Find my SSRN page here
Researchers interested in the economics of digitization can view and participate in a bi-weekly virtual seminar on the digital economy (VIDE) here and learn about data sources and recent developments in the field here.
Working papers:
"Visibility of Technology and Cumulative Innovation: Evidence from Trade Secrecy Protection Laws" (with Bernhard Ganglmair) [paper]
Patents grant an inventor temporary monopoly rights in exchange for the disclosure of the patented invention. However, if only those inventions that are otherwise already visible are patented (and others kept secret), then the bargain fails. We use exogenous variation in the strength of trade secrets protection from the Uniform Trade Secrets Act to show that a relative weakening of patents (compared to trade secrets) adversely affects the rate of process patents relative to products. By arguing that processes are on average less visible (or self-disclosing) than products, we show that stronger trade secrets have a disproportionately negative effect on the disclosure of inventions that are not otherwise visible to society. We develop a structural model of initial and follow-on innovation to determine the effects of such a shift in disclosure on overall welfare in industries characterized by cumulative innovation. In counterfactual analyses, we find that while stronger trade secrets encourage more investment in R&D, they may have negative effects on overall welfare -- the result of a significant decline in follow-on innovation. This is especially the case in industries with relatively profitable R&D.
"A Framework for Detection, Measurement, and Welfare Analysis of Platform Bias" (with Joel Waldfogel) [paper]
Regulators are responding to growing platform power with curbs on platforms' potentially biased exercise of power, creating urgent needs for both a workable definition of platform bias and ways to detect and measure it. We develop a simple equilibrium framework in which consumers choose among ranked alternatives, while the platform chooses product display ranks based on product characteristics and prices. We define the platform's ranks to be biased if they deliver outcomes that lie below the frontier that maximizes a weighted sum of seller and consumer surplus . This framework leads to two bias testing approaches, which we compare using data from Amazon, Expedia, and Spotify, as well as Monte Carlo simulations. We then illustrate the use of our structural framework directly, producing estimates of both platform bias and its welfare cost. The EU's Digital Services Act's provision for researcher data access would allow easy implementation of our approach in contexts important to policy makers.
"The potential welfare benefits of AI-based personalized predictions" (with Christoph Riedl and Joel Waldfogel)
The benefit that consumers derive from experience goods depends on the information they have prior to purchase. Artificial intelligence (AI) and rich consumer data have delivered new prediction technologies, with the promise of steering consumers toward more suitable products; but the size of the potential benefits from better prediction is unknown. Using cumulative usage time data on 50,000 users and 100 popular games on the video game platform Steam, we quantify AI's potential benefit by creating personalized predictions of how much time each user would spend playing each game. We use these predictions, along with a simple model of consumer utility maximization, to measure potential welfare effects of better predictions on buyers and sellers. Using both a Cobb Douglas calibration and a logit model of bundle choice, we find large effects: AI-based predictions, if heeded, would raise consumer surplus by roughly two thirds of current expenditure while reducing expenditure by about a fifth.
"Home Sweet Home? Covid-19, Stadium Attendance and Efficiency in Sports Betting Markets" (with James Dana)
Professional sports teams have a significant advantage when playing at home, but much is still unknown about the role of fans in creating that advantage. We document this ignorance in the context of professional European soccer leagues. We exploit exogenous variation in stadium attendance due to the Covid-19 pandemic to measure how fan attendance influences outcomes and to highlight significant inefficiencies in the betting markets. We estimate that the absence of fans decreases the home field advantage by more than one half, and more importantly that the return of even a small number of loyal fans fully restores the initial advantage. Moreover, while betting markets were largely efficient when fans were banned, they significantly underestimated the benefits of the return of a small number of fans later in the pandemic, creating fruitful profit-making opportunities for people betting on home teams.
