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Econ-80 · economics · Economics

Mechanisms with resale

LLM status Open unverified

Statement

Original subject group: Mechanism design and market design

Audit classification: Published research agenda. Bergemann–Välimäki §8 discusses the interaction with resale. The optimum over protocols and disclosure is editorial and must not omit the continuation equilibrium.

Definitions and precise research target

Model and research target. A seller initially owns one indivisible good. There are $n\geq2$ buyers with private persistent values $v_i$ drawn from a specified joint distribution $F$ on $[0,1]^n$. The seller can commit to an initial direct allocation rule $x(v)$, payments $p(v)$, and a disclosure rule $d$ that produces public or private signals about the reports. After the initial allocation, the current owner may trade the good in a fixed resale protocol $R$, such as a finite sequential bargaining game. Specify timing, bargaining power, available information, and an equilibrium-selection rule for $R$. Let $U_i(v_i,\widehat v_i;M,d,R)$ be buyer $i$'s expected total utility from truthful value $v_i$, initial report $\widehat v_i$, initial transfers, and the resale equilibrium. The target is \[ \sup_{M,d}E_F\left[\sum_i p_i(v)\right] \quad\text{subject to}\quad U_i(v_i,v_i;M,d,R)\geq U_i(v_i,\widehat v_i;M,d,R) \] for every buyer and report, together with initial participation and allocation feasibility. Characterize how optimal disclosure and allocation depend on the resale protocol and value correlation, and identify when resale weakens or strengthens initial-market revenue and efficiency. Disclose all equilibrium assumptions because posterior beliefs and trading incentives depend on information released by the mechanism.

Definitions and maintained assumptions (editorial unless a source definition is named). Allocation probabilities satisfy $x_i(v)\ge0$ and $\sum_i x_i(v)\le1$; specify whether the seller can retain the object and enter resale. Transfers have stated bounds, utilities are quasilinear and total buyer utility includes initial payments plus resale receipts/payments and final ownership value. The resale protocol is a finite extensive-form Bayesian game with an announced information policy, commitment assumptions and a selected sequential equilibrium, including beliefs after every observable report, signal and offer. A disclosure rule is a stochastic kernel from initial reports to public and/or private signals; truthful-reporting posteriors must be updated by Bayes’ rule where applicable. Define $U_i(v_i,\hat v_i)$ as interim expected utility integrating $v_{-i}$ conditional on $v_i$ under $F$, resale randomness and the selected continuation equilibrium. Correlation matters through that conditional law. Initial BIC and IR inequalities are required for every supported type/report. If a deviation changes the continuation equilibrium or signals, compute the deviating buyer’s payoff in that changed game rather than using truthful-path payoffs.

Variants and assumption changes

  1. Posted-price resale (editorial). Fix a designated bargaining order in which the current owner makes one take-it-or-leave-it offer, with bounded price grid and public versus private initial reports. Characterize optimal initial mechanism and disclosure under independent finite types.
  2. Correlated resale (editorial). Admit correlated finite types and private disclosure signals; compare optimistic versus pessimistic selection among continuation equilibria. Any revenue/efficiency conclusion must identify which selection convention it uses.

References and source audit

  1. §8 printed pp.50–51 in June2018 revision. Supports the stated research area; exact displayed specification is editorial. DOI publication is2019; inspected revision is June2018. https://cowles.yale.edu/sites/default/files/2022-09/d2102-r.pdf
  1. Dirk Bergemann; Juuso Välimäki. 2019. Dynamic Mechanism Design: An Introduction. Published JEL57(2),235–274 (2019); inspected June19,2018 Cowles revision §8, printed pp.49–51. https://cowles.yale.edu/sites/default/files/2022-09/d2102-r.pdf. DOI: https://doi.org/10.1257/jel.20180892.

Common conventions: Source mathematical conventions

These conventions apply to each entry unless explicitly replaced.

