Capital budgeting in American county governments: Analysis of current practices

This study analyzes the current practices of capital budgeting in American county governments. The analysis includes a determination of the factors believed to influence the use of a capital budget in counties. The bulk of the data for the study were gathered by means of survey research. A questionnaire was designed, pre-tested, and administered to a select group of county finance officers across the United States. Stratified random sampling procedures were employed in the selection of the sample frame. Limited supplementary data obtained from secondary sources were also used. Descriptive statistics, measures of association, and logistic regression procedures were used in the analysis and interpretation of the data. The analysis of the data using contingency tables and measures of association reveal a significant relationship between the dependent variable, i.e., the use of a capital budget, and several independent variables, notably: degree of urbanization, form of government, state requirements, capital improvement program (CIP), federal grants, state grants, and a periodic inspection program. No significant relationship was established between the use of a capital budget and the following independent variables: geographic region, risk and uncertainty, and size of capital budget or capital investments. Moreover, the analysis of the results reveals that counties with capital budget in contrast to counties without a one have a higher incidence and are more predisposed to: (1) utilize a CIP, (2) receive intergovernmental grants for capital investments, (3) consider risk and uncertainty in evaluating capital investment proposals, (4) have their infrastructure facilities in fairly good physical condition, (5) employ a periodic inspection program, (6) tend to have a large population (urban), and (7) have an elected or appointed professional administrator. Furthermore, logistic regression analysis was used to determine the covariates that have a strong explanatory power of the dependent variable. After testing several models, the parsimonious and best fitting model contained the following variables, and interaction terms: urbanization, state requirements, use a of CIP, interaction of federal grants and urbanization, and interaction of state grants and state requirements. Overall, the results from descriptive statistics, measures of association, and logistic regression analysis, seem to suggest that county governments that use a capital budget performed slightly better than counties without a capital budget when the independent variables are considered as performance indicators.