Procurement teams operate on a simple assumption: more bidders means more competition, and more competition means lower prices. This is the logic behind every open tender, every public RFP, and every policy that mandates at least three competitive bids before awarding a contract.

The assumption is not entirely wrong. It is just incomplete. In settings where bidders face genuine uncertainty about the true cost of the work — construction, infrastructure, complex services, toll road concessions — adding bidders can make prices go up, not down. Hong and Shum, analyzing New Jersey highway procurement data, found that increasing bidders from 2 to 10 raised median markups from roughly 50% to above 70%. Simulated procurement costs rose approximately 30% when bidders increased from 3 to 6.

“More bidders does not mechanically produce lower prices. In common-value settings, it can produce the opposite — and the data is unambiguous on this point.”

Why the myth exists: the competitive bidding intuition

The myth has a valid origin. In a simple private-value auction, where each bidder knows their own cost with certainty, adding bidders does increase competitive pressure. Bidder four has to beat bidder three's best price. Bidder five has to beat bidder four. The price converges toward the lowest-cost supplier's true cost. This is Econ 101, and it works in the textbook.

Procurement is rarely a private-value setting. Most categories — construction, IT implementation, facility management, logistics contracts — involve shared uncertainty about what the work will actually cost. Bidders estimate, and their estimates differ. The firm that bids lowest is probably the firm that underestimated most aggressively, not the firm that is most efficient.

When bidders recognize this dynamic, they adjust. They shade their bids upward to avoid winning at a loss. And the more bidders there are, the more they shade. This is the winner's curse avoidance effect, and the empirical evidence for it spans three decades of auction research.

Where the data contradicts the myth: three empirical findings

Finding 1: More bidders can mean higher prices. Hong and Shum's 2002 study of New Jersey highway procurement is the canonical reference. They found that the relationship between bidder count and price is not a straight line down. It curves up after a point. The competition effect pushes prices down. The winner's curse avoidance effect pushes prices up. When the common-value component is strong enough, the second effect dominates. Athias and Nunez formalized this in 2009 with their model of toll road concessions, showing that governments could reduce procurement costs by restricting entry when the winner's curse was severe.

Finding 2: Three bidders is often the optimum. Research by Lalive, Schmutzler, and Zulehner found that procurement costs in New Jersey highways were lowest with approximately three bidders. Onur and Tas, analyzing over 500,000 Turkish public procurement auctions, confirmed a non-linear relationship with an interior optimum. Beyond the optimum, more bidders increased procurement prices. Unlimited competition was not optimal for the buying organization.

Finding 3: The initial bid is not the real price. Bajari, Houghton, and Tadelis documented that adaptation costs on highway paving contracts averaged roughly 10% of the winning bid. Bidders underbid to win, then recovered through change orders and renegotiation. The competitive bid on paper was not the true economic price. Ex-post costs were systematically higher, and the distortions from renegotiation could be larger than distortions from asymmetric information.

The conditions under which competitive bidding breaks down

Strong common-value uncertainty
When bidders share the same fundamental cost uncertainty — construction costs, material price volatility, ground conditions — the winner's curse effect intensifies with each additional bidder. Highway construction is the prototypical case.
High information dispersion
When bidders have noisy, divergent cost estimates, the most optimistic bidder wins. As bidders anticipate this, they shade bids upward. Toll road concessions, where demand forecasts vary by 30-50%, are classic examples.
Incomplete contracts
When specifications leave room for change orders, bidders price the initial bid competitively and plan to recover margin during execution. The initial bid looks cheaper. The total cost of ownership does not.
Bidder asymmetries
When one firm has superior cost information or an incumbent advantage, less-informed bidders face an amplified winner's curse. Krasnokutskaya and Seim found this produced inefficient allocation in roughly 24% of auctions.

What replaces competitive bidding when it fails

The answer is not to abandon competition. It is to design the auction or sourcing process for the specific market structure. Klemperer's work on bidding markets shows that under specific stringent conditions, just two bidders can produce fully competitive outcomes. The conditions rarely hold, but the principle is important: bidder count is not the variable that matters most.

