Institutional Collective Action and Local Government Collaboration

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Institutional Collective Action and Local
Government Collaboration

• Richard C. Feiock
• Askew School of Public Administration Policy
• Devoe Moore Program in Local Governance
• Florida State University

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Overview of Paper

• Institutional Collective Action
• Motivations for Cooperation
• 1) Collective
• 2) Selective
• Identify how do transaction costs and the ability
  of local actors to overcome them depend on
• 1) characteristics of services
• 2) characteristics of communities
• 3) political institutions
• 4) structure of policy networks.
• Advance specific propositions regarding evolution
  and effectiveness of interlocal collaboration.
• Report preliminary findings regarding interlocal
  agreements and economic development joint
  ventures.
• Present an agenda to investigate institutional
  collective action among local governments.

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Institutional Collective Action (ICA)

• Focuses on collective behavior of organizations
  or governmental units rather than individuals
• Local Actors participate in collaborative
  intergovernmental arrangements when their
  benefits exceed transaction costs.

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Why Cooperate?Motivations for Collaboration

• Collective
• Economies of Scale in Production
• Spillover and Externalities
• Selective
• Political costs and benefits for elected
  officials
• Career consequences for professional managers

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Transaction Costs Barriers to Cooperation

• Bargaining Costs - there can be at most small
  resource costs associated with the process of
  negotiating a deal
• Information Costs - information on the
  preferences of all participants over possible
  outcomes and on their resources must be common
  knowledge
• Agency Costs - bargaining agents must perfectly
  represent the interests of their constituents
• Division Costs - the parties must agree to a
  division of the bargaining surplus
• Enforcement Costs - there can be at most low
  costs associated with monitoring and enforcing
  the agreement.

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Characteristics of Goodsand Services

• Proposition 1a The likelihood of the emergence
  of collaborative intergovernmental agreements and
  their durability are negatively related to the
  extent to which a service requires asset specific
  investments.
• Proposition 1b The likelihood of the emergence
  of collaborative intergovernmental agreements and
  their durability are negatively related to the
  difficulty in measuring and monitoring service
  outcomes.

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Characteristics of Communities

• Proposition 2a The likelihood of the emergence
  of collaborative intergovernmental agreements and
  their durability are negatively related to
  demographic heterogeneity among local
  governments.
• Proposition 2b The likelihood of the emergence
  of collaborative intergovernmental agreements and
  their durability are negatively related to
  demographic heterogeneity within local
  governments.
• Proposition 2c The likelihood of the emergence
  of collaborative intergovernmental agreements and
  their durability are negatively related to the
  geographic distance between local governments.

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Characteristics of Political Systems

• Proposition 3a The likelihood of the emergence
  of collaborative intergovernmental agreements and
  their durability are negatively related to the
  restrictiveness of state laws authorizing
  interlocal cooperation.
• Proposition 3b The likelihood of the emergence
  of collaborative intergovernmental agreements and
  their durability are related to form of
  government.
• Proposition 3c The likelihood of the emergence
  of collaborative intergovernmental agreements and
  their durability are negatively related to
  district based representations systems.
• Proposition 3d The likelihood of the emergence
  of collaborative intergovernmental agreements and
  their durability are positively related to tenure
  in office of elected and appointed officials.
• Proposition 3e The likelihood of the emergence
  of collaborative intergovernmental agreements and
  their durability are negatively related to
  institutional heterogeneity in the political
  structure of local governments.

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Certain Network Structures Can Mitigate or Reduce
Specific Transaction Problems

• Proposition 4a The likelihood of the emergence
  of collaborative intergovernmental agreements and
  their durability are positively related to
  bridging weak tie network relationships among
  local governments.
• Proposition 4b The likelihood of the emergence
  of collaborative intergovernmental agreements and
  their durability are positively related to
  tightly-clustered strong tie network
  relationships among local governments.
• Proposition 4c The likelihood of the emergence
  of collaborative intergovernmental agreements and
  their durability are positively related to a
  history or reciprocal dyadic relationships across
  time and policy arenas.

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Ongoing Projects

• Park, Feiock Steinacker economic development
  joint ventures
• Shrestha Feiock interlocal service
  expenditures
• Scholz Berardo water projects in Tampa Bay
  estuary
• Park Feiock regional economic development
  partnerships
• Shrestha 25 years of ILAs in Pinellas
  County
• Ramirez networks among land use actors Leon
  Cnty
• Park Feiock network survey Orlando/Tampa
• Kwon ILAs among cities in COGs, RPCs and MPOs
• Yoo developments of regional impact (DRI) in
  FL
• Farmer regional special purpose districts

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Economic Development Joint Ventures Park,
Feiock Steinacker

