Table 3.A.1. Use of home equity and employment size by total amount of startup capital Total amount of startup capital Use of home equity Average number of employees
Less than $5,000 0.021 2.7
$5,000 - $9,999 0.056 2.5
$10,000 - $24,999 0.082 2.9
$25,000 - $49,999 0.171 2.8
$50,000 - $99,999 0.235 3.1
$100,000 - $249,999 0.276 3.7
$250,000 - $999,999 0.253 5.8
$1,000,000 or more 0.153 24.3
Notes: This table shows in the second column the fraction of newly created firms that used home equity as a source of funding, and in the third column the average employment. Both variables are cross-tabulated by total amount of initial startup capital. Sample includes newly created firms in 2007 with positive employment. Observation are weighted using the provided survey weights.
Data from the U.S. Bureau of Census, Survey of Business Owner, 2007 Public Use Microdata Sample.
|3Homeequity,mortgagecreditandfirmcreation:evidencefromtheGreatRecession
Table 3.A.2. Industry heterogeneity in the effect of credit shock on firm creation: CZ-level shock
(1) (2) (3) (4) (5)
All industries
Without
construction Construction
Without non-tradables
Without non-tradables and construction
∆Credit Availability 0.089∗∗∗ 0.087∗∗ 0.089 0.106∗∗∗ 0.106∗∗∗
(3.49) (3.27) (1.18) (3.67) (3.49)
State FE Yes Yes Yes Yes Yes
NAICS FE Yes Yes Yes Yes Yes
Clustering Yes Yes Yes Yes Yes
Observations 32311 29609 2702 26150 23448
AdjustedR2 0.021 0.021 0.030 0.014 0.014
Notes: This table reports OLS regression estimates of change in firm creation, computed using equation 3.3, on the estimated change in credit availability, computed using equations 3.5 and 3.6. Standard errors are heteroscedasticity robust and where indicated clustered at the county level.
tstatistics in parentheses,+p<0.10,∗p<0.05,∗∗p<0.01,∗∗∗p<0.001
Table 3.A.3.Heterogeneous effects of credit availability on firm creation: CZ-level shock
(1) (2) (3) (4) (5) (6) (7)
∆Credit Availability 0.089∗∗∗
(3.49)
∆CA×HSE high 0.170∗∗ 0.216∗∗∗
(2.94) (3.65)
∆CA×HSE low -0.134+ -0.055
(-1.90) (-0.74)
∆CA×HE high 0.086∗∗ 0.065∗
(2.91) (2.13)
∆CA×HE low 0.092∗∗ 0.075∗
(2.97) (2.36)
∆CA×HE high×HSE high 0.234∗∗∗ 0.279∗∗∗
(3.56) (4.16)
∆CA×HE low×HSE high 0.106 0.153∗
(1.45) (2.08)
∆CA×HE high×HSE low -0.127 -0.048
(-1.60) (-0.57)
∆CA×HE low×HSE low -0.140+ -0.061
(-1.72) (-0.72)
State FE Yes Yes Yes Yes Yes Yes Yes
NAICS FE Yes Yes Yes Yes Yes Yes Yes
Demographics No No No No Yes Yes Yes
Industry composition No No No No Yes Yes Yes
Clustering Yes Yes Yes Yes Yes Yes Yes
Observations 32311 12204 32311 12204 12204 32283 12204
AdjustedR2 0.021 0.105 0.064 0.105 0.108 0.067 0.108
Notes: This table reports OLS regression estimates of change in firm creation, computed using equation 3.3, on the estimated change in credit availability, computed using equations 3.5 and 3.6. HSE high (low) corresponds to a variable that indicates if a county has an above (below) median housing supply elasticity provided by Saiz (2010). HE high (low) corresponds to a variable that indicates if a NAICS sector has an above (below) median reliance on home equity financing as found in SBO. Standard errors are heteroscedasticity robust and where indicated clustered at the county level. Demographic controls include the pre-recession county-level percentage of the white population, median household income, percentage of owner-occupied housing, percentage with less than high school diploma, percentage with only a high school diploma, unemployment rate, poverty rate, and percentage of the urban population. Industry composition contains the pre-recession share of total county employment that is in each of the 23 two-digit industries.
