The Process of Policy Innovation: Prison Sitings in Rural North Carolina

Abstract

We gauge the relative impact of economics, demographics, and politics on the decisions of 79 rural North Carolina counties whether to site a prison in the period 1970-2000. The results of this model demonstrate that, contrary to the expectation that counties site prisons in response to economic distress, the demographic characteristics of each county affect the relative likelihood of a prison siting more than its economics does. The influential demographic predictors are those inextricably bound up with development options-the education levels of its citizens-and those that limit its ability to pursue controversial projects-its not-in-my-backyard (NIMBY) constituencies-rather than those that measure its racial diversity. Therefore, prison siting is neither a simple story of economic determinism nor one of environmental racism. We use a proportional hazards regression to model this innovation adoption in response to the challenge to select methods that take the potential time dependence of adoptions into account. A duration model is also particularly suitable for cases such as this one for which the innovation adoption is better understood as a process than as an event.

Prisons as Panacea or Pariah? The Countervailing Consequences of the Prison Boom on the Political Economy of Rural Towns

“…These findings suggest that adjacent prison placement should be incorporated into future analysis. The study concludes that population density, owner occupants, and college graduates are negatively correlated with prison siting, with "the presence of African-Americans is not an important predictor" ( [49], p. 107). The authors' major theoretical contribution is that demography, not just socioeconomics and race, predicts prison siting.…”

“…Therefore, I take these factors into consideration when predicting prison impact. While Hoyman and Weinberg [49] measure poverty and Hooks et al [32,33] measure employment as outcomes, I improve on past studies by examining both. Furthermore, I improve on the ACA data used by Besser and Hanson [31] by using an extensive verification process in assigning each prison to the U.S. Census place identified by the Bureau of Prisons and the state department of corrections for each state in the contiguous United States.…”

“…Hoyman and Weinberg [49] examine prison siting at the county level. Their study uses proportional hazard modeling to examine how 24 prisons were sited in North Carolina from 1970 to 2000.…”

“…To date, the few empirical studies of prison placement have mapped key social, political, and economic traits of rural communities that predict the arrival of a new prison. Building on past studies [42,49], Eason [20] completed the most comprehensive national town-level analysis predicting prison-building to date. This study found that prison placement is a rare event, with less than 5% of all U.S. rural towns receiving a prison during the height of the prison boom.…”

Location, Location, Location: Selecting Sites for Controversial Facilities

“…Government bureaucrats at the Tennessee Valley Authority (TVA), for example, working to complete the planned Tellico dam, used political intervention to avoid being blocked by the discovery of an endangered fish in the local waters (Wheeler and McDonald, 1986, p. 212). Similarly, North Carolina politicians have intervened to bring prisons to their home constituencies when initial screening has not favored their home districts (Hoyman and Weinberg, 2006). A final approach to siting revolves around civil society characteristics.…”