Results

When running the regressions, the 2003 data is not adjusted for multiple imputation

procedures, but each of the five imputations from the 2003 data is treated separately because multiple imputations for the 1987 and 1993 SSBF data are not available. Each imputation of 2003 is

separately pooled with the 1987 and 1993 SSBF data and five different datasets are obtained. The only difference among these five datasets is the different imputations for the 2003 SSBF data. The regression results obtained are very similar among these five datasets since the imputations from 2003 are similar. Hence, results from only one dataset are displayed in this study. The results obtained from the dataset with imputation 3 of the 2003 SSBF are reported because this dataset provides significances that are consistent in the other four dataset results. However, results from the other four datasets are available upon request.

For Tables 2.3 and 2.4, the data is obtained by pooling the 1987, 1993, and 2003 SSBF data.

Table 2.3 reports the results from the first model, running the survey linear regression of interest rate premiums on relationship variables and Table 2.4 provides the average marginal effects from the

second model, running the survey logit regression of collateral and guarantor requirements on relationship variables.³³ Note that the survey regressions take into account the weight variables.

2.6.1 Results for the Interest Rate Premium Model

Table 2.3 supports the hypothesis that the importance of relationships in small business lending has weakened over time. The first notable result is that checking account was no longer statistically significant in explaining interest rate premium in 2003 even though it was significant before the mid-1990s. A firm that had a checking account with the LOC provider paid 29.584 basis points more for its interest rate premium before the mid-1990s. In the literature, a positive

relationship between contact terms and relationship variables tends to be explained by a lock-in problem.³⁴ Another explanation might be attributed to the competition in the market. It is possible that in a competitive market, the LOC provider might have initially offered lower rates to attract borrowers. Through time, a lender establishes a relationship with the borrower and locks the

customer into a relationship with that lender. After establishing this relationship, the lender learns the firm’s real risk level and adjusts the contract terms based on the real riskiness of the borrower.The interaction dummy between checking and the year 2003 is negative with a coefficient value of 45.708 basis points. This shows that there was a significant magnitude decline in the effect of checking account from before the mid-1990s to 2003. Also, when the t-test for the joint significance is performed, this study finds that there is no significance associated with the checking account variable in 2003. This implies that even though the checking account variable was significant in explaining interest rate premiums before the mid-1990s, it was no longer significant in 2003.

Second, the hypothesis can also be supported by looking at the non-relationship explanatory variables. Results in Table 2.3 show that some of the non-relationship variables gained significance in 2003 even though they were not significant before the mid-1990s. For instance, corporate

33 All the results are based on at least a 10 percent significance level. More details about specific significance levels can be obtained by referring to tables.

34There are conflicting results in the literature in regards to relationship between interest rates and duration of a relationship. Greenbaum et al. (1989), Rajan (1992), Sharpe (1990), and Von Thadden (1998) argue that as a bank observes proprietary information about a borrower over time, this creates a lock-in problem. The lender takes advantage of the borrower and the relationship, and the loan interest rate will increase as the duration of the relationship increases because it is costlier for the borrower to switch to another lender and transfer all the information that the lender has obtained.

On the other hand, there are some such as Boot and Thakor (1994) who argue that as the relationship gets longer, the informational asymmetries between the borrower and the lender are overcome and these efficiency gains are passed on to the borrower. The interest rates and collateral requirements will decrease as the duration of the

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organizational form is one of the variables that gained significance in 2003. Even though there was no statistical difference between corporations and proprietorships in the interest rate premiums they paid for their LOCs before the mid-1990s, corporations paid 52.899 basis points more for their LOCs in 2003. It is possible that due to the limited liability within the corporate organizational form, corporations are willing to invest in riskier projects compared to proprietorships. Hence, these firms end up paying higher interest rate premiums compared to proprietorships. The interaction dummy for corporate organizational form and year 2003 is positive with a coefficient value of 64.324, implying that there was statistically a significant magnitude increase over time in the effect of the corporate organizational form on interest rate premiums.

