Data and Code for: Optimal Procurement With Quality Concerns

Principal Investigator(s): View help for Principal Investigator(s) Nicola Persico, Northwestern University; Giuseppe Lopomo, Duke University; Alessandro Villa, Federal Reserve Bank of Chicago

Version: View help for Version V1

Name	File Type	Size	Last Modified
code			02/28/2023 05:49:PM
data			02/21/2023 06:03:PM
Readme.pdf	application/pdf	146.1 KB	02/28/2023 01:44:PM

Project Citation:

Persico, Nicola, Lopomo, Giuseppe, and Villa, Alessandro. Data and Code for: Optimal Procurement With Quality Concerns. Nashville, TN: American Economic Association [publisher], 2023. Ann Arbor, MI: Inter-university Consortium for Political and Social Research [distributor], 2023-05-24. https://doi.org/10.3886/E182801V1

Project Description

Summary: Adverse selection in procurement arises when low-cost bidders are also lowquality suppliers. We propose a mechanism called LoLA which, under some conditions, is the best incentive-compatible mechanism for maximizing any combination of buyer’s and social surplus in the presence of adverse selection. The LoLA features a floor (or minimum) price, and a reserve (or maximum) price. Conveniently, the LoLA has a dominant strategy equilibrium that, under mild regularity conditions, is unique. We perform a counterfactual experiment on Italian government procurement auctions: we compute the gain that the government could have made, had it used the optimal mechanism (which happens to be a LoLA), relative to a first-price auction, which is the format the government actually used.

Scope of Project

Subject Terms: Auctions; Procurement; Adverse Selection

JEL Classification:
D44 Auctions
H57 National Government Expenditures and Related Policies: Procurement

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Published Versions

V1 [2023-05-24]

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