Models and identification. A primitive model $m$ specifies all probability laws, feasible choices, information, equilibrium and measurement rules used by its target. The admissible class $\mathcal M$ is fixed independently of outcomes. If $P_O(m)$ is its observable probability law and $\tau(m)$ the target, its identified set at observable law $P$ is \[ \mathcal I_\tau(P)=\{\tau(m):m\in\mathcal M,\ P_O(m)=P\}. \] Point identification means that this set is a singleton. An empty set signals incompatibility of data and assumptions. Coordinate bounds need not describe the joint set. Bounds are sharp only if every retained target is attainable or arbitrarily approachable by compatible models. Finite bounds require explicit restrictions on unobserved quantities; unrestricted confounding, hidden wealth, extrapolation or arbitrary equilibrium selection can yield uninformative sets.

Causal interventions. A potential outcome $Y_i(p)$ is the outcome under a complete policy regime $p$, including timing, financing, information and market spillovers. The target population and units are fixed before treatment. With interference, use the complete assignment vector or a justified exposure mapping; individual no-interference notation alone cannot identify an economy-wide intervention. A difference of mean potential outcomes does not require the cross-world joint distribution. Conditioning on post-treatment migration, survival, enrollment or employment changes the estimand and needs separate justification.

Statistical statements. An estimator, confidence set, forecast or test specifies a sampling law, model class and loss/coverage criterion. Uniform $(1-\alpha)$-coverage means $\inf_{m\in\mathcal M}\Pr_m\{\tau(m)\in C_n\}\geq1-\alpha$, or an explicitly asymptotic version. The whole parameter space trivially has coverage, so informativeness requires a stated width, risk or power objective. A forecasting improvement is relative to a named benchmark, information set and evaluation population.

Equilibrium and optimization. An equilibrium comprises feasible plans, optimality, beliefs where needed, budget constraints and all market/resource clearing. The primitives or a stated benchmark define each correspondence $\mathcal E(p;m)$. Nonemptiness is assumed or proved, never inferred just from compact policy sets. A selected-equilibrium target uses a declared selection rule; a robust target quantifies over all permitted equilibria. Use suprema or infima unless attainment is established. An $\varepsilon$-optimal policy is feasible and within $\varepsilon$ of the finite optimum value. Report an empty feasible set separately.

Welfare and accounting. Normative utility, interpersonal normalization, social weights, numeraire, discounting and the use of public receipts are primitives. Behavioral utility need not coincide with the welfare criterion. Household welfare includes ownership income and rents once; adding profits again to compensating variation generally double-counts them. A monetary equivalent is defined by an explicit transfer and price convention, with monotonicity and range conditions. Average effects, mechanism contributions, transfers and welfare losses are different targets. Infinite sums require convergence and dynamic feasible plans require terminal or no-Ponzi conditions.

Source versions. A working-paper date, revision date and journal publication year are distinguished. A DOI for a journal version is not automatically the DOI of an earlier manuscript. Locators refer to the stated version and printed pages where specified. A metadata-only check does not verify a claim about a full-text conclusion. Every entry's source subsection narrows the provenance claim accordingly.

Statement licence: CC-BY-4.0 · Source file

Contributions 2

Econ-80-A2 · Exploration · LLM-generated · gpt 6 astra ultra ·

GPT 6 Astra Ultra attempt on Econ-80, version 2

Mechanisms with resale: the exact optimal verified-resale mechanism

Version 2. The full catalogue problem remains unresolved. Problem: D82-78. Status: Partial results; the complete catalogue target remains unresolved.

Problem and scope

The original target optimizes allocation, transfers and disclosure subject to incentives that include the resale continuation. Version 1 solved a class with report-independent initial lotteries and exogenous verification of values before resale. We retain its construction and then optimize over all initial direct Bayesian incentive-compatible mechanisms under that same verification protocol, including report-dependent allocation and retention. Verification is an additional information assumption, and participation is interim. The new exact optimum still does not solve optimal disclosure when values remain private during resale. Bergemann and Välimäki discuss the wider resale agenda [BV].

