The study goes beyond that counterintuitive conclusion. It also highlights possible reasons for it. “Our evidence suggests that managerial motivations may play an important role,” the two researchers write. “[T]he increased default risk may arise from aggressive managerial actions affecting risk enough to outweigh the strong risk-reducing asset diversification expected from a typical merger.”
Those unexpected conclusions emerged in large measure because Furfine and Rosen viewed mergers through a different lens. “Most of the academic research on corporate mergers has focused on addressing the questions ‘Why do firms merge?’ and ‘Do mergers create value, and if so, for whom?’,” Furfine says. “Our basic objective was to look at corporate mergers from a different angle: an acquisition not only affects a firm’s potential return stream but also changes the firm’s risk, including its chances of going bankrupt.”
An Unfamiliar Analytical Tool
To undertake their investigation, the pair relied on a tool uncommon in academic studies: the Expected Default Frequency (EDF) developed by Moody’s KMV. This provides an estimate of the probability that a particular firm will default within a year. “Because it is rather expensive, academics don’t typically consider using it,” Furfine says. “But it has great value in calculating the fate of firms in danger of default. The database calculates how far a firm is from default using traditional methods. Its advantage is that it then calculates from its historical database how often firms that far from default actually default in the next year.” Because they are based on historical evidence, he adds, “EDFs can be more accurate than traditional methods of measuring the risk of default.”
To undertake their investigation, the pair relied on a tool uncommon in academic studies: the Expected Default Frequency (EDF) developed by Moody’s KMV. This provides an estimate of the probability that a particular firm will default within a year. “Because it is rather expensive, academics don’t typically consider using it,” Furfine says. “But it has great value in calculating the fate of firms in danger of default. The database calculates how far a firm is from default using traditional methods. Its advantage is that it then calculates from its historical database how often firms that far from default actually default in the next year.” Because they are based on historical evidence, he adds, “EDFs can be more accurate than traditional methods of measuring the risk of default.”
The two researchers applied the EDF data to information in the Securities Data Corporation’s Merger database on firms that completed mergers between January 1, 1994 and March 31, 2006. Ancillary data on the acquiring firms’ stock returns and changes in their balance sheets came from CRSP and Compustat.
Mixing, matching, and applying basic business mathematics to data from the three sources revealed the relationship between mergers and default risk. Specifically, the numbers showed a mean increase of 0.519 percent in default probability for the 3,604 mergers that the pair explored. Although that “may be viewed as inconsequential for the riskiest of acquirers,” Furfine and Rosen write, it “would imply multiple downgrades for a highly rated acquirer.”
