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Juvenile Crime, Juvenile Justice (2001)

Chapter: Appendix B: The Indeterminancy of Forecasts of Crime Rates and Juvenile Offenses

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Suggested Citation:"Appendix B: The Indeterminancy of Forecasts of Crime Rates and Juvenile Offenses." National Research Council and Institute of Medicine. 2001. Juvenile Crime, Juvenile Justice. Washington, DC: The National Academies Press. doi: 10.17226/9747.
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APPENDIX B

The Indeterminacy of Forecasts of Crime Rates and Juvenile Offenses

Kenneth C. Land and Patricia L. McCall

How much crime will there be in the United States in the next 5 or 10 years? Will crime rates go up or down or remain about the same? Since juvenile crime often is a leading edge of crime problems to come, how many juvenile offenses will there be? Will the number of juvenile serious violent offenders/homicide perpetrators increase? What will be the resulting demands on the juvenile and criminal justice systems? Over the past three decades, criminologists have made a number of attempts to address these and related questions. These usually have taken the form of efforts to explain past variations or to project future levels of crime by applying techniques of demographic and statistical analysis. These techniques typically consist of:

  • the application of demographic age standardization methods to combine relatively accurate estimates of the age structure of the American population with age-specific arrest rates for various types of crimes and categories of the population to calculate expected numbers of criminal offenses or crime rates or

  • the construction of an explanatory time-series regression or structural equation models to explain or predict variations in crime rates over time.

Kenneth C. Land is John Franklin Crowell Professor of Sociology, Duke University. Patricia L. McCall is Associate Professor of Sociology, North Carolina State University.

Suggested Citation:"Appendix B: The Indeterminancy of Forecasts of Crime Rates and Juvenile Offenses." National Research Council and Institute of Medicine. 2001. Juvenile Crime, Juvenile Justice. Washington, DC: The National Academies Press. doi: 10.17226/9747.
×

Such analyses may be useful exercises with respect to explaining past experiences in the ups and downs of observed crime or the projection of recent trends in order to anticipate future problems and needs for levels of resources in the juvenile and criminal justice systems. Yet even a casual review of the various projections of crime rates or offenses that have been made over the years suggests that they contain large amounts of uncertainty. That is, the mere fact that a projection indicates that, say, juvenile homicide offenders may increase (or decrease) by some specific percentage over the next 5 or 10 years does not mean that the rates will, in fact, exhibit such an increase (or decrease).

The purposes of this paper are twofold. First, we review a number of extant demographic projections of crime rates and offenses that have been made for the United States over the past few decades, with a special focus on projections of juvenile crime rates and offenses. We commence in the next section with a brief summary of demographic analyses of the crime wave in the 1960s based on the coming of age of the baby boomers. This is followed by a review of projections of downturns in crime rates in the 1980s based on the smaller “baby bust” birth cohorts. More recently, following the rise in delinquent and criminal offenses by adolescents and teenagers in the 1985-1993 period, criminologists have produced some scary projections, which we next describe, of increasing numbers of violent criminal offenses expected in the period 1995-2005, as the “echoboomers” enter their teenage years.

It will be seen that one characteristic of most extant projections of juvenile and criminal offenses is that, until recently, they have produced only expected or average values of future levels of crime rates or offenses. But temporal variability of age-specific crime rates has been a key characteristic of offending patterns, especially for juveniles, in recent years. Yet most projections of criminal and juvenile offending rates and numbers of offenses disregard the uncertainty associated with such projections. To emphasize the significance of the uncertainty of projections of criminal and juvenile offenses, a second objective of the paper is to describe some exercises in the construction of plausible national projections of expected numbers of male juvenile homicide offenders—as well as upper and lower bounds for the expected numbers—for each year from 1998 to 2007. A final section contains a statement of the major conclusions from our review and analyses.

THE BABY BOOMERS COME OF AGE IN THE 1960s AND 1970s

One of the first attempts to examine the impact of a changing demographic age composition of the population on numbers of criminal offenses reported to the police was made during the 1960s—when the

Suggested Citation:"Appendix B: The Indeterminancy of Forecasts of Crime Rates and Juvenile Offenses." National Research Council and Institute of Medicine. 2001. Juvenile Crime, Juvenile Justice. Washington, DC: The National Academies Press. doi: 10.17226/9747.
×

United States was stunned by skyrocketing crime rates. On the heels of the relatively low levels of criminal and juvenile offending in the 1950s, scholars and politicians began searching for reasons behind the dramatic increase in crime rates during the 1960s. Criminologists were well aware of the fact that the Uniform Crime Reports (UCR) published annually by the Federal Bureau of Investigation (FBI), the primary measure of national crime levels and rates at that time, was at best a politically influenced undercount and a weak indicator of the extent of criminal activity in the United States (see, e.g., Biderman, 1966). This was an unsettling notion especially in light of the growing magnitude of crime. One of the outcomes of this crime wave was the development of the annual National Crime Victimization Survey (NCVS) beginning in 1973.1 This survey was introduced as a new tool to determine the extent of criminal activity in the United States by surveying individual households in the population regarding the victimization status of their members in the past year.

Criminologists attempted to determine the impetus behind the crime surge of the 1960s. Philip Sagi and Charles Wellford, in their 1967 report to the President's Commission on Law Enforcement and the Administration of Justice, identified the centrality of shifts in the age composition of the population as an explanation. Using a variety of demographic techniques, they attempted to accurately estimate the extent to which the increasing crime rate was due to an increase in individuals' crime proneness versus the changing composition of the population with respect to age, race, and geographic location.

In particular, Sagi and Wellford (1968) cited the contribution that the post-World War II baby boom generation was making to the crime wave in the 1960s.2 They argued that, during the early 1960s, individuals born in the early years of the baby boom hit peak criminal offending ages, i.e., their late teens and early 20s. Using techniques of demographic age standardization, Sagi and Wellford demonstrated that the population increase in these young ages between 1958 (the low point of national crime rates in the late 1950s) and 1964 (the most recent year's data available at the time of their study), in and of itself, accounted for 24 percent of the increase in

1  

The NCVS was originally called the National Crime Survey. It was redesigned and renamed in 1992 (see Bureau of Justice Statistics, 1995).

2  

Demographers have defined baby boomers in the United States as individuals born in the 18 high birth rate years from 1946 to 1964 (see, e.g., Crispell, 1993). Birth cohorts from these years are relatively large compared with those both earlier and later, and their movement through the age structure has been associated with various social movements and changes in social institutions. Sometimes “early boomers” born in 1946-1955 are further distinguished from “late boomers” born 1956-1964 (Gibson, 1993).

Suggested Citation:"Appendix B: The Indeterminancy of Forecasts of Crime Rates and Juvenile Offenses." National Research Council and Institute of Medicine. 2001. Juvenile Crime, Juvenile Justice. Washington, DC: The National Academies Press. doi: 10.17226/9747.
×

FBI Index (or UCR Part I) offenses. They further demonstrated that changes in population race, age, and place of residence in combination accounted for 46 percent of that increase (President's Commission on Law Enforcement and Administration of Justice, 1967:208; see also Sagi and Wellford, 1968).

Wellford (1973) followed up this analysis by extending the time series to include annual index crime rates through 1969. He first computed age- and crime-specific arrest rates. Then Wellford computed the age-standardized total offense rate by adjusting for the underrepresentation of the total U.S. population in the UCR. He estimated that the percentage increases in person or violent (homicide, aggravated assault, and robbery) and property (burglary, larceny-theft, and motor vehicle theft) crimes were 148 and 92 percent (age-standardized crime rates) as opposed to 165 and 117 percent (as indicated by the crude crime rates reported in the UCR), respectively. Even though the increase in offending rates during the 1960s was not as large as the official crime rates would lead one to believe, the disconcerting news was that the rate of violent crimes rose more than that of property crimes among youth during this period. The other disturbing results of Wellford 's cohort analysis showed that, with one exception, each cohort born during the baby boom was exhibiting crime rates higher than the one before. The main point made in his research was that “minimally, age composition effects must be controlled in attempting to estimate crime increase” rather than relying solely on “rates reflecting only the changes in the size of the total population” (Wellford, 1973:63).

