To study the role of tax professionals, we merge tax records of 2.5 million taxpayers in Italy with the respective audit files from the tax revenue agency. Our data covers the entire population of sole proprietorship taxpayers in seven regions, followed over seven fiscal years. We first document...

In 2002 more than 18 million low-income individual taxpayers received the Earned Income Tax Credit (EITC). Despite its size, non-participation in this program is a concern and substantial effort is devoted by the IRS, local governments and many non-profits to address it. Most of the tax returns...

We develop measures of labor-saving and labor-augmenting technology exposure using textual analysis of patents and job tasks. Using US administrative data, we show that both measures negatively predict earnings growth of individual incumbent workers. While labor-saving technologies predict...

We apply an understanding of what computers do -- the execution of procedural or rules-based logic -- to study how computer technology alters job skill demands. We contend that computer capital (1) substitutes for a limited and well-defined set of human activities, those involving routine...

In this paper we use detailed job vacancy data to estimate changes in skill demand in the years since the Great Recession. The share of job vacancies requiring a bachelor's degree increased by more than 60 percent between 2007 and 2019, with faster growth in professional occupations and...

The standard approach to modeling inequality, building on Tinbergen's seminal work, assumes factor-augmenting technologies and technological change biased in favor of skilled workers. Though this approach has been successful in conceptualizing and documenting the race between technology and...

We show that administrative hourly wage data exhibits considerable bunching at round numbers that cannot be explained by rounding of survey respondents. We consider two explanations--worker left-digit bias and employer optimization frictions. We experimentally rule out left-bunching by...

We study the impact of AI on labor markets, using establishment level data on vacancies with detailed occupational information comprising the near-universe of online vacancies in the US from 2010 onwards. We classify establishments as "AI exposed" when their workers engage in tasks that are...

Gender differences in current and past job tasks may be crucial for understanding the gender wage gap. We use novel task data to address well-known measurement concerns, including that standard task measures assume away within-occupation gender differences in tasks. We find that unique measures...

We use novel data from the Berea Panel Study to reexamine the labor market mechanisms generating the beauty wage premium. We find that the beauty premium varies widely across jobs with different task requirements. Specifically, in jobs where existing research such as Hamermesh and Biddle (1994)...