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A Predictive Model of Fiscal Distress in Local Governments
John M. Trussel,
The Pennsylvania State University at Harrisburg
Patricia A. Patrick, Shippensburg University
ABSTRACT: 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 earnings, administrative costs, and entity size. Using logistic regression on a sample of local governments in Pennsylvania, the results show support for some of these hypothesized relationships. The regression model results in a prediction of the likelihood of fiscal distress, which correctly classifies 64% to 78% 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. An increase in tax revenues as a percent of total revenues and an increase in revenue growth have the biggest influences on reducing the likelihood of fiscal distress.
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