«Manuel Adelino, Duke University Antoinette Schoar, MIT and NBER Felipe Severino, MIT December, 2012 Abstract This paper explores the role of the ...»
House Prices, Collateral and Self-Employment 1
Manuel Adelino, Duke University
Antoinette Schoar, MIT and NBER
Felipe Severino, MIT
This paper explores the role of the collateral lending channel to facilitate small business
starts and self-employment in the period before the financial crisis of 2008. We document
that between 2002 and 2007 areas with a bigger run up in house prices experienced a strong
increase in employment in small businesses compared to employment in large firms in the same industries. This increase in small business employment was particularly pronounced in industries that need little startup capital and can thus more easily be financed out of increases in housing as collateral. Our results highlight the importance of the collateral lending channel during the period of the house price boom in the creation of small establishments. We show that this effect is separate from the aggregate demand channel that relies on home equity based borrowing leading to increased demand and employment creation.
We thank seminar participants at Duke, MIT, UNC and Stanford for thoughtful comments. Preliminary and 1 incomplete. Please do not cite without authors’ permission.
1. Introduction The recession that followed the financial crisis of 2008 was marked by high and very persistent unemployment rates, which has drawn renewed interest to understanding the forces that affect labor market dynamics over the business cycle. The ensuing debate has focused on two primary explanations for the persistent unemployment. On the one side are researchers who argue that the recession was propagated by a dramatic decline in consumer demand, which was exacerbated by significant deleveraging at the household level and resulted in increased firm closures and unemployment. 2 See, for example, Romer (2011) or Mian and Sufi (2011a).
On the other side are proponents of the idea that structural mismatches in the skill composition of parts of the work force explain the persistent unemployment, see for example Kocherlakota (2010).
Similarly, Charles, Hurst and Notowidigdo (2012) argue that these structural problems in the labor market were already present pre-2008, but were masked by the increase in house prices and the ensuing rise in labor demand in the construction industry. Others, most prominently Mulligan (2011), put forward that structural factors in labor market institutions, such as counter cyclical unemployment insurance, reduce the incentives of unemployed workers to reenter the labor market.
Our paper documents an alternative channel that significantly affects the dynamics of employment creation over the business cycle: The impact of the collateral lending channel, especially mortgage lending, on self-employment and small business starts. Going back at least to the seminal papers by Bernanke and Gertler (1989) or Kiyotaki and Moore (1997) a number of theories have suggested that improvements in collateral values ease credit constraints for borrowers and can have multiplier effects on economic growth. This collateral lending channel builds on the idea that information asymmetries between banks and firms can be more easily alleviated when collateral values are high and therefore firms can have higher leverage. However, empirically it has been difficult to cleanly identify the causal direction of the collateral effect. The challenge is that increased collateral values facilitate lending but at the same time improvements in economic conditions also increase collateral values. A number of early papers tested for differential responses in the growth rate of small versus large firms across the business cycle, see for example Gertler and Gilchrist (1994) or Kashyap, Stein On average, households reduced their debt to income ratios by more than 20% following the house 2 price bust.
1 and Wilcox (1993). The idea is that small firms which are more opaque should be more dependent on the collateral than larger ones. However, as Kashyap and Stein (1994) point out, these tests are plagued by a confounding effect that even the demand for small business might be more sensitive to the business cycle. There is also a large micro literature that credit constraints at the household level matter for the creation of new businesses (Evans and Jovanovic, 1989, Holtz-Eakin et al, 1994, Gentry and Hubbard, 2004, or Cagetti and De Nardi, 2006), although some authors have argued that this relationship is only present at the very top of the wealth distribution (Hurst and Lusardi, 2004).
At the same time, housing wealth in particular has been shown to be an important factor in the funding of business startups (Fan and White, 2003, Fairlie and Krashinsky, 2012 and Black, de Meza and Jeffreys, 1996 for the UK). Previous work has also found that bank credit is an important source of financing for small businesses (Petersen and Rajan, 1994; Robb and Robinson, 2012), and that entrepreneurs often have to provide personal guarantees when they obtain financing (Berger and Udell, 1998).
In this paper we take a different approach and look directly at shocks to the value of collateral. We document that leading up to the recession of 2008, areas with rising house prices (and increased leverage) experienced a significantly bigger increase in small business starts and a rise in the number of people who are employed in establishments with fewer than 10 employees compared to areas that did not see an increase in house prices. The same increase in employment cannot be found for large establishments in these same areas. In fact, we find that the effect of house prices monotonically decreases with the size of the firms. This asymmetry supports the idea that the collateral lending channel is an important driver of employment creation in small firms, since larger firms with more than 50 employees have access to other forms of financing and thus should not be affected by this type of collateral channel.
The dichotomy in the job creation in small versus large firms also helps us rule out that job creation in small firms is driven solely by increased demand generated by home equity borrowing. A number prior papers have shown that variations in house prices are linked to increased consumption (Iacovello, 2005; Campbell and Cocco, 2007) and this could plausibly lead to better investment opportunities for entrepreneurs, in particular in non-tradable industries. This would translate into a positive relationship from house prices to small business creation, but the mechanism driving this relationship would not be through the collateral channel. Previous studies linking house prices to small business creation do not address this important distinction.
