Ye Zhang张晔


Ph.D. Candidate

Columbia University Economics Department


Welcome! I am currently a Ph.D. student in the Economics Department at Columbia University after finishing my undergraduate study at Hong Kong University of Science and Technology. 

My research explores topics related to empirical corporate finance, especially entrepreneurial finance, by using multidisciplinary research methods. In particular, I enjoy designing field and lab-in-the-field experiments to study important entrepreneurship and finance-related questions. These experiments, similar to art, help people understand the world while providing their designers with enough freedom and space for imagination. 

​( I am on the 2020-2021 job market and will be available for interviews at the 2021 ASSA Virtual Meetings. )

Research Interest: Entrepreneurial Finance, Empirical Corporate Finance, Field Experiments, Labor 

CV: available here


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Job Market Paper 

Title: "Discrimination In the Venture Capital Industry: Evidence from Two Randomized Controlled Trials"

(Available on ArXiv, Identifier 2010.16084)     Video

Abstract: This paper examines discrimination based on startup founders' gender, race, and age by early-stage investors, using two randomized controlled trials with real venture capitalists. The first experiment invites U.S. investors to evaluate multiple randomly generated startup profiles, which they know to be hypothetical, in order to be matched with real, high-quality startups from collaborating incubators. Investors can also donate money to randomly displayed startup teams to show their anonymous support during the COVID-19 pandemic. The second experiment sends hypothetical pitch emails with randomized startups' information to global venture capitalists and compares their email responses by utilizing a new email technology that tracks investors' detailed information acquisition behaviors. I find three main results: (i) Investors are biased towards female, Asian, and older founders of relatively low quality startups; while biased against female, Asian, and older founders of relatively high quality startups. (ii) These two experiments identify multiple coexisting sources of bias. Specifically, statistical discrimination is an important reason for "anti-minority" investors' contact and investment decisions, which was proved by a newly developed consistent decision-based heterogeneous effect estimator. (iii) There was a temporary, stronger bias against Asian founders during the COVID-19 outbreak, which started to fade in April 2020.

Working Papers

Title: "How Venture Capitalists Bet: Evidence From Two Randomized Controlled Trials"

(Available on SSRN)

Abstract: Understanding the importance of both human and non-human assets in firms' early-stage financing process is crucial to examining theories of the firm. However, it is difficult to empirically generate causal evidence due to data limitations and the lack of exogenous variations. This paper uses two randomized controlled trials with real venture capitalists mainly from the U.S. to identify characteristics of both the project and their teams that causally affect venture capitalist funding. Specifically, I also check their relative importance on investors' decisions. I find that multiple team characteristics (i.e. founder's educational background and previous entrepreneurial experiences) and project characteristics (i.e. traction, business model, location, comparative advantages, etc.) causally affect investors' contact and investment interests by influencing their evaluation of startups' potential financial returns, risk, and loyalty. Although project traction matters the most in my experimental setting, it is fundamentally the investors' belief in the startup’s profitability that matters the most. I also find the traditional correspondence test method, to an extent, inappropriate in testing the  significance of project characteristics in virtue of the different "signal-to-noise ratio" problem.

Title: "ESG and Venture Capital Investment: Experimental Evidence"

Abstract: This paper examines the effect of ESG characteristics of startups on venture capitalists’ investment interest by employing  a randomized controlled method. I invite real U.S. investors to evaluate multiple randomly generated startup profiles, which they know to be hypothetical, in order to be matched with high-quality startups from the collaborative incubators. I find the following three main results: (i) Aiming for environmental and social impact causally lowers investors’ expectation of the startup’s future profitability rather than risk. Therefore, profit-driven investors are less likely to contact or invest in ESG-related startups. (ii) Profit-driven investors have a stronger implicit belief that ESG related startups would not seek for collaboration with them . (iii) There is a positive interaction effect between ESG characteristics and the founder’s educational background, indicating that a high level of education helps improve investor’s expectation of the ESG startup's profitability. Experimental results challenge the traditional thesis of “doing well by doing good” and support the recent findings that investors derive non-pecuniary utility from impact investing while sacrificing their financial returns.

Title: "The Microstructure of U.S. Housing Market: Evidence from Millions of Bargaining Interactions,"

with Haaris Mateen, Franklin Qian

Abstract: We study the microstructure of the U.S. housing market using a novel data set comprising housing search and bargaining behavior for millions of interactions between sellers and buyers. We first establish a number of stylized facts, the most important being a symmetric spread of the sales price around the final listing price in our data. Second, we compare observed behavior with predictions from a large theoretical housing literature. Many predictions on the relationship between sales price, time on the market, listing price and atypicality are borne out in the data. However, existing models do not adequately explain the symmetric spread of the sales price around the final listing price. Using a modeling strategy that treats listing price changes as revisions of expectations about the sales price, we find sellers under-react to information shocks in estimating the sales price. Last, we find that the bargaining outcomes are influenced by previously undocumented buyers’ bid characteristics, e.g., financing contingencies and escalation clauses, that signal a buyer’s ability to complete or expedite the transaction. This suggests an important role for buyer bid characteristics, which are not explained by existing theories, in affecting bargaining power and surplus allocation in bilateral bargaining in housing transactions.


Work in Progress

"Who Are the Most Attractive Venture Capitalists? Evidence from Lab-in-the-field Experiment," with Junlong Feng  

"Track the Venture Capital Investment Climate: Experimental Evidence from Global VC Industry"

"Initial Public Offerings and Expectation in the Housing Market," with Haaris Mateen, Franklin Qian

Job Market Paper Video
Job Market Paper

Instructor:    Corporate Finance                           Summer 2018 


TA:                Corporate Finance (evaluation)              Fall 2017, Spring 2018, Spring 2019, Fall 2019, Spring 2020


                       Advanced Econometrics (evaluation)     Fall 2018


                       Introduction of Econometrics            Fall 2016, Spring 2017


LTF:              Economics Department Lead Teaching Fellow     2018- 2019


These digital paintings are designed to show my deepest acknowledgements to my advisors for their guidance and protection when I almost gave up. Thanks also go to our academic community and entrepreneurial community for their feedback and support.       



©2020 by YE ZHANG

Last updated: 11/2020