Beili Li

1. What do you do?

I use machine learning and AI tools to help build data science solutions for Home Depot's online business, including merchandising strategy, pricing optimization, and product enrichment.

2. What’s the coolest part of your job?

One, leveraging the cutting-edge AI and machine learning techniques to solve real business problems and make an impact on the business, and two, knowing that the work I do can generate both dollar impact and improve customer shopping experiences.

Tyler Mauldin

1. What do you do?

I'm a lead on Google's Energy Policy & Markets team. In this role, I spearhead the company's energy regulatory and policy affairs efforts in key markets. I bring nearly a decade of experience in the tech and utility industry to this role.

Most recently, I was the senior regional manager of Microsoft's commercial energy markets in the Southeast, where I led negotiation and procurement of power capacity for new AI and cloud data centers.

Stable Income, Stable Family

This study examines how unemployment insurance (UI) helps families weather the strain of job loss. Using household survey data linked to state-level changes in UI benefits, the authors show that more generous benefits reduce the likelihood that layoffs lead to divorce or separation and also moderate the impact of job loss on childbearing. Specifically, higher benefits cushion men from the increased divorce risk and lower fertility typically associated with layoffs, while also softening the effects of women’s layoffs, which otherwise raise the risk of separation and increase fertility.

Varying-coefficient Spatial Dynamic Panel Data Models With Fixed Effects: Theory and Application

Spillover effects are critical mechanisms in social and economic systems, influencing outcomes across a wide spectrum of social science research. Accurately estimating these effects is essential for policymakers. A major limitation of existing studies is the common assumption of homogeneous spillover effects—treating them as identical across all individuals, firms, or entities.

Growing up Amid Armed Conflict: Women’s Attitudes Toward Domestic Violence

This paper examines the relationship between growing up amid armed conflict and acceptance of violent behavior later in life. With this aim, we match data from 48 Demographic and Health Surveys in 23 countries in Sub-Saharan Africa with records of all conflict events in the region post-WWII. Our empirical strategy exploits within-country variation in conflict exposure across survey clusters and over birth years. We find that attitudes toward domestic violence vary with past exposure to a high-intensity conflict (war) during childhood, but the estimated association is small in magnitude.

Data-Driven Contract Design

Moral hazard is the workhorse model of financial incentive provision in economics, with applications ranging from pay-for-performance in employer-employee relationships to the design of insurance premiums. While an extensive theoretical literature has delivered important qualitative insights about the properties that real-world incentive schemes ought to have, the practical implementability of these prescriptions is limited by the model's demanding assumption that the employer knows both the employee's performance capabilities and also how strongly he responds to financial incentives.

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