VIII. State Comparisons
( Sections E - J )
Figures 9 and 10 below compare the rates at which state courts in each of the study jurisdictions found serious error in that state's capital judgments to the corresponding rates for federal courts. Figure 9 compares the rate of serious capital error that was found for each state by its courts on direct appeal to that found by federal courts on habeas review.193 Figure 10 makes a similar comparison of the rate of serious capital error found for each state by its courts on both state direct appeal and state post-conviction review to the corresponding serious-error rate found by federal courts on habeas.194
Figures 9 and 10 arrange the states by the extent of the difference between the rates of serious capital error found on state versus federal review. On the left side of each chart are states as to which state courts found more serious capital error than federal courts. On the right side are states as to which federal courts found more serious error than state courts. In between are states as to which state and federal courts found similar rates of capital error.
Especially when we put to one side the (asterisked) states that had too few capital habeas reviews to permit analysis, both charts reveal a strong degree of similarity between the rates of capital-sentencing error detected by state and federal courts in each state (i.e., in how close together the two lines are). More important is the even stronger degree of similarity between state and federal courts' judgments about the various state's comparative rates of capital-sentencing error (i.e., in how closely each line's upward and downward ticks as it moves from one state to the next are paralleled by the other line's upward and downward ticks). What Figures 9 and 10195 thus suggest is that state and federal courts examining the same pools of capital judgments generally find-and react similarly to-the same relative levels of serious capital-sentencing error. In plain English: Where state courts find comparatively high, low or average rates of error in a particular jurisdiction's capital judgments relative to error rates found elsewhere, so do the federal courts reviewing the same jurisdiction's capital cases. Figures 9 and 10 thus refute the notion that elected state judges as a group react differently to the possibility of error in capital cases from the way that federal judges react as a group. In fact state and federal judges' reactions to capital error on both these measures of comparative amounts of error196 are very much in sync.
That said, it is interesting to consider the relatively small numbers of states that fall on the left and the right edges of the chart where the state and federal error-detection lines diverge. In doing so, we focus on Figure 10 (the more informative of the two charts197) and on the (non-asterisked) states with sufficient numbers of federal habeas cases.
One interpretation of Figure 10 is that the courts of North Carolina, South Carolina, Louisiana, Florida and Alabama-the states on the left side of the chart-are doing the lion's share of error detection for capital judgments in those states, leaving significantly less error to be detected by the relevant federal courts. Alternatively, the courts of those five states may have increased their level of vigilance to compensate for what they perceive (based, e.g., on past experience and (more probably) on information transmitted by lawyers) to be unusually lax error-detection by the federal courts. This latter interpretation might explain the North and South Carolina courts' robust error-detection in capital cases. Both states fall within the United States Court of Appeals for the Fourth Circuit, which has by far the lowest capital-error detection rate of any federal judicial circuit in the country.198
The corresponding interpretation for Georgia, Montana and California-on the right side of the chart-is that federal courts have taken the lead error-detection role as to capital judgments from those states to compensate for low state court error-detection.
The hypotheses offered in the preceding two paragraphs present important questions for future research.
We conclude our discussion of Figure 10 by again noting a discrepancy between Virginia and the other states. Unlike almost every other state (Missouri, again, and Texas are in an intermediate category) Virginia's state-review "square" and its federal-review "circle" are both located at the very bottom of the chart. In this respect, the Virginia courts may be contrasted to those of the other states in the Fourth Circuit, which are discussed on pp. 51 and 65 above: unlike the courts of the neighboring states, there is no evidence that Virginia's courts have tried to compensate for very low error detection by the Fourth Circuit. Quite the contrary, Virginia courts have the lowest error-detection rates of the 28 study states. As a consequence of simultaneously low state and federal error detection, the rate of error detected in Virginia capital judgments is both extremely, and unusually, low.
Tables 9 and 10, and corresponding Figures 11 and 12, compare the various study states based on their overall rates of serious capital-sentencing error (i.e., the rates of serious error found during full state and federal court review199). Table 9 and Figure 11 consider only the first (state direct appeal) and third (federal habeas) review stages.200 A more comprehensive picture is provided by Table 10 and Figure 12, which include, in addition, what we know about the second, state post-conviction stage. For that reason, we display and discuss Table 10 and Figure 12 here. Table 9 and Figure 11 are in Appendix E (pp. E-5 and E-6).
