The impact of an adequate public facilities ordinance on the sale price of single-family housing in Cabarrus County, North Carolina

Abstract

Hedonic modeling techniques and a difference-in-difference identification strategy were used in this study to examine the impact of an adequate public facilities ordinance (APFO) on the sale price of single-family housing in Cabarrus County, North Carolina. Plans to increase development fees collected as part of this land-use regulation were found to put upward pressure on existing housing prices in the 30 month period immediately following the announced policy change. The results suggest that policy-makers evaluating the merits of APFOs must consider their desires to manage growth and maintain housing affordability when using this regulatory tool. These considerations appear to be very important when municipalities intend to use development fees to finance needed infrastructure improvements during periods of robust housing market demand, such as the one that existed in Cabarrus County in the mid-2000s.

Keywords:

• adequate public facilities ordinances
• growth management
• housing affordability

Notes

1. The empirical analysis presented in this article focuses exclusively on the effects of an announced APFO policy change on the sale price of single-family, detached housing units in Cabarrus County. The term “housing” refers to this particular product type throughout the manuscript. The sale prices and rental rates of condominiums, townhouses and apartment units were not considered.

2. Hoffman and Hogan (2007) identified the Charlotte–Gastonia–Rock Hill Metropolitan Statistical Area (MSA), of which Cabarrus County is a part, as one of only five MSAs in the country to simultaneously achieve high rankings on four measures of economic success between 1990 and 2000. These included population growth, growth rate in total employment, per capita personal income, and growth rate of per capita personal income. The success was attributed to the presence of a young and highly-skilled workforce capable of meeting the needs of firms operating in the “knowledge economy”.

3. According to Cabarrus County records, less than $450,000 was collected in the first five years of the APFOs existence due to relatively low fee levels and collection in only a small portion of the county.

4. Many similarities were found between the two counties after examining data obtained from the US Census and the North Carolina Office of Budget and Management. Cabarrus County and Iredell County experienced population growth rates of 19.7% and 18.5% respectively between 2000 and 2006. Median household income, median home values and homeownership rates were also very similar according to the 2000 US Census. These figures were $46,140, $118,200 and 74.7% respectively in Cabarrus County and $41,920, $116,100 and 75.3% in Iredell County.

5. Both Cabarrus County and Iredell County have large local employers of note such as Carolinas Medical Center and Lowe’s Companies respectively. They also serve as bedroom communities for those working in Charlotte’s central business district. Following Chin and Foong (2006), straight line distances to interstates and the MSA’s primary central business district were controlled for because the analysis was conducted at the regional level. The authors note that drive times to specific employers or related amenities might be more appropriate for “micro urban” analysis.

6. Descriptive statistics show that 1692 of the new home sales included in the analysis took place before the announcement of the APFO policy change and 2256 took place after the announcement. Among the existing home sales, 4144 of the transactions took place before the announcement and 5773 took place after the announcement.

7. Some empirical studies have found a U-shaped pattern where single-family housing prices decrease with the age of the structure for several years, but then begin to rise at some point as a result of consumer demand for vintage or historic homes (Coulson & Lahr, 2005; Coulson & McMillen, 2008). Steps were not taken to accommodate such an effect in the empirical models presented in this study because the average age of a single-family home in the data was less than 16 years and no sale transactions involving homes built before 1900 were included.

8. Empirical studies utilizing hedonic price models have shown proximity to golf courses and lakes can have a positive impact on single-family housing sale prices (Quang & Grudnitski, 1995; Landsford & Jones, 1995).

9. Ottensmann et al. (2008) contend that distance to a central business district is an imperfect means of measuring access to employment centers in hedonic growth models because many modern cities do not conform to a monocentric model of urban growth. This concern prompted the inclusion of a second location variable in the hedonic price models presented in this article, measuring distance to the interstate system, to account for decentralized employment patterns.

10. Kennedy (2002) notes that this is a common reason for the structural characteristics of housing units, such as the number of bedrooms, to have negative coefficients when included in regression models along with square footage.

Additional information

Notes on contributors

Dustin C. Read

Dustin C. Read serves as an Assistant Professor in the Department of Apparel, Housing and Resource Management at Virginia Tech. His research interests include housing policy, land-use regulations, and real estate development.