This study examines the influence of business cycle fluctuations on street crime in the conceptual framework of Cantor and Land's(1985) seminal work distinguishing between opportunity and motivation effects. The analysis contributes to the literature three ways. First, we use cross‐section/time series data, which has several important advantages over simple time‐series or cross‐section data of previous studies. Second, it introduces a new and broader measure of business cycle conditions, one that more faithfully captures the logic of Cantor and Land's framework than previous measures do. Third, it focuses on the large decline in street crime of the 1990s, a central issue facing criminologists. Statistical models indicate that the strong economy of the 1990s reduced all four index property crimes and robbery by reducing criminal motivation. Business cycle growth produced no significant opportunity effect for any of the crimes studied.

Objective. This article studies the impact of increasing incarceration rates on crime rates. First we seek to replicate the findings of previous studies utilizing the pooled, fixed-effects models (which are based on the assumption that the effect of imprisonment does not vary across states). Next we test the validity of this assumption. Finally, we present a new methodology to examine the imprisonment-crime relationship. Methods. Annual state-level data from 1971-1998 are used to estimate 51 state-specific regression models in which crime rates for seven major categories are functions of incarceration rates and a wide array of socioeconomic and dummy control variables. Results. Our findings are consistent with prior studies. More important, the assumptions upon which the fixed-effect models are based were found to be statistically invalid. The results of our new methodology reveal that imprisonment rates are not significantly related to crime in the majority of states for any of the seven crimes studied. Conclusions. Because the state-level lagged imprisonment coefficients varied from significant negative effects to significant positive effects (depending on the state and type of crime), we argue that it is inappropriate to speak about "the" effect of imprisonment on any particular crime or at the national level.

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ABSTRACT* * * This study examines the detention patterns of the insanity defendant who is successful with the plea and hospitalized, or unsuccessful and incarcerated. Further comparisons are made with felony defendants who never entered a plea of not guilty by reason of insanity (NGRI). From existing data it is unclear to what extent detention may vary if the plea is successful as compared to if it is not successful. Of all defendants who entered a plea of NGRI in Erie County, New York (Buffalo) between 1970 and 1980, 128 were institutionalized as a result of their disposition. Sociodemographic, institutionalization histories, arrest, and disposition information were collected and analyzed for all 128 individuals. The research evaluates differences in the likelihood and length of either institutionalization or incarceration and in the rates of release between successful NGRI defendants, those who entered the plea unsuccessfully, and those who did not plead NGRI. From the findings reported here the authors conclude that pleading NGRI in Eric County may not be quite as advantageous for a defendant as commonly is believed.

Almost two decades of research on the exact relationship between socio-economic variables and the rate of incarceration has produced highly divergent results. Some of these inconsistencies may be due to the various models specified (some use total crime rather than violent, and some control for system level variables while others do not). Virtually all of the previous research has focused on the direct effect only. Utilizing 1990 cross-sectional state level data this study examines the direct and indirect effects of socio-economic variables on imprisonment rates while controlling for arrests or crimes rates and system level variables (e.g., prison admissions and releases). Models using arrest rate data rather than crime rates were included to capture the effect of the recent "war on drugs" on imprisonment which is not included in the Index Crime rate data. These data reveal that percent nonwhite has a significant and direct effect on imprisonment levels across the U.S., but less of a direct effect in nonsouthern states. The data also document that percent nonwhite has a substantial indirect effect. The indirect effect of economic inequality is greater than the direct effect. Finally, there was no variation in the effects of extra-legal variables between those models which controlled for system level data and those which did not.

Previous studies have reported that state mental hospital deinstitutionalization has resulted in the criminalization of the mentally ill. Utilizing two samples of defendants found incompetent to stand trial (IST) pre-and post-deinstitutionalization, selected from three states, this study examines the correlation between the rate of deinstitutionalization and increases in the frequency of incompetency commitments, as well as changes in the characteristics of incompetent defendants. These data suggest that increases in IST commitments and the mental health histories of the postdeinstitutional cohort are positively related to deinstitutionalization. Contrary to the criminalization hypothesis, there is no evidence that incompetent defendants are now being arrested for less serious offenses.

This study examines the direct and indirect effects of race and income inequality on imprisonment rates across states. The analysis is designed to: 1) investigate whether race and income inequality are significantly related to imprisonment when controlling for crime, 2) assess the relative magnitudes of the direct and indirect effects; and 3) assess the relative magnitudes of race and income inequality. Crime is found to be the strongest predictor of incarceration rates in five of the six equations estimated. Income inequality is significantly related to incarceration rates in two of the six equations. There was no clear evidence of a direct race effect. The indirect effect of race was greater than the direct effect in four of the six equations.

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