Trade Credit: Theories and Evidence

In addition to borrowing from financial institutions, firms may be financed by their suppliers. Although there are many theories explaining why non-financial firms lend money, there are few comprehensive empirical tests of these theories. This paper attempts to fill the gap. We focus on a sample of small firms whose access to capital markets may be limited. We find evidence that firms use trade credit relatively more when credit from financial institutions is not available. Thus while short term trade credit may be routinely used to minimize transactions costs, medium term borrowing against trade credit is a form of financing of last resort. Suppliers lend to firms no one else lends to because they may have a comparative advantage in getting information about buyers cheaply, they have a better ability to liquidate goods, and they have a greater implicit equity stake in the firm's long term survival. We find some evidence consistent with the use of trade credit as a means of price discrimination. Finally, we find that firms with better access to credit from financial institutions offer more trade credit. This suggests that firms may intermediate between institutional creditors and other firms who have limited access to financial institutions.

Does Distance Still Matter? The Information Revolution in Small Business Lending

The distance between small firms and their lenders in the United States is increasing. Not only are firms choosing more distant lenders, they are also communicating with them in more impersonal ways. After documenting these systematic changes, we demonstrate that they do not stem from small firms locating differently, from simple consolidation in the banking industry, or from biases in the sample. Instead, they seem correlated with improvements in bank productivity. We conjecture that greater, and more timely, availability of borrower credit records, as well as the greater ease of processing these may explain the increased lending at a distance. Consistent with such an explanation, distant firms no longer have to be observably the highest quality credits, suggesting that a wider cross-section of firms can now obtain funding from a particular lender. These findings, we believe, are direct evidence that there has been substantial development of the financial sector in the United States, even in areas such as small business lending that have not been directly influenced by the growth in public markets. From a policy perspective, that small firms now obtain wider access to financing suggests the consolidation of banking services may not raise as strong anti-trust concerns as in the past.

The Effect of Credit Market Competition on Lending Relationships

This paper provides a simple model showing that the extent of competition in credit markets is important in determining the value of lending relationships. Creditors are more likely to finance credit constrained firms when credit markets are concentrated because it is easier for these creditors to internalize the benefits of assisting the firms. The model has implications about the availability and the price of credit as firms age in different markets. The paper offers evidence for these implications from small business data. It concludes with conjectures on the costs and benefits of liberalizing financial markets, as well as the timing of such reforms.

Estimating standard errors in finance panel data sets: Comparing approaches

In both corporate finance and asset pricing empirical work, researchers are often confronted with panel data. In these data sets the residuals may be correlated across firms and across time, and OLS standard errors can be biased. Historically, the two literatures have used different solutions to this problem. Corporate finance has relied on Rogers standard errors, while asset pricing has used the Fama-MacBeth procedure to estimate standard errors. This paper will examine the different methods used in the literature and explain when the different methods yield the same (and correct) standard errors and when they diverge. The intent is to provide intuition as to why the different approaches sometimes give different answers and thus give researchers guidance for their use

Estimating Standard Errors in Finance Panel Data Sets: Comparing Approaches

In both corporate finance and asset pricing empirical work, researchers are often confronted with panel data. In these data sets, the residuals may be correlated across firms and across time, and OLS standard errors can be biased. Historically, the two literatures have used different solutions to this problem. Corporate finance has relied on Rogers standard errors, while asset pricing has used the Fama-MacBeth procedure to estimate standard errors. This paper will examine the different methods used in the literature and explain when the different methods yield the same (and correct) standard errors and when they diverge. The intent is to provide intuition as to why the different approaches sometimes give different answers and give researchers guidance for their use.

Does the source of capital affect capital structure?

Prior work on leverage implicitly assumes capital availability depends solely on firm characteristics. However, market frictions that make capital structure relevant may be associated with a firm's source of capital. Examining this intuition, we find firms which have access to the public bond markets, as measured by having a debt rating, have significantly more leverage. Although firms with a rating are fundamentally different, these differences do not explain our findings. Even after controlling for firm characteristics which determine observed capital structure, and instrumenting for the possible endogeneity of having a rating, firms with access have 35 percent more debt

Estimating standard errors in finance panel data sets: comparing approaches.

Abstract In both corporate finance and asset pricing empirical work, researchers are often confronted with panel data. In these data sets, the residuals may be correlated across firms and across time, and OLS standard errors can be biased. Historically, the two literatures have used different solutions to this problem. Corporate finance has relied on clustered standard errors, while asset pricing has used the Fama-MacBeth procedure to estimate standard errors. This paper examines the different methods used in the literature and explains when the different methods yield the same (and correct) standard errors and when they diverge. The intent is to provide intuition as to why the different approaches sometimes give different answers and give researchers guidance for their use

Does Function Follow Organizational Form? Evidence From the Lending Practices of Large and Small Banks

Theories based on incomplete contracting suggest that small organizations may do better than large organizations in activities that require the processing of soft information. We explore this idea in the context of bank lending to small firms, an activity that is typically thought of as relying heavily on soft information. We find that large banks are less willing than small banks to lend to informationally 'difficult' credits, such as firms that do not keep formal financial records. Moreover, controlling for the endogeneity of bank-firm matching, large banks lend at a greater distance, interact more impersonally with their borrowers, have shorter and less exclusive relationships, and do not alleviate credit constraints as effectively. All of this is consistent with small banks being better able to collect and act on soft information than large banks.