Drivers of Municipal Bond Defaults during the Great Depression

107 Pages Posted: 16 Dec 2012

See all articles by Marc D. Joffe

Marc D. Joffe

Public Sector Credit Solutions

Date Written: December 14, 2012


Approximately 4800 municipal bond issuers defaulted on interest or principal payments during the Great Depression. Although municipal bond defaults have been quite rare over the last 70 years, some commentators have suggested that another large wave of municipal bond defaults will occur in the near future.

This paper assesses the likelihood of such a credit event by analyzing the Depression experience. It also reviews techniques used to gauge default risk for municipal bonds and analogous asset classes, with an eye toward determining which methods are most effective.

Statistical analysis relies upon a list of Depression-era city defaults collected by the author from contemporary bond manuals, trade publications and other historical sources. This list is used in conjunction with a database of municipal fiscal data compiled from historical censuses of local governments. This data set provides a collection of exogenous financial variables that may be predictive of default. Econometric analysis is performed on the data set with the goal of building a logistic regression model that can be used to estimate default probabilities for current municipal bond issuers. The paper also includes a discussion of the Depression-era municipal bond environment and its relevance (or lack thereof) to the current situation.

Keywords: municipal bonds, default probability model

JEL Classification: H74, C35, R51

Suggested Citation

Joffe, Marc D., Drivers of Municipal Bond Defaults during the Great Depression (December 14, 2012). Available at SSRN: or

Marc D. Joffe (Contact Author)

Public Sector Credit Solutions ( email )

1655 N. California Blvd.
Suite 223
Walnut Creek, CA 94596
United States
14155780558 (Phone)


Do you have negative results from your research you’d like to share?

Paper statistics

Abstract Views
PlumX Metrics