Published/accepted articles:
"The First Sale Doctrine and the Digital Challenge to Public Libraries" with Joel Waldfogel
(Review of Economics and Statistics, forthcoming) [paper]
"Digitization and the Demand for Physical Works: Evidence from the Google Books Project" with Abhishek Nagaraj
(American Economic Journal - Economic Policy, 2023) [paper]
"Platforms and the Transformation of the Content Industries" with Luis Aguiar and Joel Waldfogel
(Journal of Economics and Management Strategy, 2023) [paper]
"Does Amazon Exercise its Market Power? Evidence from Toys R Us" with Leshui He and Benjamin Shiller
(Journal of Law and Economics, 2022) [paper]
"Digitization, Prediction and Market Efficiency: Evidence from Book Publishing Deals" with Christian Peukert
(Management Science, 2022) [paper]
(Publishers Weekly article)
"Digitization and Pre-Purchase Information: The Causal and Welfare Impacts of Reviews and Crowd Ratings" with Joel Waldfogel
(American Economic Review, 2021) [paper]
"The Impacts of Telematics on Competition and Consumer Behavior in Insurance" with Benjamin Shiller
(Journal of Law and Economics, 2019) [paper]
"Copyright and Generic Entry in Book Publishing"
(American Economic Journal - Microeconomics, 2019) [paper]
(New York Times article)
"Do Coupons Expand or Cannibalize Revenue? Evidence from an e-Market" with Claire (Chunying) Xie
(Management Science, 2018) [paper]
"Are Public and Private Enforcement Complements or Substitutes? Evidence from High Frequency Data" with Gregory DeAngelo and Brad Humphreys
(Journal of Economic Behavior and Organization, 2017) [paper]
(Sports Illustrated article)
"Examining Regulatory Capture: Evidence from the NHL" with Gregory DeAngelo and Adam Nowak
(Contemporary Economic Policy, 2017) [paper]
"Throwing the Books at Them: Amazon's Puzzling Long-Run Pricing Strategy" with Joel Waldfogel
(Southern Economic Journal, 2017) [paper]
"Can Private Copyright Protection be Effective? Evidence from Book Publishing"
(Journal of Law and Economics, 2016) [paper]
(Publishers Weekly article)
"Storming the Gatekeepers: Digital Disintermediation in the Market for Books" with Joel Waldfogel
(Information Economics and Policy, 2015) [link]
Researchers interested in the economics of digitization can view and participate in a bi-weekly virtual seminar on the digital economy (VIDE) here and learn about data sources and recent developments in the field here.
Working papers:
"Visibility of Technology and Cumulative Innovation: Evidence from Trade Secrecy Protection Laws" (with Bernhard Ganglmair) [paper]
Patents grant an inventor temporary monopoly rights in exchange for the disclosure of the patented invention. However, if only those inventions that are otherwise already visible are patented (and others kept secret), then the bargain fails. We use exogenous variation in the strength of trade secrets protection from the Uniform Trade Secrets Act to show that a relative weakening of patents (compared to trade secrets) adversely affects the rate of process patents relative to products. By arguing that processes are on average less visible (or self-disclosing) than products, we show that stronger trade secrets have a disproportionately negative effect on the disclosure of inventions that are not otherwise visible to society. We develop a structural model of initial and follow-on innovation to determine the effects of such a shift in disclosure on overall welfare in industries characterized by cumulative innovation. In counterfactual analyses, we find that while stronger trade secrets encourage more investment in R&D, they may have negative effects on overall welfare -- the result of a significant decline in follow-on innovation. This is especially the case in industries with relatively profitable R&D.
"A Framework for Detection, Measurement, and Welfare Analysis of Platform Bias" (with Joel Waldfogel) [paper]
Regulators are responding to growing platform power with curbs on platforms' potentially biased exercise of power, creating urgent needs for both a workable definition of platform bias and ways to detect and measure it. We develop a simple equilibrium framework in which consumers choose among ranked alternatives, while the platform chooses product display ranks based on product characteristics and prices. We define the platform's ranks to be biased if they deliver outcomes that lie below the frontier that maximizes a weighted sum of seller and consumer surplus . This framework leads to two bias testing approaches, which we compare using data from Amazon, Expedia, and Spotify, as well as Monte Carlo simulations. We then illustrate the use of our structural framework directly, producing estimates of both platform bias and its welfare cost. The EU's Digital Services Act's provision for researcher data access would allow easy implementation of our approach in contexts important to policy makers.