Sagi and Wellford did not attempt to project the crime rates past the 1960s. But they noted that it is possible to forecast fairly accurately the size and age composition of the juvenile and adult populations for one or two decades into the future and, thereby, to project the extent of crime for that period. Beside noting the problems inherent in attempting to make these estimates, they also warned of the necessity to obtain arrest information for each sex and age group within each race and geographic location category in order to better account for the impact that the changing population composition has on crime trends and “to make much better judgments as to how much of any particular increase or decrease in crime rates was due to a change in the criminality of the persons involved” (President 's Commission on Law Enforcement and Administration of Justice, 1967:210). To a large extent, data readily available from the FBI today still possess the shortcomings identified by Sagi and Wellford over three decades ago.

Suggested Citation:"Appendix B: The Indeterminancy of Forecasts of Crime Rates and Juvenile Offenses." National Research Council and Institute of Medicine. 2001. Juvenile Crime, Juvenile Justice. Washington, DC: The National Academies Press. doi: 10.17226/9747.
×

DECREASING CRIME RATES FOR THE BABY BUSTERS IN THE 1980S

During the years after Sagi and Wellford conducted their initial study, the United States saw an increasing crime trend through the 1970s and into the early 1980s, at which time the crime rates began falling. With an additional 10 to 15 years of crime data at their disposal, James A. Fox (1978), Lawrence E. Cohen and Kenneth C. Land (1987), and Darrell Steffensmeier and Miles Harer (1987) reexamined the impact of age composition on crime trends. The question posed by the latter two groups of investigators was whether the decline in crime rates in the 1980s was due to the baby boomers aging out of those crime prone ages—adolescence and young adulthood.

Steffensmeier and Harer (1987) studied changes in crime rates among index crimes between 1980 and 1984. Echoing Sagi and Wellford's concern with the changes in crime trends reported in the UCR and the National Crime Survey, they noted that the official “crime figures are not age specific but are crude rates based on the U.S. population as a whole” (Steffensmeier and Harer, 1987:29). Using methods similar to Sagi and Wellford's, Steffensmeier and Harer applied the demographic technique of indirect standardization of crime rates on age-specific arrest rates adjusted for the proportions of the U.S. population not covered in the annual UCR series. By applying this age-adjustment method to data derived from the UCR and the National Crime Survey reports, they compared percentage changes between 1980 and 1984 in unadjusted crude rates (the traditional measure of change) with their adjusted percentage change that corrects for the changes in the age structure. They showed that the age composition accounted for approximately 30 to 70 percent of declines in property and robbery crime rates, since the baby boomers had aged past the property crime prone ages of adolescence and the early twenties. Violent crimes had not enjoyed such a large decline as the baby boomers had not quite reached the ages where the violent criminal offending tends to drop—that is, the late 20s and early 30s.

Based on those findings, Steffensmeier and Harer (1987) used age-specific estimates of the U.S. population produced by the Bureau of the Census through the end of the 20th century to forecast reductions in the nation's crime rate from 1980 to 2000. The forecasts assumed that age-specific offending rates would remain constant into the future and thus were based solely on changes in age composition. Specifically, they noted that the proportion of young people (ages 15-24), those at high risk for property crime, was estimated to decline sharply into the early 1990s and the proportion of youth and young adults (ages 15-35), those at high risk for person crime, were expected to decline steadily into and even beyond

Suggested Citation:"Appendix B: The Indeterminancy of Forecasts of Crime Rates and Juvenile Offenses." National Research Council and Institute of Medicine. 2001. Juvenile Crime, Juvenile Justice. Washington, DC: The National Academies Press. doi: 10.17226/9747.
×

the year 2000. This was due to the arrival of the “baby busters” at these high crime-prone ages.3 The projections made by Steffensmeier and Harer (1987) showed a steadily declining violent crime rate until the year 2000 and a somewhat steeper declining property crime rate until the mid-1990s, when the rate would plateau and begin a slight increase in the late 1990s. More precisely, they forecasted that violent crime rates would fall about 13 percent compared with about 20 percent for property crime rates during the 1980 to 2000 period.

The projections of crime rates in the 1980s and 1990s of Steffensmeier and Harer (1987) based on demographic standardization can be compared with those of two studies, Fox (1978) and Cohen and Land (1987), based on regression models of crime rate time series. Fox was the first researcher to publish forecasts of U.S. crime rates based on this type of analysis.4 Using national crime rate data for the years 1950 through 1974, he studied the impact the baby boomers had on the surge in crime rates during the 1960s and 1970s. This led to a conclusion similar to that of Steffensmeier and Harer (1987)—that crime rates would fall during the 1980s when the baby boomers matured out of the crime prone ages and were replaced by the baby busters. Fox constructed structural equation models that estimated not only the impact that race and age composition had on crime trends, but also that of socioeconomic characteristics of the population as well as police activities and expenditures. Based on his study, Fox concluded (1978:51): “The crime rate forecasts reveal a general reduction in upward trend during the 1980s and a trend increase during the 1990s. In fact, the violent crime rate . . . should decline in the 1980s before increasing once again in the 1990s.” These projections were based primarily on age-and race-specific population estimates and projections published by the Census Bureau for the last quarter of the century.

Cohen and Land (1987) also conducted an analysis of crime trends in the United States through the mid-1980s based on a time-series regression analysis for a somewhat longer post-World War II period, 1946 through 1984, to determine the extent to which changes in the age structure influenced the crime trends. By relating their analysis to the question of the relationship between age and crime then debated by Hirschi and Gottfredson (1983) and Greenberg (1985), they attempted to answer whether the decline in crime rates beginning in the mid-1980s would continue to

3  

Demographers generally refer to individuals in the United States born in the relatively low birth rate years from 1965 through 1976 that followed the baby boom years as baby busters (Crispell, 1993). Members of the baby buster birth cohorts also have been labeled in the popular press as “Generation X.”

4  

See also Cohen et al. (1980) for a time-series regression analysis of U.S. property crime rates, 1947-1974, with projections to the mid-1980s.

Suggested Citation:"Appendix B: The Indeterminancy of Forecasts of Crime Rates and Juvenile Offenses." National Research Council and Institute of Medicine. 2001. Juvenile Crime, Juvenile Justice. Washington, DC: The National Academies Press. doi: 10.17226/9747.
×

decrease symmetrically (i.e., proportionally to the declining population in the high crime-prone ages) versus asymmetrically (whereby cohortspecific effects produce non decreasing crime propensities throughout the life courses of high crime-prone cohorts as argued by Greenberg [1985], as well as suggested in the crime patterns displayed by the cohort analysis conducted by Wellford [1973]).

Cohen and Land (1987) focused specifically on homicide and motor vehicle theft rates and controlled for other social forces affecting crime rates: trends in business cycles as well as in criminal opportunity and the rate of imprisonment. They first identified the peak ages of offending for homicide and motor vehicle theft—15 to 29 and 15 to 24, respectively. By overlaying the trends in graphic form, Cohen and Land demonstrated that the homicide and motor vehicle trends mirrored the trends in age structure for these two youthful groups (see Figures B-1 and B-2, which reprint Figures 3 and 4 from their 1987 report). In their time-series regression analysis, they included the percentage of the population ages 15 to 29 as the age composition control in the homicide model and the percentage ages 15 to 24 in the motor vehicle theft model. In addition, they introduced measures for age-proneness shifts among the cohorts computed as

FIGURE B-1 Annual estimates of vehicle theft rate and the percentage of the population ages 15 to 24, United States, 1946-1984, with projections of the latter to 2001. Reproduction of Figure 3 from Cohen and Land (1987). Reprinted with permission.

