City Contracting Slides by yurtgc548


									The Governance of Contractual Relations:
    Incentives and Transaction Costs

             Steve Tadelis
             UC Berkeley
            Prepared for ESNIE
         Cargese, France May 2008
               The Role of Contracts
•   The “broad” economic problems:
    –   choice and decision-making in a world with scarcity
    –   production, distribution, and consumption of goods
        and services
•   The Role of Contracts
    –   Facilitate the production/delivery of goods and
    –   E.g., sales, rentals, licensing…
•   Activity of Focus: Procurement
    –   Delivery of goods and services between parties in the
        “shadow” of an existing institutional backdrop
               Procurement Contracts
•   The economic problem of procurement:
    –   Identify the need and understand the deliverable
    –   Find capable sellers and anticipate their costs
    –   Make sure that sellers deliver on promise
•   In practice, procurement is either:
    –   Off the shelf, well specified products/services (boring!)
    –   Custom design, uniquely built products/services
•   Problems with custom design
    –   Design and specs may be (and are often) incomplete
    –   Design problems/evolving needs require adaptation
    –   “Adaptation costs” may be severe
                   The Questions:
• What contacting structures are most efficient?
  – Uncover the costs/benefits of different contract regimes
  – Identify empirically measurable attributes for policy

• How should contracts be awarded?
  – Award mechanisms are tied to contract regimes

• What are the economic costs of adaptation?
  – Measure the impact of change on costs above and beyond
    the efficient cost of “change”
• What are the resulting policy implications?
  – Common concerns of private information may be less
    important than mitigating adaptation costs
                 The Approach
• Ingredients:
  – In the spirit of Williamson (TCE): adaptation cost
    focus (simple, right, plausible, testable)
  – Agency rigor (incentives and contracting costs)
  – Focus on empirically measurable trade-offs
• Tradeoff: productive efficiency vs. explicit
  contracting costs.
• Fresh interpretation: “make” or “buy” cast in
  terms of input versus output contracting.
          Theory: A simple model
• Based on Bajari and Tadelis (2001) and
  Levin and Tadelis (2008)
• Technology:
  – One unit of service to be procured
  – quality depends on labor inputs: q = (r+e)t.
  – t ¸ 0 is time on the job, r > 0 is baseline
    productivity and e ¸ 0 is “effort” intensity.
• Endowments:
  – Agent is endowed with time T to be allocated
    between time on the job and some outside activity
    that pays w > 0 (outside job or value of leisure)
                     Model, cont.
• Preferences:
  – Agent (seller): Likes money, not work (needs incentives)
  – Principal (buyer): Likes “performance” and money
• Contracting:
  – Principal can contract on performance or time
  – Costs of writing/enforcing contracts:
     • On time: small (some d > 0)
     • On performance: costly
         – Contracting costs increase in “complexity”
         – Complexity is hard to pin down (costly to describe,
           monitor, measure; need for flexibility…)
A Helpful Conclusion
 Proposition: The optimal contract
   either contracts only on time or only
   on performance, but not on both
        Results and Comparative Statics
costs                  V (q,s)                                    W (q |EC)
                                                                  Production costs with
                                                                  employment contracts
             W (q |PC) + k(q,m)                                   specifying “time”
             adding performance contracting costs

                                                    W (q |PC)
                                                    Production costs with
                                                    Performance contracts
                                                    specifying quality
Introducing Adaptation and Decisions

• Technology:
  – Ex post noise ε calls for making decisions to best
    adapt the production to achieve quality q:
                    q = (r+e)f(d,ε)t.
  – f(d,ε) a productivity coefficient. For any realization
    of ε there is a unique maximizer d.
• Preferences:
  – Agent’s preferences are given by

  – Notice the potential conflict over decisions.
        Contracting Assumptions
• Principal can contract on three dimensions:
   – Minimal performance standards:
   – Minimal time on job:
   – Decision rights: which party chooses d
• Costs of writing/enforcing contracts same as
  before (cost of contracting over who makes
  decisions is trivial)
• Note: Assumptions on contracting and
  information are symmetric vis-à-vis ex
  ante and ex post. (q and d)
              Results: General idea
•   The technology of a transaction:
          Labor (time)        PRT (Hart)
       Labor (“effort”)
                                      Function q
    Material and Machines


