Yikang Shen
Ph.D. Candidate in Economics, Carnegie Mellon University
2026–27 Academic Job Market
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Digital platforms · Industrial Organization · Political Economy
I study digital platforms and algorithmic markets, focusing on how algorithms and digital intermediaries shape information provision, firm behavior, and market outcomes. I combine structural modeling, causal inference, economic theory, machine learning, and large-scale data to study these questions.
Platforms as Editors: How Algorithmic Curation Shapes Online News Supply
Recommendation algorithms shape not only what consumers see but also what firms choose to produce.
Using matched print–online headlines and over 3 million Facebook posts, I study how algorithmic incentives shape news supply and exposure.
After Facebook restored political content, the online–print slant gap for political news increased by about 81%.
Outlet responses account for about 80% of the additional slant in user exposure.
Removing ideological amplification from the ranking algorithm eliminates roughly 90% of supply-induced slant.
Evaluating platform algorithms therefore requires accounting for both their direct effects on exposure and the supply responses they induce.
Following Facebook's 2025 restoration of political content, the online–print slant gap increased sharply for political relative to non-political news.
Selected presentations:
NBER Political Economy Program Meeting · ES NA Summer Meeting · ZEW Economics of ICT · ESIF Economics and AI/ML · CIST · CES NA
Working Papers
Getting the Agent to Wait
with Maryam Saeedi and Ali Shourideh
We study how an information provider controls the timing of disclosure when it values user engagement and users prefer to learn quickly. Optimal disclosure depends on relative patience and differences in beliefs; when beliefs are private, non-personalized communication leads to faster information revelation, while personalized communication delivers higher-quality information. The framework applies to digital platforms, personalized content, and other settings in which intermediaries strategically manage information provision.
Automated Exchange Economies
with Bryan R. Routledge and Ariel Zetlin-Jones
We study price discovery in decentralized exchanges where automated market makers replace traditional order books with algorithmic pricing rules. Using 19.2 million transactions from 31 Uniswap v2 pools and a dynamic model of liquidity provision, we show that liquidity providers are not purely passive: they strategically adjust prices in response to trades, with important implications for price formation in algorithmic markets.
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