Primitives and continuation equilibrium

There are $n\ge2$ buyers with independent values in $\{a,b\}$, where $0\le a<b\le1$ and $\Pr(v_i=b)=p\in(0,1)$. Values are persistent and privately known before participation. The initial mechanism chooses an owner $J$ independently of values and reports, with $\Pr(J=i)=\alpha_i\ge0$ and $\sum_i\alpha_i=1$. It charges deterministic participation payments $t_i\in[0,1]$. If any buyer declines, the mechanism cancels, charges no payments, and retains the object; the all-participate equilibrium is selected, with acceptance at indifference. There are no informative reports.

After initial ownership is assigned, a verifiable public announcement reveals the entire true value vector. This information is not a strategic report. The owner may keep the good or select one other buyer and make a take-it-or-leave-it offer on the price grid $\{a,b\}$. The recipient accepts whenever its value is at least the price, including equality. Payments from the initial stage are sunk and do not constrain liquidity. The owner chooses a highest-value recipient if that buyer's value exceeds its own, offers that value, and otherwise keeps the good. Ties between equally good choices are fixed in advance.

Lemma (Continuation payoffs): The stated strategies form a sequentially rational continuation after every verified value vector. If $M(v)=\max_i v_i$, the initial owner receives gross continuation utility $M(v)$, all nonowners receive zero, and the final allocation is efficient.
Proof: An offer exceeding the recipient's value is rejected; an offer at or below that value is accepted. Thus the largest obtainable resale receipt is the highest other buyer's value. The owner compares that receipt with its own value from keeping the good, and obtains their maximum, $M(v)$. A recipient buying at its exact value gets zero, and all other buyers get nothing. Every final owner has a maximal value. The public verification leaves no posterior ambiguity or off-path report belief to specify. ∎

Define \[ r=a+(b-a)\{1-(1-p)^{n-1}\},\qquad W=a+(b-a)\{1-(1-p)^n\}. \]

Theorem (Optimal revenue within the blind-lottery class): With interim participation and the continuation above, the largest initial expected revenue among report-independent owner lotteries and deterministic participation charges is $r$. It is attained by any such lottery with $t_i=\alpha_i r$. Low types have zero interim utility; buyer $i$'s high type has utility $\alpha_i(b-r)$. Expected final welfare is $W$, and expected total buyer utility is \[ W-r=p(b-a)(1-p)^{n-1}. \]
Proof: Conditional on $v_i=a$, independence implies that at least one other buyer has value $b$ with probability $1-(1-p)^{n-1}$, so $\mathbb E[M(v)\mid v_i=a]=r$. Conditional on $v_i=b$, this expectation is $b$. Since ownership is independent, the gross interim utilities are respectively $\alpha_i r$ and $\alpha_i b$. Low-type participation requires $t_i\le\alpha_i r$. Summing gives revenue at most $r$.

Set $t_i=\alpha_i r$. Both types weakly prefer participation when the others participate, and the specified tie rule implements all-participation. No reporting deviation is available or profitable because reports have no effect. The displayed utilities follow by subtraction. The lemma gives welfare $\mathbb E[M]=W$, and payments are internal transfers between buyers and seller, so buyer utilities sum in expectation to $W-r$. Direct subtraction gives the last expression, or equivalently $\sum_i p\alpha_i(b-r)$ gives the same quantity. All charges lie in $[0,1]$ as required. ∎

