Richard C. Feiock

dRCN/SRN Policy Actors Workshop:

Institutional Collective Action Framework

Richard C. FeiockLocal Governance Research Laboratory

Askew School of Public Administration and Policy

Institutional Collective Action Dilemmas

ICA dilemmas arise from problems of fragmented authority

Horizontal – jurisdiction/boundaries too small to achieve scale economies or avoid spillovers

Vertical – organizations at multiple levels pursuing overlapping policy objectives

Functional – spillovers across related or unrelated policy arenas

Governance Mechanisms to Mitigate ICA Dilemmas

Two Dimensions

AuthoritySocial Embeddedness

Contracting/Legal Obligations

Delegated Authority

Imposed AuthorityEncompassingness – complexity/scope

Narrow-single issue/bilateralIntermediate-multilateralEncompassing-complex/collective

ICA Mitigation Mechanismsin US Metros

EncompassingComplex/Collective

MultiplexSelf-organizing

Systems

CouncilsofGovernments/MPOs

RegionalAuthorities

ExternallyImposedAuthority/Annexation

Intermediate/multilateral

WorkingGroups

Partnerships/MultilateralILAs

Multi-PurposeDistricts

ManagedNetwork

Narrowsingleissue/bilateral

InformalNetworks

ServiceContracts

SinglePurposeSpecialDistricts

ImposedDistrict/Mandated Agreements

Embeddedness Contracts DelegatedAuthority

ImposedAuthority

Transaction Cost Imposed by Governance

Complexity and Authority Impose Decision and Autonomy Costs on Participants

Decision Costs - information, bargaining etc.

Autonomy Cost – loss of individual autonomy to make choice based on individual interests




Systems


RegionalAuthorities



WorkingGroups



ManagedNetwork


InformalNetworks

ServiceContracts




ImposedAuthority




Systems


RegionalAuthorities



WorkingGroups



ManagedNetwork


InformalNetworks

ServiceContracts




ImposedAuthority

Low decision andautonomy cost

High decision and autonomy cost

Collaboration Risk Risks that a specific governance mechanisms

will failThree forms of collaboration risk

Incoordination – finding partners

Division problems – fair allocation of costs and benefits

Defection – free riding or reneging on commitments

Where collaboration risk is high actors prefer encompassing and authoritative institutions

Collaboration Risk in Mechanism Choice

Three Sources of Collaboration RiskProblems – type/nature of the problemActors – actors involved and their preferencesInstitutions – existing institutions in place

Empirical tests of ICA seek to explain governance mechanisms to mitigate ICA dilemmas based on collaboration risk

Empirical StudiesLarge body of research on horizontal and vertical

collaboration in the USsingle and multiple mechanisms

case studies, network analysis, large n models (using ICSD and other data)

range of policy areas: land use, environment, energy, development, sustainability

Recent extensions:Internal functional ICA within cities

Cities/metro regions of Central America, Europe, and Asia

Empirical Study #1: Functional Collective Action of Sustainability

Feiock,R.Krause,R,HawkinsC.(2018).TheImpactofAdministrativeStructureontheAbilityofCityGovernmentstoOvercomeFunctionalCollectiveActionDilemmasJournalofPublicAdministrationResearchandTheory,28.forthcoming.

Functional Collective Action Problems§ Fragmentation of authority among policy areas, services, and

departments and agencies within a single government

§ Two questions§ What factors account for the internal admirative apparatus to

govern sustainability within cities?§ What types of governance institutions produce the

integrative portfolios of sustainability actions?

AdministrativeDesignDimensionsScopeofLeadAgencyAuthority

Numberofagenciesinvolvedindevelopingplansandinitiatives

§ Three factors will shape cities’ administrative design: § Political institutions§ Governmental capacity;§ Community and interest group support;

§ Broad lead agency authority and participation by more administrative units will produce more functionally integrated portfolios of sustainability policy.

