Hanlin Zhao (pronounced hAEn-lihn JOW)
I am a Ph.D. candidate in Economics at Toulouse School of Economics. My research
focuses on Empirical Industrial Organization and the Digital Economy. I study how
digital platforms shape consumer search and belief formation through the information they
present, and develop structural methods to quantify the consequences for welfare and
competition among firms and to evaluate platform regulation. I was a Visiting Scholar at
NYU Stern School of Business in Fall 2025.
I will be on the academic job market this year (2026–2027).
Industrial Organization·Digital Economics·Quantitative Marketing·Structural Econometrics
Research
Job Market Paper
Decoding Rankings: Consumer Search, Price Competition, and Platform Regulation
Using Expedia data, this paper shows that consumers substantially underestimate how much
commission revenue shapes platform rankings. The gap between actual and perceived
monetization makes ranking neutrality and transparency complements. Transparency alone
reduces consumer welfare because attractive offers remain costly to discover; neutrality
improves recommendations, but uncorrected beliefs limit its welfare gain. Together, the
policies align improved recommendations with consumer beliefs and raise on-platform bookings by 26%
after hotel repricing. Transparency also reverses the platform's revenue comparison in favor
of neutrality.
Abstract
Online platforms often use monetized rankings: product positions reflect both
predicted consumer value and commission revenue. Monetization can steer costly search
toward high-commission offers, motivating two policies: neutrality that removes
commission from the ranking criterion, and transparency that discloses the ranking's
monetization. These policies may substitute if transparency suffices to let consumers
discount steering, but complement if improved recommendations under neutrality remains
misread with uncorrected beliefs. The determinant is therefore the gap between actual
and perceived monetization. Using Expedia data, we estimate an equilibrium model of
consumer search and hotel price competition that separately identifies the two.
Consumers substantially underestimate monetization. Transparency corrects reliance on
the monetized ranking but attractive options remains costly to discover, reducing
consumer welfare. Neutrality instead facilitates search but uncorrected beliefs imply
excessive skepticism, limiting the welfare gain. The policies are therefore
complements: together they align what recommendations deliver with what consumers
believe and raise on-platform bookings by 26% even after hotel repricing. The same
mechanism also reverses the platform's revenue comparison: neutrality earns less
commission with uncorrected beliefs but more under transparency.
Draft available upon request
Working Papers
Estimating Choice Models with Unobserved Expectations over Attributes
with Mathias Reynaert
and Wenxuan Xu
Abstract
Agents often choose based on expectations about uncertain attributes, yet researchers
rarely observe the information behind those expectations. We develop two methods to
estimate discrete choice models with heterogeneous, unobserved information sets. Our
point-identification approach uses repeated realizations of the uncertain attribute to
estimate its statistical process with observed predictors and recoverable latent
factors, then represents conditional expectations as a finite mixture over these
components. A complementary approach set-identifies preferences using partial
information about expectations. Both methods apply to individual- and market-level data.
Applications to firms' export decisions and consumers' automobile purchases show that
our method corrects for substantial bias in preference estimates that arises when
unobserved information heterogeneity is ignored.
Paper
IIOC 2025 · EARIE 2025* · APIOC 2024 · University of Vienna* · TSE workshops (IO · IO Winter · Yinghua He Empirical Micro · EEE*)
Patent Challenge and Generic Entry
with Xin Zhang
Abstract
Pharmaceutical innovation depends on strong primary patents that allow originators to
recoup R&D costs. However, drug companies often engage in evergreening that prolongs
patent protection by filing follow-on patents with little therapeutic gain. We study a
policy lever that works with market forces to screen out weak follow-on patents: the
Hatch-Waxman Act, which incentivizes challenges to evergreening patents by granting the
first successful challenger a period of marketing exclusivity. We investigate how the
length of first-filer exclusivity shapes generic firms' incentives to initiate
challenges, which can curb the extra monopoly protection created by evergreening while
preserving incentives for genuine discovery and protecting consumer welfare through
earlier generic entry. Using a two-stage structural model that endogenizes challenge and
entry decisions, we estimate the fixed costs of generic entry with moment inequalities.
We find that the current 180-day exclusivity raises challenge rates by about 4
percentage points. Extending exclusivity primarily activates challenges in markets that
would otherwise go unchallenged: a two-year exclusivity increases the challenge rate to
15.38%. Effective exclusivity is highly heterogeneous across therapeutic classes:
reaching a 20% challenge rate requires roughly two years for antimicrobials but less
than one year for genitourinary drugs.
Paper
IO Lunch Seminar, Northwestern University* · Brown Bag Seminar, Kellogg School of Management* · TSE workshops (IO* · EEE Luchon* · Empirical Micro*)
Specification Test for Models of Consumer Search
Abstract
Measuring consumer preferences requires knowing how consumers search. This paper
develops a search-conduct test that distinguishes sequential from simultaneous search
with differentiated products and outside options. The framework allows individual- and
product-specific search costs and observed or unobserved searched attributes. Estimating
both models with a unified maximum-likelihood approach, I develop a corrected Vuong test
to compare their fit. Monte Carlo evidence shows that misspecified search conduct
generates inconsistent preference estimates and that the test reliably selects the
correct model.
Draft available upon request
EARIE 2025 · Doctoral Workshop on the Economics of Digitization 2025 · TSE workshops (IO · Ph.D.)
Work in Progress
- Identification of Consumer Search Models with Moment Inequalities
- Disintermediation, Platform Competition, and Ranking Algorithmswith Steve (Shitai) Zhang
- Ranking Competition under Two-Sided Learningwith Chuqing Jin
- Collusive Price Floors and Bounded Rationality: Evidence from the Chinese Movie Industrywith Chun YiEARIE 2025* · TSE IO Winter Workshop
Teaching
Best Teaching Assistant Award, Toulouse School of Economics, 2023
Teaching Assistant, Toulouse School of Economics
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Undergraduate Finance
in French
Spring 2024, 2025
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Graduate Econometrics
Fall 2024
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Undergraduate Econometrics
Spring 2023, 2024
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Graduate Empirical Industrial Organization
Fall 2023