Yannick Schindler

Yannick Schindler

Job Market Candidate

Department of Economics

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Languages
English, German
Key Expertise
Macroeconomics

About me

Yannick is a PhD candidate in the Department of Economics. He is on the job market in 2024/25. His research interests are in macroeconomics, financial intermediation, and the economics of longevity. He also holds research fellow positions at London Business School (LBS), the Ellison Institute of Technology in Oxford, and the Centre on Longevity at Stanford University. In his work, he combines tools from macroeconomic theory with novel empirical methods, including text-as-data and large language models.

In his job market paper, co-authored with Peter Lambert, the authors collect 35 million loan documents to construct a novel dataset of the banking relationships of small and medium-sized enterprises (SMEs) in the US dating back to 2000. They use this dataset to study how bank failure affects firm-level outcomes and find that most bank failures have large and scarring impacts on firm survival and employment growth, with effects persisting for up to a decade and being of equal magnitude both during and after the Global Financial Crisis period. Surprisingly, they observe that a small selection of bank failure events in the US had positive effects on firms revealing that bank failure can, in rare cases, actually be fortuitous for business borrowers.

Contact Information

Email
y.schindler@lse.ac.uk

Office Address
Department of Economics
London School of Economics and Political Science
Houghton Street, London WC2A 2AE

Contacts and Referees

Placement Officer
Matthias Doepke

Supervisors
Wouter Den Haan
Benjamin Moll

References
Wouter Den Haan
Department of Economics
London School of Economics and Political Sciences
Houghton St, London WC2A 2AE
w.denhaan@lse.ac.uk

Ben Moll
Department of Economics
London School of Economics and Political Sciences
Regent’s Park, London NW1 4SA
b.moll@lse.ac.uk

Andrew Scott
Department of Economics
London Business School
Houghton St, London WC2A 2AE
ascott@london.edu

Download CV

Job Market Paper

Bad Bank, Bad Luck? Evidence from 1 Million Firm-Bank Relationships, with Peter Lambert.  

This paper studies the effects of bank failure on firm performance. We collect over 36 million loan records to build a novel dataset on the credit relationships of 1.8 million US firms, pre-dominantly composed of small and medium-sized enterprises (SMEs). We then analyze 179 bank failures from 2000 to 2023 to estimate the effect of bank failure on firm-level survival and employment growth. We find that firms who had a credit relationship to a bank that fails are 8.1 percentage points (36.5%) more likely fail themselves within five years of the bank failure. Additionally, surviving firms affected by bank failure experience employment growth rates of approximately half compared to firms banking with non-failed banks. These impacts of bank failure on firm performance persist for over 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 robust to a host of controls and to two natural experiments in which the timing of the bank failure is plausible exogenous to the health of the bank’s borrowers. Surprisingly, we observe that a small selection of bank failure events in the US had positive effects on business borrowers revealing that bank failure can, in rare cases, actually be fortuitous for its business borrowers. 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 I Link to paper.

Publications and Research

Publications

Prosperity Through Health: The Macroeconomic Case for Investing in Preventative Health Care in the UK, with John Bell, Tamsin Berry, John Deanfield, Ines Hassan, Roshni Joshi, and Andrew Scott​.
In this report, we argue for a shift towards preventative healthcare measures to address the economic challenges posed by an aging population and increasing disease burden. Using our novel model that combines health interventions with macroeconomic indicators, we estimate that a 20% reduction in six major disease categories could boost annual GDP by £26.3 billion within ten years and generate significant fiscal savings. We highlight the potential of treatments targeting multiple conditions, such as GLP-1 RA drugs, to unlock even greater economic benefits. Our case study on cardiovascular disease interventions demonstrates that even targeted treatments can yield substantial long-term economic gains. We emphasize the need for swift implementation of prevention programs and suggest starting with cardiovascular disease-focused initiatives due to available cost-effective interventions. We conclude that prioritizing preventative health measures can create a virtuous cycle of improved health, economic growth, and sustainable healthcare budgets.

 

Works in Progress

The Macroeconomic Impact of Chronic Disease in the United Kingdom​, with Andrew Scott.
We examine the macroeconomic consequences of chronic disease in the United Kingdom. We develop a tractable growth model that links individual-level health shocks to aggregate economic outcomes. The model features a population age structure and a distribution of labour supply across age that evolves over time. Each age group's labour supply is decomposed into population size and worker productivity as well as endogenously evolving labour force participation and hours worked. Using data from the UK Household Longitudinal Study (UKHLS) and the Labour Force Survey (LFS), we calibrate how these components of labour supply are affected by the diagnosis of six different chronic diseases. Simulating these effects in our growth model, we estimate that a 20% reduction in chronic disease incidence would boost UK GDP by 1.89% over the next decade. Our results are robust to various model specifications. We discuss the implications of our findings for health policy and argue for increased investment in chronic disease prevention as a strategy for promoting sustainable economic growth. 

Machinery of Progress: Charting Capital-Embodied Technological Progress 1998 to 2024, with Peter Lambert.
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.  

Relocatable Capital: Theory and Empirical Evidence from 35 Million Lien Filings.
This paper studies the dynamics of capital reallocation. Leveraging a novel dataset of over 35 million lien filings spanning five US states, this paper documents capital reallocation patterns for over two 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 partly due to an efficient response of the economy to asymmetric changes in the firm productivity distribution. The model is capable of rationalising a variety of investment-related business cycle moments including the puzzling negative correlation between productivity dispersion and capital reallocation observed in the data.