IGL database (beta)

We report the results of a field experiment that randomly placed unemployed young people as apprentices with small firms in Ghana and included no cash subsidy to firms (or workers) beyond in-kind recruitment services. Treated firms experienced increases in firm size of approximately half a worker and firm profits of approximately 10 percent for each apprentice placement offered, documenting frictions to novice hiring.

There is a growing belief that scalable and low-cost AI assistance can improve firm decision-making and economic performance. However, running a business involves a myriad of open-ended problems, making it hard to generalize from recent studies showing that generative AI improves performance on well-definedwriting tasks. In our field experiment with 640 Kenyan entrepreneurs, we assessed the impact of AI-generated advice on small business revenues and profits.

Management strategies significantly influence worker productivity, retention, career growth, and the overall performance of a firm. Traditional top-down approaches have typically underscored the importance of supervisors in shaping managerial quality and employee performance. Much research suggests that training supervisors to effectively manage their subordinates may be a useful way to enhance supervisor-worker relationships and, in turn, boost firm productivity. However, these approaches may face two primary challenges.

Innovation plays a pivotal role in fostering economic growth, yet there is a limited understanding of whether it can be taught. I conduct a randomized evaluation of an education program implemented by a state government and a nonprofit organization, providing an opportunity to 6,224 8th-grade students from disadvantaged backgrounds to develop frugal innovations for global and local problems. To assess students’ innovative ability, I created a novel scale with inputs from experienced inventors and used a lab-in-the-field game from experimental economics.

Management strategies significantly influence worker productivity, retention, career growth, and the overall performance of a firm. Traditional top-down approaches have typically underscored the importance of supervisors in shaping managerial quality and employee performance. Much research suggests that training supervisors to effectively manage their subordinates may be a useful way to enhance supervisor-worker relationships and, in turn, boost firm productivity. However, these approaches may face two primary challenges.

Can artificial intelligence (AI) assist human employees in increasing employee creativity? Drawing on research on AI-human collaboration, job design, and employee creativity, we examine AI assistance in the form of a sequential division of labor within organizations: in a task, AI handles the initial portion which is well-codified and repetitive, and employees focus on the subsequent portion involving higher-level problem-solving. First, we provide causal evidence from a field experiment conducted at a telemarketing company.

The public release of Large Language Models (LLMs) has sparked tremendous interest in how humans will use Artificial Intelligence (AI) to accomplish a variety of tasks. In our study conducted with Boston Consulting Group, a global management consulting firm, we examine the performance implications of AI on realistic, complex, and knowledge-intensive tasks. The pre-registered experiment involved 758 consultants comprising about 7% of the individual contributor-level consultants at the company.

We study how local public infrastructure investment affects neighborhood economies. By tracking the impacts of US$68 million of randomized investments in Mexican municipalities, we document how government investment leads to sustained increases in the size and profitability of treated private-sector companies. Initially, wages rise to compensate for higher costs of living, inefficient firms die, and more efficient firms grow faster. Over the subsequent decade treated firms increase their capital stocks and revenues, suggesting durable improvements in the structure of the local economy.

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 document interest in labor reallocation among small firm owners in Ghana; 60% and 41%, respectively, self-report willingness to hire or work for the average local firm owner. Firm owners also exhibit high willingness-to-pay for information on a random subset of hiring firms and jobseeking firm owners, during a Becker-Degroot-Marschak exercise. Conditionally random variation in access to this information generates immediate labor adjustments within and between firms, though rarely of firm owners themselves, and impacts firm closure 5-months post-intervention.

There is a growing belief that scalable and low-cost AI assistance can improve firm decision-making and economic performance. However, running a business involves a myriad of open-ended problems, making it hard to generalize from recent studies showing that generative AI improves performance on well-definedwriting tasks. In our field experiment with 640 Kenyan entrepreneurs, we assessed the impact of AI-generated advice on small business revenues and profits.

Effective workplace management plays a crucial role in determining employee performance, retention, and subsequently, overall firm performance. While conventional management strategies often emphasize hierarchical relationships, peer-to-peer management, or "managing across," represents a promising yet largely unexplored approach. This study aims to investigate the impact of peer-to-peer management training on various employee outcomes and identify the conditions under which the intervention proves most effective.

As more and more activities in the economy become digitized, analytics and data-driven decision-making (DDD) are becoming increasingly important. The adoption of analytics and DDD has been slower in small-to-medium enterprises (SMEs) compared to large firms, and reliable causal estimates of the impacts of analytics tools for small businesses have been lacking. We derive experiment-based estimates of the effect of an analytics tool on SME outcomes, analyzing the randomized introduction of eBay’s Seller Hub (SH), a data-rich seller dashboard.

Although entrepreneurship training programs are designed to help necessity entrepreneurs acquire skills and capabilities to take entrepreneurial action, participants in these programs often fail to do so. In partnership with a local government agency, we conducted a randomized field experiment involving 165 entrepreneurs in rural Tanzania where in addition to providing technical-skills training, approximately half of the participants also received “growth mindset” psychological training.