Suggested Citation:"Appendix B: The Indeterminancy of Forecasts of Crime Rates and Juvenile Offenses." National Research Council and Institute of Medicine. 2001. Juvenile Crime, Juvenile Justice. Washington, DC: The National Academies Press. doi: 10.17226/9747.
×

FIGURE B-2 Annual estimates of the murder rates and the percentage of the population ages 15 to 29, United States, 1946-1984, with projections of the latter to 2001. Reproduction of Figure 4 from Cohen and Land (1987). Reprinted with permission.

the product of a dummy variable, equal to one for the years 1966-1984 and zero for 1947-1965, times the natural logarithm of the age structure index. This variable was “incorporated in order to test for the time series significance of changes in the levels of the age-specific crime rates in the later as compared to the earlier part of the sample period” (Cohen and Land, 1987:178). The results of their time-series analyses showed that the age structure variables in both homicide and motor vehicle theft models were significant, but that the age proneness shift measure was not (contrary to the finding of Wellford 's 1973 study). They argued that whatever cohort changes have occurred are not of sufficient magnitude net of those cohort differences transmitted through the other causal measures included in their models: unemployment rate, unemployment fluctuations, criminal opportunity, and imprisonment rate variables. They concluded from their analyses that the age structure-crime relationship, at least as evident in the homicide and motor vehicle theft rates series up to the mid-1980s, appeared to be symmetric.

Cohen and Land (1987) compared their findings to those of Steffensmeier and Harer (1987), noting that the latter's use of age-

Suggested Citation:"Appendix B: The Indeterminancy of Forecasts of Crime Rates and Juvenile Offenses." National Research Council and Institute of Medicine. 2001. Juvenile Crime, Juvenile Justice. Washington, DC: The National Academies Press. doi: 10.17226/9747.
×

standardized arrest rates focused on the offender population and attributed all variation either to changes in the entire age composition of the population or to changes in offending rates. Cohen and Land argued that by using a single age composition index for each crime model, they concentrated exclusively on the relative frequency of adolescents and young adults in the population, which takes into account the pool of potential victims as well as offenders. Whereas Steffensmeier and Harer's techniques accounted for about two-thirds of the decline in motor vehicle theft and none of the decline in homicide, Cohen and Land's analysis accounted for about 26 percent of the year-to-year change in the vehicle theft series and about 58 percent of the change in the homicide series.

Based on Census Bureau projections of the U.S. population age composition into the 21st century, Cohen and Land cautiously forecasted generally declining homicide and vehicle theft rates for the post-1985 period into the mid-1990s to be followed by increases into the next decade. Noting that increases already had occurred in the homicide and motor vehicle theft rates for 1985 and 1986 after they concluded their analysis of crime trends in the 1946-1984 period, Cohen and Land (1987) further conjectured that these increases could be explained by three possible scenarios. One was that the increases were due to a short-term illegal “drugs/crime bubble,” which their models were not designed to capture. This conjecture proved somewhat prophetic relative to recent explanations of the high levels of crime reported in the late 1980s and the early 1990s.

SCARY PROJECTIONS OF INCREASING VIOLENT CRIME RATES FOR THE ECHO-BOOMERS IN THE 1990s

Instead of the predicted drop in crime trends through the 1980s, the American public enjoyed only a five-year hiatus from the surging crime trends of the previous two decades. The increasing violent crime rates in 1985 and 1986 noted by Cohen and Land (1987) continued to climb until 1993. Violent crime rates particularly spiked for teenage males. Since males ages 15-19 in, say, 1990 were born in the 1971-1975 period, they were members of the baby buster birth cohorts who, according to both the demographic standardization and the time-series analyses cited above, were expected to have relatively low crime rates. Yet it became evident in the late 1980s and early 1990s that these members of the tail end of the baby buster cohorts were not behaving with respect to participation in index crimes, especially violent crimes, as had been expected.

Responding to these increases, some criminologists projected that the age-specific violent crime trends of young offenders (ages 14-24) would continue to rise throughout the latter part of the 1990s and into the next

Suggested Citation:"Appendix B: The Indeterminancy of Forecasts of Crime Rates and Juvenile Offenses." National Research Council and Institute of Medicine. 2001. Juvenile Crime, Juvenile Justice. Washington, DC: The National Academies Press. doi: 10.17226/9747.
×

decade (Fox, 1996). This trend in violence among adolescents—particularly shocking to the public—raised serious concerns about the potential harm posed by these youths. In addition, some analysts argued that what had typically been only a threat to lower-class, inner-city dwellers, might become a reality for the rest of society. “Americans are sitting on a demographic crime bomb . . . . Despite the recent decline in murder rates, homicides committed by 14- to 17-year-olds between 1985 and 1993 increased by 165 percent (more for minority males). The next wave of homicidal and near-homicidal violence among urban youth is bound to reach adjacent neighborhoods, inner-ring suburbs, and even the rural heartland” (DiIulio, 1995a:15).

Prominent criminologists and policy scientists such as John J. DiIulio (1997), James A. Fox (1996), and James Q. Wilson (1995) also warned that rising violent crime trends would only worsen as the echo boomers aged into their crime-prone years—a phenomenon that would begin during the first two decades of the 21st century.5 Census Bureau population projections supported this contention (U.S. Bureau of the Census, 1985; 1995; 1996). The numbers of teenage males in America were due to climb by 1 million from 1995 to 2000. Based on extant cohort studies that estimated that 6 percent of the youthful population become high rate, repeat offenders, Wilson estimated that there would be 30,000 more serious offenders on the streets by the turn of the century. “Get ready,” he warned (Wilson, 1995:507).

Heeding Wilson's warning and expanding his depiction of this growing tide of youthful offenders, DiIulio coined the term “superpredators”— noting that today's offenders are worse than yesterday 's and that tomorrow's will be worse than today's. “According to Professor Wolfgang, . . . each male cohort has been about three times as violent as the one before it. We concur” (Bennett et al., 1996:29). DiIulio's (as well as Wilson's) characterization of the 21st century youthful offenders is nothing short of scary (Bennett et al., 1996:27):

America is now home to thickening ranks of juvenile “super-predators”— radically impulsive, brutally remorseless youngsters, including ever more preteenage boys, who murder, assault, rape, rob, burglarize, deal deadly drugs, join gun-toting gangs, and create serious communal disorders. They do not fear the stigma of arrest, the pains of imprisonment,

5  

Due to the large size of the baby boomer cohorts, even with lower birth rates than their parents, the number of children they bore is larger than the number of children in the baby buster years. Because these baby boomlet birth cohorts, born 1977-1995, thus reflect their parents' large cohorts, they often are referred to as echo boomers (Crispell, 1993). In the popular press, following the labeling of the cohorts who were born just before them as Generation X, the echo boomers have been dubbed “Generation Y.”

Suggested Citation:"Appendix B: The Indeterminancy of Forecasts of Crime Rates and Juvenile Offenses." National Research Council and Institute of Medicine. 2001. Juvenile Crime, Juvenile Justice. Washington, DC: The National Academies Press. doi: 10.17226/9747.
×

or the pangs of conscience. They perceive hardly any relationship between doing right (or wrong) now and being rewarded (or punished) for it later. To these mean-street youngsters, the words “right” and “wrong” have no fixed moral meaning.

Touting the success of tougher law enforcement efforts against adult offenders especially during the war on drugs (DiIulio, 1995b) and demanding the incarceration of youthful offenders as a minimum requirement for curbing the tide of violence among youthful offenders, DiIulio (1997) stated that most juvenile criminals still received no punishment for their crimes and that prosecutors and judges are unduly burdened with caseloads, which leaves them impotent against this struggle to bring justice to and incarcerate juvenile offenders. The bottom line for DiIulio (DiIulio, 1995a:16) is that “we must remain deadly serious about targeting hardened adult and juvenile criminals for arrest, prosecution, and incarceration.”6

IS AN IMPENDING EXPLOSION IN YOUTH VIOLENCE REALISTIC?

