Work in Progress
Digital Networks
Measuring Social Media Network Effects - 2025
We measure heterogeneity in what types of connections drive value on four social media platforms.
Regulating Digital Platform Monopolies: The Case of Facebook - 2022
We develop a model of platform participation in the presence of heterogenous network effects and demand, prove some analytical results about the model, and then calibrate it on survey data for Facebook. We simulate the impact of different regulatory reforms.
Joint with Avi Collis
Measuring How University Students Form and Value Instagram Connections
Funded by a Chapman Seed Grant, we study the network of connections on Instagram, measure which types of connections are most valued, and find evidence of non-linear returns to connections, in an incentive compatible lab study.
Other Digital Network
Work-in-Progress
Blitzscaling and Unravelling - 2023
Examining the role of the time endurance of network effects in dynamic platform pricing decisions.
Do Startups Invert? API Networks and Startup Exits - 2022
Examining the productivity effect of API use and network strategy on startup success.
Joint with Jonathan Hersh and Marshall Van Alstyne
Technology as Strategy - 2022
Practitioner piece on the implications of our API research.
Joint with Jonathan Hersh and Marshall Van Alstyne
Power Law Distributions in Social Media - 2023
What determines the distribution of followers and attention in the upper tail of social media platform accounts?
Joint with Ruyu Chen and Yikai Li
Automation, Skill Biased Technological Change, and the Macroeconomics and Business of AI
Automation Experiments and Inequality - 2025
An increasingly large number of experiments study the labor productivity effects of automation technologies such as generative algorithms. A popular question in these experiments relates to inequality: does the technology increase output more for high- or low-skill workers? We explain how to extrapolate from empirical evidence to real world predictions about inequality in multi-task settings. With Kyle Myers, under review.
Simulating Endogenous Global Automation - 2023
This paper develops a 17-region, 3-skill group, overlapping generations, computable general equilibrium model to evaluate the global consequences of automation. In our baseline scenario, automation has a moderate effect on regional outputs and a small effect on world interest rates. However, it has a major impact on inequality, both wage inequality within regions and per capita GDP inequality across regions.
Joint with Victor Ye, Laurence Kotlikoff and Guillermo Lagarda
Robots are Us: Some Economics of Human Automation - 2023
Automation, in the form of AI trained through supervised and unsupervised machine learning, may lead to a boom-bust cycle in welfare, inter-generationally. Under certain conditions, future generations can be left worse off.
Joint with Laurence Kotlikoff, Guillermo Lagarda, and Jeff Sachs
Digital Abundance and Scarce Architects - 2022
Digital labor and capital can be reproduced much more cheaply than its traditional forms. But if labor and capital are becoming more abundant, what is constraining growth? We posit a third factor, ‘architecture’, that cannot be duplicated by digital technologies.
Skill Biased Technological Change Within and Across Firms - 2019
Using LinkedIn resume records, BLS OES data, and Compustat employee counts, we estimate occupational employment for publicly traded US firms from 2000 through 2016. We find that faster employment growth among firms that disproportionately employ non-routine workers is the most important cause of SBTC, followed by within firm occupational mix rebalancing.
Joint with Daniel Rock and Guillermo Lagarda
Working paper available
NSF Funded "Recyclofacturing" Feasibility Study - 2025-2029
The National Science Foundation (NSF) is investing $25.5 million to support fundamental research and workforce development that will enable next-generation U.S. manufacturing. The awards will support seven research grants and nine seed projects across 36 institutions and companies through the NSF Future Manufacturing program. The goal is to spur new manufacturing capabilities, materials or systems. Projects span a range of topics, including “recyclofacturing” using artificial intelligence to create products from metal scrap, and using robotics and digital twins for additive manufacturing of multimaterial systems. My team will evaluate the socio-tecnical feasibility of rec
Additional Automation and AI Work in Progress
I am working with Victor Ye and a team of other researchers to further develop the global simulation model in "Simulating Endogenous Global Automation." We will apply the model to understand the implications of UBI and other fiscal policy responses in different technological scenarios. We also plan to bring back-testing to this class of models for the first time to measure the reliability of our finds.
Joint with Victor Ye
I am collaborating on an NSF grant proposal with a team of researchers to study the productivity and distributive implications of collaborative robots. Our proposal was rated "competitive" in 2023, and we will be resubmitting in 2024.
Draft proposal available upon request
Superstars at Work: Increasing Returns to Scale Across Occupations - 2023
Joint with Erik Brynjolfsson and Ruyu Chen
The Innovation/Complexity Tradeoff: How Bottlenecks Create Superstars and Constrain Growth - 2022
Investigating the tradeoff between increased maximum productivity and increased production fragility in implementing more complex production processes, and the implications for firms and the economy.
Working paper available
Identifying the Multiple Skills in Skill Biased Technological Change - 2019
Joint with Erik Brynjofsson, Frank MacCrory, and George Westerman
Working paper available
Robots: Curse or Blessing? A Basic Framework - 2015
Joint with Jeff Sachs and Guillermo Lagarda
Working paper available
Additional General Information Systems Research
Speedruns and the Science of Science - 2023
Joint with Kai Zhu and Kyle Myers
Essay on how digital technologies are increasing the importance of power-law distributions in the economy
Joint with Erik Brynjolfsson
IT and the Age of Leaders - 2023
Joint with Frank Li
Other Working Papers
Simulating Business Cash Flow Taxation: An Illustration Based on the Better Way Corporate Tax Reform -2017
Automation, in the form of AI trained through supervised and unsupervised machine learning, may lead to a boom-bust cycle in welfare, inter-generationally. Under certain conditions, future generations can be left worse off.
Joint with Laurence Kotlikoff and Guillermo Lagarda