This paper studies the effects of bank failure on firm performance. We collect 36 million loan records to build a novel dataset on the credit relationships of 1.8 million US firms, predominantly composed of small and medium-sized enterprises (SMEs). We then implement a staggered treatment difference-in-differences estimation strategy with 179 bank failures from 1990 to 2023 to estimate the effect of bank failure on firm-level survival and employment growth. We find that firms that had a credit relationship to a bank that fails are 6.7 percentage points (44.3%) more likely to fail themselves within five years of the bank failure. Additionally, firms that survive bank failures show 25% lower employment growth compared to firms banking with non-failed banks. These impacts of bank failure on firm performance persist for more than 10 years, are present for bank failures both during and outside the US financial crisis period, and are strongest for smaller enterprises. Our estimated effects are further supported by two natural experiments. Surprisingly, we observe that some bank failures had positive effects on firm outcomes, revealing that bank failure can, in rare cases, actually be fortuitous for affected firms. Overall, our findings suggest that bank failures exert a substantially larger influence on the real economy than previously recognized, possibly requiring a re-evaluation of current regulatory approaches to managing such events.

This paper examines the macroeconomic impact of chronic disease in the United King- dom (UK). We use individual-level data to estimate how diagnoses of six major diseases affect labor market transitions and combine these with a tractable growth model with age-specific productivity and labor force participation to quantify the impact on GDP. Our findings indicate a 20% reduction in disease incidence would increase annual GDP by 1.2% after five years and 1.8% after ten years. Most of the gains stem from higher la- bor force participation and increased full-time employment, especially on workers aged 50–65. Reductions in mental health disorders and musculoskeletal conditions contribute most to these effects. A compression of morbidity is also achieved with life expectancy increasing by 1.23 years and healthy life expectancy by 2.13 years. Our analysis points to three important features of preventative health policies : 1) the potential welfare gains are substantial and manifest themselves in terms of both improved population health and increased output growth, 2) only around 40% of long term effects show up after five years, and 3) the 50-65 age group experiences the largest labor force participation gains due to two factors: improved health at those ages prevents transitions into health-related inactivity, and a larger share of workers reaches this age band as a result of reduced tran- sitions into inactivity at earlier ages. This latter compounding effect underscores the importance of targeting prevention efforts at earlier ages to maximize the impact on the aggregate labor force participation rate.

This paper charts technological progress embodied in capital equipment, and the innovation and diffusion patterns therein. To do this, we digitize archival administrative filings from 1998 to 2024 and extract 50 million capital equipment transactions from five large US States. From these documents, we deploy an `agentic AI' measurement approach, where multiple AI `agents' collaborate to build and validate the data. The final dataset contains the make and model millions of pieces of IT equipment, heavy machinery, agricultural tools, vehicles, robotics, CNC machines, and much more. It also contains equipment-level characteristics, including time varying prices. We use these data to document five facts: First, new capital equipment with substantial productivity-enhancing capabilities takes years or decades to diffuse. Second, capital which is labor-replacing depressing both hiring and wages of lower-skilled workers. Third, equipment which is labor-augmenting drives hiring growth and raises wages for higher-skilled workers. Fourth, the skill-mix of labor is heavily influenced by new capital equipment adoption.

Leveraging a novel dataset of over 10 million lien filings spanning four US states, this paper documents capital reallocation patterns for over 1 million unique pieces of heavy equipment and machinery at the serial number level. Reallocation of these capital goods is significantly procyclical and three times as volatile as aggregate output. A dynamic heterogeneous firm general equilibrium model with trade in used and new capital goods is developed to show that the coincidence of lower capital reallocation and lower output can be explained by the asymmetric nature of recessions: smaller, higher-growth firms are affected more in recessions than larger, lower-growth firms. This asymmetry implies that demand for used capital declines disproportionately more than the supply of used capital increases, which results in a lower quantity of used capital traded and a lower price of used capital during recessions. The implication of this explanation is that the lower rate of capital reallocation observed during recessions is an efficient response of the economy to asymmetric changes in the firm productivity distribution. The model is able to rationalize a variety of empirical facts on the dynamics of capital investment including the fact that periods of low capital reallocation coincide with periods of high productivity dispersion.