Prison commitments, crime, and unemployment: A theoretical and empirical specification for the United States, 1933?1985

Abstract

This paper examines sources for the changing commitment rates to U.S. state prisons (PCR) from 1933 to 1985 using a variety of time-series techniques. Theoretically, it resolves ambiguous interpretations of how crime, unemployment, and imprisonment are related. Hypotheses that crime and punishment are in equilibrium are rejected. Our final specification supports theories integrating institutionally endogenous and socially exogenous causes of prison use and includes feedback effects between crime and punishment. We reached several general conclusions. (1) Changes in PCR are due partly to changes in the levels of unemployment, age composition of the population, and military active-duty rates. (2) Effects of the criminal justice system, captured as autoregressive institutional drift, account for approximately half of the year-to-year fluctuations in the PCR. The contemporaneous prison discharge rate also influences the rate of prison commitments. (3) Neither the specified nor the unspecified institutional effects mediate the effects of other exogenous variables. (4) Under most simultaneousequation specifications, the crime rate is moderately influenced by the contemporaneous unemployment rate and strongly influenced by prior levels of prison commitments. The preferred simultaneous causal model estimates a modest positive coefficient for the unemployment-crime causal path and a substantial positive coefficient for the unemployment-prison commitment causal path.

When Prisoners Get Out: The Impact of Prison Releases on Homicide Rates, 1975-1999

“…With respect to the connection between prisoners and economic conditions, the basic argument is that prisons are an effective way to manage populations (e.g., unemployed and marginal workers) perceived as threatening during economic downturns, and the business community will devalue potential laborers when unemployment rates are high (Cappell & Sykes, 1991;Hale, 1989;Parker & Horwitz, 1986;Rusche & Kirchheimer, 1939;Sabol, 1989;Speiglman, 1977). Others have suggested that judges may become frightened because of threats made by unemployed workers (e.g., Greenberg, 1977) or consider them a greater risk for returning to crime (Box, 1987) and, therefore, sentence them more harshly.…”

Conflict Theory, Economic Conditions, and Homicide

“…Although considerable variation in both economic conditions and homicide exist within the United States, the added benefit of having monthly time-series data restricts our ability to apply our methodological approach to multiple levels of analysis. Accordingly, consistent with a number of time-series models in the criminological literature, our analysis is focused at the national level (see, e.g., Box & Hale, 1984;Cantor & Land, 1985;Cappell & Sykes, 1991;Gartner, 1990;Kapuscinski et al, 1998;Land et al, 1995;London & Robinson, 1989;Marvell & Moody, 1999).…”

Intervention time series analysis of crime rates: The case of sentence reform in Virginia

“…Some of the time series references using the UK data are Pyle and Deadman (1994), Dhiri et al (1999), Hale and Sabbagh (1991). Examples of papers using the U.S. data are Greenberg (2001), O'Brien (1999, Corman et al (1987), Cappell and Sykes (1991), Witt and Dryden Witte (1998), Saridakis (2004), and Nunley et al (2011a). For Switzerland, examples of papers which analyse crime rates using a time series approach are papers by Funk and Kugler (2003a) and Funk and Kugler (2003b).…”

“…Estimation results in most of these papers are based on the cointegration modelling approach, which assumes a stable long-run relationship between crime and underlying explanatory variables. An exception is a paper by Cappell and Sykes (1991), who base their results on the autoregressive integrated moving average (ARIMA) time series approach to modelling crime. system, and increased sentence length for violent offenders on or after January 1, 1995.…”