Table 10 and Figure 12 reveal that:
Figure 13 below plots (1) the combined state direct appeal and state post-conviction reversal rates, (2) the federal habeas reversal rate, and (3) the overall error rate that is a composite of the other two.205 Figure 13 illustrates three points that (for the most part) we have discussed above:
The multiple inspections needed to detect all this error take time-a 23-year average of about 9 years if the outcome is execution (with that figure rising to 10.6 years in the latter third of the study period), and 7.6 years if the outcome is reversal on habeas corpus.206 Figures 14-16 below provide a variety of perspectives on the length of time required to cleanse capital judgments of chronically high rates of error.
Figure 15210 compares the 23 study states in which at least one execution (consensual or non-consensual) took place between 1973 and 1995 based on the amount of time that elapsed, on average, between the same prisoner's death sentence and execution. Subject to missing data, and the fact that the table counts consensual executions, which causes it to understate the time needed for full review,211 Figure 15 reveals that:
Figure 16212 below compares states based on the proportion of their 1973-1995 death sentences that were awaiting direct review in 1995. As is discussed above, this comparison provides a rough measure of the extent to which state direct appeal is a bottleneck in the inspection process.213 Nationally, 21% of capital sentences imposed between 1973 and 1995-about 5-years-worth of death sentences-were awaiting direct appeal in 1995:
This section compares states to each other based on (1) how many death sentences they impose "per capita" and (2) how many executions the carry out "per capita." We use three different per capita measures-sentences and executions per 1,000 homicides, per 100,000 population, and per 1,000 prison population.214 The middle measure is particularly interesting, given the expectation that the number of death sentences each jurisdiction imposes and carries out would be responsive to the number of homicides committed there. This section also asks whether, as one would expect, states that undertake to capitally sentence more offenders per capita than other states also execute more people per capita.
Figure 17 below compares states based on their death sentencing rates per 1,000 homicides, per 100,000 population and per 1,000 prisoners. Figure 18 below compares states based on their non-consensual execution rates per the same three populations.
Figures 17 and 18 reveal huge variations among states in both their death-sentencing rates and their execution rates measured per homicides and per population:215
Figures 19-21 below consider whether high (or low) death-sentencing rates (per homicide, per population or per prisoners) translate, as one would expect, into high (or low) execution rates.
Judging from figures 19-21, there is no relationship between death-sentencing and execution rates. When states are arranged in order of their death sentences per capita, the line representing their executions per capita fluctuates wildly and randomly:
Figure 22 below asks a related question: Are states that are most likely to punish homicides with death also most likely to translate death sentences into executions?
Figure 22 reveals no relationship between death sentencing and execution rates. Indeed, for nearly half the states-Louisiana, Virginia, Missouri, and Texas (with comparatively low death-sentencing but high death-sentences-carried-out rates) and Wyoming, Idaho, Nevada, Arizona, Oklahoma, Florida, Alabama, and Mississippi (with comparatively high death sentencing rates but low death-sentences-carried-out rates), the relationship is the inverse: the more frequently states sentence killers to die, the less frequently they execute them, and vice versa.
Overall, therefore, it seems clear that a powerful disposition to sentence offenders to die does not go hand in hand with a strong capacity to carry out the death sentences that are imposed. Figuring out why this is so is a question we will address in a subsequent report. Our analysis so far, however, suggests one place to look for the source of the discrepancy: the distribuingly high rates of capital-sentencing error that we document above.
This section considers two other possible explanations for the frequency with which states sentence individuals to die, and the frequency with which they carry out the capital sentences they impose. The first is violent crime-measured by each state's homicide rate per 100,000 population.219 The second is race-based on the proportion of each state's population that is non-white.220
Figures 23 and 24 below consider the relationship between homicide rates per 100,000 population and, respectively, capital-sentencing and execution rates.
If there is any relationship at all between homicide and capital-sentencing rates (a matter requiring more sophisticated analysis), Figure 23 suggests that it is weak and inverse. Figure 24 asks whether variations in rates of serious crime, as measured by homicides per 100,000 population, can explain variations in execution rates, or vice versa. Figure 24's decisive answer is that there is no such relationship between a state's serious crime rate and its willingness or capacity to execute its citizens.
Turning to the issue of race, Figure 25 below compares capital-sentencing states' relative death-sentencing rates (per 1,000 homicide) to their percent nonwhite population.
Surprisingly, perhaps, this chart suggests that proportionately larger minority populations are associated with somewhat lower death-sentencing rates, and vice versa. Figure 25 also reveals the sharp variation among capital-sentencing states in terms of the proportion of their populations that are nonwhite, ranging from 5% in Idaho (which, incidently, has a very high death sentencing rate per homicide) to 37% in Mississippi (where the death-sentencing rate per homicide is relatively low).