Besides the projected “baby boomerang” effect of the echo boomers on violent crime rates of the 21st century (Fox, 1996:1), there is little hard evidence that changes in other social and economic forces would exacerbate or relieve the forecasted explosion in youth violence. To be sure, the demographic force of increasing numbers of echo boomer adolescents and teenagers up to about the year 2010 is inexorable. Assuming further that age-specific delinquent and crime rates, especially violent crime rates, remain constant at the high levels experienced in the 1985-1993 period, it would appear inevitable that juvenile crimes would increase substantially, especially in the years 1996-2005. Assuming also that a constant proportion of birth cohorts become high rate, repeat offenders, Wilson 's conclusion that the numbers of such offenders in the youth population — and the associated numbers of offenses they commit—will increase dramatically and disturbingly during these years also appears indisputable.

With the benefit of several additional years of data, however, it is clear that the age-specific delinquent and crime rates of adolescents and teenagers rose dramatically in the 1985 to 1993 years (relative to the rates

6  

In spite of his call for enhanced law enforcement efforts, DiIulio (1997: A23) argues that the superpredators—“these more savage than salvageable young criminals could not and should not be punished into submission. Instead, the only responsible option is to try and save these typically abused, neglected, fatherless, Godless and impoverished children before it's too late, working mainly through the youth outreach efforts of local churches.”

Suggested Citation:"Appendix B: The Indeterminancy of Forecasts of Crime Rates and Juvenile Offenses." National Research Council and Institute of Medicine. 2001. Juvenile Crime, Juvenile Justice. Washington, DC: The National Academies Press. doi: 10.17226/9747.
×

that had been observed through the 1960-1985 period) and then began falling. This decline continued through 1996 and, evidently, based on preliminary UCR estimates, through 1997 and 1998 as well (Bureau of Justice Statistics, 1998). The reasons behind recently shrinking crime rates are as obscure today as were the reasons for the booming crime rates of the late 1980s and early 1990s circa 1990. Criminologists and politicians have speculated on the impetus behind the fluctuations in crime trends— each side of the liberal/conservative stance taking advantage of the numbers as providing support for their ideologies. Explanations offered for the 1985-1993 climb in youth violence include:

  • the reluctance of juvenile justice agencies to incarcerate youths (DiIulio, 1997);

  • prevalence of drug use and drug trafficking, especially crack cocaine (Blumstein, 1995);

  • availability of deadly weapons, especially firearm possession by youths (Blumstein, 1995);

  • casual attitudes about violence—resulting from “cumulative, desensitizing effects of media-glamorized violence” (Fox, 1996:2); and

  • ineffective socializing efforts of family, school, religion, and neighborhood, the absence of parental supervision, and the diminished role of the family (Bennett et al., 1996).

And what accounts for the declines in crime rates, especially violent and juvenile crime rates since 1994? Steffensmeier and Harer (1999) recently reviewed the effects of age composition and other forces on crime rates. They noted the following plausible explanatory factors:

  • reductions in drug use and stabilization of drug markets;

  • tougher laws and enforcement that have deterred and incapacitated offenders;

  • changes in crime opportunities—e.g., due to shifts in the population age structure towards more elderly, who rarely are exposed or have their property exposed to crime risk, improvements in domestic and commercial security, and changes from cash to credit card and electronic transactions;

  • a strong economy in the mid- to late 1990s and improvements in social and economic conditions;

  • greater police visibility and effectiveness through wide improvements in problem-oriented or community-oriented policing;

  • gang abatement programs; and,

  • with the aging of the boomers, a collective conscience shift toward greater civility and mediation.

Suggested Citation:"Appendix B: The Indeterminancy of Forecasts of Crime Rates and Juvenile Offenses." National Research Council and Institute of Medicine. 2001. Juvenile Crime, Juvenile Justice. Washington, DC: The National Academies Press. doi: 10.17226/9747.
×

What are the implications of these trends for crime rates in the first decade of the 21st century? Steffensmeier and Harer (1999) observed that other analysts (such as Fox, DiIulio, and Wilson in the publications cited above) have concentrated on the effects of the projected increase in the number of teenagers by 20 percent from 1995 to 2005—to roughly 30 million—on expected crime increases. They argued, however, that these scary forecasts considered only the changes in the size of the youth population and ignored projected shifts in the size of the middle-aged and elderly populations that are at low risk for crime. Again assuming that age-specific rates of offending remain constant through the forecast period, Steffensmeier and Harer updated their 1987 age-standardization analyses using the whole age structure of the population. This yielded projections of violent crimes that rise very slowly to the year 2010, rising about 5 percent from 1996 levels; see Figure B-3, which reproduces Figure 14 from Steffensmeier and Harer (1999). They similarly projected values for property crime rates that rise even more slowly, to about 4 percent from 1996 levels to the year 2010. Steffensmeier and Harer (1999) specifically rejected the forecast of a crime explosion in the first decade of the 21st century.

As with the other crime rate forecasts reviewed above, however, these projections assumed that age-specific arrest rates for juveniles continue at the levels observed in 1996 to the year 2010. This is the reason that

FIGURE B-3 Projected age-adjustment effects for person and property crimes to year 2010 (base year is 1996). Reproduction of Figure 14 from Steffensmeier and Harer (1999). Reprinted with permission.

Suggested Citation:"Appendix B: The Indeterminancy of Forecasts of Crime Rates and Juvenile Offenses." National Research Council and Institute of Medicine. 2001. Juvenile Crime, Juvenile Justice. Washington, DC: The National Academies Press. doi: 10.17226/9747.
×

Steffensmeier and Harer's projected increases for 1997 and 1998 already are inconsistent with UCR estimates of declines in violent and property crimes for 1997 and (preliminarily) 1998. If, in fact, these age-specific rates continue to decline, then the modest increases in violent and property crime rates projected by Steffensmeier and Harer could become even more modest or even turn into decreases. In any event, it almost surely will be the case that the age-specific arrest rates for juveniles will vary over these years. Accordingly, these projections should be considered expected values only, and some account should be taken of the uncertainly surrounding the production of the expected values.

THE NEED TO RECOGNIZE UNCERTAINTY IN FORECASTS OF CRIME AND JUVENILE OFFENSES

Based on the foregoing review of various efforts to forecast levels of crime, it is evident that the typical forecast consists of a “point estimate” (i.e., a specific number) of expected crime rates or numbers of offenders for each of a sequence of years in some forecast period. Furthermore, all of these forecasts either explicitly or implicitly assumed fixed curves of age-specific rates of offending—that is, they assumed that the rates of offending will remain fixed at each age across an age range from childhood to the eldest age group in the population.7 When the age-specific schedules in fact remains relatively fixed, as in the 1970s with the baby boomers aging through the teenage and young adult years of relatively high criminal offending, then such point estimates can be relatively accurate. The reason is straightforward —under such circumstances, the main forecasting task is to trace out the implications of changes in the age distribution of the population as projected by the Census Bureau. When, however, there are significant turning points or points at which age-specific rates of offending rise or fall significantly, then crime forecasts based on the assumption of fixed age-specific offending rates may be substantially off the mark. This occurred during the 1985-1993 period when age-specific offending rates for teenagers and young adults, due to what Cohen and Land (1987) labeled a short-term “drug bubble,” rose rapidly to historically high levels. The consequence was that the forecasts for the 1985-1995 period of Fox (1978), Cohen and Land (1987), and Steffensmeier and Harer (1987) for crime rates and numbers of offenses were far too low.

7  

Demographers refer to this as the age-specific schedule of event occurrence of a specific type, in this case criminal offending.

Suggested Citation:"Appendix B: The Indeterminancy of Forecasts of Crime Rates and Juvenile Offenses." National Research Council and Institute of Medicine. 2001. Juvenile Crime, Juvenile Justice. Washington, DC: The National Academies Press. doi: 10.17226/9747.
×

But offense rates for juveniles and young adults also changed rapidly in the 1994-1998 period—this time falling to levels not seen in some cases since the early 1970s. This rapid fall in age-specific offense rates again confounded analysts, who forecasted a scary wave of juvenile and young adult offending to begin in the mid-1990s. A case in point is the 1996 Bureau of Justice Statistics report, Trends in Juvenile Violence: A Report to the United States Attorney General on Current and Future Rates of Juvenile Offending by James A. Fox. This report focuses on trends in homicide, especially teenage homicide, from 1976 through 1994 and thus embodies the frightening rise in teenage homicide in the period 1985 to 1994. The Executive Summary (Fox, 1996) of the report notes the following “key statistical findings” (among others):

  • From 1985 to 1994, the rate of murder committed by teens, ages 14-17, increased 172 percent. The rate of killing rose sharply for both black and white male teenagers, but not for females.

