Chapter Ⅲ. The Cost to Firms of Changing the Names: Evidence from the Bank
4. Multivariate analysis
4.1 The effect of corporate name changes on the cost of loan
facility is priced by firm performance and zero otherwise. Secured dummy equal one if the loan facility is secured by collaterals and zero otherwise.
As reported in Table 3.2, firms are required to have more collateral and more general covenant restrictions on dividends, prepayment and voting right, such as collateral release, term changes after name changes. There is no significant difference in loan maturity, number of lenders and number of financial covenants. I show in the multivariate regression analysis that after controlling firm characteristics and loan contract variables, the number of lenders deceases considerably after name changes.
[Insert Table 3.2 here]
4. Multivariate analysis
4.1 The effect of corporate name changes on the cost of loan contracting
In this section, I use multivariate regression to analyze the effect of corporate name change on the cost of loan contract. Since the cost of loan contract is likely to depend on various factors, including firm characteristics, loan characteristics and macroeconomic factors, I construct a multivariate regression model of the following form.
Each observation in this multivariate regression represents a loan, referred to as a facility or tranche in Dealscan. The dependent variable,Log LoanSpread , is natural ( )
‧
國立 政 治 大 學
‧
N a tio na
l C h engchi U ni ve rs it y
logarithm of loan spread for loan j borrowed by firm i in date t. Loan spread is measured as the amount a borrower pays in basis points over LIBOR for each dollar drawn down. To examine the effect of name changes on the cost of loan contract, I define a dummy variable, PostChange , which equals one if the loan initiation date is after corporate name change event date and zero otherwise. The regression result in column 1 of Table 3.3 shows that the coefficient of name change variable is equal to 0.2453, which is significant at 1% significance level. This result indicates that loan spread increases significantly over 20% on average after the firm’s name change.
[Insert Table 3.3 here]
The regression in column 2 of Table 3.3 shows that I include firm characteristics which might also affect the cost of loan contract into. Larger firms usually have less information asymmetry problem and they are likely to pay less spread to lenders. I proxy a firm’s growth opportunities using market-to-book ratio, calculated as the ratio of book value of debt plus market value of equity to the book value of total assets.
After controlling asset tangibility, I find that firms with more growth options have more value over book assets; therefore, growth firms may be required to pay lower spread by lenders. I also control for leverage level and profitability and Modified Altman’s (1968) Z-score in the regression. I expect that firms with higher leverage level, lower Z-score or lower profitability have more default risk and are required to pay higher loan spread by lenders. Finally, I include tangibility, which is defined as the ratio of property, plant, and equipment (PPE) to total assets, in the regression.
Since lenders have the right to recover the tangible assets if firms default, I expect that firms with greater tangible asset face lower cost of borrowing. In addition, I control
‧
國立 政 治 大 學
‧
N a tio na
l C h engchi U ni ve rs it y
for the potential difference in the degree of information asymmetry and industry competition across firms. I measure information asymmetry, using the market adjusted relative effective spread. Rakowski and Wang (2008) suggest that a wider market adjusted relative effective spread is associated with more information asymmetry. I expect that a firm with more information asymmetry would face more costs of loan contracting. Industry competition is measured as Herfindahl-Hirschmann index (HHI). When industry competition increases, a firm may not maintain a sustained profitability and would bear more cost of debt. All firm data refers to the fiscal year prior to the name-change announcement. The regression in column 2 of Table 3.3 shows that the estimate coefficient of PostChange is equal to 0.2384, which is significant at 1% significance level. Furthermore, the result indicates that small firms with fewer growth opportunities, fewer tangible assets, lower profitability, more industry competition as well as more leverage and information asymmetry are associated with higher cost of loan contract. The effect of corporate name changes on the cost of debt and the relation between loan spread and firm characteristics are consistent with my expectation.
Further, I control for loan characteristics that related to the cost of debt contract in the regression and the results are reported in column 3 of Table 3.3. I control for Log (loan size), the natural logarithm of loan facility amount and expect that larger loan size might face lower cost of borrowing due to the economies of scale. I also control for Log (loan maturity), the natural logarithm of the maturity of loan facility in months. I expect that loans with longer term have higher default probability and borrowers will be required to pay higher liquidity premium for long-term loan, which will translate into a higher loan spread. I also include performance pricing as a control variable. I define that performance pricing dummy takes the value of one if the loan
‧
國立 政 治 大 學
‧
N a tio na
l C h engchi U ni ve rs it y
facility is priced by firm performance and zero otherwise. This is to control for lenders adopting different methods of loan pricing. As the result reported in column 3 of Table 3.3, the estimate coefficient of PostChange is equal to 0.2011, which remains significant at 1% significance level. The effect of corporate name changes on the cost of debt and the relation between loan spread and firm characteristics remain consistent with my expectation. In addition, the results show that smaller loan, loan with longer maturity and less performance pricing are related to higher loan spread.
