Private Prison Adoption Sample Clauses

Private Prison Adoption. This original data allows me to examine the use of private prison over the last few decades, in a manner not possible to scholars studying this phenomenon before (e.g. Xxx and Price 2014, Xxxxxxxxx-Xxxxxx 2004, Price and Riccucci 2005). Armed with that dataset, I first estimate models evaluating whether and to what degree the four theories above contribute to a state adopting private prisons for the first time. I estimate a Xxx proportional hazards (CPH) model, a type of survival analysis. In the data, a state’s decision to privatize is considered a failure, while the remaining states that did not privatize by 2012 are censored. I collect the information on when the state privatized from my original dataset: if the state had an active contract to house some inmates under their jurisdiction in a private facility, that state “fails” and drops out of the dataset for the remaining years. If a state never privatizes, that state contains observations for each year from 1983 to 2012 and is censored in the final year. I recorded the year when a state initially decided to privatize11 and dropped the state from subsequent years once it “failed,” or privatized its prisons. This methodology will estimate each state’s probability of privatizing, conditional on that state not having privatized already and will model the theoretical first stage of deciding to privatize I describe above (Xxxxxxxxx-Xxxxxx 2004). The CPH model, which will measure the determinants of states’ initial adoption of privatization, tests for the influence of politics, economics, and union membership on the probability of privatizing. I estimate a model using Republican Governor, Repub- lican Control, Republican Governor * Republican Control, Budget Gap Per Capita, and Unionized Corrections Officers as the main independent variables. I also control for Violent Crime Rate and Incarceration Rate. First, I include two dummy variables, the first of which is Republican Governor, which takes on the value 1 if the state had a Republican governor and 0 otherwise. The second dummy variable is Republican Control, which takes on the value 1 if Republicans controlled both xxxxxxxx of the state legislature and 0 otherwise. Finally, I interact these two variables to analyze how unified Republican government affects prison privatization12. Including indicators for the partisanship of both the executive and legislative branch is useful, as state legislatures can pass legislation allowing 11Sources of the year each...