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buying_to_bundle_profit_intermediate_surrogate_gap_bound

Proved

by qm2204 · Jul 3, 2026 · Mathlib c5ea003 (Lean v4.30.0)

asymptoticseconomicsmechanism-designprobability

First gap bound in the proof of Theorem 4.6 of Buying to Bundle: Optimal Sourcing from Monopolistic Sellers (App. C.2 pp. 35–36). Define the intermediate surrogate profit ϖ′(x)=Eμ[Rev(∑ix(μi)(μi+σZi))]−N Em[φ(m)x(m)]\varpi'(x)=E_{\boldsymbol\mu}\big[Rev\big(\sum_i x(\mu_i)(\mu_i+\sigma Z_i)\big)\big]-N\,E_m[\varphi(m)x(m)]ϖ′(x)=Eμ​[Rev(∑i​x(μi​)(μi​+σZi​))]−NEm​[φ(m)x(m)] — the profit with the random inclusion pattern replaced by deterministic inclusion weights inside the buyer valuation (the payment term is written N∫φ x dΦN\int\varphi\,x\,d\PhiN∫φxdΦ, equal to Eμ[∑iφ(μi)x(μi)]E_{\boldsymbol\mu}[\sum_i\varphi(\mu_i)x(\mu_i)]Eμ​[∑i​φ(μi​)x(μi​)] by symmetry — the same shape as eq. (1) in the root statement). Then there exists K>0K>0K>0 depending only on (σ,γ,ξ,μH)(\sigma,\gamma,\xi,\mu_H)(σ,γ,ξ,μH​) such that for every IC allocation rule xxx and every N≥1N\ge1N≥1,

∣Π(x)−ϖ′(x)∣ ≤ K N2/3.|\Pi(x)-\varpi'(x)|\ \le\ K\,N^{2/3}.∣Π(x)−ϖ′(x)∣ ≤ KN2/3.

Paper proof: for every realization (μ,I)(\boldsymbol\mu,\mathbf I)(μ,I), triangle inequality through the revenues at Y=∑iIiμiY=\sum_iI_i\mu_iY=∑i​Ii​μi​ and Υ=∑ix(μi)μi\Upsilon=\sum_ix(\mu_i)\mu_iΥ=∑i​x(μi​)μi​; the outer terms are O(N2/3)O(N^{2/3})O(N2/3) by Lemma 4.5 (monopoly_revenue_subexponential_dispersion_bound, applied with C=Y,ai=IiC=Y,a_i=I_iC=Y,ai​=Ii​ and C=Υ,ai=x(μi)C=\Upsilon,a_i=x(\mu_i)C=Υ,ai​=x(μi​), using C≤NμHC\le N\mu_HC≤NμH​, A≤NA\le NA≤N), and the middle term integrates to ≤μHN\le\mu_H\sqrt N≤μH​N​ by eq. (5) (buying_to_bundle_expected_bundle_quality_fluctuation_bound).

Preamble
import Mathlib.MeasureTheory.Constructions.Pi
import Mathlib.Analysis.SpecialFunctions.Pow.Real
import Definitions.Def_buying_to_bundle_market

open MeasureTheory
Formal statement
theorem buying_to_bundle_profit_intermediate_surrogate_gap_bound
    (σ μL μH γ ξ : ℝ) (qual noise : Measure ℝ)
    [IsProbabilityMeasure qual] [IsProbabilityMeasure noise]
    (qualPdf noisePdf : ℝ → ℝ)
    (hM : BuyingToBundle.MarketAssumptions σ μL μH γ ξ qual noise qualPdf noisePdf) :
    ∃ K : ℝ, 0 < K ∧ ∀ N : ℕ, 1 ≤ N → ∀ x : ℝ → ℝ,
      BuyingToBundle.IsAllocationRule μL μH x →
      |BuyingToBundle.profit qual noise σ qualPdf N x -
          ((∫ μ : Fin N → ℝ,
              BuyingToBundle.monopolyRevenue
                ((Measure.pi fun _ : Fin N => noise).map
                  fun z => ∑ i, x (μ i) * (μ i + σ * z i))
              ∂(Measure.pi fun _ : Fin N => qual)) -
            N * ∫ m, BuyingToBundle.virtualCost qual noise σ qualPdf m * x m ∂qual)| ≤
        K * (N : ℝ) ^ ((2 : ℝ) / 3) := by sorry
Source
Buying to Bundle: Optimal Sourcing from Monopolistic Sellers (2025), Appendix C.2 (proof of Theorem 4.6)

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