A presentation for the Conference: Contracts, Procurement, and Public-Private Arrangements Frederic Blanc-Brude (EDHEC) & Dejan Makovšek (University of.

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Presentation transcript:

A presentation for the Conference: Contracts, Procurement, and Public-Private Arrangements Frederic Blanc-Brude (EDHEC) & Dejan Makovšek (University of Maribor/KPMG) June 2013, Florence, Italy NATIXIS LOGO ?

An introduction Construction cost overruns are generally considered to be one of the greatest risks faced in infrastructure project development. Before Flyvbjerg et al. (2002) little was known about the probability distribution of cost overruns. His research team measured a systematic cost overrun of 20 % in traditionally delivered transport infrastructure. In project finance, the results are better for the project sponsor, but how much construction risk was absorbed by the special purpose entity is poorly researched and understood. Currently, most project finance lenders believe that the risk profile of the project (in project finance) changes (is reduced) after construction completion.

Research focus Which part of the contractual relation are we looking at: Project sponsor SPE Subcontractor Construction Lenders ? In the past no empirical data available On budget/time performance (start of revenue flow dependant on on-time operations start)

Research focus Known characteristics: SPE passes construction risk to the subcontractor via fixed price/fixed date contract. Additional incentives - risk mitigating measures such as liquidated damages and performance bonds. Some risk is thought to remain due to incomplete contracts or the inability of contractors to absorb all risk. SPE Subcontractor Construction ?

Construction risk defined Very simple to define: outturn cost (and time) vs. estimated cost (and time); Not so simple to compare and explain: different reference estimates vs. outturn cost; decision to build; detailed design/tendering; contracting/financial close; difficulties with the representativity of samples; differences in indexes used and the possible influence of business/construction market cycles.

The relevance of reference estimates used Construction risk defined Source: Schexnayder et al

What we know from past research: the overwhelming majority of research focusses on traditional public procurement (design-bid-build); root causes of cost overruns – two main literature strands: voluntary/involuntary estimation error ; oportunistic behaviour of agents (bidders) in publicly tendered contracts. Construction risk defined

The nature of construction risk Two types of risk: risk, which can not be managed/influenced by the contractor (ground conditions, weather, archeological discoveries…); risk, which depends on who is managing: if little risk is transfered to the agent => no big requirements for cost/risk control (efficient and inneficient contractors act alike); [traditional delivery] if a lot of risk is transfered to the agent => “you can’t play, if you’re not good and big enough” (self-selection of efficient firms, but consequence possibly less competition); [lump sum contracts/project finance]

The NATIXIS/EDHEC dataset (I) Basic dataset characteristics 75 projects with outturn cost ranging from $24 m -$13 b; projects achieved financial close between 1993 – 2010; diverse sector composition: transport, energy, environment, telecomms, social accomodation; greenfield and brownfield; all continents, but majority from Europe.

The NATIXIS/EDHEC dataset (II) Observed construction risk (outturn cost vs. contract value at financial close) Median Source: NATIXIS, Authors’ computations.

The NATIXIS/EDHEC dataset (III) Traditional delivery vs. project finance – construction risk distribution: Note: Flyvbjerg et al. use a different estimate reference point! Source: NATIXIS, Flyvbjerg et al (2002), authors’ computations.

The NATIXIS/EDHEC dataset (IV) Project finance construction risk drivers: no statistically significant driver: geography (exception – Middle East) sector; time. Source: NATIXIS, Authors’ computations.

The NATIXIS/EDHEC dataset (V) Other findings – security package incentives: OLS regression of lender comfort measures vs. cost performance Lender comfort measureDummiesActual Caps Full Completion Guarantee insignificant Construction Cap & Responsibility Liquidated Damages insignificant Construction Delays Liquidated Damages insignificantInsignificant Construction Performance Bond Liquidated Damages insignificant

Discussion – Main findings Main findings – construction risk in project finance: expected cost overruns should be zero; project specific risk idiosyncratic => diversifiable; lender comfort measures may be unnecessary, if proper contractual/ownership incentives present!

Discussion – Contract incentives Lender comfort measures: To what extent are they necessary in such a setup?! SPE Subcontractor Construction contract Shareholder

Discussion – Open Challenges Cost underruns in lump sum contracts ≠ savings for the sponsor => if risk transfer to the contractor large, competition low = profits high! The key to on time/ on budge in project finance: => Why can’t the public sector better define the scope of work and enter lump sum (design and build) contracts more often, as is the case for large complex project financing? = better upfront scope definition+fixed price/date contract

Discussion – Open Challenges Cost performance in FDOT’s road projects: 1998 – 2006 Contract Type Contract Type Category 1 Number of Projects Average project size ($) Cost performance 1 Alternative A+B8611,304, % A+B Bonus3018,918, % Bonus1427,274, % Design and Build6813,115, % Incentive/Disincentive1444,870, % Lane Rental273,440, % Liquidated Savings865,641, % Lump Sum5491,261, % Alternative Contracting Total1,1324,802, % Traditional Design-bid-build Total1,9082,873, % Grand Total3,0403,591, % Notes: (1) Cost performance is measured against the contract (award) value as estimate reference point. Source: Ellis et al

Personal research interest Relations between the contractual setup, security/insurance mechanisms and the project’s cost and time performance. (the main challenge is getting useful data) Relation between risk management approach (traditional vs. probability based) and project’s cost and time performance. (the main challenge is getting useful data) What is the optimal model for most infrastructure financing (project finance as an asset class? A combination between the RAB based financing model and project equity finance)

Thank you for your attention! Any questions? Contacts: