ABSTRACT * * * An article by Joubert, Picon and McIntosh (1981) is found to contain several serious methodological flaws. A second analysis using a similar data set suggests that t h e methodological prob- lems may have caused them to draw e r r o n e m conclusions regarding the effects of social structural variables on prison admission and release rates.

U.S. Social Structure and Imprisonment

A Comment

LEO CARROLL MARY BETH DOUBET University of Rho& Island

In a recent article in this journal, Joubert, Picou, and McIntosh (1981) present the results of their research on the impact of several features of American social structure on prison admission and release rates. Some of their findings are as follows: Of seven structural variables, the percen- tage of a state's population that is black (B=.65) has the strongest direct effect on admission rates; this effect exceeds even that of the crime rate (B=.43); only two variables directly influence release rates, the rate of admission (B=.65) and per capita income (B=.21); several other variables indirectly affect the release through their effects on the rate of admis- sion. Intriguing and suggestive as they may be, these findings lack credibility because of serious methodological flaws.

First and most importantly, their equations likely are subject to specification bias due to the omission of several variables that may

AUTHORS' NOTE: We would like to acknowledge the technical assistance given to us by Alexa Albert. Computer factilities were provided by Academic Computer Center of the Unzversity of Rtwde Island.

EDITORS NOTE: Joubert et al. were invited to react to this comment, but they did not respond to the invitation.

CRIMINOLOGY, Vol. 21 NO. 3. August 1983 449-456 0 1983 American Society of Criminology

449

450 CRIMINOLOGY 1 AUGUST 1989

reasonably be expected to influence prison admissions and releases. I t is well known that southern states have higher rates of incarceration; indeed, the eleven states of the Confederacy all rank among the top 20 states in the rate of incarceration (U.S. News and World Report, 1981). Such regional differences are acknowledged by Joubert el al. (1981: 357), but they do not include a dummy variable for region in their model. Nor do they include a measure of unemployment despite research that sug- gests that over time the rate of unemployment has been a stronger predictor of the rate of admission to prison than the crime rate has (Greenberg, 1977; Yeager, 1979).

A second problem concerns their measure of the crime rate. At one point in their anaylsis, Joubert et al. differentiate between violent and property crime and find that the two types have different predictors. Moreover, they note in passing that the violent crime rates are better predictors of prison admissions that are the rates of property crime. In their path analysis, however, they use only the aggregated crime rate. As conviction for a violent crime seems more likely to result in a prison sentence-and a longer one at that-it would seem best to use the disag- gregated measure. Failure to have done so may, at least partially, explain why they found such a strong direct effect of percentage black on the rate of prison admission.

Finally, there is a question of whether their data accord with the asumption of homoscedasticity. They claim to have used all states except Alaska in their analysis.' For 1970 (the year of their analysis), Delaware by our calculation had a release rate of 281.57 per 100,000.2 This rate is slightly in excess of six standard deviations above the mean release rate of 42.99 per 100,000 (s = 38.73). This extreme case makes the assumption of equal variances implausible. We calculated the variance of the release rate for large and small states and for states with hiigh and low per capita incomes, each variable being divided a t the median. The variance of the release rate for small states is more than 20 times larger than that for large states (2882.95 versus 128.88), and the release rate for the wealthier states is in excess of ten times larger than that for the poorer states (3035. versus 246.88).

These methodological problems are so severe as to suggest that the substantive findings reported by Joubert et al. may be in error. To check this, we have replicated their analysis adding a dummy variable for region (South = l ) 3 and the unemployment rate, disaggregating crime into property and violent crime, and excluding Delaware. Our data sources are listed in the Appendix.

FINDINGS

As the first step in the reanalysis, we regressed the total crime rate, the admission rate and the release rate on the same set of independent

Carroll, Doubet 1 IMPRISONMENT 451

variables used by Joubert et al. We did this for all states on which we had data and a second time excluding Delaware. The standardized coeffi- cients for these regressions, together with those reported by Joubert et al., are presented as Table 1.

The coefficients presented in panel A of Table 1 indicate a high degree of comparability between our data and that of Joubert et al. The stand- ardized coefficients are within .10 of each other in 18 of the 21 compari- sions, and in two of the three cases outside that range the differences are .ll and .12. The only substantive difference in interpretation one may draw concerns the effects of the percentage that is urban on the admis- sion rate; we find this to be negligible (B = -.05), and Joubert et al. find it to be moderately negative (B = -.26). This difference may be due to the fact that we could find admissions data for only 48 states while Joubert et al. apparently had data on 49.

