December 18, 2021
During the past year, Stanford Digital Economy Lab researchers and affiliates published working papers and journal articles covering a range of topics related to the digital economy. From digital resilience to predictive analytics to racial segregation, these publications demonstrate how AI, machine learning, and other brilliant technologies are shaping society and the future of work.
Scroll down to find a collection of these remarkable working papers and articles from 2021. Looking for publications from previous years? Go here.
Brad Larsen, Matthew Backus, Thomas Blake, Steven Tadelis
February 3, 2021
Oxford Academic: The Quarterly Journal of Economics
We study patterns of behavior in bilateral bargaining situations using a rich new data set describing back-and-forth sequential bargaining occurring in over 25 million listings from eBay’s Best Offer platform. We compare observed behavior to predictions from the large theoretical bargaining literature. One-third of bargaining interactions end in immediate agreement, as predicted by complete-information models.
Jae Joon Lee, John A. Clithero, Joshua Tasoff
February 5, 2021
Direct elicitation, guided by theory, is the standard method for eliciting latent preferences. The canonical direct-elicitation approach for measuring individuals’ valuations for goods is the Becker-DeGroot-Marschak procedure, which generates willingness-to-pay (WTP) values that are imprecise and systematically biased by understating valuations. We show that enhancing elicited WTP values with supervised machine learning (SML) can substantially improve estimates of peoples’ out-of-sample purchase behavior.
Riitta Katila, Sruthi Thatchenkery
February 25, 2021
How a firm views its competitors affects its performance. Simply put, firms with an unusual view of competition are more innovative. We extend the networks literature to examine how a firm’s positioning in competition networks—networks of perceived competitive relations between firms—relates to a significant organizational outcome, namely, product innovation. We find that when firms position themselves in ways that potentially allow them to see differently than rivals, new product ideas emerge.
John (Jianqiu) Bai, Erik Brynjolfsson, Wang Jin, Sebastian Steffen, Chi Wan
March 1, 2021
Oxford Academic: The Quarterly Journal of Economics
Digital technologies may make some tasks, jobs and firms more resilient to unanticipated shocks. We extract data from over 200 million U.S. job postings to construct an index for firms’ resilience to the Covid-19 pandemic by assessing the work-from-home (WFH) feasibility of their labor demand. Using a difference-in-differences framework, we find that public firms with high pre-pandemic WFH index values had significantly higher sales, net incomes, and stock returns than their peers during the pandemic.
Brad Larsen, Dominic Coey, Kane Sweeney, Caio Waisman
March 18, 2021
This paper studies reserve prices computed to maximize the expected profit of the seller based on historical observations of the top two bids from online auctions in an asymmetric, correlated private values environment. This direct approach to computing reserve prices circumvents the need to fully recover distributions of bidder valuations.
Researchers Erik Brynjolfsson, Wang Jin, and Kristina McElheran surveyed more than 30,000 manufacturers and discovered a sizable increase in productivity among plants that use tools to automate prediction. In “The Power of Prediction,” the research team outlines their findings and offers reasons why some companies using predictive analytics aren’t seeing such gains. Recognized for excellence by the Strategic Management Society and the National Association of Business Economists.
Erik Brynjolfsson, Wang Jin, Sarah Bana, Xuipeng Wang, Sebastian Steffen
March 8, 2021
Do firms react to data breaches by investing in cybersecurity talent? We assemble a unique dataset on firm responses from the last decade, combining data breach information with detailed firm-level hiring data from online job postings. Using a difference-in-differences design, we find that firms indeed increase their hiring for cybersecurity workers.
Susan Athey, Fiona Scott Morton
In order to avoid competition, market leaders in platform markets often search for tactics. This paper considers a category of tactics that we refer to as “platform annexation,” designed to achieve this objective. Platform annexation refers to a practice where a platform takes control of adjacent tools, products, or services and operates them in a way that interferes with efficient multi-homing among platform users.
Seth Benzell, Avinash Collis, Christos Nicolaides
July 22, 2021
The COVID-19 pandemic has called for and generated massive novel government regulations to increase social distancing for the purpose of reducing disease transmission. A number of studies have attempted to guide and measure the effectiveness of these policies, but there has been less focus on the overall efficiency of these policies.
Marshall Van Alstyne, Zhou Zhou, Lingling Zhang
June 3, 2021
One of the deepest platform challenges is understanding how users create network value for each other and which investments provide leverage. Is more value created by advertising to attract users, discounting to subsidize users, or investing in architecture to connect and retain users? Having grown a user network, which promotes “winner-take-all” dominance, why do platforms with large user bases fail?
Marshall Van Alstyne, Georgios Petropoulos, Geoffrey Parker
June 17, 2021
WINNER OF THE 2022 ANTITRUST WRITING AWARD
Digital platforms are at the heart of online economic activity, connecting multi-sided markets of producers and consumers of various goods and services. Their market power, in combination with their privileged ecosystem position, raises concerns that they may engage in anti-competitive practices that reduce innovation and consumer welfare. This paper deals with the role of market competition and regulation in addressing these concerns.