  • By the year 2005, the number of teens, ages 14-17, will increase by 20%, with a larger increase among blacks in this age group (26%).

  • Even if the per-capita rate of teen homicide remains the same, the number of 14-17 year-olds who will commit murder should increase to nearly 5,000 annually because of changing demographics. However, if offending rates continue to rise because of worsening conditions for our nation's youth, the number of teen killings could increase even more.

Figure B-4, which reproduces Figure 15 from the report (Fox, 1996), illustrates this last point. Specifically, the lower bound of projected numbers of homicide offenders to the year 2005 (as shown by the lower dotted line in the figure), which is based on the assumption of no change in offending rates from those of 1994, rises to about 5,000. By contrast, the upper bound projection to 2005 in the figure (also shown by a dotted line), which is based on the assumption that the “recent trend ” (i.e., the trend observed in 1985-1994) of increases in the homicide rate for 14- to 17-year-olds persists, rises to nearly 9,000.

As noted, however, the rising trend in the teenage homicide offending rate of 1985-1993 did not persist. The downturn in the teenage homicide rate in 1994 continued through 1995 and 1996. This fact was noted by Fox (1997) in his follow-up Bureau of Justice Statistics report, Trends in Juvenile Violence: 1997 Update. Remaining cautious, however, Fox (1997:1) states that “it is premature to suggest that the problem of teen violence has disappeared.” Nonetheless, the continuing downturn of teenage homicide rates through the mid-1990s brought the number of offenders to a level of about 3,000 by 1996—well below the lower bound of about 4,000

Suggested Citation:"Appendix B: The Indeterminancy of Forecasts of Crime Rates and Juvenile Offenses." National Research Council and Institute of Medicine. 2001. Juvenile Crime, Juvenile Justice. Washington, DC: The National Academies Press. doi: 10.17226/9747.
×

FIGURE B-4 Forecast of homicide offenders, ages 14-17. Reproduction of Figure 15 from Fox (1996).

projected for 1996 in Fox (1996), as reproduced in Figure B-4. Accordingly, Fox (1997) presented a revised forecast of teenage homicide offenders, which is reproduced in Figure B-5. This revised forecast of the numbers of teen perpetrators of homicide assumes constant levels of age/race/sex-specific offending rates at the 1994-1996 average. It can be seen from Figure B-5 that the upper and lower bounds of Figure B-4 again are replaced by a single projection series. Regarding the forecast in Figure B-5, Fox (1997:1) states: “If only because of demographic shifts, the annual number of teen killers could once again surpass 4,000, just as it did in the early 1990s in the midst of the last youth crime wave.”

The purpose of citing this latest round of crime forecasts by James Fox is not to dwell on their relative accuracy. Rather, the objective is to use them to make two points about extant forecasts of crime levels in the United States. First, forecasts into the future must depart from some base or jump-off year. As such, they may embody continuity biases or a ten-

Suggested Citation:"Appendix B: The Indeterminancy of Forecasts of Crime Rates and Juvenile Offenses." National Research Council and Institute of Medicine. 2001. Juvenile Crime, Juvenile Justice. Washington, DC: The National Academies Press. doi: 10.17226/9747.
×

FIGURE B-5 Forecast of teen homicide offenders. Reproduction of Figure 1 from Fox (1997). Counts include both known perpetrators and an estimate of unidentified perpetrators.

dency to be unduly influenced by, and to project into the future, the most recent trends in crime levels and rates observed in the years immediately prior to the base year of the forecasts.8 This is evident, for example, in crime forecasts from the 1980s, which assumed that the relatively low age-specific offense rates of the mid-1980s would continue into the future. It also is evident in the forecasts in Fox (1996), and even those of Fox (1997), which did not anticipate the continued downturn of juvenile violent offending rates in the mid-1990s. Second, the focus on point forecasts ignores the uncertainty in crime forecasts, or the fact that the eventually observed crime rates almost surely will not track along the paths of expected values described in the forecasts. On this subject, criminologists can learn from demographers, who long have recognized uncertainty in their forecasts. We now turn to some illustrations of how this can be done and what the implications are for forecasting levels of juvenile crime offenders into the next decade.

8  

Continuity biases in forecasts are not unique to crime forecasts; for evidence of this in demographic projections, see Stoto (1983) and Lutz et al. (1999).

Suggested Citation:"Appendix B: The Indeterminancy of Forecasts of Crime Rates and Juvenile Offenses." National Research Council and Institute of Medicine. 2001. Juvenile Crime, Juvenile Justice. Washington, DC: The National Academies Press. doi: 10.17226/9747.
×

SOME HIGH AND LOW BOUNDS ON JUVENILE HOMICIDE OFFENSES TO THE YEAR 2007

Demographers have been in the business of producing demographic forecasts or projections longer than criminologists. And they also have had their share of forecasting blunders. After World War II, demographers failed to anticipate the baby boom. At the end of the baby boom in the mid-1960s, they then failed to anticipate how rapidly and far fertility would fall in the 1970s (see, e.g., Lee, 1999, for a review of past major forecasting errors by demographers). On the mortality side, demographic forecasts in the early 1970s tended to assume that period of stable adult and elderly death rates from the late 1950s to the late 1960s would continue indefinitely into the future. Adjusting to these forecasting errors, however, demographers have begun to recognize that large-scale social systems are governed by complex nonlinear interactions like those for weather, climate, and ecology (Land and Schneider, 1987; see, e.g., Lutz et al., 1999). As such, these systems may have chaotic elements and intrinsic limits to predictability. Accordingly, for some time, demographers have been developing various ways to incorporate uncertainty into their forecasts. Criminologists can learn from studying these approaches to dealing with uncertainty.

Both forecasters and users of forecasts would like to know how much confidence to place in different forecasts. As noted by Ahlburg and Lutz (Ahlburg and Lutz, 1999:10), there are three main approaches to the presentation of the degree of uncertainty in demographic forecasts: (1) variants and scenarios, (2) stochastic forecasts, and (3) the combination of statistical approaches with expert judgment.9

The variants approach is the conventional method applied by demographers to produce high, medium, and low projections of expected population size (usually by age, sex, and race) by year into the future (usually 50 to 100 years). The variants approach—often with several variations on high, medium, and low series—still is the methodology employed by the Bureau of the Census for projections of the U.S. population into the 21st century. This method consists of choosing a combination of assumptions about the components of demographic change (fertility, mortality, and migration) that are internally consistent and represent paths of likely outcomes for population under certain conditions without specifying any probabilities of occurrence.

9  

For surveys of the state of the art of demographic forecasting methods as of the 1980s and early 1990s, see Land (1986) and Ahlburg and Land (1992); Lutz et al. (1999) present a collection of articles on more recent contributions.

Suggested Citation:"Appendix B: The Indeterminancy of Forecasts of Crime Rates and Juvenile Offenses." National Research Council and Institute of Medicine. 2001. Juvenile Crime, Juvenile Justice. Washington, DC: The National Academies Press. doi: 10.17226/9747.
×

If the variants are designed to demonstrate the future consequences of certain specified conditions, then they are called scenarios. A set of scenarios can be chosen to predict the most likely outcome (usually designated the “middle” variant) and also less likely but possible outcomes (usually designated “high” and “low” variants). The scenarios correspond to particular sets of conditions determined in part by policies and in part by possible outcomes of uncontrolled societal conditions or trends. In this way, scenarios are like simulations: they show the effects of changing a policy or the working out of societal conditions or trends.10 The high and low projection series also can be viewed as forming projection cones (since they typically expand in width with successive years into the future from the base or jump-off year of the projection series), within which it is considered highly likely that the actual historically observed population numbers of future years will lie. 11 A methodological problem in the use of scenarios is that choices of certain values for some assumptions can imply unreasonable values for others, and the approach can give probabilistically inconsistent indications of uncertainty (Lee, 1999).