Profitability is another variable that gained significance in 2003. The interaction dummy for profitability and the year 2003 has a coefficient of -4.189 basis points and implies that the magnitude for profitability significantly increased over time. Based on the t-test for the joint significance, as the profitability ratio increased by 1 percent, the firm paid 2.723 basis points less for its interest rate premium in 2003.

Even though the accounts receivable collection period did not explain interest rate premiums before the mid-1990s, the t-test for the joint significance shows that accounts receivable collection period became significant in explaining interest rate premiums in 2003. For each additional day it took for the firm to collect its money, the firm ended up paying 0.265 basis points less for its interest rate premium in 2003. The sign for the coefficient value for the accounts receivable collection period variable is negative, contradicting the expectations of a positive coefficient value. It is most probable that there were some other risk factors that the study could not control for and might be affecting the variable, accounts receivable collection period. The interaction dummy for accounts receivable collection period and the year 2003 is also statistically significant and has a coefficient value of -0.288 basis points. This shows that there has been a significant magnitude increase in the coefficient for the variable, accounts receivable collection period.

Age was not statistically significant in explaining interest rate premiums before the mid-1990s but it was significant in 2003. The t-test for the joint significance shows that a firm that was 10 years old versus a firm that was 9 years old paid 2.764 basis points less for its interest rate premium in 2003.³⁵ The interaction dummy between age and the year 2003 also shows that there was a

significant magnitude increase in the effect of age in 2003. Additionally, before the mid-1990s, there were not significant differences between firms that were located in a metropolitan area versus a

35 (ln(1+10)-ln(1+9))*29.003 = 2.764

metropolitan area. However, the significance of the interaction dummy between metropolitan area and the year 2003 indicates that the magnitude of the coefficient for the metropolitan area variable increased significantly in 2003. Also, the t-test result for the joint significance shows that the

metropolitan area variable helped to explain interest rate premiums in 2003. In 2003, firms that were in a metropolitan area paid 55.147 basis points more for their interest rate premiums compared to firms in a non-metropolitan area. The higher premium may be due to the small business

characteristics; metropolitan areas might have riskier borrowers that are more aggressive in their investments. A second possible explanation is that the pricing structure is more expensive in metropolitan areas.

The Herfindahl index is another variable that gained significance in 2003. In 2003, a firm paid 34.902 basis points more if it was getting its loan from a market with a high Herfindahl index. It is possible that through consolidations the banking industry became more concentrated and banks took advantage of their customers and charged higher interest rate premiums. Organizational form, profitability, accounts receivable collection period, age, being in a metropolitan area, and the Herfindahl index are all used in hard-information based models. Hence, an implication of these variables gaining significance in 2003 is that hard-information is becoming more important over the years.

Another important variable to consider is the amount of sales for the firm. This is a common variable used by lenders in evaluating firms. There is an increased effect of the sales variable over the years. A firm that has $150,000 worth of sales paid 5.897 basis points less before the mid-1990s but 14.387 basis points less in 2003 compared to a firm with sales of $100,000.³⁶ A higher sales amount is most probably associated with a lower risk from the lender side and that is why the firm is charged a lower interest rate premium. The interaction dummy is also significant, implying that the increase in the magnitude of the coefficient value in 2003 is statistically significant.

Even though the variable, whether LOC is secured, was not significant and did not statistically explain interest rate premiums in either period, there was a significant magnitude increase in 2003 for this variable. The interaction dummy has a coefficient value of -46.932 basis points.

Third, there are some non-relationship explanatory variables that were significant before the mid-1990s but were no longer significant in 2003. For instance, before the mid-1990s, a firm that received its LOC from a non-depository financial institution or non-financial supplier paid 131.243

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basis points more for its interest rate premium compared to obtaining it from a depository financial organization. This result is consistent with the findings of Carey et al. (1998). Carey et al. (1998) find that non-depository financial institutions are as much of a relationship lender as depository financial institutions are, but they have riskier borrowers. The riskiness in borrowers is reflected in the higher interest rate premiums charged by these non-depository financial institutions. Additionally, as the firm’s LOC ratio increased by 1 percent, its interest rate premium declined by 0.065 basis points before the mid-1990s. The coefficient sign is negative unlike expectations but the coefficient magnitude is economically not very significant.

