Measuring the Financial Crisis in Local Governments through Data Mining

In local government, the financial analysis is focused on evaluating the financial condition of municipalities, and this is normally accomplished via an analytic process examining four dimensions: sustainability (or budgetary stability), solvency, flexibility and financial independence. Accordingly, the first goal the authors set out to achieve in this chapter is to determine the principal explanatory factors for each of the above dimensions. This is done by examining a wide range of ratios and indicators normally available in published public accounts, with the aim of extracting the most significant explanatory variables for sustainability, solvency, flexibility and financial independence. They use a rule induction algorithm called CHAID, which provides a highly efficient data mining technique for segmentation, or tree growing. The research sample includes 877 Spanish local authorities with a population of 1000 inhabitants or more. The developed model presents a high degree of explanatory and predictive capacity. For the levels of budgetary sustainability the most significant variables are those related to the current margin, together with the importance of capital expenditure in the budgetary structure. On the other hand, the short-term solvency depends on the liquid funds possessed by the entity. The flexibility, however, depends mainly on the financial load per inhabitant of the municipality, on the total sum of fixed charges. Finally, financial independence depends fundamentally on the transfers that the entity receives and on the fiscal pressure, among other elements.