| NSF Org: |
SES Division of Social and Economic Sciences |
| Recipient: |
|
| Initial Amendment Date: | July 7, 2015 |
| Latest Amendment Date: | July 13, 2016 |
| Award Number: | 1530632 |
| Award Instrument: | Standard Grant |
| Program Manager: |
Kwabena Gyimah-Brempong
kgyimahb@nsf.gov (703)292-0000 SES Division of Social and Economic Sciences SBE Directorate for Social, Behavioral and Economic Sciences |
| Start Date: | August 1, 2015 |
| End Date: | July 31, 2020 (Estimated) |
| Total Intended Award Amount: | $392,892.00 |
| Total Awarded Amount to Date: | $392,892.00 |
| Funds Obligated to Date: |
|
| History of Investigator: |
|
| Recipient Sponsored Research Office: |
1050 MASSACHUSETTS AVE CAMBRIDGE MA US 02138-5359 (617)868-3900 |
| Sponsor Congressional District: |
|
| Primary Place of Performance: |
1050 Massachusetts Avenue Cambridge MA US 02138-5398 |
| Primary Place of
Performance Congressional District: |
|
| Unique Entity Identifier (UEI): |
|
| Parent UEI: |
|
| NSF Program(s): | Economics |
| Primary Program Source: |
|
| Program Reference Code(s): |
|
| Program Element Code(s): |
|
| Award Agency Code: | 4900 |
| Fund Agency Code: | 4900 |
| Assistance Listing Number(s): | 47.075 |
ABSTRACT
Abstract:
This project develops new methods and presents new data to study two important forms of price discovery: auctions and bargaining. Both auctions and bargaining have received attention in the theoretical economic literature but many empirical questions remain, and both forms of transaction are widely used methods of price discovery and trade which affect governments, consumers, and suppliers worldwide, both in developed and less-developed countries. Providing tools for robust analysis of bargaining and auction data will better allow researchers and policymakers to make informed decisions about how to design markets. For example, these tools can help identify markets in which a fixed, nonnegotiable price would be more efficient in practice than allowing for negotiated prices, and identifying cases in which the opposite is true. These tools can also be used for studying how buyers and sellers are affected by different designs of auctions or bargaining settings, measuring the impact of collusion on market participants, or many other questions about the design of marketplaces. The specific real-world settings which this project uses to illustrate these tools are bargaining and auctions transactions for online consumer-to-consumer sales and bargaining and auctions for used cars.
At a technical level the project brings together econometric tools for partial identification and bounds estimation and the questions of empirical market design. Bounds approaches provide a framework for analyzing questions about efficiency and optimality of market mechanisms under weak structural assumptions. The project will provide new nonparametric partial and point identification results and estimators of important model features. Estimation will build on recent developments in the moment inequality literature. The first part of the project will demonstrate how data on auction bids and reserve prices can be used to either point or partially identify all features of the auction (depending on whether the reserve price is private knowledge of the seller or publicly observed) while allowing for an unknown number of bidders and unobserved heterogeneity. These results will then be applied to evaluate consumer surplus under different legal regimes regarding used smartphone sales. The second part of the project is concerned with data on alternating-offer price negotiations and will derive bounds on both buyer and seller valuations under minimal assumptions and provide estimators for bounds of functions of these distributions. These bounds will be used to analyze how close the current bargaining mechanism is to a fully efficient bargaining mechanism and document features of products or bargaining parties which contribute to efficiency. Finally, in a combined auction and bargaining setting the proposed research will show that the object of interest in the auction (distribution of buyer values for a given car type) is point identified and the object of interest in bargaining (distribution of seller values for a given car type) is partially identified.
PUBLICATIONS PRODUCED AS A RESULT OF THIS RESEARCH
Note:
When clicking on a Digital Object Identifier (DOI) number, you will be taken to an external
site maintained by the publisher. Some full text articles may not yet be available without a
charge during the embargo (administrative interval).
Some links on this page may take you to non-federal websites. Their policies may differ from
this site.
PROJECT OUTCOMES REPORT
Disclaimer
This Project Outcomes Report for the General Public is displayed verbatim as submitted by the Principal Investigator (PI) for this award. Any opinions, findings, and conclusions or recommendations expressed in this Report are those of the PI and do not necessarily reflect the views of the National Science Foundation; NSF has not approved or endorsed its content.
Through this project, the researchers developed several new methods for studying large datasets from real-world auction and bargaining settings, resulting in several new findings for empirical economics. First, the researchers derived a method for inferring the willingness to pay of auction participants from online auction settings, such as eBay. The researchers applied this method to data from eBay auctions for used smartphones to study the effects of a 2013 change in digital copyright law. The researchers found that banning users from unlocking their own smartphones from the cellular carrier led to a decrease in consumers’ willingness to pay, suggesting that consumers react to changes in digital copyright law. This research is under revision for Quantitative Economics, a peer-reviewed journal.
Second, the researchers developed a methodology for inferring buyers’ and sellers’ willingness to pay from alternating-offer bargaining data. The researchers applied this methodology to a large dataset of business-to-business used-car transactions containing all back-and-forth actions taken by the negotiating parties. The researchers found that real-world bargaining was inefficient: over half of the cases where a buyer and seller failed to reach agreement, the buyer actually valued the car more than the seller (and hence trade should have occurred, but did not), suggesting that existing models of bargaining—used in courts and by government agencies—that ignore inefficiencies may be inaccurate. This bargaining research is forthcoming in the Review of Economic Studies, a top tier, peer-reviewed journal. The researchers also extended this methodology to apply it to bargaining data from eBay.com.
The researchers have presented the results of this work at numerous seminars and conferences throughout the United States and abroad. The project helped in the creation of large datasets on real-world bargaining, which have been publicly released on the NBER website for other researchers to study. Several PhD student research assistants received mentoring and training while working on the projects related to this grant, some of whom have now moved on to assistant professor positions at high-ranking business schools.
Last Modified: 10/20/2020
Modified by: Brad Larsen
Please report errors in award information by writing to: awardsearch@nsf.gov.