In summary, the checking account variable, which is a relationship variable, was no longer significant in explaining interest rate premiums in 2003. There is also a decline in the magnitude of the checking account variable in 2003. However, firm organizational form, profitability, age, firm’s accounts receivable collection period, metropolitan area, and the Herfindahl index became significant in explaining the interest rate premiums in 2003. The magnitudes for these variables, except the magnitude for Herfindahl index, also increased in 2003. The sales variable was significant in both periods and the magnitude of the coefficient for sales increased in 2003. Moreover, the magnitude of the coefficient for the variable, whether LOC is secured, increased in 2003. These results indicate that, over time, there is a declining effect for some of the relationship variables and an increasing effect for some of the non-relationship variables that are considered to be significant determinants for hard-information based models.

2.6.2 Results for the Collateral and Guarantor Requirements Model

When a survey logit is run on equation (2.1), coefficients for the log of the odds estimates for the explanatory variables, including the interaction terms, are obtained. Those results are reported in the form of average marginal effects. ³⁷ Since this study is interested in two time periods, average marginal effects for explanatory variables are calculated for the period before the mid-1990s and for 2003. To calculate the 2003 average marginal effects for the variables, the time interacted

explanatory variables are integrated into the calculations. Table 2.4 provides the average marginal effects from running the survey logit regression on collateral and guarantor requirements. A t-test is also applied to test whether the two periods’ marginal effects are significantly different from each other. The t-test results give information regarding whether there has been a significant magnitude

37 Average marginal effects are the sample average of the effects of partial or discrete changes in the explanatory variables.

change in the average marginal effects for the explanatory variables and these t-test results are also reported in Table 2.4. The results from Table 2.4 also support the hypothesis that the importance of borrower-lender relationships in small business lending has weakened over time.

Some of the relationship variables were no longer significant in explaining the collateral and guarantor requirements in 2003 even though they were significant before the mid-1990s. For

instance, the likelihood of securing the LOC before the mid-1990s was higher for firms that were at a farther distance. A firm that is 15 miles away versus 10 miles away from its lender was 1.386 percent more likely to be asked for collateral or guarantor requirements before the mid-1990s.³⁸ One possible explanation is that as the distance gets larger, there is more informational opacity and the lender is more likely to ask for collateral or guarantor to overcome the associated risk. The distance variable no longer explained collateral and guarantor requirements in 2003. Distance might no longer have been an issue because the firm riskiness could have been measured through SBCS, without the need to establish a close relationship with the firm.

Length of relationship was another variable that helped to explain collateral and guarantor requirements before the mid-1990s. However, this variable did not explain the collateral and guarantor requirements in 2003. Before the mid-1990s, a firm with 3 months compared to 2 months of relationship with its LOC provider was 1.151 percent less likely to have to secure its loans. ³⁹ The t-test for the difference between the two period marginal effects also shows that the magnitude of the marginal effects for the length of relationship decreased in 2003.

Before the mid-1990s, a firm that had a savings account with its LOC provider was 7.9 percent less likely to be asked to secure its LOC. This negative value may be due to the relationship between the lender and the borrower and the lender obtaining further valuable information about the firm. However, there was no effect of savings account on collateral and guarantor requirements in 2003. Savings account is an important relationship variable and it is important to note that savings account was no longer significant in 2003.

Another significant relationship variable is whether the firm has previous loans with the LOC provider. Before the mid-1990s, when the firm got previous loans from the lender, the firm was 14.4 percent more likely to be asked for collateral or guarantor requirements. This positive effect is generally explained in the literature by a lock-in problem created through the relationship between the firm and the lender. It might well be interpreted that with the new information gathered based on a previous loan relationship, the lender adjusts for the new loan contract terms that reflects the firm’s

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real risk level. The average marginal effect of a previous loan account on the probability of being asked for collateral or a guarantor requirement was not significant in 2003. It can be concluded that the relationship variables, distance, length of relationship, savings account, and previous loan account, lost significance in 2003.