Figure 26 below considers whether race influences execution, as opposed to death-sentencing, rates. Here, the relationship is weaker than in Figure 25, and runs in the opposite direction: Although states with larger proportions of racial minorities tend to capitally sentence less often than states with proportionately smaller minority populations, those same states tend to carry out relatively more of the death sentences they impose.
Here, we consider whether differences among states' judicial systems account for the marked variability in their capital-case error rates, death-sentencing rates, and execution rates. Relevant, reliable, and comparable state-court contextual data are difficult to obtain. For purposes of this initial report, we have developed three comparative measures: "political pressure" (the extent to which state sentencing and appellate judges are subject to electoral discipline for actions they take as judges221), judicial workloads (which we measure by comparing the various states' criminal court caseloads per 1,000 persons during the relevant period) and judicial resources (comparing the dollars the respective states spent on their courts per capita during the relevant period).222 The details of each of these measures are described at pp. 44-45 above.223
Figure 27 and Figure 28 below consider the impact of political pressure on, respectively, death-sentencing and execution (more specifically, death-sentences-carried-out) rates. Because error rates and the rates at which death sentences are carried out are so highly correlated (see Figure 1, supra p. 11), the latter chart is also a rough measure of the relationship between political pressure and capital error rates.
Figures 27 and 28 reveal a curious and potentially significant pattern: In general, the more electoral pressure a state's judges are under, the higher the state's death-sentencing rate, but the lower the rate at which it carries out its death sentences. Assuming a causal relationship, this suggests that political pressure tends to impel judges-or to create an environment in which prosecutors and jurors are impelled-to impose death sentences, but then tends to interfere with the state's capacity to carry out the death sentences that are imposed.
Whether it is fair to infer a causal relationship here and, if so, what might account for that relationship is a question for further research. One hypothesis is suggested by possible relationships between high death-sentencing rates and high error rates, and between the latter and low execution rates: Public opinion may place a premium on obtaining death sentences.224 If so, a desire to curry favor with voters may lead elected prosecutors and judges to cut corners in an effort to secure that premium- simultaneously causing death-sentencing rates, and error rates, to increase. In that event, high rates of reversible error would explain why high political-pressure states, after imposing so disproportionately many death sentences-making so many errors in the process-end up carrying out so disproportionately few of their death sentences. These are questions for further research.
Figures 29 and 30 below relate, respectively, states' death-sentencing rates, and the rates at which they carry out death sentences, to their per capita court expenditures.
With some exceptions, Figure 29 appears to indicate that comparatively high expenditures on courts are associated with relatively high death-sentencing rates. It is difficult to know what to make of this relationship, especially because capital cases are themselves costly and thus may partly account for high expenditures. It may be, however, that states whose courts have substantial amounts of resources are more capable of handling capital cases-and thus do so more often-than states with less well-funded courts.
As was the case when we looked at capital punishment and political pressure, the relationship between capital punishment and spending reverses when we move from analyzing death sentencing rates to rates of death sentences carried out: Figure 29 shows a direct relationship between court expenditures and death sentencing (the higher the one is, the higher the other tends to be); by contrast, Figure 30 shows a weak inverse relationship between court expenditures and death sentences carried out-as states' spending on their courts increases, the proportion of the death sentences imposed that are carried out tends to decrease. The cause of that relationship (if any exists) is unclear. If, however, it were the case that the processing of death cases is itself responsible for significantly driving up court expenditures, then Figures 29 and 30 might suggest that spending relatively large sums to secure relatively large numbers of death sentences has little pay off-and, indeed, is counterproductive-when it comes to securing executions. If so, the policy alternative of spending less by securing fewer death sentences225-each of which, however, is more likely to be carried out-would be indicated.
Figures 31 and 32 below consider the relationship between state court caseloads and, respectively, death sentencing rates and the rate of death sentences carried out.
Judging from Figure 31, there is no relationship between how many cases per capita state courts handle and the rate at which those courts impose death sentences. Figure 32 does, however, suggest a weak relationship between court caseloads and death sentences carried out: As per capita caseloads drop, the rate of death sentences carried out also tends to drop. One might hypothesize that states with smaller courts (ones with lower caseloads) are more likely to generate seriously flawed death sentences at the trial level, thus depressing the rate at which their death sentences are carried out. Alternatively, state appellate courts with lower caseloads may be superior error detectors, thus (given high error rates across all states) accounting for lower rates of executions-or, in this scenario, lower rates of flawed executions. Further research is called for.