mapping interest group populations
DESCRIPTION
Joost Berkhout, post doctoral researcher, department of political science. Mapping interest group populations. ECPR Summer School on Interest Group Politics. Contents. Group populations: so what? Knoke, and more State of the field; top-down vs bottom up Descriptive efforts: data challenges - PowerPoint PPT PresentationTRANSCRIPT
Mapping interest group populationsECPR Summer School on Interest Group Politics
Joost Berkhout,
post doctoral researcher, department of political science
Joost Berkhout 2
Contents
Group populations: so what?
Knoke, and more State of the field; top-down vs bottom up Descriptive efforts: data challenges
Brulle et al, Halpin et al, Wonka et al Examining and explaining the EU population
Berkhout, Lowery, Messer (2/3 articles)
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Interest populations: So what?
Typical raw data Knoke (and others): who are in positions of
power? Links to stages in influence production process:
on strategies, policy success,
and organizational survival/maintenance. Lowery: theoretically interesting in itself
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Population data in your PhD project:
In your research:
As independent or dependent variable?
Of a specific (policy) sector or issue? Of a
specific type of organization? Comparing
countries? Snapshot or time-series? Research strategies?
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Top-down or bottom-up nature of registers (1):
Top-down: Priority to policy-related activities E.g. consultation lists, entry-registers (or other lobby
disclose rules), lobby offices Suitable for questions about strategies and
influence
Other activity-related sources: police registers on protest, newspaper coverage, negotiating actors in corporatist bargaining
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Top-down or bottom-up nature of registers (2):
Bottom-up: Priority to collective action E.g. directories of associations, formal
registers related to legal status (tax, commerce)
Suitable for questions about mobilisation and populations
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State of the field; top-down, policy perspective
US origin, recent EU, Scottish and comparative work
Common findings: Institutions numerically dominate Volatile / fluid: ‘political hibernation’, EU
tourists, policy amateurs Increase of ‘social interests’ Arena matters
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State of the field: bottom-up, collective action perspective
Studies of social movement organizations Common findings:
Cross-sector, cross-issue, cross guild
variation
Density dependence
Variation in political interest
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US environmental movement, Brulle et al.
About 100 years Required a large number of directories, ‘bottom
up’ Defined by aim: ‘organization that seeks to
bring about improvement of natural environment’ (257). And: exc.: representatives of ‘for profit’ or ‘government’ organizations
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Mapping Organised Interests, Halpin and Baxter
Consultation registers in Scotland. Support for:
Salisbury (1984): institutions dominate the system
Scholzman (2009): Fluid system, ‘non-political’ organizations briefly take ‘political’ roles
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EU data set by Wonka et al.
Snapshot of organizations seemingly active in the EU policy process in 2008
Combination of: Public Affairs Directory (Dod´s / Landmarks) EP register (from EP website) CONECCS (EC stopped in summer 2007,
started new register in 2008)
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The changing demography of the EU interest system since 1990 (1)
EUP, 11(3), 2010 Patched-up design
of multiple directories, 1996
Use of samples to estimate overlap
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The changing demography of the EU interest system since 1990 (2)
Findings: Growth in early nineties, then stability From end of nineties: Larger proportion of ‘public’
interests and change in organizational forms; think tanks, regional representations.
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Short-Term Volatility in the EU Interest Community
JEPP, 18(1), 2011 EP entry register (and a
bit of CONECCS), sample ‘Surprisingly volatile’ Typical age-distribution:
‘old bulls’ vs ‘tourists’
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The Density of the EU Interest System: A Test of the ESA Model
BJPS, forthcoming Variation in numbers of organizations per interest
guild explained by: Area (supply): Value added // potential
membership Energy (demand): legislation, consultation
Difficult empirical integration of social and economic interests; contrasting underlying mechanisms
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Figure 2: Predicted numbers of interest organizations by economic guild area size (indexed), based on Model 3
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Economic guild area size (indexed)
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Predicted values of Y, Model 3 Linear (Predicted values of Y, Model 3)Poly. (Predicted values of Y, Model 3)
Outlier: Banking, finance and insurance
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Figure 1: Predicted numbers of interest organizations by social guild area size (indexed), based on fully specified model
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-1 -0,5 0 0,5 1 1,5
Social guild area size (indexed)
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Predicted values of Y, full model Poly. (Predicted values of Y, full model)
Human rights, development
Health issues
Environment, animal rights Labor unions
Social welfare
Education, art, culture
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Recap: Population data in your PhD project:
In your research:
As independent or dependent variable?
Of a specific (policy) sector or issue? Of a
specific type of organization? Comparing
countries? Snapshot or time-series? Research strategies?