The analysis of the non-relationship explanatory variables shows that there is a statistical increase in the significance levels in 2003 for some of the variables that are commonly used in hard-information based models. For instance, some of the industry variables were significant in explaining the collateral and guarantor requirements in 2003 even though they were not significant before the mid-1990s. If a firm was in the manufacturing, retail trade, or business services industries, it was 20.4 percent, 12.7 percent, and 11.9 percent less likely to be asked to provide collateral or guarantor requirements, respectively. For instance, firms in business services have less liquid assets to secure the loan. A possible reason for a lower probability of collateral and guarantor demand from these firms may be due to this fact. There were also significant increases in the magnitudes of the marginal effects for these industry variables in 2003.

Moreover, the leverage ratio gained statistical significance in 2003 even though it was not significant before the mid-1990s in explaining the collateral and guarantor requirements. For a 100 percent increase in the leverage ratio in 2003, a firm was 0.5 percent less likely to be asked for collateral or guarantor requirements but this value is not economically significant. A negative relationship may indicate that the lender perceives that the small business can afford to have more leverage and hence, the probability of the lender asking the firm to secure its LOC may be lower.

There might well be a positive relationship between leverage and collateral and guarantor

requirements if the firm exceeds a certain leverage level because after exceeding that limit, highly levered firms will be considered risky. The t-test between the two period marginal effects also shows that the magnitude for the leverage ratio increased in 2003 even though the value is not economically significant.

Corporate organizational form is another variable that gained significance in 2003. A firm that has a corporate organizational form has a marginal effect of 13.9 percent in 2003. A lender is more likely to ask a corporation to secure the loan so that the lender can have the equivalent of a personal commitment in the case of default. The leverage ratio, organizational form, and industry types are the variables that are commonly used for hard-information based models and hence it is important that these variables became statistically significant in 2003 whereas they were not before the mid-1990s.

The sales variable was significant both before the mid-1990s and in 2003. A firm with

$150,000 worth of sales was 1.581 percent more likely before the mid-1990s and 1.176 percent more likely in 2003 to secure its LOC compared to a firm with $100,000 worth of sales.⁴⁰ This result is consistent with the findings of Degryse and Cayseele (2000) who also find a positive relation between firm size and collateral requirement. One explanation is that a firm with higher sales is bigger in size and is more likely to have assets to secure the LOC and hence is more likely to be required to provide collateral and guarantor compared to a smaller firm that may not be able to afford to provide collateral or guarantors. However, it cannot really be said whether the magnitude effect of sales variable decreased over time since the t-test shows that the differences between the two period marginal effects are not statistically significant.

On the other hand, there are some non-relationship variables that were previously significant but lost significance in explaining the collateral and guarantor requirements in 2003. As the ratio for amount of LOC granted got higher by 100 percent, the likelihood of a firm securing the loan was 43.3 percent higher before the mid-1990s. Based on the t-test for the difference between the two period marginal effects, it is concluded that the magnitude effect of the amount of recent LOC granted declined in 2003. The variables, LOC provider, age of firm, and metropolitan area are the other variables that explained collateral and guarantor requirements before the mid-1990s but not in 2003. Before the mid-1990s, a firm that obtained its LOC from a non-depository or non-financial supplier was 23.6 percent less likely to secure its loan. A firm that was 10 years old versus 9 years

On the other hand, there are some non-relationship variables that were previously significant but lost significance in explaining the collateral and guarantor requirements in 2003. As the ratio for amount of LOC granted got higher by 100 percent, the likelihood of a firm securing the loan was 43.3 percent higher before the mid-1990s. Based on the t-test for the difference between the two period marginal effects, it is concluded that the magnitude effect of the amount of recent LOC granted declined in 2003. The variables, LOC provider, age of firm, and metropolitan area are the other variables that explained collateral and guarantor requirements before the mid-1990s but not in 2003. Before the mid-1990s, a firm that obtained its LOC from a non-depository or non-financial supplier was 23.6 percent less likely to secure its loan. A firm that was 10 years old versus 9 years