The impact of intergovernmental fiscal tools on local service decision: the Nebraska case for water and wastewater systems

ABSTRACT

This study examines the impact of federal funding on local spending for water and wastewater infrastructure (hereafter ‘W&WI’) in Nebraska. The recent deterioration of W&WI creates potential risks to citizens’ lives. The federal government operates several programmes to assist with W&WI improvements. However, funding is limited, while there are substantial demands for funding. To understand the fiscal impact of intergovernmental aid on local expenditures, this study utilised panel data from 2010 to 2018 for 129 Nebraska municipalities with population over 800 that have water and wastewater systems. This study finds some evidence of the stimulating (‘flypaper’) effect of federal aid on local expenditures. However, in disaggregated models, the aid has crowd-out effects on specific types of spending (e.g. operating expenses). The findings can contribute to policymakers’ understanding of the impact of federal funding programmes and suggest directions for improvement of these tools.

KEYWORDS:

• Intergovernmental Grants
• Intergovernmental Loans
• Fiscal Tools
• Local Expenditures
• Public Infrastructure
• Water and Wastewater Systems

Acknowledgement

This article is modified and developed from a part of the author’s doctoral dissertation: Kim (2021). Fiscal Impact and Allocation of Water and Wastewater Funding Sources, University of Nebraska at Omaha.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Notes

1. The American Society of Civil Engineers (ASCE) publishes the infrastructure report card every four years based on the eight criteria (capacity, condition, funding, operation &maintenance, public safety, resilience, and innovation).

2. The Chow test, as a joint F-test, is to confirm differences in characteristics across individual samples (i.e., municipalities) through comparison between the fixed effects model with dummies to estimate time- or individual effects, and pooled OLS model without dummies. The null hypothesis is that ‘there is no two-way effect’ (or cross-section effect or time effect).

3. The Hausman test is a specification test to find a more appropriate estimation model for panel data analysis between the fixed effects and random effects models. The null hypothesis of the test is that ‘the individual effects are not correlated with the other regressors’.

4. The instrumental variables selected may be weakly related to intergovernmental transfer variables, which is called a ‘weak instrument’ by Stock and Yogo (2005). According to test results suggested by Staiger and Stock (1997), the instrumental variables proved to be weak (F-statistics: below 10). Therefore, to address the weak instrument issue, this study applied the k-class estimation method introduced by Fuller (1977) but again did not find endogeneity issues.

5. Given the long-term decision-making of capital project, this study analysed models including longer-lagged dependent variables and used a dynamic model, vector error correction model (VECM). The test results using longer lagged variables and the VECM make no difference in the models using 1-year lagged variable in terms of the fiscal impact of grants and loans, and the existence of flypaper effect (see Appendix A & B).

Additional information

Funding

The work was supported by the GRACA grant from the University of Nebraska at Omaha.