Determinants of Debt Burdens: Evidence from California Counties

Abstract

This study aims at developing a better understanding and measure of the relative debt burden of governments. We use panel data from California counties for the period of 1999–2011. The analysis consists of two steps. First, we use a lognormal regression model to analyze the relationship between debt levels and socio-economic, political and financial variables. Results indicate that larger counties, poorer counties, and counties with higher levels of capital investment and higher tax prices have higher debt burden levels. Next, we calculate debt burden indices for each county by dividing the actual debt by the results of the predicted debt burdens from the first step. The debt burden indices indicate a jurisdiction's relative reliance on debt compared to their expected debt reliance. The results of this study have direct policy implications related to debt administration and debt monitoring.