• Survey of development directors of cities over
  50K population.
• -responses from 254 of 522 cities (48.7).
• Questionnaire gathered information on development
  policies and politics, contacts with other
  governments, development partnerships, and joint
  ventures.
• Combined with archival demographic, fiscal data
  and service expenditure data.
• Probit Analysis

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Collaboration in the Supply of Public Goods
Transaction Costs and Social Exchange
TheoriesManoj Shrestha Richard Feiock

• Dependent Variable City expenditure for
  payment-for-service and/or joint service
  agreements to other local governments for the
  supply of 11 public services in Georgia
• H1 The relationship between asset specificity
  and interlocal service cooperation follows an
  inverted U shape at lower levels, asset
  specificity increases cooperation, but beyond
  some point, further increases in asset
  specificity decrease cooperation.
• H2 The relationship between measurement
  difficulty and interlocal service cooperation has
  an inverted U shape at low levels, measurement
  difficulty increases cooperation, but after some
  point measurement difficulty decreases
  cooperation
• H3 The relationship between trust resulting from
  previous exchange and interlocal cooperation is
  linear the greater the level of previous
  exchange, the higher the interlocal service
  cooperation.

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Heckman two-stage results
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Probability of Cooperation by Asset Specificity
and Measurement Difficulty
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Statistical Models of Collaboration
NetworksSimulation Investigation for Empirical
Network Analysis (SIENA)

• Compares the likelihood of the observed network
  with randomly generated networks having the same
  number of links.
• Actor-oriented model. At random time points
  actors evaluate current configurations and make
  or terminate a link to maximize the implicit
  utility function
• The utility function can include a parameter
  vector containing both structural properties of
  the network and actors particular attributes.
• The output provides parameter estimates as well
  as estimates of the uncertainty of estimation
  which permits statistical testing.

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Insights from ICA

• Collaborations and regional governance is
  possible even in very decentralized political
  systems.
• Political, not just economic, interests shape the
  costs and benefits of cooperation for local
  actors.
• Endogenous network relationships are important.
• Salience of both actors and relationships.

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Thank You
http//www.fsu.edu/localgovresearch_projects/regi
onal_governance.htm
http//www.fsu.edu/localgovresearch_projects/regi
onal_governance.htm
http//www.fsu.edu/localgovresearch_projects/regi
onal_governance.htm
http//www.fsu.edu/localgovresearch_projects/regi
onal_governance.htm
http//www.fsu.edu/localgovresearch_projects/regi
onal_governance.htm
http//www.fsu.edu/localgovresearch_projects/regi
onal_governance.htm
http//www.fsu.edu/localgovresearch_projects/regi
onal_governance.htm
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What Network Structures Emerge for Water
Services

• Relational analysis of water related services
• Actors - 25 governments in Pinellas County, FL
• Use of inter-local service agreements
• Payment-for-service agreements
• Perspective of the receiver (buyer) government
• Directed relationships (digraphs)
• One moment in time

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Observed networks
Density 0.04 Av. degree 1.04
Density 0.05 Av. degree 1.24
Water network
Sewer network
Density 0,02 Av. Degree 0,40
Density 0.013 Av. Degree 0.32
Utility billing network
Conservation network
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Why the star network? - Theory

• Fragmented governments and inefficiency in local
  service supply
• Voluntary bargaining and service cooperation
  (Coase theorem)
• Gains from service cooperation
• Direct benefits
• Indirect benefits
• Costs - Transaction risks and uncertainties
• Maintaining the relationship (link)
• Finding a good partner (search cost)
• Risks associated with asset specificity
• Locked up in transaction (needs assurance in
  supply)
• Things change (adaptability)
• Dependency (repeated action)

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Local Government Response

• Emulative behavior
• Limited access to information
• Bounded rationality
• Emulation combined with cost of maintaining links
  lead to emergence of star network
• Future eventualities and dependency reinforce and
  maintain the star structure
• Reputation restrains opportunism by star
• Actor with critical ability emerges as the star
• Indirect link results extended star network
• Heterogeneity leads to multiple star network

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Emergence of Star Networks
A
A
Economies of scale
A
A
Homogeneous world
Heterogeneous world
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Various in-star configurations
In-star network
Extended in-star network
Interlinked multiple in-star network
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Modeling networks with SIENA

• P model
• Structural effects
• Alternating in-k-star
• Reciprocity
• Out 2-star
• 2-path
• transitivity
• Attribute effects
• Size effect
• Geographic proximity
• Similarity effect gt same service, council-manager
  government

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Configuration of network effects
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SIENA p estimation results
Effects labeled in italics indicate significance
at p lt 0.05. All the models meets the
goodness-of-fit test.
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Which government is popular?
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Conclusion

• Main findings
• Prevalence of popularity structure
• Popularity through structural process is evident
  in water service
• In other services, the popularity structure is
  driven by size
• Bottom line
• Connecting to the well-connected seems to be
  the general rule