tstatistics in parentheses,+p<0.10,∗p<0.05,∗∗p<0.01,∗∗∗p<0.001
References
Adelino, Manuel, Song Ma, and David Robinson.2017. “Firm Age, Investment Opportunities, and Job Creation.”Journal of Finance72 (3): 999–1038. [150]
Adelino, Manuel, Antoinette Schoar, and Felipe Severino.2015. “House prices, collateral, and self-employment.”Journal of Financial Economics117 (2): 288–306. [124]
Adelino, Manuel, Antoinette Schoar, and Felipe Severino.2018. “Perception of House Price Risk and Homeownership.” National Bureau of Economic Research Working Paper Series No.
25090: [143]
Amromin, Gene, Mariacristina De Nardi, and Karl Schulze.2017. “Household Inequality and the Consumption Response to Aggregate Real Shocks.”National Bureau of Economic Research Working Paper SeriesNo. 24073: [122, 128, 130]
Autor, David H, and David Dorn.2013. “The Growth of Low-Skill Service Jobs and the Polarization of the US Labor Market.”American Economic Review103 (5): 1553–97. [138]
Avery, Robert B, Raphael W Bostic, and Katherine A Samolyk.1998. “The role of personal wealth in small business finance.”Journal of Banking & Finance22 (6): 1019–61. [124]
Bahaj, Saleem, Angus Foulis, and Gabor Pinter.2017. “Home Values and Firm Behaviour.” Working paper 1724. [124]
Bahaj, Saleem, Angus Foulis, Gabor Pinter, and Paolo Surico.2019. “Employment and the Collat-eral Channel of Monetary Policy.” Working paper. Bank of England. [124]
Berger, Allen N, and Gregory F Udell.1995. “Relationship Lending and Lines of Credit in Small Firm Finance.”Journal of Business68 (3): 351–81. [124]
Black, Sandra E, and Philip E Strahan.2002. “Entrepreneurship and Bank Credit Availability.” Jour-nal of Finance57 (6): 2807–33. [123]
Chodorow-Reich, Gabriel.2014. “The Employment Effects of Credit Market Disruptions: Firm-level Evidence from the 2008–9 Financial Crisis.”Quarterly Journal of Economics129 (1): 1–59. [123, 131]
Corradin, Stefano, and Alexander Popov.2015. “House Prices, Home Equity Borrowing, and En-trepreneurship.”Review of Financial Studies28 (8): 2399–428. [121, 124]
Davis, Steven J., John Haltiwanger, and Scott Schuh.1996.Job Creation and Destruction. MIT Press.
[131]
Decker, Ryan A., Meagan Mccollum, and Gregory B. Upton.2018. “Firm Dynamics and Local Eco-nomic Shocks : Evidence from the Shale Oil and Gas Boom.” [150]
Dell’Ariccia, Giovanni, Deniz Igan, and Luc Laeven.2012. “Credit Booms and Lending Standards:
Evidence from the Subprime Mortgage Market.”Journal of Money, Credit and Banking44 (2-3):
367–84. [133]
Di Maggio, Marco, and Amir Kermani.2017. “Credit-Induced Boom and Bust.”Review of Financial Studies30 (11): 3711–58. [123]
Fairlie, Robert W., and Harry A. Krashinsky.2012. “Liquidity constraints, household wealth, and entrepreneurship revisited.”Review of Income and Wealth58 (2): 279–306. [124]
FED.2016. “Small Business Credit Survey: Report on Employer Firms.” Working paper. Atlanta:
Federal Reserve Bank of Atlanta. [121]
Greenstone, Michael, Alexandre Mas, and Hoai-Luu Nguyen.2020. “Do Credit Market Shocks Affect the Real Economy? Quasi-experimental Evidence from the Great Recession and "Normal"
Economic Times.”American Economic Journal: Economic Policy12 (1): 200–25. [123, 131, 132]
Haltiwanger, John, Ron S. Jarmin, and Javier Miranda.2012. “Who Creates Jobs? Small versus Large versus Young.”Review of Economics and Statistics95 (2): 347–61. [121]