Macroeconomic condition might also influence the cost of loan contract. The literature suggests credit spread and term spread are good proxies for macroeconomic conditions so that I employ credit spread and term spread to proxy as macroeconomic factors. When the market is in a recession, investors need more compensation for increased credit risk, which leads to the increase in credit spread. When people have good prospect for the future, term spread tends to increase. In the regression analysis, I measure credit spread and term spread one month before the loan initiate date.
Moreover, the distribution of name change shown in Panel B of Table 3.1 indicates that in the overall sample, there is a large number of name changes during 1996 to 2000. I define a period dummy variable, Period (1996-2000), which equal one if firms experience name change during 1996-2000 and zero otherwise to examine whether the effect of corporate name changes is dominated by certain name changes during 1996-2000.
Finally, I control for loan type, loan purpose and industry effects. There is a variety of different Loan types, such as 364-days loans, term loans, and resolving loans. Loans are also available for many purposes, such as corporate purpose, debt repayment, takeovers, working capital, and so forth. Different loan types and purposes have different risks, and may influence the effect of corporate name changes on the
‧
國立 政 治 大 學
‧
N a tio na
l C h engchi U ni ve rs it y
cost of debt. In addition, I use one-digital SIC dummies to control for different risks and loan pricing across industry. After controlling for these variables, the regression result in column 4 of Table 3.3 shows that the estimated coefficient of PostChange is equal to 0.1125, which remains significant at 1% significance level. The effect of corporate name changes on the cost of debt and the relation between loan spread and explanatory variables support my expectation. Besides, the results indicate that credit spread is significantly positive related to loan spread, meaning that market condition affects loan spread. However, the results show that Period (1996-2000) is not significantly related to the loan spread.
To summarize, after control for firm characteristics, loan characteristics and macroeconomic factors, the results show that the effect of corporate name changes on the cost of loan contract is significantly positive, especially for small firms with few tangible assets, few profitability, few investment opportunities as well as higher leverage level, higher information asymmetry and higher industry competition.
Moreover, smaller loan, loan with longer maturity and less performance pricing are related to higher loan spread.
4.1.1 The effect on the cost of loan contract among different types of corporate name changes
Because firms have different reasons to change their names, I attempt to investigate the effect of different reasons behind name changes on the cost of loans using multivariate regression with four types of corporate name change: brand adoption, radical changes, broader focus, and narrower focus. The former two types are major name changes, the latter two types are minor name changes. Wu (2010) shows that compared with brand adoption type of name change, radical name changes
‧
國立 政 治 大 學
‧
N a tio na
l C h engchi U ni ve rs it y
has poorer past stock return and firm performance. On the other hand, compared with narrower focus type, broader focus type of name changes is related to superior stock return and firm performance. Wu (2010) also considers the probability that firms adopt their major brand name in order to focus on the line of product or operation.
Besides, she also compares brand adoption with narrower focus name changes, and finds that narrower focus name changes have worse stock return and less media coverage, but more investment opportunities. Therefore, I expect that radical name change faces a higher cost of loan contract than brand adoption name change does, and narrower focus name changes is requested a higher loan spread by lenders, relative to broader focus and brand adoption name changes.
I report the multivariate regression results on the cost of name changes among these four types of name changes in Table 3.4. The regression result in columns 1 and 2 of Table 3.4 show the effect of major name change on cost of loan. The estimated coefficients of PostChange of brand adoption and radical name changes are 0.1024 and 0.2455, which are both significant at the 1% level. The effect on the cost of loan of radical name changes is approximately twice than the effect of brand adoption name changes. On the other hand, the estimated coefficient of PostChange of narrower focus name changes is 0.2043, which is significant at the 10% level, while the estimated coefficient of PostChange of broader focus name changes is insignificant. These results suggest that the magnitude of effect on cost of loan contract of radical name changes is the largest, and firms adopting narrower focus name changes face higher borrowing cost than broader focus and brand adoption firms. The relation between loan spread and explanatory variables nearly remain consistent with my expectation among these four types of name changes. Specifically, major name changes are more likely to be less priced depending on firm performance,
‧
for brand adoption name changes loan spread is significantly negatively related to firm tangibility, and loan spread is significantly related to firm default risk and information asymmetry for radical name change firms. For the case of broader focus name changes, more loan spread is significantly related to less firm profitability, while more loan spread is significantly associated with more information asymmetry and industry competition for narrower focus type of corporate name changes.
