Abstract
We provide the first parcel-level, time-series empirical analysis of municipal annexation behavior. We also exploit a unique natural experiment created by the incorporation and exogenous (court-mandated) dissolution of a new neighboring municipality to examine the public-choice motivations behind annexation. Our results indicate that an existing city’s annexation behavior differed significantly in the areas threatened with the formation of a competing jurisdiction, yielding the most compelling evidence yet that political motivations play a major role in the annexation behavior of cities. We also are the first to construct and include measures reflecting the strategic stepwise dependence between parcels in the annexation process—in terms of what other parcels subsequently can be annexed. We find that the characteristics of a parcel itself in many cases are of only secondary importance relative to considerations regarding the other parcels to which it gives access for future annexation. Such a spatially dependent stepwise factor has been overlooked entirely in prior literature assuming that parcel annexation decisions are independent of one another.
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Notes
For example, the available evidence includes local police enforcement (Garrett and Wagner 2009; Mast et al. 2000; Benson et al. 1995), transportation funding and road quality (Nesbit and Kreft 2009; Escaleras and Calcagno 2018; Holcombe and Williams 2010), economic development incentives (Calcagno and Hefner 2018), school funding (Brunner and Balsdon 2004; Brunner and Squires 2013; Brunner et al. 2019; Hall 2015; Ross et al. 2014), municipal consolidation (Hall et al. 2018), and higher education spending (Brunner and Johnson 2016).
In the literature, the tendency to avoid annexing surrounding minority or low-income areas is known as ‘municipal underbounding’.
A similar initiative in January 2006 targeted the West Ashely area to which the City mailed letters to property owners containing a statement of the benefits of annexation, a comparison between property tax bills should the property change jurisdictions, an annexation petition, and a return envelope addressed to City’s planning department.
While parcels sometimes are annexed as a group, it is empirically intractable to base the model on groups of parcels because of the almost infinite number of possible groupings of n parcels, and each parcel could be in multiple groupings. In practice, that issue is not common in our data as the vast majority of annexations (1078 of 1151 ordinances) contained only one parcel. Only 16 contained more than five parcels, and only seven contained 10 or more parcels. Thus, our model is based on observations consisting of individual parcels.
The assessed values of some parcels are zero; therefore, we use the inverse hyperbolic sine function to approximate the natural log function.
In practice, we covert the Accessible Count variable to approximate natural logs using the inverse hyperbolic sine formula since using the former are better fits for the data.
To verify annexations and identify annexation dates, we collected and analyzed the City of Charleston’s GIS annexation dataset, the U.S. Census Boundary Annexation Survey, the County of Charleston’s Tax Assessor’s parcel and municipal boundary GIS information, and the City of Charleston’s City Council’s minutes. We identified 1349 annexed parcels as well as each annexed parcel’s ordinance and the date Charleston City Council approved it.
The Charleston County Tax Assessor’s data run from 2008 to 2017; the 2008 dataset contains historical records for all parcels. Since the tax assessor’s data are not reported on an annual basis, we assign values to each unique parcel based on the closest tax year. In the case of a tie, we assign data using the most recent year. There are 4326 observations without a reported real estate transaction. We set those observations’ housing tenure variable to zero and enter an indicator variable in each regression for them.
The results are available upon request from the corresponding author.
These are calculated as the percent changes in the odds ratios.
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Acknowledgements
We would like to thank two anonymous referees of this journal, the journal’s editors, as well as seminar and conference participants at The College of Charleston, Western Carolina University, and the Public Choice Society meetings for helpful comments and suggestions. Partial funding for the project came from the Center for Public Choice and Market Process, School of Business, College of Charleston.
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Mothorpe, C., Woolsey, W.W. & Sobel, R.S. Do political motivations and strategic considerations influence municipal annexation patterns?. Public Choice 188, 385–405 (2021). https://doi.org/10.1007/s11127-020-00833-2
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DOI: https://doi.org/10.1007/s11127-020-00833-2