Statistical or stochastic approaches to the incorporation of uncertainty into population forecasting tend to be of two general types: forecasts that include probability distributions and forecasts generated by probabilistic population renewal (also called stochastic population forecasts). Lee (1999) argues that only fully probabilistic population forecasts from stochastic renewal models are capable of producing internally consistent probability distributions. Examples of the stochastic approach to population forecasting are Ahlo (1990), Lee (1993), Lee and Carter (1992), and Lee and Tuljapurkar (1994). The main drawbacks to the widespread use of the stochastic approach are its substantial data requirements and the levels of expertise they require of both the forecaster and the user.

A third approach to population forecasting that has emerged in the 1990s is the use of expert opinion to calculate uncertainty by combining

10  

Indeed, it is for this reason that demographers typically refer to their numbers as “projections,” reserving the term “forecast” for the particular scenario or variant a user chooses as most plausible.

11  

Just how likely is it that an observed historical population series will fall within a typical demographic high and low projection series? Do they correspond to the conventional + 2 sigma (i.e., 95 percent) confidence intervals of statistics? Stoto (1983) compared projected and actual U.S. population totals and differences in projected and observed growth rates for Bureau of the Census high-low projection series made every five years for jump-off years 1945 through 1970 for target years 1950 through 1975. He concluded that the high-low projection series corresponded to two-thirds rather than 95 percent confidence intervals. That is, the observed population growth rates for each of these target years were within the respective high-low bounds about two-thirds of the time.

Suggested Citation:"Appendix B: The Indeterminancy of Forecasts of Crime Rates and Juvenile Offenses." National Research Council and Institute of Medicine. 2001. Juvenile Crime, Juvenile Justice. Washington, DC: The National Academies Press. doi: 10.17226/9747.
×

statistical approaches with expert judgment. One variation of this approach consists of asking a group of interacting experts to give both a point estimate and a range for fertility, mortality, and migration (Lutz et al., 1999). Another variation applies a formal Bayesian statistics framework to the combination of expert judgments in demographic forecasting (Daponte et al., 1997). One advantage of this general approach is that the combination of subjective probability distributions of a number of experts to form one joint predictive probability distribution diminishes the danger of individual bias. This approach may be particularly useful for forecasting when structural changes or unanticipated events need to be factored into the forecasts. Its main drawback is the difficulty of eliciting the necessary input from experts.

A careful and sophisticated application of the stochastic and combined stochastic-expert judgment approaches to the production of forecasts of crime levels and rates for a decade or two into the future clearly requires a large research project (or projects) and is beyond the scope of this paper. However, the application of the variants/scenarios forecasting recipe combined with a dash of expert judgment can be illustrated. For this, we focused on the construction of plausible national projections of expected numbers of male teenage (ages 14-17) homicide offenders—as well as upper and lower bounds for the expected numbers—for each year from 1998 to 2007.12 This is the age group and the crime that led to the scary projections of DiIulio, (1995b), Fox (1996), and Wilson (1995) reviewed above. It thus is an instructive exercise to examine the plausibility of the assumptions necessary to produce the high-level wave of teen-age homicide offenders cited by these analysts. Since the last year for which official estimates of homicide offending rates for this age group are available is 1997, we used 1997 as a jump-off year for the projection series and constructed high and low projection series annually for 10 years from 1998 to the year 2007.

To generate the high and low projection series, we first accessed homicide offending rate time series for the 14-17 age group provided in

12  

Only the results of our projection exercises for annual numbers of teenage homicide offenders are reported here. However, we also have produced high and low projection series of numbers of offenders for the years 1998 to 2007 for the following crimes and population-age groups: white male homicide offenders (ages 18-24, 25-59), black male homicide offenders (ages 18-24, 25-59), all violent offenders (ages 10-17, 18-24, and 25-59), all property offenders (ages, 10-17, 18-24, 25-59), white violent offenders (ages 0-17), black violent offenders (ages 0-17), white property offenders (ages 0-17), and black property offenders (ages 0-17). Generally, the results from the projection cones for these other crimes are comparable to those for teenage homicide as reported in Figures B-6 and B-7. They are available from the authors on request.

Suggested Citation:"Appendix B: The Indeterminancy of Forecasts of Crime Rates and Juvenile Offenses." National Research Council and Institute of Medicine. 2001. Juvenile Crime, Juvenile Justice. Washington, DC: The National Academies Press. doi: 10.17226/9747.
×

Fox (1997) for the years 1980 through 1997.13 These rates were estimated by Fox from FBI Supplementary Homicide Reports and include both known perpetrators as well as an estimated share of unidentified perpetrators computed by a statistical imputation procedure. Since almost all teenage homicide offenders are males, we focused on projections for males only. Furthermore, since the white male and black male rates are quite different, we constructed projections for these two groups separately. Second, we examined the ages 14-17 black male and white male homicide rates for the years 1980-1997 to determine the highest and lowest rates observed during this period. These are:

Population Category

Year and Low Homicide Rate

Year and HighHomicide Rate

Black males, 14-17 years old

1984 - 47.6 per 100,000

1993 - 244.1 per 100,000

White males, 14-17 years old

1984 - 9.4 per 100,000

1994 - 22.4 per 100,000

Consistent with previous characterizations of trends in crime over the past two decades reviewed above, it can be seen that 1984 was the low year for homicide rates for both race groups in the 1980-1997 period—just before the 1985-1993 upsurge in young male homicide rates. By comparison, the high years occurred in 1993 for black male teenagers and 1994 for white male teens.

As a third step, we next conjectured about the highest and lowest bounds that these rates could plausibly attain in the 10 years 1998-2007 — given (1) the “observed” time series of homicide offending rates for the observation period 1980-1997 and (2) the high and low rates noted above. In doing so, we had the advantage, compared to Fox (1997), of information about the teenage homicide offending rates for 1997 as well as preliminary UCR data on aggregate homicide levels for 1998. These preliminary data indicate overall declines in homicide of about 7 percent from 1997 to 1998. These overall homicide trends have not yet been transformed into age-specific offending rates (as in Fox, 1997). However, we know from Fox's (1997) data that homicide declines for teenagers in the mid-1990s were on the order of 2 to 2.5 times larger than the declines in the overall homicide levels.

13  

Fox actually provides estimates of homicide offending rates by age back to 1976. But, for consistency with high and low projection series, we generated for other crime categories, we used Fox's data series only back to 1980. We also used the update for 1997 of teenage homicide offending rates provided by the Federal Bureau of Investigation at the Internet address: http://www.fbi.gov/ucr/prelim98.pdf.

Suggested Citation:"Appendix B: The Indeterminancy of Forecasts of Crime Rates and Juvenile Offenses." National Research Council and Institute of Medicine. 2001. Juvenile Crime, Juvenile Justice. Washington, DC: The National Academies Press. doi: 10.17226/9747.
×

Assuming this pattern has continued, these overall homicide rate declines suggest that homicide offending rates for black and white males ages 14-17 continued to decline by 15 to 20 percent in 1998. Although informal observations suggest the declines in overall and teenage homicide offending have continued through mid-1999 (the date of construction of our projections), it is impossible to know how long this downward trend in teenage homicides will continue. But it is clear that the lower bound of a plausible projection cone for the annual numbers of homicides for these two teenage populations must accommodate the continuing rapid decline in 1998 and possibly for a few additional years into the future. Accordingly, we chose a lower bound to which the homicide offending rates could decline of 25 percent of the lowest rate observed during the 1980-1997 period. Furthermore, since the declines in the 1997 and 1998 offending rates have continued the rapid pace of the mid-1990s, we chose to allow the lower bound for the projection cones to decline linearly to this rate within five years from the jump-off year, i.e., from 1998 to 2002, and then remain fixed for the years 2003 to 2007.