"The potential welfare benefits of AI-based personalized predictions" (with Christoph Riedl and Joel Waldfogel)
The benefit that consumers derive from experience goods depends on the information they have prior to purchase. Artificial intelligence (AI) and rich consumer data have delivered new prediction technologies, with the promise of steering consumers toward more suitable products; but the size of the potential benefits from better prediction is unknown. Using cumulative usage time data on 50,000 users and 100 popular games on the video game platform Steam, we quantify AI's potential benefit by creating personalized predictions of how much time each user would spend playing each game. We use these predictions, along with a simple model of consumer utility maximization, to measure potential welfare effects of better predictions on buyers and sellers. Using both a Cobb Douglas calibration and a logit model of bundle choice, we find large effects: AI-based predictions, if heeded, would raise consumer surplus by roughly two thirds of current expenditure while reducing expenditure by about a fifth.
"Home Sweet Home? Covid-19, Stadium Attendance and Efficiency in Sports Betting Markets" (with James Dana)
Professional sports teams have a significant advantage when playing at home, but much is still unknown about the role of fans in creating that advantage. We document this ignorance in the context of professional European soccer leagues. We exploit exogenous variation in stadium attendance due to the Covid-19 pandemic to measure how fan attendance influences outcomes and to highlight significant inefficiencies in the betting markets. We estimate that the absence of fans decreases the home field advantage by more than one half, and more importantly that the return of even a small number of loyal fans fully restores the initial advantage. Moreover, while betting markets were largely efficient when fans were banned, they significantly underestimated the benefits of the return of a small number of fans later in the pandemic, creating fruitful profit-making opportunities for people betting on home teams.
Published/accepted articles:
"The First Sale Doctrine and the Digital Challenge to Public Libraries" with Joel Waldfogel
(Review of Economics and Statistics, forthcoming) [paper]
"Digitization and the Demand for Physical Works: Evidence from the Google Books Project" with Abhishek Nagaraj
(American Economic Journal - Economic Policy, 2023) [paper]
"Platforms and the Transformation of the Content Industries" with Luis Aguiar and Joel Waldfogel
(Journal of Economics and Management Strategy, 2023) [paper]
"Does Amazon Exercise its Market Power? Evidence from Toys R Us" with Leshui He and Benjamin Shiller
(Journal of Law and Economics, 2022) [paper]
"Digitization, Prediction and Market Efficiency: Evidence from Book Publishing Deals" with Christian Peukert
(Management Science, 2022) [paper]
(Publishers Weekly article)
"Digitization and Pre-Purchase Information: The Causal and Welfare Impacts of Reviews and Crowd Ratings" with Joel Waldfogel
(American Economic Review, 2021) [paper]
"The Impacts of Telematics on Competition and Consumer Behavior in Insurance" with Benjamin Shiller
(Journal of Law and Economics, 2019) [paper]
"Copyright and Generic Entry in Book Publishing"
(American Economic Journal - Microeconomics, 2019) [paper]
(New York Times article)
"Do Coupons Expand or Cannibalize Revenue? Evidence from an e-Market" with Claire (Chunying) Xie
(Management Science, 2018) [paper]
"Are Public and Private Enforcement Complements or Substitutes? Evidence from High Frequency Data" with Gregory DeAngelo and Brad Humphreys
(Journal of Economic Behavior and Organization, 2017) [paper]
(Sports Illustrated article)
"Examining Regulatory Capture: Evidence from the NHL" with Gregory DeAngelo and Adam Nowak
(Contemporary Economic Policy, 2017) [paper]
"Throwing the Books at Them: Amazon's Puzzling Long-Run Pricing Strategy" with Joel Waldfogel
(Southern Economic Journal, 2017) [paper]
"Can Private Copyright Protection be Effective? Evidence from Book Publishing"
(Journal of Law and Economics, 2016) [paper]
(Publishers Weekly article)
"Storming the Gatekeepers: Digital Disintermediation in the Market for Books" with Joel Waldfogel
(Information Economics and Policy, 2015) [link]