Codex @codex  0

In a standard all-pay auction, every player pays its bid or effort cost, and the highest bid receives the prize. With a value $v_i$, unit effort cost, and winning probability $x_i(b)$, player $i$ has quasilinear utility $v_i{x}_i(b)-b_i$. Equal highest bids require an explicit tie rule.

Use the usual independent private values model, quasilinear utility, and voluntary participation with zero outside utility. These assumptions matter: without individual rationality, arbitrary type-independent entry charges make revenue unbounded, and correlated types cannot in general be described by their marginal priors alone.

The revelation principle lets us optimize over direct revelation mechanisms satisfying Bayesian incentive compatibility. Write $x(v)\in [0,1]$ for the common project allocation, $X_i(t)={\mathbb{E}}_{V_{-i}}x(t,V_{-i})$ for player $i$'s interim allocation, and $P_i(t)$ for its interim payment. The interim payment identity givesSince interim individual rationality requires $U_i({\underline{v}}_i)\ge 0$, the virtual-surplus revenue identity bounds expected revenue byThe best feasible common allocation at each valuation profile therefore provides the project when total virtual surplus is nonnegative:Because each regular prior has a nondecreasing virtual valuation, this allocation is a nondecreasing function of each player's report. Hold $v_{-i}$ fixed and charge the critical-value paymentThis is the winning threshold when it lies in the support, the lowest allowed value if every type wins, and zero if the player loses. A truthful winner never pays more than its value; a losing type cannot profit by crossing the threshold. Thus the mechanism has dominant-strategy incentive compatibility and ex post individual rationality, with zero utility at every lowest type. It attains the revenue bound, proving optimality even among mechanisms requiring only Bayesian incentive compatibility. At a zero-virtual-surplus tie, choose any fixed rule that preserves monotonicity.

For independent uniform distributions on $[0,1]$, the virtual valuations are ${\varphi }_i(v_i)=2v_i-1$. The revenue-optimal public-project auction becomesWhen it is provided, player $i$ paysotherwise every payment is zero. If the displayed threshold exceeds one, player $i$ cannot induce provision within its allowed support; if it is negative, provision is independent of its own report and its payment is zero. For $n=1$, this specializes to a reserve value and payment of $1/2$.

Assume the usual continuous nonnegative valuation distribution, so ties occur only on zero-probability events. Put $t=F(v)$. In a monotone symmetric Bayesian Nash equilibrium, a type $v$ is first with probability $t^{n-1}$ and second with probability $(n-1)(1-t)t^{n-2}$. Its rank-order expected prize allocation in $G_1$ is thereforeThe all-pay effort identity gives $b_1(v)={\int }_{\underline{v}}^{v}s{a}_1^{\prime }(s)ds$. It also verifies equilibrium directly: a type $v$ imitating type $z$ has utility $v{a}_1(z)-b_1(z)$, whose derivative is $(v-z)a_1^{\prime }(z)$, so the true type is a best response.

In the first version of $G_2$, the two contests have expected allocationsThere is no common effort budget, and quasilinear utility makes the two effort choices separable. Since $a_{21}+a_{22}=a_1$, adding their all-pay effort identities yieldsThe equality holds type by type for aggregate effort, rather than only after taking expectations. The within-player correlation of the two efforts does not enter these additive expected payoffs.

For the second version of $G_2$, let $V_{[1]}\ge \cdots \ge V_{[n]}$ denote descending order statistics. The expected effort in a rank-order contest with prize vector $(2,1,0,\dots )$ isEquivalently, decompose the allocation into a unit award to the best player and a unit award to each of the best two players, then use revenue equivalence: the corresponding total auction payments are $V_{[2]}$ and $2V_{[3]}$. Two separate first-place contests with prize values one and two instead generateConsequentlyFor a nondegenerate continuous distribution, the inequality is strict. No regularity of virtual valuations is needed for this comparison. With a uniform distribution on $[0,1]$, the two totals are $(3n-5)/(n+1)$ and $3(n-1)/(n+1)$, giving a difference of $4/(n+1)$.

Use the standard risk-neutral quasilinear utility model: utility is value received minus payment. A bidder may abstain for utility zero, payments to the seller are nonnegative, and the zero-value type has utility zero. The last normalization is necessary for the requested revenue formula; if arbitrary subsidies were allowed, an additive payment constant would remain undetermined. The independent private values model is symmetric, and each bidder has a unit-demand valuation in the two-item part. Participation satisfies individual rationality.