With respect to plausible upper bounds for the homicide offending rates, we conjectured that if teenage homicide offending rates were to reach 125 percent of the highest rates observed during the 1980-1997 period, the public outcry would be so strong that all sorts of societal homeostatic mechanisms—from even more active policing to more active involvement of school, religious, community, and civic organizations in juvenile crime prevention programs—would come into play to stabilize the rates and pressure them down again. And yet the possibility of a new wave of teenage homicide offending associated with the coming of age of the echo boomers—like that of the 1985-1993 period—should not entirely be ruled out of a projection cone designed to contain with a high probability the possible range of future teen homicide offending. Accordingly, we set the upper bound for our projection series to 125 percent of the highest rates reported above for each race group, 1980-1997. We also chose to allow the high bound for the projection cones to increase linearly to this level over a five-year period beginning in 1998 and then remain fixed for 2003 to 2007.

The fourth step in the calculation of our projection cones consisted of multiplying the projected homicide offending rates for the entire 1998 through 2007 period by Census Bureau population race-specific projections for the 14-17 age group (U.S. Census Bureau, 1996). The results of the projected upper and lower bounds for the years 1998-2007 are displayed in Figures B-6 (black males) and B-7 (white males) together with the observed series (based on the rates provided in Fox, 1997) for the years 1980 to 1997.

Suggested Citation:"Appendix B: The Indeterminancy of Forecasts of Crime Rates and Juvenile Offenses." National Research Council and Institute of Medicine. 2001. Juvenile Crime, Juvenile Justice. Washington, DC: The National Academies Press. doi: 10.17226/9747.
×

FIGURE B-6 Black male homicide offenders, ages 14-17: Observed series 1980 to 1997 with projected upper and lower bounds to 2007.

FIGURE B-7 White male homicide offenders, ages 14-17: Observed series 1980 to 1997 with projected upper and lower bounds to 2007.

Suggested Citation:"Appendix B: The Indeterminancy of Forecasts of Crime Rates and Juvenile Offenses." National Research Council and Institute of Medicine. 2001. Juvenile Crime, Juvenile Justice. Washington, DC: The National Academies Press. doi: 10.17226/9747.
×

Several observations can be made about these projection cones. First, it can be seen that the projection cones widen fairly rapidly from the jump-off year of 1997 to the year 2002. This is consistent with our decision to allow the projected lower and upper bounds of homicide offending rates for these two populations to reach the respective limits in five years. Second, at the same time, on the basis of the preliminary evidence regarding homicide trends from 1997 to 1998, and evidently from 1998 to 1999, cited above, the lower bounds of the projection cones decline just rapidly enough to envelop the expected numbers of teenage homicide offenders for these two years. Third, if indeed these declines are on the order of magnitude we expect, this will reduce the numbers of teenage black and white male homicide offenders to levels last seen in the middle 1980s. Fourth, it is evident that the effects of allowing the teenage homicide offending rates to grow to a maximum of 125 percent of the highest rates observed in the 1980-1997 period by the year 2002 are to produce upper bounds that increase by 2002 to about 3,800 for black males and about 1,800 for white males. Fifth, after 2002, the lower and upper bounds for both population groups continue to exhibit slow growth to 2007. Since the homicide offending rates are held constant for these years, these increases are due to continuing growth in the teenage populations at risk during this remaining five years of the forecast period.

Since we approached this projections exercise primarily from a variants/scenarios perspective rather than as an attempt at the formal combination of stochastic forecasting with expert judgment, we have not sampled expert opinion about the probabilities that should be attached to the high and low bounds of our projection cones. However, based on the historical record of juvenile homicide offending rates, we believe they would contain future numbers of teenage homicide offenders with a high (.9 or .95) probability.

Within the confines of the broad upper and lower bounds for the projection cones plotted in Figures B-6 and B-7, we also can describe the trajectories of expected values as well as the probability surfaces for various paths of juvenile homicide offenders across the years shown in the graphs. For us, these probability densities initially are highest along ridges—corresponding to the paths of expected values of the series (i.e., the paths of the annual numbers of offenders we consider most likely)— running close to the lower bounds of the graphs. This is necessary in order to accommodate what evidently are continuing declines in juvenile homicide offenses in 1998 and 1999 (despite highly visible and shocking mass shootings in public middle and high schools during these years). Nonetheless, because of the inherent unpredictability of the series plotted in the figures, we also allow for small but nonzero probability densities (corresponding to the possibility that they could occur) of numbers of

Suggested Citation:"Appendix B: The Indeterminancy of Forecasts of Crime Rates and Juvenile Offenses." National Research Council and Institute of Medicine. 2001. Juvenile Crime, Juvenile Justice. Washington, DC: The National Academies Press. doi: 10.17226/9747.
×

offenders in the middle and upper reaches of the projection cones for these two years.

For the years 2000 through 2002, we then allow the ridges containing our most likely scenarios/expected values of juvenile homicide offenders to continue to decline, but at decelerating rates. Because of greater uncertainty with increasing years into the forecast period, however, we concentrate the probability densities somewhat less in this region of the projection cones. For the years 2003 to 2007, we then locate the probability ridges along slightly increasing lines toward the middle part of the projection cones, due to the larger numbers of echo-boomer juveniles at risk of homicide offending in these years. We also flatten the probability surface for our forecasts for these years even more—allowing for somewhat higher probabilities that there may be another upsurge in juvenile homicide offenders later in the 10-year forecast horizon.

These exercises in the calculation of expected values, probability density surfaces, and high and low rate projection bounds for juvenile homicide offenders also can be used to assess the plausibility of the forecasts of homicide and other crimes by Fox (1996, 1997) and Steffensmeier and Harer (1999) summarized above in Figures B-3 and B-5. As noted earlier, the forecasts by these analysts were in the form of single expected values for each of a series of years into the first decade of the 21st century. In contrast, the forecast cones exhibited in Figures B-6 and B-7 are in the spirit of the conventional demographic high-medium-low projection scenarios or variants. As such, they provide lower and upper bounds within which the expected values of single-series forecasts should be contained. Recall that the forecasts of Steffensmeier and Harer (1999) did not focus on teenage homicides specifically but pertained to the general categories of person and property index crimes. Assume, however, that the slow increases in the person index crime rate that they expect over the years 1997 to 2010 (to a maximum increase of about 5 percent by 2010) also imply slow increases in teenage homicide offending rates. Then it clearly is the case that the Steffensmeier and Harer forecasts would fall well within the upper and lower projection series exhibited in Figures B-6 and B-7. In fact, this even would be true if teenage homicide rates over the projection period grow at twice the general rate of increase Steffensmeier and Harer expect for person crimes.

A somewhat more direct comparison can be made between Fox's single-expected-value forecast series and the projection cones in Figures B-6 and B-7 by summing the bounds in these figures to compare with the non-race-specific forecasts of total teenage homicide offenders reproduced in Figures B-4 and B-5 above. Specifically, the upper bounds of our projection cones in 2005 sum to a total number of teenage homicide offenders of about 6,200, which is well below the approximately 8,500 upper bound

Suggested Citation:"Appendix B: The Indeterminancy of Forecasts of Crime Rates and Juvenile Offenses." National Research Council and Institute of Medicine. 2001. Juvenile Crime, Juvenile Justice. Washington, DC: The National Academies Press. doi: 10.17226/9747.
×

of Fox's (1996) forecast reproduced above in Figure B-4. Our upper bound for 2005 does, however, contain Fox's (1997) forecast for this year of approximately 4,000. But it also is the case that even the latter forecast requires a considerable growth in homicide offending rates for the two teenage groups in Figures B-6 and B-7. Put otherwise, Fox's (1997) forecast lies in the upper regions of the projection cones of Figures B-6 and B-7. Thus, his 1997 forecasts are not entirely implausible, but, in view of the apparent continuing declines in homicide in 1997 and 1998, perhaps not as plausible as forecasts that fall further within our upper and lower bounds projection series.