• Question: Optimal contract/Governance?
  – Buy: Buy performance/function
  – Make: Buy inputs and control decisions
• Similar complementarties and comparative statics
     Implications for Public Procurement
Basic comparative statics predictions.
    1. Higher costs of specifying, measuring, or adjusting desired performance Þ
       less performance contracting (more C+ and more “make”).
Scale economies: city size and location.
    2. Small/rural cities are more constrained (less economies of scale and less
       markets) Þ modeled trade-offs most relevant for larger cities.
    3. Small cities may use public contracts as imperfect substitute for inhouse.
Political economy effects.
    4. Cities with more politically motivated decisions -- mayor rather than
       manager, older cities with established unions Þ less contracting.
    6. These cities should also place less emphasis on economic trade-offs Þ
       model trade-offs less relevant.
Contracting scope economies.
    7. City managers must learn to write/manage contracts, so contracting may
       be more likely in cities that provide a lot of services
• These predictions are tested and verified in Levin
  and Tadelis (2007) (Survey was key!).
    Award Mechanism Policies
• When transactions are simple, FP contracts
  should be selected and awarded by auction
• When transactions are complex, C+ contracts
  should be selected and negotiated with
  reputable sellers
  – Another reason to negotiate complex projects is to
    extract information ex ante from the selected seller
• These predictions are verified in the private
  sector (Bajari, McMillan and Tadelis, 2008) but
  not in the public sector. Why?
• FARs prohibit negotiated contracts
• What are the implied adaptation costs?
     Trying to Measure Adaptation Costs
• Do anticipated changes affect seller bids?
    – Need to Incorporate changes into a bidding model
    – Back out the effect of expected changes on bids

• What are the economic costs of adaptation?
    – Need to know contract’s initial condition
    – Need to know what the changes were
    – Need to measure the impact of change on the project’s
      costs above and beyond the efficient cost of change
• What are the resulting policy implications?
    – Need to try and stack up the adaptation costs against fear
      from corruption
•   BHT (2007) address the first two questions
Unit Price Auctions: A Hybrid Contract
• Highway construction:
  – Gravel, asphalt, sidewalk, measured in some units
  – A specification of a project can be in how much of
    each input (output) is needed
  – (Timber selling auctions: Haile; Athey-Levin)
• flexibility built into the contract:
  – Task is known but quantities are not
  – If there are changes to the quantities ex post
    (incomplete design) then the payment mechanism
    for changes is clear.
          Unit Price Auctions: Example
• A specification is a vector of quantities for the
  measurable units expected to be used
• A bid is a vector of unit prices per quantities
• A price is the dot product of these two vectors
   Item   Description       Est. Quantity   Unit Bid     Est. Item Bid
   1.     asphalt (tons)    25,000          25.00        625,000.00
   2.     sidewalk (sq. yds) 10,000         9.00         90,000
   3.     rumble strip      50              5.00         250.00
                                            Bid Price:   $715,250.00

• Winning bid is evaluated by price (usually lowest)
Adjustments, Extras and Deductions
• Adjustments
  –   Engineer’s estimated quantities may be off
  –   actual quantities differ from estimated ones.
  –   Large deviations: adjustments to final payment
  –   Our data includes estimated quantities, actual
      quantities and adjustments to payments
• Extra Work
  – Unanticipated problems in the design
  – Our data includes payments for extra work
• Deductions
  – Contractor screw ups (time, specs, etc.)
  – Our data includes deductions
             Adaptation Costs
• τ = proportional adaptation costs so total
  adaptation costs are:
          K = τA+A+ - τA-A- + τXX - τDD
• With adaptation costs,
        R(bi) = ∑Tt=1btiqta + A + X + D – K
• If changes and adaptation costs are
  anticipated, we can use bids to back out
  the implied adaptation costs!
• BHT (2007) do exactly this: adaptation
  costs are very large!
            Concluding Remarks
• Simple model of procurement Contracts
  – View as choice of contractual form (employment/C+
    vs. specific performance/FP).
  – When “output” contracting is too expensive then
    replace it with a partial control of inputs and decisions
  – Trade-off: productive efficiency vs. contracting costs.
• Designed with empirical predictions in mind
  – Consistent with previous empirical studies
  – Useful to guide public (and private) sector
• Offers some “Williamsonian” guidance into the
  choice of procurement regimes as they relate to
  transaction characteristics.
• Lesson is that adaptation costs can be severe,
  so contractual choice should be mindful of these.

To top