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 | ||
|
|
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:
View help for 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:
View help for Subject Terms
Auctions;
Procurement;
Adverse Selection
JEL Classification:
View help for JEL Classification
D44 Auctions
H57 National Government Expenditures and Related Policies: Procurement
D44 Auctions
H57 National Government Expenditures and Related Policies: Procurement
Related Publications
Published Versions
Report a Problem
Found a serious problem with the data, such as disclosure risk or copyrighted content? Let us know.
This material is distributed exactly as it arrived from the data depositor. ICPSR has not checked or processed this material. Users should consult the investigator(s) if further information is desired.