Comparing Apples to Apples: Estimating Fiscal Need in the United States with a Regression-Based Representative Expenditure Approach

摘要

State fiscal governance requires both raising revenue and spending on government services. The literature on fiscal equalization and horizontal equity has established that measures of fiscal capacity, or the revenue-raising ability of a sub-national government, should be complemented by measures of fiscal need, the ability of a sub-national government to provide services given an average level of revenue. The representative tax system is an established method for measuring fiscal capacity, but the measurement of fiscal need has received less attention, with economically significant consequences. This paper provides the first regression-based estimates of state-level fiscal need in the United States, introducing a novel, data-intensive extension of the representative expenditure system that estimates fiscal need in the United States using regression methods rather than the current workload-based approach. Data from the 50 states and the District of Columbia were used, including actual expenditure by spending category as well as a large set of potential determinants of both capacity and need, to estimate the level of spending required for each state to provide a national average level of public services. Three regression approaches are considered: the most data-intensive, least data-intensive, and an intermediate method to determine the robustness of the estimates to methodological changes. Regression-based results indicate that prior workload-based approaches provide estimates at odds with both theory and actual state expenditure behavior. Among regression-based approaches, even the least data-intensive approach appears to offer improvements on existing methods. This paper estimates that 1.3% of gross domestic product may be misallocated.