2020
DOI: 10.1257/pol.20160005
|View full text |Cite
|
Sign up to set email alerts
|

Do Credit Market Shocks Affect the Real Economy? Quasi-experimental Evidence from the Great Recession and “Normal” Economic Times

Abstract: Using comprehensive data on bank lending and establishment-level outcomes from 1997–2010, this paper finds that small business lending is an unimportant determinant of small business and overall economic activity. A shift-share style research design is implemented to predict county-level lending shocks using variation in preexisting bank market shares and bank supply shifts. Counties with negative predicted lending shocks experienced declines in small business loan originations, indicating that it is costly to… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
2
1

Citation Types

3
223
2
1

Year Published

2023
2023
2024
2024

Publication Types

Select...
6
1
1

Relationship

0
8

Authors

Journals

citations
Cited by 151 publications
(229 citation statements)
references
References 37 publications
3
223
2
1
Order By: Relevance
“…For simplicity we use the language of locations and industries throughout. Other influential and recent examples of shift-share IVs include Luttmer (2006), Saiz (2010), Kovak (2013), Autor et al (2013), Nakamura and Steinsson (2014), Oberfield and Raval (2014), Greenstone et al (2014), Diamond (2016), Suárez and Zidar (2016), and Hornbeck and Moretti (2018). randomly assigned conditional on industry-level observables, and to panel data.…”
Section: Introductionmentioning
confidence: 99%
“…For simplicity we use the language of locations and industries throughout. Other influential and recent examples of shift-share IVs include Luttmer (2006), Saiz (2010), Kovak (2013), Autor et al (2013), Nakamura and Steinsson (2014), Oberfield and Raval (2014), Greenstone et al (2014), Diamond (2016), Suárez and Zidar (2016), and Hornbeck and Moretti (2018). randomly assigned conditional on industry-level observables, and to panel data.…”
Section: Introductionmentioning
confidence: 99%
“…Similarly, Greenstone et al (2014) utilize county-level data from the U.S. to quantify the effect of the credit contraction on small firm employment following the 2008 crisis but differentiate themselves from the aforementioned papers in terms of identification. More specifically, they first estimate individual bank-level credit supply effects, and then, construct a county-level measure of credit supply.…”
Section: The Effect On Total Employmentmentioning
confidence: 99%
“…Interestingly, the evidence on employment effects is sometimes moderate (e.g., Greenstone et al, 2014;Popov and Rocholl, 2018) or not significant (e.g., , presumably because employment protection laws might induce companies to cut wages rather than employees (e.g., Popov and Rocholl, 2018). The role of employment protection is also consistent with the observation that labour force adjustments often concentrate on less educated (e.g., Hochfellner et al, 2015), shorter-tenured (e.g., Caggese et al, 2019), younger (e.g., Berton et al, 2018) and/or female employees (e.g., Berton et al, 2018), and in particularly those with temporary contracts (e.g., Caggese and Cuñat, 2008).…”
Section: Introductionmentioning
confidence: 99%
“…The CRA requires banks above a certain asset threshold to report small business lending each year. During our sample period, the asset threshold was $250 million Greenstone, Mas, and Nguyen (2014). estimate that CRA-eligible banks accounted for approximately 86% of all loans under $1 million.19 FollowingGreenstone, Mas, and Nguyen (2014), we define small business loans as those up to $1 million, and small businesses as firms with less than $1 million in annual gross revenue.…”
mentioning
confidence: 99%
“…During our sample period, the asset threshold was $250 million Greenstone, Mas, and Nguyen (2014). estimate that CRA-eligible banks accounted for approximately 86% of all loans under $1 million.19 FollowingGreenstone, Mas, and Nguyen (2014), we define small business loans as those up to $1 million, and small businesses as firms with less than $1 million in annual gross revenue. Ideally, we would measure the share of all lending that goes to small firms, rather than just the share of loans under $1 million, but county-level data on all loans are not available.…”
mentioning
confidence: 99%