We use data from the Annual Survey of Manufactures to study the characteristics and geographic distribution of investments in robots across US manufacturing establishments. Robotics adoption and robot intensity (the number of robots per employee) cluster in "robot hubs." Establishments that report having robotics are larger and have a larger production worker share, lower pay per worker, lower labor share, and higher capital expenditures, including higher IT capital expenditures. Notably, establishments are more likely to have robots if other establishments in the same core-based statistical area and industry also report having robotics, suggestive of agglomeration and peer effects.

Utilizing near real-time QuickBooks data from over 1.6 million small businesses and a targeted survey, this paper highlights the critical role credit card financing plays for small business activity. We examine a two year period beginning in January of 2021. A turbulent period during which, credit card usage by small U.S. businesses nearly doubled, interest payments rose by 60%, and delinquencies reached 2.8%. We find, first, monthly credit card payments were up to three times higher than loan payments during this time. Second, we use targeted surveys of these small businesses to establish credit cards as a key financing source in response to firm-level shocks, such as uncertain cash flows and overdue invoices. Third, we establish the importance of credit cards as an important financial transmission mechanism. Following the Federal Reserve’s rate hikes in early 2022, banks cut credit card supply, leading to a 15.75% drop in balances and a 10% decline in revenue growth, as well as a 1.5% decrease in employment growth among U.S. small businesses. These higher rates also rendered interest payments unsustainable for many, contributing to half of the observed increase in delinquencies. Lastly, a simple heterogeneous firm model with a cash-in-hand constraint illustrates the significant macroeconomic impact of credit card financing on small business activity.

This field experiment investigates the causal impact of mothers’ perceptions of gender norms on their employment attitudes and labor-supply expectations. We provide mothers of young children in Germany with information about the prevailing gender norm regarding maternal employment in their city. At baseline, over 70% of mothers incorrectly perceive this gender norm as too conservative – the most pronounced misperception among the various gender norms we examine. Our randomized information treatment improves the accuracy of these perceptions, significantly reducing the share of mothers who perceive gender norms as overly conservative. The treatment also shifts mothers’ own labormarket attitudes in a more liberal direction. Leveraging the fact that we assessed attitudes in a prior survey, we show that specifically the shifted attitude is a strong predictor of mothers’ future labor-market participation. Consistently, treated mothers are more likely to plan an increase in their working hours, particularly those with existing support to facilitate their employment.

We investigate public preferences for equity-enhancing policies in access to early child care, using a survey experiment with a representative sample of the German population (n ≈ 4, 800). We observe strong misperceptions about migrant-native inequalities in early child care that vary by respondents’ age and right-wing voting preferences. Randomly providing information about the actual extent of inequalities has a nuanced impact on the support for equity-enhancing policy reforms: it increases support for respondents who initially underestimated these inequalities, and tends to decrease support for those who initially overestimated them. This asymmetric effect leads to a more consensual policy view, substantially decreasing the polarization in policy support between under- and overestimators. Our results suggest that correcting misperceptions can align public policy preferences, potentially leading to less polarized debates about how to address inequalities and discrimination.

This paper analyzes the distribution and composition of pre-tax national income in Germany since 1992, combining personal income tax returns, household survey data, and national accounts. Inequality rose from the 1990s to the late 2000s due to falling labor incomes among the bottom 50% and rising incomes in the top 10%. This trend reversed after 2007 as labor incomes across the bottom 90% increased. The top 1% income share, dominated by business income, remained relatively stable between 1992 and 2019. A large share of Germany’s top 1% earners are non-corporate business owners in labor-intensive professions. At least half of the business owners in P99-99.9 and a quarter in the top 0.1% operate firms in professional services – a pattern mirroring the United States. From 1992 to 2019, Germany’s top 0.1% income concentration exceeded France’s and matched U.S. levels until the late 2000s.