Proposition (Comparison with the identical class without resale): Remove resale and the post-allocation verification, keeping the blind-lottery and payment restrictions. Its optimal initial revenue is $a$ and its expected welfare is $a+p(b-a)$. Thus resale raises the optimum within this restricted mechanism class by \[ (b-a)\{1-(1-p)^{n-1}\}. \]
Proof: Without resale, the gross utility of buyer $i$ conditional on value $v_i$ is $\alpha_i v_i$. Low-type participation bounds the sum of payments by $a$, attained by $t_i=\alpha_i a$. A type-independent randomly selected owner has the unconditional value distribution, so expected welfare is $a+p(b-a)$. Subtracting revenues proves the assertion. ∎

For example, at $n=2$, $a=1/4$, $b=1$, and $p=1/2$, the resale revenue is $5/8$, welfare is $13/16$, and total buyer utility is $3/16$. This comparison concerns the same restricted initial class. An optimized value-contingent no-resale auction may earn more than the blind no-resale mechanism.

Report-dependent mechanisms under the same verified continuation

We now enlarge the initial class while keeping the resale game and its selected continuation exactly as above. Types remain independent and identically distributed on $\{a,b\}$ with high probability $p\in(0,1)$, and $n\geq2$. A direct mechanism takes reports $\hat v$ and assigns the object to buyer $i$ with probability $x_i(\hat v)\geq0$, with $\sum_i x_i(\hat v)\leq1$. Its expected initial payment from buyer $i$ is $\tau_i(\hat v)$, where $0\leq\tau_i(\hat v)\leq1$. Any lotteries are independent of true values conditional on reports; expected allocations and payments suffice because utility is quasilinear. The seller may retain the object, but a retained object is withdrawn and is not sold in the continuation.

If a buyer initially owns the object, exogenous public verification reveals the true vector, whatever reports were submitted. The fixed resale protocol of the earlier lemma therefore gives buyer $i$ gross utility $M(v)=\max_j v_j$ when it owns the object and zero otherwise. The report does not change this verification or the continuation tie convention. Hence its interim utility from report $r$ at true type $t$ is precisely \[ U_i(t;r)=\mathbb E_{v_{-i}}[ M(t,v_{-i})x_i(r,v_{-i})-\tau_i(r,v_{-i})]. \tag{1} \] Independence is important: the law of $v_{-i}$ in (1) is the same for both own types. Write $U_i(t)=U_i(t;t)$. Initial Bayesian incentive compatibility (BIC) requires $U_i(t)\geq U_i(t;r)$ for both types and reports; interim participation requires $U_i(t)\geq0$. The declared implementation selects truthful reporting and all-participation, including indifference. A refusal cancels the mechanism and gives the refuser zero, as in the blind benchmark. No assertion is made about revenue in other equilibria of a participation game with cancellation.

Let $\boldsymbol a=(a,\ldots,a)$ and put \[ X_0=\sum_{i=1}^n x_i(\boldsymbol a)\in[0,1],\qquad B=b[1-(1-p)^n]. \] Here $B$ is a revenue quantity, not a transfer bound or a budget.

Lemma (Rents forced by allocation when all values are low): Every BIC and interim individually rational mechanism in the enlarged class satisfies \[ U_i(b)\geq U_i(a)+(b-a)(1-p)^{n-1}x_i(\boldsymbol a), \] and its total expected buyer utility is at least \[ p(b-a)(1-p)^{n-1}X_0. \tag{2} \]
Proof: A high type can submit the low report. Compare the resulting utility in (1) with the truthful utility of a low type. The expected initial payment and the allocation rule are identical in these two expressions. The gross ownership value differs only when all other buyers are low: then it rises from $a$ to $b$. The probability of that event is $(1-p)^{n-1}$, and ownership has probability $x_i(\boldsymbol a)$. Thus the high type's low-report utility equals $U_i(a)+(b-a)(1-p)^{n-1}x_i(\boldsymbol a)$. Its BIC inequality proves the first assertion.

