Entrepreneurship is a key driver of economic growth, as it boosts innovation, creates jobs, and improves productivity. Mentorship is crucial to entrepreneurial success, providing valuable guidance and support. To commercialize their ideas, entrepreneurs must navigate multiple potential strategies, and mentors help refine these choices. The Creative Destruction Lab (CDL) is a global mentorship-driven startup accelerator. The mission of the CDL is to advance the commercialization of scientific innovations to benefit humanity. Its core idea is that the obstacle to transforming excellent science and innovation into successful businesses is a failure in the market for high quality judgment.
Mohaddeseh Heydari Nejad, a PhD candidate with the Department of Economics, examined this unique focus on mentorship within the CDL’s program. Her job market paper, A Structural Model of Mentorship in Startup Accelerators: Matching, learning, and value creation (JMP), examines how mentorship improves entrepreneurial outcomes.
“Mentorship provided by experienced entrepreneurs, potential investors, industry experts, and scientists is crucial for entrepreneurial success,” Heydari Nejad explained. “Using data from the Creative Destruction Lab, I developed a novel structural model of mentorship to study the mechanisms through which mentorship generates value: the direct effect of improving startup quality and the screening effect of identifying high-quality startups. In this model, mentorship improves startup quality while also enabling mentors to learn about the underlying quality of startups through interactions, helping them allocate resources more effectively.”
Heydari Nejad’s analysis included data from 1,800 startups and 1,500 mentors across eight cohorts of startups participating in the Creative Destruction Lab (CDL). She applied machine learning algorithms and used Text-as-Data methods to generate quantifiable measures of mentors’ advice.
“Mentorship generates value through both the direct effect and the screening effect. Mentors learn about the quality of startups through their interactions with entrepreneurs, and there are significant spillovers of quality signals among mentors,” she said. “I show that entrepreneurs benefit from mentors’ strategic guidance. Breaking down this value, I find that their strategic guidance not only improves startup quality but also generates learning gains and helps identify high-quality startups.”
Insights from Heydari Nejad’s paper suggest that intermediaries and institutions that provide scalable, lower cost forms of mentorship improves entrepreneurial outcomes.
“Mohaddeseh introduces an innovative structural model that captures the dynamic role of mentorship, offering both theoretical and practical insights into how accelerators drive startup success,” said Professor Victor Aguirregabiria, a member of Heydari Nejad’s supervisory committee. “This work serves as a valuable resource for academics exploring the intersection of mentorship and entrepreneurship, as well as practitioners aiming to optimize accelerator programs.”
Researching and communicating results for both academics and practitioners, is a product of the interaction between PhD student and faculty, and between students themselves at the department. It’s a part of the economics community culture here at the University of Toronto that Heydari Nejad hopes to bring out in her career.
“It’s great to see faculties take detailed notes during presentations and give those notes to the speaker afterward,” she said. “They provide a lot of good feedback and detailed comments. We also have a common area in the basement where students engage in discussions about their research after seminars. I’ve learned to always take notes during presentations instead of trying to remember everything or interrupting with small details. I then send the notes to the presenter right after the presentation because it helps them track possible improvements. This is something I plan to continue doing.”
In Heydari Nejad’s view, these detailed and meaningful exchanges are a chance to learn about what’s going on in other fields and how to incorporate those methods and perspectives into her own work.
“It’s about finding intersections and opportunities for generating new ideas,” she said. “The main thing that connects everyone and everything is the learning aspect.”
That learning aspect is also clear in her approach to teaching. As a teaching assistant for undergraduate level courses in Principles of Economics and Industrial Organization, as well as a PhD course in Econometrics has required her to create opportunities for that intersectional cross pollination of ideas.
“One of my main methods in teaching tutorials is to help students understand the basics using their own examples and words, instead of just memorizing everything,” she said. “If they can think about an example and bring their own judgment into the mechanisms at play, it makes it easier for them to understand the core theory.”