Methods to Answer Question 1

§ CombinesICSDwitha2015sustainabilitypolicyinstrumentsurveybyFSULocalGovernanceLab

§ Descriptiveanalysis§ Estimationofpredictivemodels

§ Dependentvariable- LocationofLeadAgency§ Multinomiallogit

§ Dependentvariable– CountofNumberofPartners§ Negativebinomialregression

Descriptive Analysis of Governance

FactorsInfluencingtheScopeofHeadquartersforSustainability

Headquarter: Elected Official’s Office

Headquarter: Manager’s Office

Headquarter: Line Department

Political Institutions Mayor-council form of government

0.760* (0.447)

-1.304*** (.451)

-0.258 (.371)

Council elected at-large 0.010* (.005)

0.011** (.005)

0.004 (.004)

Council size 0.018 (.047)

0.024 (.048)

-0.048 (.049)

Government Capacity Per-capita own source revenue -0.123***

(.045) -0.068** (.031)

-0.099 *** (.029)

Budgetary conflict 0.185 (.0183)

0.181 (.161)

0.192 (.144)

Population size 0.005 (.004)

-0.050*** (.018)

-0.018** (.009)

Community Support Public support 0.316

(.274) 0.504** (.256)

0.369* (.214)

Neighborhood group support -0.923*** ( .298)

-0.683** (.273)

-0.634** (.249)

Constant 1.939 (1.768)

1.701 (1.647)

3.544** (1.474)

n = 492, LR χ2 = 102.06, p = 0.000 Multinomial regression, Independent Sustainability Unit base outcome * p < 0.05, ** p < 0.01, *** p < 0.001, Standard errors in parentheses

Coefficient

Incidence Rate Ratio

Political Institutions Mayor-council form of government -0.092

(0.073) 0.912

(0.066) Council elected at-large -0.002**

(0.000) 0.998**

(0.001) Council size -0.001

(0.003) 0.999

(0.002) Government Capacity Per-capita own source revenue 0.008

(0.006) 1.008

(0.064) Budgetary conflict -0.056**

(0.001) 0.946**

(0.027) Population size 0.001*

(0.001) 1.002* (0.001)

Community Support Public support 0.068

(0.046) 1.070

(0.050) Neighborhood group support 0.227***

(0.045) 1.255***

(0.057) Constant -0.116

(0.275) 0.891

(0.245) n = 492, LR χ2 = 49.66, p = 0.000 Negative binomial regression * p < 0.05, ** p < 0.01, *** p < 0.001, Standard errors in parentheses

Number of Functional Partners for Sustainability

Question 2 Design

§ DependentVariable- IntegrationPortfolioScore§ Negativebinomialregression

§ Dependentvariableisacitypolicyintegrationportfolio§ Portfolioofsevenpoliciesin2015

§ encourageorrequiremembersofthecommunitytomakeenergyefficiencyimprovementstobuildingsthatundergosignificantretro-fits

§ providechargingstationsforpluginelectricvehiclesinthecity

§ incorporateenergyuseconsiderationsintolandusedecisions

§ purchaseelectricityfromrenewablesources

§ developaclimateactionplantoreducecommunity-widegreenhousegasemissions

§ requiregreenprocurementpractices

§ utilizedemonstrationprojectstoexposecommunitymemberstotechnologyinnovationsrelatedtoclimateandenergy.

PercentofCitieswithEachPortfolioComponentinPlace

0

5

10

15

20

25

30

35

40

45

50

Green procurement

Buildings Transport Climate planning Renewables Land use Tech innovation

Perc

ent o

f citi

es

Policy Integration Portfolio Component (n=258)

DistributionofSustainabilityIntegrationPortfolioScore

0

10

20

30

40

50

60

70

80

90

100

0 1 2 3 4 5 6 7

Num

ber o

f citi

es

Number of portfolio policies in place (n=258)

Coefficient

Incidence Rate Ratio

Administrative Structure Number functional partners 0.064*

(0.037) 1.066* (0.040)

Hdqtr: Elected official’s office -0.423 (0.313)

0.655 (0.205)

Hdqtr: Manager’s office -0.620** (0.246)

0.537** (0.132)

Hdqtr: Line department -0.270 (0.198)

0.764 (0.152)

Hdqtr: Independent sustainability unit (excluded) (excluded) Political Institutions Mayor-council form of government 0.162