Open competitive bidding (when it breaks)
Unrestricted entry, sealed bids, lowest price wins. In common-value settings, bidders shade upward. The initial price looks competitive but renegotiation drives true costs higher. Wrong bidder can win due to information asymmetries.
Result: Prices rise with bidder count beyond the optimum. True cost exceeds apparent cost.
Restricted two-stage process (when it works)
Stage 1: pre-qualify bidders on technical capability and financial stability. Shortlist 3-5 qualified firms. Stage 2: competitive negotiation with shortlisted bidders on price, quality, and terms. Reduces information asymmetries and winner's curse.
Result: Qualified bidders compete on a more informed basis. Prices reflect actual costs, not uncertainty premiums.

Additional alternatives include competitive dialogue (used in EU procurement to discuss solutions before formal tenders), framework agreements with pre-qualified supplier pools, and cost-plus or target-cost contracts that shift risk-sharing when uncertainty is high. Kong's 2025 research suggests unit-price contracts perform better for high-risk projects while fixed-price contracts work for low-risk, well-specified work.

Reverse auctions for standardized goods — where specifications are complete and the common-value component is minimal — can deliver 5-25% cost savings compared to traditional negotiation. The key distinction is whether the item being procured carries genuine common-value uncertainty. If it does not, open competition works. If it does, auction design matters more than bidder count.

What this means in practice

Audit your last ten competitive bids. For each, check: Did the winning bidder deliver at the bid price, or did change orders and renegotiation drive costs higher? If ex-post costs systematically exceed bid prices, the competitive bidding process is producing cosmetic competition, not real price discovery.

Classify your categories by common-value component. Categories with well-defined specifications and minimal uncertainty (office supplies, standard raw materials, commodity IT hardware) are fine for open bidding. Categories with high uncertainty (construction, IT services, complex logistics, consulting engagements) need restricted processes. Move each category to the right process.

Experiment with restricted entry. Pick one complex category currently run as an open tender. Pre-qualify bidders to a shortlist of three to five. Run a competitive negotiation with the shortlisted firms. Compare the outcome — including post-award costs — against the previous open tender for the same category. The difference tells you whether your procurement setting is private-value or common-value.

FAQ

Does more competitive bidding produce lower procurement prices?

Not always. Academic research on highway procurement auctions found that increasing bidders from 2 to 10 raised markups from roughly 50% to above 70%. The winner's curse effect can dominate the competition effect in common-value settings. The relationship is non-linear with an interior optimum.

What is the optimal number of bidders in procurement auctions?

Research on New Jersey highway procurement suggests costs are lowest with approximately three bidders. Onur and Tas, analyzing over 500,000 Turkish auctions, confirmed a non-linear relationship. The optimal number depends on the degree of common-value uncertainty in the specific category.

When should procurement teams use restricted rather than open bidding?

Use restricted processes when there is strong common-value uncertainty, high information dispersion across bidders, incomplete contracts subject to renegotiation, or significant bidder asymmetries. Open bidding remains appropriate for standardized goods with complete specifications and minimal cost uncertainty.

What is the winner's curse in procurement?

The winner's curse occurs when the winning bidder in a common-value auction is the one who most underestimated the true cost. Rational bidders anticipate this and shade their bids upward to avoid winning at a loss. The more bidders there are, the more aggressively they shade — which is why prices can rise with bidder count.

Sources

  1. Hong & Shum — Increasing Competition and the Winner's Curse: Evidence from Procurement (2002). Review of Economic Studies 69, 871-898. Found median markups rise from ~50% to above 70% as bidders increase from 2 to 10 in NJ highway procurement.
  2. Athias & Nunez — The More the Merrier? Number of Bidders, Information Dispersion, Renegotiation and Winner's Curse in Toll Road Concessions (2009). EPPP Discussion Paper No. 2009-7. Formalizes the Competition Effect vs. Winner's Curse Avoidance Effect trade-off.
  3. Bajari, Houghton & Tadelis — Bidding for Incomplete Contracts: An Empirical Analysis (2006). NBER Working Paper 12051. Documents ~10% adaptation costs on highway contracts and the gap between bid price and true economic cost.
  4. Onur & Tas — Optimal Bidder Participation in Public Procurement Auctions (2019). International Tax and Public Finance. Analysis of 500,000+ Turkish auctions confirms non-linear relationship with interior optimum.
  5. Klemperer — Bidding Markets (2007). Journal of Competition Law and Economics 3(1), 1-47. Shows that under stringent conditions, just 2 bidders can produce fully competitive outcomes.
  6. Krasnokutskaya & Seim — Bidder Asymmetries in Procurement Auctions (2011). Journal of Econometrics. Documents inefficient allocation in ~24% of auctions due to informational asymmetries.