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2009 | OriginalPaper | Buchkapitel

3. Does Distance Matter in Banking?

verfasst von : Kenneth P. Brevoort, John D. Wolken

Erschienen in: The Changing Geography of Banking and Finance

Verlag: Springer US

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Abstract

Deregulation and technological change have reduced the transaction costs that led to the dominance of local financial service suppliers, leading some to question whether distance still matters in banking. This debate has been particularly acute in small business banking, where transactions costs are believed to be particularly high. This paper provides a detailed review of the literature on distance in banking markets, highlighting the reasons why geographic proximity is believed to be important and examining the changes that may have affected its importance. Relying on new data from the 2003 Survey of Small Business Finances, we examine how distances between small firms and their financial service suppliers changed over the 1993–2003 decade. Our analysis reveals that distances increased, though the extent varied substantially across financial services and supplier types. Generally, increases were observed in the early half of the decade, while distances declined in the following 5 years. There was also a trend toward less in person interaction between small firms and their suppliers of financial services. Nevertheless, most relationships remained local, with a median distance of 5 miles in 2003. The results suggest that distance, while perhaps not as tyrannical as in the past, remains an important factor in banking.

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Vorheriges Kapitel Financial Innovation, Organizations, and Small Business Lending

Nächstes Kapitel Distance, Bank Organizational Structure, and Lending Decisions

Several published studies have established the reliance of households and small businesses on local suppliers of financial services. For example, see Kwast et al. (1997), Amel and Starr-McCluer (2002), Amel and Brevoort (2005).

We suspect that the same evolutionary process is playing out for similar reasons across the developed world and that consequently our results for US markets will be more broadly applicable. One advantage of using US data is that our analysis can focus specifically on the issue of distance, without worrying about the effect of international borders. The distinction between the related concept of distance and borders is made by Degryse and Ongena (2004).

A detailed discussion of the importance of soft information in small business lending is provided by Berger and Udell (2002).

Even though local banks may have an advantage in information production, it is possible that distant lenders could be competitive with local lenders if their cost of funds was sufficiently lower than the cost of funds for the local lenders. Such a situation is possible if the nonlocal institution is very large. Dell’Ariccia and Marquez (2004) provide such a theoretical model.

The notable exception to this may be residential mortgages, which tend to be larger than other types of consumer loans. In evaluating mortgage applications, lenders often expend effort to document income levels and secure other information about the borrower or the property.

Refer to Mester (1997) and Cowan and Cowan (2006).

Kallberg and Udell (2003) discuss the small business credit information collected by Dun and Bradstreet. They find that the information contained in these models provides significant additional predictive power above that provided by the other credit information available to lenders.

The services accessible through ATMs are generally related to deposit-account-related activities (e.g., cash withdrawals or deposits) and do not include credit-related activities like loan application processing or underwriting.

For a discussion of the use of credit scoring in the solicitation of credit, see Board of Governors of the Federal Reserve System (2006).

Consequently, the Federal Reserve Board’s conclusion was based primarily on public comments, as opposed to published empirical studies or original research.

For example, both Dick (2008) and Adams et al. (2007) estimate discrete choice models of consumer choice of depository institutions where the utility an individual receives from each alternative institution is a function of the branch density of the institution in that market. While higher branch densities should be correlated with distances, these studies ignore the location of individual branches relative to individual depositors.

The distance data reported in the SCF is truncated from above at 50 miles. Consequently, mean distances are not available. The distance referred to is the distance to the office or branch used most frequently. In many instances, this is the office where the loan payment is sent and not where the firm or consumer applied for the loan.

By product, distances remained the same for checking accounts, savings accounts, money market accounts, and certificates of deposit. Median distances increased, however, for IRA/Keogh, brokerage, and trust accounts.

Similar increases were observed for mortgages, vehicle loans, and “other” loans. The median distances for lines of credit only increased slightly from 3 to 4 miles.

As a robustness check, Petersen and Rajan (2002) also incorporated data from the 1987 SSBF. Rather than examining how distances changed across the two time periods, the authors created a synthetic panel from the 1987 observations as well, using those relationships that began between 1973 and 1987.

The Community Reinvestment Act data provide information on the geographic distribution of small commercial loans made by depository institutions in each calendar year. The data supply the number and dollar volume of loans made by each bank in each census tract to which it extended credit. For each bank, the data are aggregated at the census tract level, so no detail is available about the characteristics of the loans or the borrowers. For more detail on the CRA data, see Bostic and Canner (1998).

