VoxEU Column Labour Markets

Housing market and bank lending effects on young firms and local economies

Young firms live a financially precarious life, often dependent on self-funding tied to the value of the business owners’ homes. This column uses data from the US to show that housing market fluctuations play a major role in driving medium-term changes in young firm employment shares. As young firms hire a disproportionate number of younger and less-educated workers, these groups are disproportionately affected by house price fluctuations. 

The Great Recession of 2007–09 raised numerous questions about the effects of housing markets on economic activity. One question concerns the impact of house price changes on new and young businesses. A related question involves how housing market ups and downs affect local economies. Highly influential research by Mian and Sufi (2011, 2014) stresses the role of housing market developments working through consumption demand channels. In a recent article, we show that house price changes have particularly pronounced effects on new and younger firms, and that the effects of house price changes on young firms and local economies work partly through investment channels (Davis and Haltiwanger 2019). 

In the US, employment at young firms (i.e. less than 60 months since first paid employee) fell secularly from 18% private sector employees in 1987 to just 9% in 2014. Overlaying this long-term development, there is a clear pattern of pro-cyclical fluctuations in the national young firm employment share, as seen in Figure 1. Young firms experienced an especially sharp contraction in their employment share during the Great Recession and a slow recovery afterwards. More broadly, as we show in Davis and Haltiwanger (2019), young firm activity shares move strongly with local economic conditions and local house price growth. 

Figure 1 Cyclicality of log changes in the young-firm share of private sector employees

Notes: Each bar shows the annual average log change in the share of private sector employees at young firms during the indicated cycle episode, deviated about the sample mean log change of minus 2.2 log points per year.  ‘Young’ means fewer than five years (60 months) since hiring the first paid employee. Green bars denote aggregate expansion episodes, and red bars denote aggregate contraction episodes.  All annual changes are from one mid-March payroll period to the next. For example, the bar for “1980–83” shows the average annual log changes for 1980–81, 1981–82 and 1982–83. Authors’ calculations using data from US Census Bureau’s Business Dynamic Statistics.

Identifying the local effects of house price changes

Motivated by these facts, we implement two instrumental variables (IV) estimation approaches to identify the causal effect of local house price changes on local young-firm employment shares. Our first approach exploits national housing boom and bust episodes that differentially affect MSA-level house prices due to differences in local housing supply elasticities. To obtain instruments that isolate arguably exogenous variation in local house price movements, we interact period effects (boom and bust) with the Saiz (2010) housing supply elasticity measure. The identification idea is that a common shock to housing demand generates cross-MSA differences in local house price movements due to exogenous spatial differences in housing supply elasticities. This approach follows the same identification strategy as Mian and Sufi (2011, 2014), but we focus on a different outcome variable (young firm activity shares) and consider additional controls to address various threats to identification. In our second IV approach, we instrument local house price changes using the interaction between local housing supply elasticity and local cyclical indicators.  

Our two IV approaches exploit different sources of data variation, but they yield similarly large, statistically significant effects of local house price changes on local young-firm activity shares. Both IV approaches address (serious) concerns about measurement error in local house price data. Beyond that, each approach offers certain advantages and disadvantages. In its focus on national boom and bust episodes, the first IV approach facilitates comparisons to previous research. By encompassing a much longer time period and eleven times as many observations, the second approach readily accommodates the inclusion of other shocks.   

Quantifying aggregate effects and including a role for loan supply shifts

When we aggregate our estimated local effects to the national level, housing market ups and downs play a major role – as transmission channel and driving force – in medium-run fluctuations in young-firm employment shares in recent decades. Figure 2 summarises our results in this regard. The blue bars show actual annual log changes in national young-firm employment shares, and the red bars show the changes implied by our second IV approach and preferred empirical specification, which includes a large battery of controls for potential confounds. As seen in Figure 2, the great housing bust after 2006 largely drove the cyclical collapse of young-firm activity during the Great Recession. Our results also say that the house price boom in the preceding decade offset what otherwise would have been a much larger fall in the young-firm activity share. 

Figure 2 Contributions of housing market ups and downs to aggregate changes in young-firm employment shares from 1980 to 2014

Notes: Blue bars show annual log changes in national young-firm employment shares. Red bars show the log changes implied by aggregating our estimated local effects of house price changes. We estimate the local effects using our second IV approach and aggregate the estimated local effects to the national level using local employment shares. 

We supplement our second IV approach by building on Greenstone et al. (2015) to isolate exogenous MSA-level shifts in the supply of bank lending to small and young firms. The idea here is that large banks differ in their financial fortunes, geographic footprints, and propensities to lend to smaller and younger firms. When a national bank pulls back from lending to smaller and younger firms in a given MSA for reasons other than local economic conditions, it produces a locally exogenous drop in loan supply to young firms in the MSA. Consistent with this view, we find that bank loan supply shocks have statistically significant, material effects on young firm activity shares in certain episodes, most notably in reinforcing the negative effects of the great housing bust on young firm employment shares.