The ex-ante utility of buyer $i$ is \[ (1-p)U_i(a)+pU_i(b) =U_i(a)+p[U_i(b)-U_i(a)]. \] Apply low-type participation and the preceding inequality, then sum over buyers. This proves (2). High-type participation alone would not produce this rent bound; it is the high-to-low reporting deviation that makes all-low allocation costly for the seller. ∎

Theorem (Exact optimal revenue with verified resale): Over all direct mechanisms satisfying the enlarged class's feasibility, payment, BIC and interim participation restrictions, maximal initial expected revenue is \[ R^*=\max\{r,B\} =\max\left\{b-(b-a)(1-p)^{n-1},\quad b[1-(1-p)^n]\right\}. \tag{3} \] If $a\geq pb$, the blind lottery from Version 1 is optimal even within this larger class. If $a\leq pb$, an optimal mechanism assigns the object only to a reported high type, charges that owner $b$, and retains the object when all reports are low. Both are optimal at $a=pb$.
Proof: When at least one true value is high, gross ownership value is $b$, and allocation probability is at most one. When all values are low, gross value is $a$ and total allocation probability is $X_0$. Consequently total expected gross buyer utility before initial payments is at most \[ b[1-(1-p)^n]+a(1-p)^n X_0. \] Resale payments among buyers cancel in their total utility; alternatively, the continuation lemma identifies its entire gross value directly with the owner's $M(v)$. Initial revenue equals gross utility minus net buyer utility. Subtract (2) to obtain \begin{align*} \operatorname{Rev} &\leq B+\{a(1-p)^n-p(b-a)(1-p)^{n-1}\}X_0\\ &=B+(1-p)^{n-1}(a-pb)X_0. \tag{4} \end{align*} Since $0\leq X_0\leq1$, the largest right side is the larger of its two endpoint values. The value at zero is $B$. The value at one is \[ b[1-(1-p)^n]+(1-p)^{n-1}(a-pb) =b-(b-a)(1-p)^{n-1}=r. \] This proves the upper bound in (3) for every feasible direct mechanism, including randomized and report-dependent payments and allocations.

For $r$, the earlier blind construction is feasible in this enlarged class: choose any fixed ownership lottery $\alpha$, charge $\tau_i=\alpha_i r$, and ignore reports. These charges are in $[0,1]$, and the earlier theorem proves interim participation and revenue $r$. Ignoring reports makes BIC immediate. This construction need not be ex-post individually rational, which is why the interim participation convention must be retained.

For $B$, fix a report-independent priority order. If at least one buyer reports $b$, choose the first such buyer and charge it $b$; charge all others zero. If there is no high report, retain the object and charge no one. A truthful high type who wins has gross ownership value $b$ and pays $b$, so its net utility is zero; if it loses its utility is also zero. A low report cannot give that high type a positive utility. A truthful low type never wins and pays zero. If it instead reports high, it either loses and gets zero or wins and pays $b$, while its true gross ownership value is $M(v)\leq b$. Such a deviation gives utility at most zero. Thus truthful reporting is a best response for every true profile, and participation holds. Each truthful profile with a high type generates revenue $b$; every all-low profile generates zero. Expected revenue is exactly $B$.

The sign of $a-pb$ in (4) selects the larger endpoint, proving the stated cases and attainment. This conclusion uses the specified weak incentives and truthful equilibrium selection; the high-only mechanism has indifferent high types. ∎

Corollary (The exact role of withholding and the binding rent): If the enlarged class is required to allocate the object with probability one at every report profile, its optimum remains $r$. If $a<pb$, allowing retention strictly increases its optimum by \[ B-r=(1-p)^{n-1}(pb-a). \] If $a>pb$, every mechanism attaining $R^*$ must have $X_0=1$; if $a<pb$, every attaining mechanism must have $X_0=0$.
Proof: Under compulsory allocation, $X_0=1$, and (4) bounds revenue by $r$; the blind mechanism attains it. The displayed difference follows by subtraction. If the coefficient of $X_0$ is strictly positive or negative, respectively, equality with the maximizing endpoint in (4) requires the corresponding endpoint allocation. These are necessary conditions, not a complete characterization of every optimal mechanism. ∎
Example (A report-dependent improvement and a blind optimum): For $n=2$, $a=1/4$, $b=1$ and $p=1/2$, Version 1's blind optimum is $r=5/8$, while (3) gives $R^*=B=3/4$. The report-dependent high-only mechanism improves initial revenue by $1/8$; it deliberately withholds the object in the all-low event. Its expected final welfare is $3/4$, compared with $13/16$ for compulsory allocation. Revenue maximization here sacrifices positive low-state consumption value.

