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Spatial Analysis of Local Government Fiscal Condition in Nebraska
Author(s) -
Craig Maher,
Mahbubul Majumder,
WeiJie Liao,
Yansi Liao
Publication year - 2019
Publication title -
socialiniai tyrimai
Language(s) - English
Resource type - Journals
eISSN - 2351-6712
pISSN - 1392-3110
DOI - 10.21277/st.v42i1.261
Subject(s) - metropolitan area , context (archaeology) , population , government (linguistics) , state (computer science) , census , empirical research , local government , geography , political science , economic growth , demographic economics , economics , sociology , public administration , demography , statistics , linguistics , philosophy , mathematics , archaeology , algorithm , computer science
The effects of urban growth on outlying communities is a long-stand empirical question. Often couched in the concept of spread-backwash effect, Ganning, Baylis and Lee (2013) find that not until the late-1980s did empirical studies on the spread and backwash effects emerge. Most empirical investigations examine this theoretical phenomenon within the context of either population or income change. We propose to consider the spread-backwash effect from the perspective of local government fiscal health. There is a substantial body of research in the public finance literate focusing on government fiscal health/fiscal condition that is applicable and the setting of Nebraska offers a unique case-study. The U.S. state of Nebraska has approximately 1.8 million residents and the state’s population is changing (getting older and more diverse), as well as shifting to the urban centers of Omaha and Lincoln. In 1950, two-thirds of the state’s population lived outside of the metropolitan counties of Lancaster, Sarpy and Douglas. In 2050, the U.S. Census is projecting the two-thirds of the state’s population will reside in these three counties. This is raising a host of challenges and questions that residents and policy-makers are being forced to address.Methodologically, we propose a spatial neighborhood statistics model, the Markov Random Field model, to assess our central hypotheses that the further the distance from the urban center, the weaker the municipality’s fiscal condition. The study is prepared according to the procedure used by Pandey et al. (2015). While the Pandey et al. (2015) research was on E.coli flows through streams, the research design offers a good deal of applicability to this study. We will also run a set of regression models to ensure the robustness of this study. We examined the fiscal data of 69 municipalities in Nebraska that are in the Omaha-Council Bluffs MSA and the Lincoln-Beatrice MSA from 2001 to 2016. The data analysis focuses on the fiscal condition of municipalities and their proximity to the two urban centers in Nebraska, Omaha and Lincoln. The five indicators used as the dependent variables are: general revenues/general expenditures, debt per capita, debt/property valuation, net cash balances/general expenditures and property taxes/general revenues. The key independent variable of this research is the municipalities’ proximity to the Nebraska urban centers of Omaha or Lincoln, which is measured by the municipalities’ distance to the urban centers on Google Map. Other independent variables will reflect economic, demographic and institutional constructs. Our findings support the backwash effect in that, the further a city is from the urban center, the worse their fiscal condition. More specifically, the greater the distance a city is from Lincoln or Omaha, NE (urban center), the lower the city’s revenues to expenditures, the lower its net balance and the lower the city’s property tax collections as a percentage of revenues.

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