2 In fact, increasing house prices did not increase overall employment but instead shifted employment 3 towards smaller establishments. Additionally, our results are not driven by the construction industry or the non-tradable sector and they hold when we restrict our sample to manufacturing industries, those that are least likely to depend on local demand. This distinguishes the collateral lending channel that we identify from the work of Mian and Sufi (2011a) who show that areas where house prices increased most also exhibited an increase in unemployment in non-tradable industries due to deleveraging in the aftermath of 2008.
In order to identify the causal effect of house prices on the creation of small establishments we instrument for the growth in house prices between 2002 and 2007 using exogenous geographical and regulatory constraints to housing supply developed by Saiz (2010). The measure therefore differentiates areas where an increase in housing demand either translates into higher house prices and more collateral (low elasticity areas) or into higher volume of houses built (high elasticity). By relying on exogenous restrictions on the expansion of housing volumes, we separate out the effect of high collateral values on the creation of small businesses. This approach is similar to the study by Chaney, Sraer and Thesmar (2012), which looks at corporate investment decisions or Mian and Sufi (2011b) who look at increases in consumption from household leverage. But it is important to note that a drawback of using housing and zoning restrictions for obtaining identification is that it relies on cross sectional differences between high and low elasticity areas, which means that these areas could also vary along other dimensions, such as the level of urbanization or economic vitality. For example, areas with low elasticity might not only see high house price increases when demand picks up, i.e. more available collateral, but they might also be the ones where more investment opportunities become available.
Therefore, to further narrow in on the importance of the collateral lending channel, we look at the cross-sectional variation across industries in the start-up capital that is needed to set up a new firm.
The idea is that there are differences in the minimal feasible scale of businesses across industries and thus the availability of collateral should matter differently depending on that minimal scale. For example, some businesses like home healthcare services can be started with small amounts of capital that could reasonably be financed through house price appreciation. In contrast, most manufacturing firms, for example, require larger amounts of capital and fixed investments where the housing channel should not be as effective since the capital needs are too high to be financed via A similar relationship exists when we include proprietorships and unincorporated businesses in the regressions.
Our results follow exactly the predicted pattern: when we repeat our regressions disaggregated by industries above and below the median needs in terms of start-up capital we find that the effect of house price growth on the creation of employment in small establishments is especially strong among industries with lower capital needs. These results confirm that the collateral lending channel played an important role in shaping employment dynamics. Borrowing against their housing wealth allowed people in the areas with quicker house price appreciation to start small businesses and potentially alleviate the impact of job losses in the period leading up to 2008.
In addition we confirm that the results in our study are not driven by the non-tradable or the construction sectors. If the relationship between house price increases and job creation in small firms was purely constrained to the non-tradable or construction sectors, one could worry that the results are not driven by changes in the collateral lending channel but by unobserved differences in local demand. However, we show that our results are also hold for the manufacturing sector where products are easily tradable. Since for these firms local demand is not driving output, but they could locate anywhere, any change in output in the low elasticity areas must therefore be driven by changes on the input (or production) side. This is the collateral lending channel.
The rest of the paper proceeds as follows: Section 2 describes the data used in the paper, as well as the empirical methodology. Section 3 discusses the results and Section 4 concludes.
2. Data and Empirical Methodology
We obtain employment growth from the County Business Patterns (CBP) data set published by the U.S. Census Bureau. The CBP contains employment data by county, industry and establishment size (measured in number of employees) between 1998 until 2010 as of March of the reported year. We use the data at the 4-digit National American Industry Classification System (NAICS) level, broken down by county and establishment size to construct our main dependent variable of interest, the 4 employment growth by establishment size between 2002 and 2007. The breakdown of establishments by the number of employees allows us to differentially estimate the effect of house price growth in the net creation of establishments of different sizes. 4 We use five establishment categories in our regressions that are commonly used by the Census Bureau – establishments of 1 to 4 employees, 5 to 9 employees, 10 to 19 employees, 20 to 49 and more than 50 employees. All these categories are given by the CPB except for the last one, where we aggregate all establishments of more than 50 employees. The CBP has multiple categories above 50 employees, but using each one individually would only add noise to our estimation, as they become rare at the county level, and even more so at the county and industry level, which we need for some of the specifications discussed below. In order to create the category of establishments with more than 50 employees we take the number of establishments in each category above 50 and multiply those by the midpoint of the category (for example, for the category of 100 to 249 employees we multiply the number of establishments by 174.5), and then we add all of them up.
The house prices used in the regressions come from the Federal Housing Finance Agency (FHFA) House Price Index (HPI) data at a Metropolitan Statistical Area (MSA) level. The FHFA house price index is a weighted, repeat-sales index and it measures average price changes in repeat sales or refinancings on the same properties. This information is obtained by reviewing repeat mortgage transactions on single-family properties whose mortgages have been purchased or securitized by Fannie Mae or Freddie Mac since January 1975. We use data on the MSA-level index between 2002 and 2007.
The use of MSA level house prices is consistent with our identification strategy. In order to identify the casual effect of house prices on small business creation we instrument house price growth between 2002 and 2007 with the measure of housing supply elasticity of Saiz (2010), which varies at the MSA level. The measure of the supply elasticity is constructed using geographical and local regulatory constraints to new construction. Areas where it is difficult to add new housing (due to geographic or regulatory restrictions) are classified as low elasticity and vice versa for areas where land is easily available. Low elasticity areas correlate strongly with steeper house price growth in the The data only includes the number of establishments in each county, industry and year by category of employment size 4 (1-4 employees, 5-9, 10-19, etc.), not the total employment for each establishment category. As such, in order to construct the employment in each bin we multiply the number of establishments by the middle point of each category.