IGL Trials Database

Whose problems do investors see as worth solving? I experimentally study how investors evaluate a startup idea based on the socioeconomic background of the founder, the target customer, and the (in)congruence between the two. I am also interested in how the socioeconomic background of investors themselves affect these evaluations. I aim to contribute to the research on diversity and inequality in entrepreneurial funding in which socioeconomic backgrounds have been relatively understudied.

We examine the productivity effects of a generative artificial intelligence technology—the assistive chatbot ChatGPT—in the context of mid-level professional writing tasks. In a preregistered online experiment, we assign occupation-specific, incentivized writing tasks to 444 college-educated professionals, and randomly expose half of them to ChatGPT. Our results show that ChatGPT substantially raises average productivity: time taken decreases by 0.8 SDs and output quality rises by 0.4 SDs.

We study the allocation and productivity consequences of managerial training via a randomized controlled trial among supervisors in a large ready-made garment firm. We designed a program using practices identified as productive in Adhvaryu et al. (2022c), and asked factory and floor managers (FFMs) – who are directly above supervisors in the hierarchy – to recommend which of the supervisors they manage should be prioritized for training. We then randomized access to the program within these recommendation rankings.

We examine the influence of physical proximity on between-startup knowledge spillovers at one of the largest technology co-working hubs in the United States. Relying on the random assignment of office space to the hub's 251 startups, we find that proximity positively influences knowledge spillovers as proxied by the likelihood of adopting an upstream web technology already used by a peer startup.

We seek to understand what is limiting women's access to finance, in particular for highly skilled start-up entrepreneurs. To investigate supply side constraints, we run a lab-in-the-field experiment in which loan officers in Uganda evaluate several business ideas based on real pitch decks from start-ups. We separate biases in idea evaluation from other constraints (such as gender specific differences in the ability to implement a project, or in external constraints that start-up entrepreneurs are facing).

We study the demand for government participation in China’s venture capital and private equity market. We conduct a large-scale, non-deceptive field experiment in collaboration with the leading industry service provider, through which we survey both sides of the market: the capital investors and the private firms managing the invested capital by deploying it to high-growth entrepreneurs. Our respondents together account for nearly $1 trillion in assets under management.

What is preventing entrepreneurs and managers from forming peer connections themselves? This paper argues that entrepreneurs may be under-networked because they lack the necessary social skills that allow them to match efficiently with knowledgeable peers.

This lab-in-the-field experiment will measure the gender bias in entrepreneurship and investment among youth and credit officers in Ethiopia. Chigign Tobiya “Ethiopia Emerges” is a television show in Ethiopia where entrepreneurs pitch their business ideas to a panel of business tycoons for a chance to get investment funding.

This experiment tries to understand how managers respond to uncertainty when making research and development decisions. Three experiments were conducted with master’s degree students in a program focused on the intersection of business and technology.

Women are underrepresented as inventors on U.S. patents (Toole et al. 2019, Toole et al. 2020). Although the gender gap is closing over time, it is not closing quickly. This suggests that there is a role for policy to help reduce invention and commercialization barriers for women. However, the potential effectiveness of policies to address this issue are unclear, primarily because the underlying causes of the gender gap are complex and not well understood. Recent research has begun to cast light on this issue (Whittington 2005; Ding et al. 2006; Murray and Graham 2007; Colyvas et al.

We analyze, benchmark, and run randomized controlled trials on a panel of 7,463 U.S. entrepreneurs making incentivized sales forecasts. We assess accuracy using a novel administrative dataset obtained in collaboration with a leading US payment processing firm. At baseline, only 13% of entrepreneurs can forecast their firm’s sales in the next three months within 10% of the realized value, with 7.3% of the mean squared error attributable to bias and the remaining 92.7% attributable to noise.

Climate change poses an urgent and existential threat to the wine sector. However, it is not easy for wineries and farmers to take action to reduce carbon emission comparing to adaptation. How can we encourage these actions? Farmers often seek information before take action, which influences their current risk perceptions of extreme weather condition or moral norms. Regarding the information, a positive approach focusing on empowering farmers to take action to address climate change is generally more successful at engaging people and minimizing defensive reactions.

The study investigates the role of information constraints and behavioral biases in the under-adoption of key business practices by micro-enterprises in Brazil. We combine a randomized control trial with online surveys to study these questions.

We experimentally study the impact of substantially larger enterprise loans, in collaboration with an Egyptian lender. Larger loans generate small average impacts, but machine learning using psychometric data reveals dramatic heterogeneity. Top-performers (i.e., those with the highest predicted treatment effects) substantially increase profits, whereas profits for poor-performers drop. The magnitude of this difference implies that an individual lender’s credit allocation choices matter for aggregate income.