Academic journal article Economic Review (Kansas City, MO)

What Determines Creditor Recovery Rates?

Academic journal article Economic Review (Kansas City, MO)

What Determines Creditor Recovery Rates?

Article excerpt

The 2007-09 financial crisis illustrated the importance of healthy banks for the overall stability of the financial system and economy. Because banking is inherently risky, the health of banks depends importantly on their ability to manage risk and the associated exposure to losses. The crisis revealed that risk management at banks and other financial institutions had shortcomings. As a result, the riskiness of their loans and other investments resulted in large losses that arguably contributed to the severity of the recession.

An important component of a strong risk management system is a bank's ability to assess the potential losses on its investments. One factor that determines the extent of losses is the recovery rate on loans and bonds that are in default. The recovery rate measures the extent to which the creditor recovers the principal and accrued interest due on a defaulted debt. While financial companies, their regulators, and researchers commonly assume that the recovery rate is constant, in practice, actual recovery rates vary significantly. Moreover, recovery rates are systematically related to default rates. For example, recovery rates on corporate bonds are inversely related to the aggregate corporate default rate. As a result, assuming constant recovery rates can lead to an incorrect assessment of potential losses, which in turn, would reduce the effectiveness of risk management programs.

One reason why recovery and default rates may be inversely related is that they are both likely to be strongly influenced by the economy. For example, the same adverse economic conditions that cause defaults to rise--such as a recession--can cause recoveries to fall. Drawing on more than 30 years of recovery data on defaulted debt instruments, this article shows that the state of the economy does indeed help determine creditor recovery rates. Industry distress also drives recovery rates, and evidence suggests that industry distress can be triggered by an overall weak economy.

Section I examines why the recovery rate is an important input to credit risk models. Section II analyzes recovery rates on U.S. corporate debt securities. It shows that recoveries vary considerably across time, sectors, seniority, and security type of the defaulted debt instrument. The variation in the recovery rate across time is also related to the aggregate default rate and to the business cycle. Section III examines in detail the different potential factors that explain recoveries, including bond market conditions, the macroeconomy, industry distress, and their interrelationships.


The goal of risk management is to reduce the risk of large losses and to increase a financial firm's resilience to large losses. One key assumption in risk management is how the recovery rate is determined. This assumption is important because additional risk is introduced when the recovery rate is not constant. Weaknesses in modeling this risk may cause common measures of credit risk to be understated.

The recovery rate in credit risk

Credit risk is the dominant source of risk for banks (Pesaran, Schuermann, Treutler, and Weiner). Credit risk is the risk of changes in value from unexpected changes in credit quality (Duffle and Singleton). (1) Unexpected changes in credit quality can come from changes to the likelihood of default, the exposure at default, and the loss given default (where loss given default is 1 minus the recovery rate). Credit risk therefore comprises both default risk and recovery risk, where recovery risk is the chance of recovering less than the full amount of principal and accrued interest due, given a default event. (2) Recovery is uncertain and often less than the full amount due, meaning that the recovery rate varies between zero and 100 percent.

A common assumption in analyzing credit risk, however, is that the recovery rate is known with certainty, so that the analysis focuses on modeling the likelihood of default. …

Search by... Author
Show... All Results Primary Sources Peer-reviewed


An unknown error has occurred. Please click the button below to reload the page. If the problem persists, please try again in a little while.