Thank you!

For the full paper, visit my website: yannickschindler.com

If you want to chat about the paper, feel free to reach out!

Also thanks to the many people who provided feedback and comments incl.: @arnauddyevre.bsky.social, @deriddermaarten.bsky.social , @mdoepke.bsky.social, @mbellif.bsky.social (and many more not on this site!)

Huge thanks to my amazing co-author @econopete.bsky.social, and my supervisors Wouter Den Haan, @benmoll.bsky.social, and Andrew Scott!

By building a new dataset comprising millions of firm-bank credit relationships across the US, which covers 179 bank failures over 30 years, we offer the first evidence of the negative and highly persistent firm-level effects of these events.

In sum: this paper answers an important empirical question: "Do bank failures matter for the real economy?" and answers this question with an emphatic "yes!". We also provide evidence on mechanisms that are informative for the design of optimal bank resolution policy.

Branch networks play an important role in propagating the effects of bank failure. Firms with fewer branches in their locality are significantly more affected by bank failure, in line with the relationship lending literature that emphasizes the role of "soft" information and physical proximity.

We also show that bank failure is significantly more harmful for the smallest firms in our dataset, in line with the idea that smaller firms face significantly higher switching costs when changing banks than larger firms. We then turn our attention to branch networks.

We first show that the negative effects of bank failures happen both during financial crises AND in normal times. This gives a lot of external validity to important prior literature which presents evidence from crisis periods (e.g.
Chodorow-Reich 2014 & Huber 2018).

While the typical failure has long-lasting and negative consequences, a handful of failure events lead to significant IMPROVEMENTS in borrower performance. What can we learn from this variation in effects?

To answer this question and to interrogate mechanisms, we first run our estimation for each bank failure separately and find our second surprising result: not all failures are created equal!

Yet our results uncover the hidden, and lasting, effects that this process nevertheless has on small business borrowers and raise an important question: *why* does the US bank resolution process have such a large negative impact on small firms?

These results are surprising! Bank failure is a highly regulated process in which the FDIC facilitates the acquisition of a struggling bank by a healthy bank. On paper, this process looks frictionless, with deposits and loans being transferred to the healthier bank.

For survivors, the pain continues. Firms whose banks fail see their employment growth fall by about 25% compared to similar firms whose banks do not fail. Over a ten-year horizon, these businesses show 6 pp (29%) lower growth rates. No evidence of recovery or catching up.

The long time coverage of our data allows us to study both the short- and long-term (up to a decade!) effects of bank failure. We find that firms affected by bank failure are 6.7 pp (44%) more likely to fail within five years.

Our dataset bridges this gap, enabling us to study the impact of bank failures on the smallest firms in the economy. We do this by leveraging 179 bank failures and a staggered treatment DiD design to estimate the effects of bank failure on firm-level survival and employment.

They are also particularly vulnerable to bank shocks due to heavy reliance on loans, often from a single bank, and high switching costs when changing lenders. Yet, much of what is known about firm-level effects of banking shocks comes from studies of much larger firms.

Our data has extensive coverage of businesses with only a few employees: think restaurants, cafes, retail shops, and the like. Small businesses like these play an important role in the economy, making up the vast majority of firms & employing a large share of the labour force.

After years of data collection and processing, we've assembled what we believe to be the most comprehensive dataset on the banking relationships of small businesses in the US: 36 million loan records spanning three decades, parsed and linked using novel AI methods.