Digital technologies are making some tasks, jobs, and firms more resilient to unanticipated shocks. S-DEL researchers extracted data from more than 200 million US job postings to construct an index that measure a firms’ resilience to the COVID-19 pandemic by assessing the work-from-home (WFH) feasibility of their labor demand.
Erik Brynjolfsson, Wang Jin, Kristina McElheran
June 29, 2021
Anecdotes abound suggesting that the use of predictive analytics boosts firm performance. However, large-scale representative data on this phenomenon have been lacking. Working with the U.S. Census Bureau, we surveyed over 30,000 manufacturing establishments on their use of predictive analytics and detailed workplace characteristics.
Brad Larsen, Daniel Keniston, Shengwu Li, J.J. Prescott, Bernardo S. Silveira, Chuan Yu
This paper uses detailed data on sequential offers from seven vastly different real-world bargaining settings to document a robust pattern: agents favor offers that split the difference between the two most recent offers on the table. Our settings include negotiations for used cars, insurance injury claims, a TV game show, auto rickshaw rides, housing, international trade tariffs, and online retail.
Matthew Gentzkow, Amy Finkelstein, Heidi Williams
American Economic Review
We estimate the effect of current location on elderly mortality by analyzing outcomes of movers in the Medicare population. We control for movers’ origin locations as well as a rich vector of pre-move health measures. We also develop a novel strategy to adjust for remaining unobservables, using the correlation of residual mortality with movers’ origins to gauge the importance of omitted variables.
Brad Larsen, Carol Hengheng Lu, Anthony Lee Zhang
August 26, 2021
We analyze data on tens of thousands of alternating-offer, business-to-business negotiations in the wholesale used-car market, with each negotiation mediated (over the phone) by a third-party company. We find that who intermediates the negotiation matters: high-performing mediators are 22.03% more likely to close a deal than low performers.
Erik Brynjolfsson, Jason Dowlatabadi, Meng Liu
August 27, 2021
Traditional marketplaces are prone to market inefficiencies such as moral hazard due to information asymmetries between market participants. Digital platforms often build transparency and dispute resolution mechanisms into their marketplaces. This may reduce moral hazard.
Does the text content of a job posting predict the salary offered for the role? There is ample evidence that even within an occupation, a job’s skills and tasks affect the job’s salary. Using a dataset of salary information linked to posting data. postdoctoral fellow Sarah Bana is applying natural language processing (NLP) techniques to build a model that predicts salaries from job posting text.
Seth Benzell, Victor Yifan Ye, Laurence Kotlikoff, Guillermo LaGarda
September 21, 2021
This paper develops a 17-region, 3-skill group, overlapping generations, computable general equilibrium model to evaluate the global consequences of automation. Automation, modeled as capital- and high-skill biased technological change, is endogenous with regions adopting new technologies when profitable. Our approach captures and quantifies key macro implications of a range of foundational models of automation.
October 8, 2021
Does the text content of a job posting predict the salary offered for the role? There is ample evidence that even within an occupation, a job’s skills and tasks affect the job’s salary. Capturing this fine-grained information from postings can provide real-time insights on prices of various job characteristics. Using a new dataset from Greenwich.HR with salary information linked to posting data from Burning Glass Technologies, I apply natural language processing (NLP) techniques to build a model that predicts salaries from job posting text.
Erik Brynjolfsson, Seth Benzell, Guillaume Saint-Jacques
November 4, 2021
Digital technologies are creating dramatically cheaper and more abundant substitutes for many types of ordinary labor and capital. If these inputs are are becoming more abundant, what is constraining growth? We posit that most growth requires a third factor, a scarce `bottleneck’ input, that cannot be duplicated by digital technologies.
Erik Brynjolfsson, Seth Benzell
November 4, 2021
We introduce a model of technological advances as allowing for greater productivity at the cost of increased complexity. Complex goods and services, like Swiss watches, require a large number of strongly complementary inputs which themselves must be precisely calibrated.
Susan Athey, Billy Ferguson, Matthew Gentzkow, Tobias Schmidt
November 16, 2021
Proceedings of the National Academy of Science of the United States of America
Racial segregation shapes key aspects of a healthy society, including educational development, psychological well-being, and economic mobility. As such, a large literature has formed to measure segregation. Estimates of racial segregation often rely on assumptions of uniform interaction within some fixed time and geographic space despite the dynamic nature of urban environments. We leverage Global Positioning System data to estimate a measure of segregation that relaxes these strict assumptions.
Avinash Collis, Alex Moehring, Ananya Sen, Alessandro Acquisti
November 30, 2021
We investigate how consumer valuations of personal data are affected by real-world information interventions. Proposals to compensate users for the information they disclose to online services have been advanced in both research and policy circles. These proposals are hampered by information frictions that limit consumers’ ability to assess the value of their own data.