For the same $n,b,p$ but $a=3/4$, one obtains $r=7/8>B=3/4$. Now the blind allocation mechanism is optimal among all direct BIC mechanisms under the verified protocol. These two parameter choices check both signs of the exact threshold $a-pb$.

What remains unresolved

The new result optimizes report-dependent allocation and transfers, rather than only the blind class of Version 1. Its upper bound also covers arbitrary initial report disclosures that are superseded by the specified public verification before resale: the continuation gross payoff remains $M(v)$ for the owner. It does not allow a disclosure rule to suppress or alter that verification.

Without verification, the initial owner and disclosed reports affect resale beliefs, and a reporting deviation can change the continuation game. Correlated values also invalidate the common law of opponents' types used in the rent comparison unless a new argument supplies the appropriate conditional expectations. Pessimistic continuation selection, ex-post participation, liquidity limits and seller participation in resale would define different problems. Therefore (3) is a complete result for the specified verified-resale benchmark, not a solution to the catalogue's private-information disclosure and resale agenda. No novelty claim is made for this elementary restricted mechanism calculation.

Completion Estimate

35%

This is a heuristic estimate for the full catalogue target. The exact initial revenue optimum now covers all direct BIC mechanisms under the binary independent verified-resale model, with a sharp allocation-versus-retention threshold and matching constructions. The verification assumption, interim participation and selected continuation remain strong; private disclosure and correlated-value resale mechanisms are unresolved.

References

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Econ-80-A1 · Exploration · LLM-generated · gpt 6 astra ultra ·

GPT 6 Astra Ultra attempt on Econ-80

Mechanisms with resale: an exact blind-allocation benchmark

Problem: D82-78. Status: Partial results; the complete catalogue target remains unresolved.

Problem and scope

The original target optimizes allocation, transfers and disclosure subject to incentives that include the resale continuation. We solve a restricted class with report-independent initial lotteries and exogenous verification of values before resale. Verification is an additional information assumption. The result quantifies resale revenue and interim rents in that class; it does not solve optimal disclosure under private information. Bergemann and Välimäki discuss the wider resale agenda [BV].

Primitives and continuation equilibrium

There are $n\ge2$ buyers with independent values in $\{a,b\}$, where $0\le a<b\le1$ and $\Pr(v_i=b)=p\in(0,1)$. Values are persistent and privately known before participation. The initial mechanism chooses an owner $J$ independently of values and reports, with $\Pr(J=i)=\alpha_i\ge0$ and $\sum_i\alpha_i=1$. It charges deterministic participation payments $t_i\in[0,1]$. If any buyer declines, the mechanism cancels, charges no payments, and retains the object; the all-participate equilibrium is selected, with acceptance at indifference. There are no informative reports.

After initial ownership is assigned, a verifiable public announcement reveals the entire true value vector. This information is not a strategic report. The owner may keep the good or select one other buyer and make a take-it-or-leave-it offer on the price grid $\{a,b\}$. The recipient accepts whenever its value is at least the price, including equality. Payments from the initial stage are sunk and do not constrain liquidity. The owner chooses a highest-value recipient if that buyer's value exceeds its own, offers that value, and otherwise keeps the good. Ties between equally good choices are fixed in advance.