The effect of excluding Delaware from the analysis can be assessed by comparing the results reported in panel B with those in panel A. The biggest differences occur with respect to the estimated direct effects of per capita income, population size, and the crime rate on the release rate. The estimated direct effect of per capita income changes from moder- ately positive (B = .21) to moderately negative (B = -.25), that of popula- tion size from negligible but negative (B = -.11) to slight but positive (B = .16), that of crime rate from negligible (B = .01) to moderately positive (B = .23). The estimates for these variables are most affected because Delaware is small in size, has a high per capita income, and a low crime rate. Thus, it appears that by including in their analysis a state that, for whatever reasons, had an atypically high release rate in 1970, and thereby violating the assumption of homoscedasticity, Joubert et al. may have arrived at incorrect estimates. In the case of at least one variable- per capita income-the error seems to be substantial, amounting to more than twice the estimated direct effect.

In Table 2 we present the standardized regression coefficients result- ing from our path analysis. We find the statistically significant predic- tors of the rate of property crime to be the percentage urban, per capital income, and the rate of unemployment. For the violent crime rate, the strongest predictors are the percentage black, the percentage urban, population size, and region; however, only the first three are statistically significant. These results are generally comparable to those reported by Joubert et al.; the major differences are in the effects we found for unemployment and region, which they did not include.

Our findings begin to diverge more from those of Joubert et al. as we consider the determinants of the rate of admissions. As can be seen in Table 2, we find four variables to have statistically significant direct effects on prison admissions. In order of their relative importance, these are region, median education, the rate of violent crime, and population size. We find that the percentage black-which Joubert et al. find to have

TA

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.09

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.07

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.60

.55

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.17

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Carroll, Doubet / IMPRISONMENT 453

TABLE 2 Structural Equations (Beta Weights) for Types of Crime,

Admission Rate, and Release Rate (N = 45) ~

Dependent Variables

Independent Property Violent Admission Release Variables Crime Crime Rate Rate

Percentage Urban Percentage Black Percentage Aged 15-24 Median Education Per Capita Income Population Size Regiona Unemployment Property Crime Violent Crime Admission Rate

Adjusted R Z

.70x -.04 .16 .02 .28*

-.04 . I 7 .I 9'

.69

.38*

.42* -.lo .10 .I0 .25* .19 .09

.59

-.05 -.02 .02 .60" .10 -.34* .88"

-.02 -.12 .53'

.40

.15

.03 -.03 ,351 -.36* .20 -.65" .16 .20 -.lo 1 .OO"

.64

a. South = 1. *P < .05.

the strongest direct effect on the rate of admissions (B = .65)-has no effect; median education has a stronger relative effect in our equation than in theirs. Both these differences are largely attributable to their omission of a regional variable. When region is entered into our equation stepwise (after the other structural variables), the beta weights for both the percentage black and median education change dramatically. The coefficient for percentage black drops from .57 to .20; that for median education increases from .16 to .65.

In disregarding region, Joubert et al. have omitted from their equa- tion the variable we find to have the strongest direct effect on the admission rate, and they have also overestimated the direct effect of percentage black and underestimated that of median education. Further- more, by not disaggregating the crime rate, they underestimate the effects of crime and also fail to uncover a moderate positive indirect effect of the percentage black operating through its effect on the rate of violent crime.

Like Joubert et al., we find that the rate of admissions has the strong- est direct effect on the rate of release. Thereinafter, however, our find- ings are markedly different. The only other significant direct effect they find is one for per capita income (B = .21). As can be seen in Table 2, our

454 CRIMINOLOGY 1 A UGUST 1983

estimate of the direct effect of income is slightly stronger and in the opposite direction (B = -.36). We also find rather substantial and signifi- cant direct effects for region and education.

Both region and education (because of their strong positive effects on admissions) have substantial indirect effects (region +.98, median edu- cation +.65)on the release rate. With other factors held constant, location in the South and a higher median education are found to be related to lower rates of release. Because of the strong positive effects of both variables on admission, however, and strong effect admission has on the release rate, the net effect of both region and education is positive. I t seems plausible that the higher than average release rates in these states is due to turnover caused by their high rates of admission.

Joubert et al. report a rather strong indirect effect of percentage black on the release rate. In their analysis, this effect is mediated by the admissions rate. As we find no direct effect of percentage black on admissions, it is not surprising that we find a smaller indirect effect than did they (-15 versus .42)-all of which is passed through the violent crime and admission rate jointly.

We find a rather strong indirect effect on the rate of release for the violent crime rate (B = .53). This effect is the result of the impact of the violent crime rate on admission (.53) and of admission’s effect on the release rate (1.00). The rate of property crime, we find, has a moderate positive direct effect (.20) on the release rate but no indirect effects. On the one hand, this suggests that violent crime rate has a positive effect on the release rate because of the high rate of incarceration and/or the need to make space for new admissions. On the other hand, the positive effect of property crime-not of violent crime-likely results from the use of alternative dispositions and/or the imposition of shorter prison senten- ces for property crime.

