
mean are not important, it means difficult to
construct questions that allow comparable
information to be generated across households
in many different regions