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Comments on “Financial Innovation and Corporate Default Rates” by Maurer, Nguyen, Sarkar, and Wei. Bill Keeton Federal Reserve Bank of Kansas City January 2, 2009. Objective of paper. --Determine if financial innovation in corporate debt market
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Comments on“Financial Innovation and Corporate Default Rates”by Maurer, Nguyen, Sarkar, and Wei Bill Keeton Federal Reserve Bank of Kansas City January 2, 2009
Objective of paper --Determine if financial innovation in corporate debt market can explain the unusually low default rates of recent years. --Particular theory authors want to test is that new forms of financing such as CLOs and CDOs allowed distressed firms to postpone default: “As more capital becomes available to even highly risky borrowers, companies that might have to default otherwise can survive longer” (p. 2)
Objective of paper (cont.) --An unanswered question about this theory is whether the new forms of financing are socially beneficial (give viable firms a chance to recover) or harmful (allow inefficient firms to linger on and make bad investments) --Authors try to provide empirical support for the theory by showing that 1) corporate default rates were unusually low in the second half of the 2000s 2) financial innovation was partly responsible for the low default rates --First effort is more successful than second
First issue: were default rates unusually low after 2005? --Authors first show that default rates were lower on cohorts of bonds outstanding at beginning of 2004, 2005, and 2006 than on cohorts of bonds outstanding at beginning of previous expansion years. --To better control for macroeconomic and financial conditions, they next show that a regression model for monthly change in default rate estimated over 1990-2007 overpredicts the change in default rate after 2005.
Comments on regression model --For most part, explanatory variables seem reasonable average “distance to default (DD) growth in corporate debt rate of return on stock market index change in junk bond rate spread macro variables (change in unemployment, change in consumer confidence, term spread) 12 lags of change in default rate --Explanatory variables generally have expected effect, with important exception of DD and growth in debt
Comments on the regression model (cont.) --Some questions and criticisms: --Authors point out that adjusted R-square is high (48 percent), but much of this seems to be due to including 12 lags of dependent variable --To get monthly values for DD and growth of debt, authors have to interpolate quarterly data. Since DD is such an important variable in the analysis, why not estimate the model at quarterly frequency?
Comments on the regression model (cont.) --Rather than use average DD to explain aggregate default rate, it would seem better to use a bottom percentile, because it’s only the firms in the left tail of distribution that are going to default. This is what Moody’s apparently does when they calculate DD by industry. --Two concerns about calculation of DD at firm level: --Wasn’t clear that standard deviation of assets (σA) was calculated in best way, using option pricing methods --Short-term and long-term debt appear to be given equal weight in calculating default threshold
Second issue: was default rate unusually low after 2005 due to financial innovation? --Basic approach in this part is to try to identify direct and indirect effects of financial innovation on the default rate. --Authors say financial innovation affects default rate directly by allowing distressed firms to “avoid or postpone default,” and indirectly by changing DD. --In the analysis, however, the direct effect is just the effect on default rate not captured by the effect on DD.
Why try to measure indirect effect via DD? --Presumably, indirect effect can’t explain tendency for the 1990-2007 regression to overpredict default rate after 2005, since that regression included DD as a variable. --It’s not clear how availability of new forms of financing to distressed firms would affect the measure of DD used in this paper. --If short-term debt had bigger weight than long-term debt in default threshold, substitution of long-term debt for short-term debt could increase DD. But short-term debt appears to be treated same as long-term debt in this paper.
Comments on regressions --Authors use a two-stage approach to estimate the direct and indirect effects of financial innovation on default rate. --In first stage, monthly change in DD is regressed on lagged growth in CLS or CDO issuance over period from Jan. 2005 to Oct. 2007. --In second stage, monthly change in default rate is regressed on fitted change in DD, unexplained change in DD, and growth in CLO or CDO issuance. --Coefficient on fitted change in DD is interpreted as indirect effect, and coefficient on growth in CLO or CDO issuance as direct effect.
Comments on regressions (cont.) --Overall, regression results don’t provide a whole lot of support for hypothesis that financial innovation has been responsible for the low default rate. --Indirect effect is significant but has wrong sign (coefficient of fitted DD in second-stage regression is positive) --Direct effect has right sign and is significant for only one of the two measures of financial innovation (CDO growth but not CLO growth).
Comments on regressions (cont.) --Trying to identify an indirect effect via DD was probably doomed from the start, because the change in DD did not help explain the change in default rate over the longer sample period 1990-2007. --Given the poor performance of DD in the longer sample, authors might be better off going back to the approach they took in an earlier draft. That approach was to regress the residuals from the1990-2007 regression on the two measures of financial innovation.
Comments on regressions (cont.) --Unfortunately, though, there are two other problems with the 2005-2007 regressions --Sample period may be too short to identify the effect of financial innovation on the default rate (there are only 30 monthly observations) --There is an endogeneity problem. Causation could run from changes in probability of default to changes in CLO or CDO growth (e.g., if lenders expect default rates to decline, they may become more willing to make leveraged loans).
Overall assessment of paper --On positive side, authors make a careful and persuasive case that there was a structural change in the behavior of the default rate after 2005. This is a useful and important point to make. --On negative side, authors don’t make a very convincing case that this structural shift was due to new forms of financing for distressed firms. Regression results are quite mixed, and even if they were stronger, they would be suspect because of small sample and endogeneity problem.
Two further suggestions --Consider other explanations for unusually low default rate of recent years besides rapid growth of CLOs and CDOs. --For example, Carey and Gordy argue that decreased reliance on covenant-heavy bank debt has reduced the bankruptcy threshold. Idea is that if banks own less of a firm’s debt but are still senior, they can afford to let the firm’s asset value fall by a greater amount before using their covenants to force default.
Two further suggestions (cont.) --Examine impact of financial innovation on default rates using firm-level rather than aggregate data. -- Cross-section relationship between default rate and use of CLOs among a large number of firms is likely to tell us more than an aggregate time series relationship over a two or three-year period.