Autoregressive LLMs generate text by sampling from estimated probability distributions over the next token, conditional on prior context. We use these probabilities to construct an entropy-based ...

Target date funds – which initially invest a large share of retirement savings in stocks and shift gradually towards bonds over the life cycle – are designed to provide a “one stop shop” for ...

However, a party can sustain extremism only if the other side is extreme, too. A small moderation of one side’s voting electorate can trigger a discontinuous collapse of candidate extremism on both ...

Organized interests are thought to influence policy, but whether and when interest group money overrides public opinion remains poorly understood. We investigate how gun interest group money and ...

This paper investigates household preferences over who should work and whether these preferences are malleable. We document that men and women prefer that husbands work over wives. To understand why, ...

We construct a novel dataset linking academic publication records to U.S. Census employer–employee data to track 42,000 AI researchers over two decades. We document systematic changes in the ...

We investigate how fertility relates to work from home (WFH) in the post-pandemic era, drawing on original data from our Global Survey of Working Arrangements and U.S. Survey of Working Arrangements ...

Research Associate Kosali Simon, the Herman B. Wells Professor and Distinguished Professor at the Paul H. O'Neill School of Public and Environmental at Indiana University, will direct the NBER Program ...

We use high-frequency retail microdata to measure the short-run impact of the 2025 U.S. tariffs on consumer prices. By matching daily prices from major U.S. retailers to product-level tariff rates and ...

Amid an aging population and a growing role for private equity (PE) in elder care, this paper studies how PE ownership affects U.S. nursing homes using patient-level Medicare data. We show that PE ...

We examine two approaches to improving urban school systems: changing who gets to go to existing schools (reallocation) and restructuring school portfolios through closures and reconstitution ...

Using rich Swedish administrative data, we apply causal machine learning methods to study how earnings losses after job displacement vary with observable characteristics that may be relevant for ...