Zhenling Jiang

Zhenling Jiang

Assistant Professor of Marketing

Biography

Zhenling Jiang is an Assistant Professor of Marketing at the Wharton School, University of Pennsylvania. Her research program bridges substantive inquiries into consumer financial markets with methodological innovations that integrate machine learning and econometrics. She specifically investigates how market frictions—such as behavioral biases, information asymmetry, and intermediary incentives—shape outcomes in high-stakes sectors like auto loans and mortgages. These real-world challenges drive her to develop scalable empirical tools, including neural network estimators, that can process unstructured data while maintaining the essential ability to simulate policy counterfactuals. Ultimately, her work seeks to promote market efficiency and financial equity by providing a more rigorous understanding of modern market dynamics.

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Interests

  • Integrating Machine Learning with Econometric Models
  • Consumer Financial Markets and Lending
  • Market Intervention for Equity and Inclusion

Education

  • Ph.D. in Marketing, 2013 - 2019

    Washington University in St. Louis

  • M.A. in International Economics and Finance, 2006 - 2008

    Brandeis University

  • B.A. in Economics, 2002 - 2006

    Nankai University

Journal Articles

(2025). Referral Contagion: Downstream Benefits of Customer Referrals. Journal of Marketing Research, 62 (1), 97-116.

DOI Abstract Harvard Business Review

(2025). Estimating Parameters of Structural Models Using Neural Networks. Marketing Science, 44 (1), 102-128.

Code DOI

(2023). Designing Dealer Compensation in the Auto Loan Market: Implications from a Policy Experiment. Marketing Science, 42 (5), 958-983.

DOI Abstract

(2022). The Value of Verified Employment Data for Consumer Lending: Evidence from Equifax. Marketing Science, 41 (4), 367-386.

DOI Abstract

(2021). How Does Bonus Payment Affect Auto Loan Demand and Delinquency?. Journal of Marketing Research, 58 (3), 476-496.

DOI Abstract The New York Times

(2021). Can Non-tiered Customer Loyalty Programs Be Profitable?. Marketing Science, 40 (3), 508-526.

DOI Abstract

(2021). Consumer Search and Purchase: An Empirical Investigation of Retargeting Based on Consumer Online Behaviors. Marketing Science, 40 (2), 219-240.

DOI Abstract

Selected Work in Progress

Machine Learning and Prediction Errors in Causal Inference.

Teaching

 
 
 
 
 
Data and Analysis for Marketing Decisions
University of Pennsylvania, the Wharton School
Sep 2020 – Present MBA and Undergraduate
 
 
 
 
 
Introduction to Structural Modeling
Georgia State University, J. Mack Robinson College of Business
Jan 2020 – May 2020 Doctoral seminar
 
 
 
 
 
Data Driven Marketing
Georgia State University, J. Mack Robinson College of Business
Jan 2020 – May 2020 Graduate