[Insert Table 3.4 here]
4.1.2 Wealth effect versus information effect of name change
As abovementioned, my results show that there is economical and significant effect of corporate name changes on the cost of borrowing, and loan spread increases after firms change their names. I consider that the effect of name changes on the cost of loan contracting comes from two sources. The first is wealth effect, which is the change of lenders’ belief in expected future cash flows of a firm after a name change.
The second is information effect, which is the degree of uncertainty lenders have to bear when they evaluate expected future expected cash flows of a firm after the firm changes its name. In this section, I attempt to distinguish between wealth effect and information effect from loan spread changes. I include the forward-looking explanatory variables like analyst forecast and forecast dispersion, and the interaction term PostChange Dispincrease× into the following multivariate regression:
, , 0 1 , 2 , ,
‧
國立 政 治 大 學
‧
N a tio na
l C h engchi U ni ve rs it y
I define a dummy variable, Dispincrease , which equals one if analysts forecast dispersion increase after corporate name changes and zero otherwise. Analyst forecast and forecast dispersion data are retrieved from I/B/E/S database. To the extent that analyst forecast dispersion influences information uncertainty, after controlling firm characteristics, loan characteristics and macroeconomic factors I expect thatβ1 can capture wealth effect andβ2 can capture information effect. As the result in column 1 of Table 3.5 shown, the wealth effect contributions to a loan spread increase 7.63%
after corporate name changes, and the information effect contributions to a loan spread to an additional 15.32%. the results show that firms which changed their name have an information effect approximately 70% (15.32%/(7.63%+15.32%)) of total effect of name changes, and a wealth effect about 30% of total effect of name changes.
[Insert Table 3.5 here]
Among the four types of name changes, the wealth effect and information effect are most significant when corporate experiences a radical name change. The result in column 3 of Table 3.5 shows that the wealth effect contributions to a loan spread increase 15% after radical name changes, and the information effect contributions to a loan spread increases an additional 49.15%, after controlling for analyst forecast variables, firm characteristic, loan characteristics and macroeconomic factors. Firms with radical name change have an information effect approximately 75% of total effect of name changes, and a wealth effect approximately 25% of total effect of name changes. The result is consistent with my hypothesis that firms adopting a radical name change policy have higher credit risk and financial uncertainty. If lenders do
‧
not have adequate information about a firm’s historical operation and financial statements, they may face higher information asymmetry and financial uncertainty to evaluate the present value of future cash flows of the firm. Therefore, in this case, lenders require the firms to pay more cost of borrowing as the agency costs.
The results for firm size, growth opportunities, profitability, tangibility, loan size, performance pricing, and Z-score are negatively associated with the change in loan spread, while credit spread, leverage, information asymmetry, and analyst forecast dispersion are positively associated with the change in loan spread. These results indicate that the changes in firm characteristics, loan characteristics, market conditions, and analyst forecast dispersion are reflected in the change of loan spread.
4.1.3 The effect of positive CAR corporate name change on the cost of loan contract
In this section, I examine whether firms change their names pay higher financing costs after these activities, especially when firms earn positive abnormal returns from equity market with cosmetic name changes. I construct the following regression:
, , 0 1 , 2 , ,
I add an interaction term, PostChange PositiveCAR× , into the multivariate regression. I define a dummy variable, PositiveCAR, which equals one if firm changing their names earn a cumulative abnormal return from the 15 days before the name change event date to the 30 days after the event date and zero otherwise.
Compared with negative and zero CAR name change cases, I expect that positive
‧
國立 政 治 大 學
‧
N a tio na
l C h engchi U ni ve rs it y
CAR name changes have more information asymmetry problems and default risk so that these positive CAR firms might experience more loan spread after corporate name changes.
The result in Table 3.6 shows that the estimate coefficient of PostChange is 0.1818 and the estimate coefficient of PostChange PositiveCAR× is 0.2312, and coefficients are significant at 5% and 1% significance level, respectively. The result indicates that firms changing their name with non-positive CAR experience a 18.18%
increase on loan spread, while firms changing their names with positive CAR experience greater increase about 41.3% (18.18%+23.12%) on loan spread. The results provide evidence that firms changing their names with positive CAR face higher cost of borrowing from loan market, although they earn a positive reaction from equity market with cosmetic name changes. The result is consistent with previous literature that financial intermediaries play an important role in monitoring and controlling their borrowers. When firms change their names and produce more information asymmetry and credit risk, financial intermediaries would strengthen their control by adjusting loan contract terms, such as increasing the loan spread.
[Insert Table 3.6 here]
4.2 Effect of corporate name change on non-price loan contract terms and loan