CONCLUSION

This analysis was undertaken because of perceived flaws in the prior research by Joubert et al., and we find that these shortcomings result in several erroneous conclusions on their part. By not including a dummy variable for region in their equations, they ignore what we find to be the strongest determinant of the prison admission rate and the second strongest predictor of the release rate. Moreover, as a consequence of the relation of region with the percentage black and the median educational level, their failure to include region causes them to overestimate the effects of the percentage black and to underestimate the effects of median education on both dependent variables.

Carroll, Doubet / IMPRISONMENT 455

In using an aggregated measure of crime, Joubert et al. tend to underestimate the significance of violent crime. Furthermore, they fail to see how violent crime and property crime have differential impacts on both the admission rate and the release rate. They also fail to uncover a moderate indirect effect of the percentage black on the admission rate as a result of its influence on the rate of violent crime.

Finally, by not excluding Delaware-a state with an extremely high release rate in 1970-they violate the assumption of homoscedascity. The major consequence of this violation seems to be an incorrect estimate of the direct effect of per capita income on the rate of release; they find this to be significantly positive, but we-in excluding Delaware-find it to be significantly negative.

In their conclusion, Joubert e t al. speculate on whether the positive effects of the percentage black on the rate of admission results from its impact on violent crime or whether it is due to discrimination. We conclude that the effects are partly due to the former but are largely spurious due to the correlation of percentage black and location in the South. It appears that there may exist within Southern political culture a predisposition toward the use of incarceration as a criminal sanction. In this conclusion, we are mindful of the possibility that this cultural predisposition may have its origins in the history of racial conflict in the South. At present, however, it seems that the use of incarceration is not directly related to the percentage black.

APPENDIX

DATA SOURCES

Variable Percentage Urban

Percentage Black Percentage Aged 15-24 Median Education

Per Capita Income Population Size Region Unemployment Rate

Source U.S. Bureauof thecensus, Statistical Abstract of the United States, 1971. (Washington: US. Government Printing Office, 1971), Table 17. Statistical Abstract, 1971. Table 27. Statistical Abstract, 1971. Table 24. U.S. Bureau of the Census, U.S. Census of Population, 1970, Vol. 1. (Washington: U. S. Government Printing Office). Table 46. Statistical Abstract, 1971. Table 497. Statistical Abstract, 1971. Table 11. Defined in footnote 3. U S . Manpower Administration, Manpuwer Report of the President. (Washington: U.S. Government Print- ing Office, 1971). Table 337.

456 CRIMINOLOGY/AUGUST 1983

Crime Rates U S . Bureau of the Census. Statistical Abstract of the United States, 1972. (Washington: U.S. Government Printing Office, 1972). Table 225. U S . Bureau of the Prisons, State Prisoners: Admis- sions and Releases, 1970. (Washington: U S . Govern- ment Printing Office, 1971). Table Al . State Prisoners. 1970. Table R1.

Prison Admission Rate

Prison Release Rate

NOTES

1. We, however, could not find complete data for four states. Admission data were not found for Alaska and Rhode Island. Release data were not found for Alabama, Alaska, New Jersey and Rhode Island. As we indicated in the Appen- dix, our source was U.S. Bureau of Prisons, State Prisoners: Admissions and Releases, 1970 (Washington, Dept. of Justice, 1971).

2. With a 1970 population of 548,000, Delaware had a total of 1,543 first releases.

3. States defined as southern are the following: Alabama, Arkansas, Florida, Georgia, Kentucky, Louisiana, Maryland, Mississippi, North Carolina, Okla- homa, South Carolina, Tennessee, Texas, Virginia, West Virginia.

REFERENCES

GREENBERG, D. F. (1977)“The dynamics of oscillatory punishment processes.”

JOUBERT, P. E., J. S. PICOU, and W. A. McINTOSH (1981) “U.S. social

U.S. News & World Report (1981) “Inmate count-state by state.” 91 (October 26):

YEAGER, M. D. (1979)“Unemployment and imprisonment.” J. of Criminal Law

J. of Criminal Law and Criminology 68: 643-651.

structure, crime and imprisonment.” Criminology 19: 344-359.

6.

and Criminology 70: 586-588.

Leo Carroll is Professor of Sociology and Chairman of the Department of Sociology and Anthropology at the University of Rho& Island. He is the author of a book and numerous articles dealing with race relations and racial biases within the criminal justice system. He is currently engaged in a study of the impact of racial inequality on crime rates and rates of incarceration.

Mary Beth Doubet i s an undergraduate student, majoring in sociology, at the University of Rhode Island.