A predictive model of fiscal distress in local governments

Bibliographic Data

ID20201207
AuthorsJohn M Trussel (0000-0003-3050-9628, Dalton State College), Patricia A Patrick (0000-0001-5101-6967, California University of Pennsylvania)
Year2009
Volume21
Issue4
Pages578-616
Publication date2009-03-01
Peer ReviewedYes
Open AccessYes
TypeARTICLE
VenueJournal of Public Budgeting Accounting & Financial Management (JOURNAL)
Journal identifiersISSN: 1096-3367 • E-ISSN: 1945-1814
PublisherEmerald (PUBLISHER)
DOI10.1108/jpbafm-21-04-2009-b004
OpenAlexW2415659466
LanguageEN
Citations received9
References cited21

This paper investigates the financial risk factors associated with fiscal distress in local governments. We hypothesize that fiscal distress is positively correlated with revenue concentration and debt usage, while negatively correlated with administrative costs and entity resources. The regression model results in a prediction of the likelihood of fiscal distress, which correctly classifies up to 91% of the sample as fiscally distressed or not. The model also allows for an analysis of the impact of a change in a risk factor on the likelihood of fiscal distress. A decrease in intergovernmental revenues as a percent of total revenues and an increase in administrative expenditures as a percent of total expenditures have the biggest influences on reducing the likelihood of fiscal distress

Debt · Distress · Econometrics · Economics · Financial distress · Financial system · Fiscal policy · Monetary economics · Regression analysis · Revenue · Statistics · Clinical Psychology · Credit Risk and Financial Regulations · Fiscal Policies and Political Economy · Local Government Finance and Decentralization · Medicine · Finance

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