House price effects work partly through investment channels

Housing market conditions can affect young firms and the local economy through a variety of wealth, liquidity, collateral, credit supply, and consumption demand channels. Since many studies find large effects of housing price changes on consumption expenditures, we test whether they affect local economies only through consumption demand. Our test of this view is new and conceptually simple – if house price changes work entirely through consumption demand channels, the local industry growth rate response should be invariant to the age structure of firms in the local industry. A natural alternative to this age-invariance hypothesis says that the local industry response rises with its young firm activity share due to wealth, collateral, and liquidity effects of house prices on the propensity to start a new business or expand a young one. 

We find overwhelming statistical evidence against the age-invariance hypothesis. Moreover, the departures from age invariance fit the alternative view and involve large effects on the distribution of employment growth across MSA-industry cells in periods with large housing price movements. In a dynamic extension, we also find that the positive effect of local house price changes on local industry growth rates is both larger and more persistent in MSA-industry cells with a larger share of young firm activity. These results do not mean that consumption demand effects are unimportant. Rather, they imply that consumption demand is not the only important channel through which housing market ups and downs affect local and national economies.

Labour market consequences

Previous research offers ample grounds for hypothesising that the fortunes of young firms have important and uneven effects in the labour market. Young firms account for a disproportionate share of newly created job positions (Davis and Haltiwanger 1992, 1999), which makes them highly active in the search, matching and hiring process. Ouimet and Zarutskie (2014) show that young firms disproportionately employ young workers. They point to several reasons: skill-demand differences between young and mature firms, positive assortative matching, and a higher propensity for young firms and young workers to engage in search and matching. Haltiwanger et al. (2018a, 2018b) show that young firms facilitate movements up the job ladder by younger and less-educated workers. Young firms are important for these workers as initial labour market entry ports and as re-entry ports when they get knocked off the job ladder in contractions.

Motivated by these earlier works, we investigate the relationship between young-firm activity and employment outcomes by worker age, education, and gender. To this end, we use data from the Quarterly Workforce Indicators (QWI), which lets us investigate how young-firm activity shares vary with employment outcomes by gender, age, and education in MSA and MSA-industry level data for more than 30 states from 1999 to 2015. 

We first confirm Ouimet and Zarutkskie’s finding that young firms disproportionately hire younger workers. We further show that they disproportionately hire less-educated workers. These employment patterns leave younger and less-educated workers more exposed to the cyclical fortunes of young firms. Indeed, we find that changes in local young firm activity disproportionately load onto the employment of younger and less-educated workers for both men and women. As a result, the fortunes of young firms have an outsized impact on younger and less-educated workers. Thus, the housing bust and financial crisis hurt younger and less-educated workers through their particular effects on the fortunes of young firms in addition to their broader effects on the overall level of economic activity. 

Concluding remarks

Young firms live a financially precarious life, often dependent on self-funding tied to the value of business owners’ homes. This dynamic played out with great force during the US housing bust that commenced in 2006. As our evidence shows, the effects of housing markets on young firms and local economies work partly through investment channels in addition to the consumption demand channels.


Davis, S J and J Haltiwanger (1992), “Gross job creation, gross job destruction, and employment reallocation,” Quarterly Journal of Economics 107(3): 819–863.

Davis, S J and J Haltiwanger (1999), “Gross job flows,” in O Ashenfelter and D Card (eds), Handbook of Labor Economics 3, Elsevier Science. 

Davis, S J and J Haltiwanger (2019), “Dynamism diminished: The role of housing markets and credit conditions,” NBER, Working paper no 25466.

Greenstone, M, A Mas and H-L Nguyen (2015), “Do credit market shocks affect the real economy? Quasi-experimental evidence from the Great Recession and ‘normal’ times,” working paper.

Haltiwanger, J, H Hyatt, L Kahn and E McEntarfer (2018a), “Cyclical job ladders by firm size and firm wage,” American Economic Journal: Macroeconomics 10(2): 52–85. 

Haltiwanger, J, H Hyatt and E McEntarfer (2018b), “Who moves up the job ladder?”  Journal of Labor Economics 36(S1): 301–336.

Mian, A and A Sufi (2011), “House prices, home equity-based borrowing, and the US household leverage crisis,” American Economic Review 101: 2132–2156.

Mian, A and A Sufi (2014), “What explains the 2007-2009 drop in employment?” Econometrica 82(6): 2197–2333.

Ouimet, P and R Zarutskie (2014), “Who works for startups? The relation between firm age, employer age, and growth,” Journal of Financial Economics 112(3): 386–407.

Saiz, A (2010), “The geographic determinants of housing supply elasticity,” Quarterly Journal of Economics 125(3): 1253–1296.

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