(0.152) 1.176

(0.178) Council elected at-large 0.003

(0.002) 1.003

(0.002) Council size 0.018

(0.027) 1.018

(0.028) Government Capacity Per-capita own source revenue 0.027

(0.017) 1.028

(0.002) Budgetary conflict -0.011

(0.055) 0.989

(0.054) Population size 0.008*

(0.005) 1.008* (0.005)

Community Support Public support 0.164*

(0.090) 1.178* (0.107)

Neighborhood group support -0.015 (0.091)

0.985 (0.090)

Constant -0.386 (0.559)

0.679 (0.380)

n = 214, LR χ2 = 30.32, p = 0.003 Negative binomial regression * p < 0.05, ** p < 0.01, *** p < 0.001, Standard errors in parentheses

Impact of Administrative Structure on Sustainability Policy Integration

Summary§ Insights into intra-jurisidictional functional collective action dilemmas

can be gained building on the rich research on inter-jurisdictional ICA dilemmas.

§ Administrative structure and constituencies matter§ Community support for sustainability, form of government, and support of

certain types of interest groups influence the organization and structure of sustainability.

§ Administrative headquarters and number of agency partners influence policy integration.

§ Manager office, population and public support for sustainability are linked to integration

EmpR. Zhang J. Ramaswami, A. Feiock, R. (2018). Regional irical Study #2: ICA Agreements on Regional Environmental Issues in China

What are environmental policy collaboration mechanisms among local governments in China?

What factors account for use of different regional collaboration mechanisms in China?

How well does ICA framework fit the context of Chinese local governance?

Yi, H., Suo, L. Shen, Governance and Institutional Collective Action for Environmental Sustainability in China. Public Administration Review, forthcoming.

Four Regions Studied

Beijing-Tianjin-Hebei

Pearl River DeltYangtze River DeltaChengdu Plain

Data Collection

China City Statistical Yearbook (2009-2012)289 prefecture cities in China

Demographic information (population, economy, budget, energy consumption, education, environment quality)

Digital Newspaper Dataset from China Digital Library

Media Search of media reports of every city

Daily and other papers; full text information

Central media reports, government annual work report

Research Design

Unit of analysis - Inter-governmental agreements

Method: Ordinal Logit Regression Analysis Dependent Variable: ICA mechanisms: informal, formal,

and imposed authority (1,2,3)

Independent VariablesProblem situation: Environmental quality

Contract characteristics: Multiple function or single function

Actor characteristics: Number of policy actors; scope of variation in administrative levels of cities involved; involvement of national government; involvement of provincial governments

HypothesesContract complexity

Single issue agreements are more likely to be enforced through social embeddedness,

Multiple issue agreements are more likely to be enforced through delegated authority

Actor characteristicsInvolvement of national/provincial governments will more

likely lead to delegated authority than informal agreement.

The fewer the number of policy actors involved in the agreement, the more informal the agreement.

The more the levels of cities involved in the agreement, the more hierarchical (delegated authority) the agreement.

Ordinal Logit Regression AnalysisDependent variable: ICA agreement type

(informal, formal, imposed)

Variables Coefficient SE PredictedRelationship

Environmentalquality -0.002 0.002 +

multiplefunctioncontract

0.559*** 0.199 +

numberofpolicyactors 0.048*** 0.018 +

levelsofcitiesinvolved -0.299* 0.157 +

involvementofnationalgovernment

0.888*** 0.192 +

involvementofprovincialgovernment

0.412** 0.182 +

N 287

Summary

More actors and functions lead to more formal agreements

Differences in levels among cities leads to more formal agreements

Involvement of higher governments leads to more formal agreements

ExtensionsCity as Unit of Analysis - Hierarchical Linear Model

Dyads as Units of Analysis - Network Analysis

ICA: What is Next?

Applications of ICA within SRNInternalcoordinationofWHEe withincities

RegionalCoordinationthroughMPOsandotherregionalentities

MultistateAgreements

InternationalAgreements

Applications of ICA across scaleAll situations of fragmented authority

FSU Local Governance Labhttp://localgov.fsu.edu

Richard C. Feiock

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