For a description of the SBA’s 7(a) Loan Program, see United States Government Accountability Office (2007).

This credit scoring survey also served as the basis for the papers by Frame et al. (2001, 2004) and Berger et al. (2005).

The importance of distance and its effect on policy (e.g. market definition of banking services) may be different if the incidence of distance changes is concentrated in certain portions of the distribution or among certain groups of customers, products, or institutions.

During the 1993, 1998, and 2003 surveys, respondents were asked the following: “Think of the office of branch of (NAME) that the firm used most frequently. (i) Approximately how many miles from the main office of the firm is this office or branch of (NAME)? (ii) What was the most frequent method of conducting business with this office of branch?” For additional details, see the questionnaire or codebook for the surveys at Board of Governors of the Federal Reserve (2008).

All data presented are weighted to provide estimates of population parameters. The samples drawn in each of the 3 survey years are stratified (by size, region, and urban/rural status) nonproportional random samples. The weights adjust for unequal selection probabilities and response rates.

Other nondepository sources, including credit card and check processors, governments, individuals, and otherwise unclassified sources are not included in the tables. Information about the location and method of conducting business with these types of suppliers was not collected in the 1993 survey. These sources account for about 10 percent of all sources used in each of the survey years.

Estimates of the statistical significance of differences of means and proportions between 1993 and 2003, and between 1998 and 2003 are reported in the 1993 and 1998 columns, respectively. These calculations are adjusted for sampling weights and sampling strata, using survey statistical techniques available in STATA.

While the use of 30 miles to denote local suppliers is somewhat arbitrary, using alternative definitions (e.g., 15, 20, 25, or 35 miles) would not change the qualitative results.

In 1993 and 1998, firms were asked about credit card processing as part of the question on transactions services. In 2003, the question on credit card processing was split from the question on transactions services and the new question on credit card processing was expanded to include pin- and signature-based debit card processing. The question changes may have led to more institutions being identified in 2003. However, we expect that institutions that provide credit card processing also provide debit card processing, which should mitigate any overstatement. For additional information, see Mach and Wolken (2006).

The inclusion of credit card processing as a separate service in the 2003 survey, which has a relatively high median distance of 17 miles, may have been responsible for some of the observed increase in median distance among financial management services between 1998 and 2003.

The distance measures for nondepository institutions that provide asset services may be noisy due to the fact that relatively few firms obtain checking and savings accounts from these institutions.

The change in the incidence of in person interaction for relationships involving loans between 1993 and 1998 was not significant at the 10 percent level.

For each of the six loan types, none of the changes in incidence between 1993 and 1998 was statistically significant at the 5 percent level. Only equipment loans had a statistically significant change over this 5-year period at the 10 percent level (data not shown in tables).

Some evidence that such differences may be important is available from the SSBF. In the 2003 survey, firms that applied for loans within the last 3 years were asked to report on how they applied and whether they at some point had to go in person to obtain the loan. Roughly 78 percent of loan applicants went in person at some point in the application process. In contrast, as documented in this chapter, on average in 2003, 44 percent of firms with lending relationships conducted business in person. Likewise, the average and median distances for loan applications were 77 and 5 miles, respectively. For outstanding loans, the average and median distances were 181 and 11 miles. We speculate that the difference is in part because once the loan is approved, many businesses need only make loan payments, and the loan payment office may differ from the loan application office.

There are two notable exceptions to this. The first is the work of Alessandrini et al. (2005), who distinguish between two different types of distance: operative distance, which is the physical distance between the bank and its customers, and functional distance, which is the distance between the bank’s decision-making center and the local community of the borrower. This latter type of distance is not limited to measures of geographic distance but may include economic or cultural differences. The second exception is a related work by Alessandrini et al. (2009: Chapter 5, in this volume) who find that both of these measures of distance are important predictors of several different measures of credit rationing to small businesses.

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Titel: Does Distance Matter in Banking?
verfasst von: Kenneth P. Brevoort
John D. Wolken
Verlag: Springer US
Buch: The Changing Geography of Banking and Finance
Print ISBN: 978-0-387-98077-5

Electronic ISBN: 978-0-387-98078-2

Copyright-Jahr: 2009
DOI: https://doi.org/10.1007/978-0-387-98078-2_3