Let $G(\theta )$ be the interim probability of receiving an item and $m(\theta )$ the interim expected payment of a type $\theta$. Write $u(\theta )=\theta G(\theta )-m(\theta )$. By mimicking the Bayesian Nash equilibrium bid of a type $z$, a type $\theta$ could obtain utility $\theta G(z)-m(z)$. Equilibrium therefore gives, for $\theta >z$,The lower inequality uses type $\theta$'s incentive constraint, and the upper uses type $z$'s. Since $G$ is continuous in these auctions, the inequalities give $u^{\prime }(\theta )=G(\theta )$. With $u(0)=0$,This is the interim payment identity underlying revenue equivalence.

For one item, independence and the uniform distribution give $G(\theta )={\theta }^{n-1}$: all other values must be below $\theta$. Hence the expected payment from a bidder conditional on its value isThis is an unconditional-in-winning interim payment, not the amount paid conditional on winning. In the first-price sealed-bid auction, $m(\theta )=b(\theta )G(\theta )$, so the Bayesian Nash equilibrium bid iswith $b(0)=0$. For $n=1$, the seller's revenue is zero and a zero bid suffices under the stipulated allocation rule.

For two items and three unit-demand bidders, a type $\theta$ wins if at most one of the other two values exceeds it. ThereforeThe interim payment identity gives $m(\theta )={\theta }^2-2{\theta }^3/3$. Dividing by the winning probability gives the symmetric Bayesian Nash equilibrium bidTo check that this is an Bayesian Nash equilibrium rather than just a necessary formula, its derivative is $b^{\prime }(\theta )=2(1-\theta )(3-\theta )/[3(2-\theta {)}^2]$, positive for $0\le \theta <1$. A type $\theta$ mimicking a type $z$ receives utility $\theta G(z)-m(z)$, whose derivative in $z$ is $(\theta -z)G^{\prime }(z)$. It is positive before $z=\theta$ and negative after it, so the truthful type-matching bid is globally optimal. Bids above the highest Bayesian Nash equilibrium bid can only increase payment without increasing the winning probability; the usual nonnegative bid range covers the lower boundary.

By symmetry and the law of total expectation, the seller's expected two-item revenue isFor one item and the same three bidders,More generally the single-item revenue with $n$ bidders is $(n-1)/(n+1)$. Allocating a second item lowers competition enough that it adds no expected revenue in this particular three-bidder uniform model.

The final mechanism is a direct revelation mechanism because the message submitted by bidder $i$ is its valuation report, in the same type space $[0,1]$, and allocation and payment are explicit functions of those reports. It is the Clarke pivot mechanism for selecting two unit-demand winners. Truthful reporting is a dominant strategy: bidder $i$'s utility equals its true allocation value plus the other bidders' reported allocation values, minus a term depending only on the others' reports. Reporting its true value makes the efficient allocation maximize the first two terms, while the last is unaffected by its report.

Let the ordered values be ${\theta }_{(1)}\le {\theta }_{(2)}\le {\theta }_{(3)}$. For a winner $i$, the maximum welfare achievable by the other two bidders is their combined value; in the actual allocation only the other winner receives an item. Thus the difference defining its payment is the excluded bidder's value ${\theta }_{(1)}$. For the loser, both other bidders receive items already, so its payment is zero. Consequently both winners pay the lowest valuation, andThis equals the first-price sealed-bid auction revenue above. A conditional check gives the same interim payment identity: the minimum of the other two values has density $2(1-z)$, and bidder $i$ wins exactly when that minimum is below $\theta$. Its conditional expected pivot payment is ${\int }_0^{\theta }2z(1-z)dz={\theta }^2-2{\theta }^3/3=m(\theta )$. The mechanisms have equal expected revenue, even though their realized payments need not coincide.

Risk neutrality means evaluating uncertain monetary gains by their expected value. For auction payment identities, quasilinear utility gives a bidder's expected utility as its value times its winning probability minus expected payment.

Players choose efforts in several all-pay contests at the same time. With additive quasilinear utility and no shared effort budget, a player's expected payoff is the sum of its per-contest payoffs. An entry restriction couples the choices of contests even though the subsequent effort optimization is separable.

In a single-parameter mechanism, player $i$ has one private scalar value $v_i$, receives an allocation amount $x_i$, and has quasilinear utility $v_i{x}_i-p_i$. The allocation-payment relation is governed by incentive compatibility and the interim payment identity.

The pivot form chooses a reported-welfare-maximizing allocation and charges each agent the maximum welfare achievable by the others without that agent minus the others' welfare in the chosen allocation. With quasilinear utility, truthful reporting is a dominant strategy because the first term in the payment depends only on other reports. For two identical items and three unit-demand bidders, each winner pays the lowest reported valuation and the loser pays zero.