The Capital Structure Decisions of New Firms

Understanding how capital markets affect the growth and survival of newly created firms is perhaps the central question of entrepreneurial finance. Yet, much of what we know about entrepreneurial finance comes from firms that are already established, have already received venture capital funding, or are on the verge of going public—the dearth of data on very-early-stage firms makes it difficult for researchers to look further back in firms’ life histories. Even data sets that are oriented toward small businesses do not allow us to measure systematically the decisions that firms make at their founding. This article uses a novel data set, the Kauffman Firm Survey (KFS), to study the behavior and decision-making of newly founded firms. As such, it provides a first-time glimpse into the capital structure decisions of nascent firms.

In our paper, The Capital Structure Decisions of New Firms, forthcoming in the Review of Financial Studies, we use the confidential, restricted-access version of the KFS, which tracks nearly 5,000 firms from their birth in 2004 through their early years of operation. Because the survey identifies firms at their founding and follows the cohort over time, recording growth, death, and any later funding events, it provides a rich picture of firms’ early fund-raising decisions.

Rather than attempt to test specific theories of capital structure, our main goal is a more modest, descriptive one. We aim to examine the financing outcomes that entrepreneurs experience when they launch firms, explore the patterns that emerge from the data, and draw conclusions from these patterns that are useful to both theory and policy. In the paper, we offer an analytical framework for thinking about entrepreneurial financing decisions. This allows us to develop a classification scheme that distinguishes funding sources both in terms of their security type (debt vs. equity) as well as their source (personal accounts of the business owner(s) vs. friends and family vs. arm’s-length formal financial channels). This two-way classification scheme in turn allows us to separate the issue of risk-bearing from that of liquidity provision. For example, if an entrepreneur uses a home equity line of credit from a bank to finance a startup, the entrepreneur is bearing the risk of failure through a levered equity stake in the business, but the bank is providing liquidity to the business through a debt instrument to the entrepreneur. Because many startups are sole proprietorships, and many that are not are financed with personal guarantees and personal wealth as collateral, distinguishing risk-bearing from liquidity provision is important for understanding how startups are financed. The distinction between risk-bearing and liquidity provision is a direct consequence of the bank’s ability to contractually sidestep limited liability through the use of personal assets as collateral or guarantees.

Our central finding is that newly-founded firms rely heavily on formal debt financing: owner-backed bank loans, business bank loans, and business credit lines. Funding from formal debt dwarfs funding from friends and family. The average amount of bank financing is seven times greater than the average amount of insider-financed debt; three times as many firms rely on outside debt as they do inside debt. Even among firms that rely on inside debt, the average amount of outside debt is nearly twice that of inside debt.

Again, it is important to highlight the distinction between liquidity provision and risk-bearing. The fact that formal credit channels provide about 40% of a firm’s initial startup capital implies in many cases that the entrepreneur effectively holds a highly levered equity claim on their business, because their own personal assets stand as collateral or guarantees for the bank financing.

The reliance on formal credit channels over personal credit cards and informal lending holds true even for the smallest firms at the earliest stages of founding. The average pre-revenue firm in our sample has twice as much capital from bank loans as from insider sources. And, when we look at only those firms that access outside equity sources, such as venture capital or angel financing, we still see a heavy reliance on debt; the average firm that accesses external private equity markets still has around 25% of its capital structure in the form of outside debt.

We also examine trade credit as a potential source of capital, since it may be especially important in scenarios in which trade creditors possess information (or stand to forge relationships through supply channels) that banks might not be able to obtain (Peterson and Rajan 1997). Although our data show that trade credit is undoubtedly important, the average firm uses less than half as much trade credit as it does outside debt, and almost twice as many firms rely on outside debt as they do on trade credit. In fact, if trade credit were counted as a source of financial capital (instead of operating capital), it would rank third, behind outside debt and owner equity, but ahead of outside equity and inside debt or equity.

Of course, these statements only speak to the equilibrium amount of borrowing from inside and outside sources; the quantities are determined by both the supply and the demand of different types of capital. Indeed, to couch startup decisions as choices suggests that entrepreneurs can freely choose between alternative capital providers: the pronounced information asymmetries that characterize startup firms’ search for capital may in fact imply that startups simply seek capital where it is most plentiful. Evidence from Cosh, Cumming, and Hughes (2009) suggests that this indeed may be the case. They find that rejection rates are lower in credit markets than from other sources of capital, which suggests that the variation in financing decisions owes to supply considerations as well as demand considerations. Ultimately, it is challenging to separate supply and demand in the absence of some quasi-experiment. We nevertheless take some small steps in this direction.

To control for the fact that differences in firm quality or creditworthiness may be driving the patterns we see in the data, we identify plausibly exogenous variation in access to capital by using housing price elasticity data calculated by Saiz (2010). Using sophisticated GIS techniques to measure geographical constraints on local land supply, as well as factors that account for endogenous restrictions on land use through zoning, he estimates price elasticities of the housing stock at the MSA level. These estimates partially allow us to capture the effect of the housing boom on access to capital, by taking advantage of the fact that high-elasticity areas saw housing inventories increase as the housing bubble expanded, whereas low-elasticity areas saw home prices increase instead. In areas with high elasticity of supply, homes provide better loan collateral, because the underlying home equity is less sensitive to local pricing conditions.

Indeed, we find that entrepreneurs in areas with high supply elasticity were more reliant on bank loans as a source of capital. Because our data do not map the entrepreneurs’ actual home prices onto bank financing choices, we must remain cautious; nevertheless, we find evidence that high price stability acts as a catalyst for bank loans.

This of course raises the concern that credit conditions at the time of our survey were so unique that they do not necessarily reflect broader patterns from other time periods. Although ultimately we are limited to the data that are available, we speak to this possibility by considering the correlation between capital structure decisions and outcome variables like employment, size, and profitability growth. We find that having a capital structure that is more heavily tilted toward formal credit channels results in a greater likelihood of success. This fact holds even when we include the credit score as a measure of firm quality to guard against the possibility that unobserved factors drive both success and credit access. Our findings indicate that, even if credit conditions in 2004 were unique, credit market access had an important impact on firm success.

This article is related to a number of articles in the banking, capital structure, and entrepreneurship literature. Given the emphasis in the current work on the role of formal banking channels and trade credit, our article is also related to the literature on the role of banks and other sources of financing for small firms (see, e.g., Peterson and Rajan 1994, 1997, 2000, or Berger and Udell 1998). Cosh, Cumming, and Hughes (2009) find a similarly important role for bank capital using British data.

Our findings speak to a debate in the literature surrounding the role of financing constraints as impediments to startup activity. It is widely observed that the wealthy are more likely to be entrepreneurs (Gentry and Hubbard 2004), which has led many to conclude that financing constraints are important impediments to business startup activity. On the other hand, Hurst and Lusardi (2004) and Nanda (2011) show that the relation between wealth and entrepreneurship is flat throughout most of the wealth distribution, suggesting that financing constraints are less important. Our evidence indicates that indeed formal credit channels are important for startups, which in turn suggests that credit markets alleviate many financing constraints for startups. Yet, at the same time, we see pronounced differences in the overall size of startup businesses based on measures of access to credit.

The full paper is available for download here.