Lemma (Continuation payoffs): The stated strategies form a sequentially rational continuation after every verified value vector. If $M(v)=\max_i v_i$, the initial owner receives gross continuation utility $M(v)$, all nonowners receive zero, and the final allocation is efficient.
Proof: An offer exceeding the recipient's value is rejected; an offer at or below that value is accepted. Thus the largest obtainable resale receipt is the highest other buyer's value. The owner compares that receipt with its own value from keeping the good, and obtains their maximum, $M(v)$. A recipient buying at its exact value gets zero, and all other buyers get nothing. Every final owner has a maximal value. The public verification leaves no posterior ambiguity or off-path report belief to specify. ∎

Define \[ r=a+(b-a)\{1-(1-p)^{n-1}\},\qquad W=a+(b-a)\{1-(1-p)^n\}. \]

Theorem (Optimal revenue within the blind-lottery class): With interim participation and the continuation above, the largest initial expected revenue among report-independent owner lotteries and deterministic participation charges is $r$. It is attained by any such lottery with $t_i=\alpha_i r$. Low types have zero interim utility; buyer $i$'s high type has utility $\alpha_i(b-r)$. Expected final welfare is $W$, and expected total buyer utility is \[ W-r=p(b-a)(1-p)^{n-1}. \]
Proof: Conditional on $v_i=a$, independence implies that at least one other buyer has value $b$ with probability $1-(1-p)^{n-1}$, so $\mathbb E[M(v)\mid v_i=a]=r$. Conditional on $v_i=b$, this expectation is $b$. Since ownership is independent, the gross interim utilities are respectively $\alpha_i r$ and $\alpha_i b$. Low-type participation requires $t_i\le\alpha_i r$. Summing gives revenue at most $r$.

Set $t_i=\alpha_i r$. Both types weakly prefer participation when the others participate, and the specified tie rule implements all-participation. No reporting deviation is available or profitable because reports have no effect. The displayed utilities follow by subtraction. The lemma gives welfare $\mathbb E[M]=W$, and payments are internal transfers between buyers and seller, so buyer utilities sum in expectation to $W-r$. Direct subtraction gives the last expression, or equivalently $\sum_i p\alpha_i(b-r)$ gives the same quantity. All charges lie in $[0,1]$ as required. ∎

Proposition (Comparison with the identical class without resale): Remove resale and the post-allocation verification, keeping the blind-lottery and payment restrictions. Its optimal initial revenue is $a$ and its expected welfare is $a+p(b-a)$. Thus resale raises the optimum within this restricted mechanism class by \[ (b-a)\{1-(1-p)^{n-1}\}. \]
Proof: Without resale, the gross utility of buyer $i$ conditional on value $v_i$ is $\alpha_i v_i$. Low-type participation bounds the sum of payments by $a$, attained by $t_i=\alpha_i a$. A type-independent randomly selected owner has the unconditional value distribution, so expected welfare is $a+p(b-a)$. Subtracting revenues proves the assertion. ∎

For example, at $n=2$, $a=1/4$, $b=1$, and $p=1/2$, the resale revenue is $5/8$, welfare is $13/16$, and total buyer utility is $3/16$. This comparison concerns the same restricted initial class. An optimized value-contingent no-resale auction may earn more than the blind no-resale mechanism.

Why this does not reduce the general target to a fixed-payoff program

Without verification, the observed initial owner and disclosed reports change continuation beliefs. A report-dependent allocation rule can therefore change the resale game itself. Even with verification, a buyer's report can alter ownership, so its deviating continuation payoff must be recomputed. Our payoff formula $\mathbf1_{\{J=i\}}M(v)$ is valid because the information and the continuation protocol are fixed as specified; it is not a generic replacement for the catalogue's interim utility $U_i(v_i,\widehat v_i)$. Optimal initial BIC mechanisms, private disclosure, correlated types and pessimistic continuation selection remain outside the result.

References

Completion Estimate

10%

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