CONCLUSIONS

Criminologists have engaged in a number of attempts to forecast both numbers of criminal offenders and crime rates in the United States over the past three decades. In addition to their sheer intellectual interest, there are other reasons for an increasing interest in crime forecasts, such as the policy need to plan for resources for the juvenile and criminal justice systems. Our review of several existing contributions to the crime forecasting literature suggests, first of all, that these forecasts often contain continuity biases, i.e., are heavily influenced by recent trends in crime rates in the years just prior to the period for which the forecasts are made. Admittedly, forecasts of crime rates/offenses have various purposes, one of which could be the projection of recent trends into the future in order to draw out their implications (as in the case of the Fox, 1996, projections). However, to the extent that crime forecasts are meant to go beyond drawing out the implications of recent trends to represent likely paths that crime rates and offenses may take, they should attempt to minimize, or at least be cognizant of, the effects of continuity bias on the forecasts.

A second characteristic of existing crime forecasts is that they typically produce only single-expected-value projections of juvenile or adult crime rates into the future and fail to recognize the uncertainty surrounding such forecasts. It is clear, however, that just because the projection of recent levels of crime rates or trends therein into the immediate future suggests that, say, juvenile crime will rise by a certain percentage does not mean that juvenile crime will in fact rise by that amount. In other words, there is a lot of indeterminancy or, in statistical terminology, uncertainty in crime forecasts. Future efforts in crime forecasting should recognize this and attempt to provide bounds on levels of uncertainty in the forecasts.

We have illustrated some ways in which this can be done by adapting and applying the high-medium-low scenarios approach widely employed in demography to the projection of annual numbers of juvenile homicide

Suggested Citation:"Appendix B: The Indeterminancy of Forecasts of Crime Rates and Juvenile Offenses." National Research Council and Institute of Medicine. 2001. Juvenile Crime, Juvenile Justice. Washington, DC: The National Academies Press. doi: 10.17226/9747.
×

offenders for the years 1998 to 2007. Based on the high-low projection cones reported above, we concluded that scary forecasts of a new wave of juvenile homicide offenders in the first decade of the 21st century are relatively implausible. Rather, it is more likely that the numbers of juvenile male homicide offenders will continue to decline during the period 1998 to 2002 and then increase slightly thereafter to the year 2007. However, the possibility that members of the relatively large echo-boomer birth cohorts will develop—as they age into their teen and young adult years—a new fad or fashion related to dangerous and violent interpersonal activities (such as a new attachment to illegal drugs) and, accordingly, that the annual numbers of teenage homicide offenders will again increase in the 1998-2007 period cannot be entirely ruled out.

Our exercise in forecasting juvenile homicide offenders also illustrates two additional implications of uncertainty in forecasts of crime rates and offenders. These are that the periods over which crime forecasts are made should be as short as possible and that the forecasts should be updated as often as possible (i.e., when new or updated data are available). As noted above, large-scale social systems have elements of complexity or nonlinear dynamics and chaos that militate against the accuracy of long-term forecasts. In practical terms, this means that forecasting cones (upper and lower bounds) for enveloping the ranges within which crime forecasts are likely to fall with a high probability will grow very rapidly from the base year into the future. For instance, the forecasting cones for juvenile homicide offenders developed herein lose their informative content very rapidly (i.e., the probability surfaces of the projections become less and less concentrated around the expected values). By the fifth year into the forecasting period, the probability density surfaces for these forecasts have diffused quite extensively. This corresponds to the fact that juvenile homicide offending rates can change very rapidly. To take this into account, the time periods of the forecasts should be relatively short and the forecasts should be revised when new information becomes available. For most police, court, and penal components of the juvenile and criminal justice systems, this is not particularly problematic, as forecasts typically are necessary only for one- or two-year government budgeting cycles. Only occasionally are projections more that five years into the future required for budgeting and/or planning purposes.

In sum, future forecasts of crime rates/offenders should:

  • guard against continuity biases or at least recognize their presence in projections the objective of which is to draw out implications of recent trends;

Suggested Citation:"Appendix B: The Indeterminancy of Forecasts of Crime Rates and Juvenile Offenses." National Research Council and Institute of Medicine. 2001. Juvenile Crime, Juvenile Justice. Washington, DC: The National Academies Press. doi: 10.17226/9747.
×
  • take into account uncertainty in the forecasts by developing upper and lower bounds within which paths of crime rates and offenses are expected to lie;

  • shorten the forecast time period as much as the purpose for which the forecasts are produced will allow; and

  • be updated as often as possible.

The incorporation of these characteristics into crime forecasts should result in more realistic uses and assessments of the forecasts.

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Suggested Citation:"Appendix B: The Indeterminancy of Forecasts of Crime Rates and Juvenile Offenses." National Research Council and Institute of Medicine. 2001. Juvenile Crime, Juvenile Justice. Washington, DC: The National Academies Press. doi: 10.17226/9747.
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1997 Jail alone won't stop juvenile super-predators. The Wall Street Journal (June 11): A23.

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Lee, R.E., and L. Carter 1992 Modeling and forecasting the time series of U.S. mortality. Journal of the American Statistical Association 87: 659-671.

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President's Commission on Law Enforcement and Administration of Justice 1967 Task Force Report: Crime and its Impact: An Assessment. Washington, DC: U.S. Government Printing Office.

Sagi, P.C., and C.F. Wellford 1968 Age composition and patterns of change in criminal statistics. The Journal of Criminal Law, Criminology and Police Science 59(1): 29-36.

Steffensmeier, D., and M.D. Harer 1987 Is the crime rate really falling? Journal of Research in Crime and Delinquency 24: 23-48.

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Suggested Citation:"Appendix B: The Indeterminancy of Forecasts of Crime Rates and Juvenile Offenses." National Research Council and Institute of Medicine. 2001. Juvenile Crime, Juvenile Justice. Washington, DC: The National Academies Press. doi: 10.17226/9747.
×

Stoto, M.A. 1983 The accuracy of population projections. Journal of the American Statistical Association 78: 13-20.

U.S. Census Bureau 1985 Estimates of the population of the United States and components of change by age, sex, and race: 1980 to 1984. Current Population Reports, Series P-25, No. 965. Washington, DC: U.S. Government Printing Office.

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Suggested Citation:"Appendix B: The Indeterminancy of Forecasts of Crime Rates and Juvenile Offenses." National Research Council and Institute of Medicine. 2001. Juvenile Crime, Juvenile Justice. Washington, DC: The National Academies Press. doi: 10.17226/9747.
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Even though youth crime rates have fallen since the mid-1990s, public fear and political rhetoric over the issue have heightened. The Columbine shootings and other sensational incidents add to the furor. Often overlooked are the underlying problems of child poverty, social disadvantage, and the pitfalls inherent to adolescent decisionmaking that contribute to youth crime. From a policy standpoint, adolescent offenders are caught in the crossfire between nurturance of youth and punishment of criminals, between rehabilitation and "get tough" pronouncements. In the midst of this emotional debate, the National Research Council's Panel on Juvenile Crime steps forward with an authoritative review of the best available data and analysis. Juvenile Crime, Juvenile Justice presents recommendations for addressing the many aspects of America's youth crime problem.

This timely release discusses patterns and trends in crimes by children and adolescents--trends revealed by arrest data, victim reports, and other sources; youth crime within general crime; and race and sex disparities. The book explores desistance--the probability that delinquency or criminal activities decrease with age--and evaluates different approaches to predicting future crime rates.

Why do young people turn to delinquency? Juvenile Crime, Juvenile Justice presents what we know and what we urgently need to find out about contributing factors, ranging from prenatal care, differences in temperament, and family influences to the role of peer relationships, the impact of the school policies toward delinquency, and the broader influences of the neighborhood and community. Equally important, this book examines a range of solutions:

  • Prevention and intervention efforts directed to individuals, peer groups, and families, as well as day care-, school- and community-based initiatives.
  • Intervention within the juvenile justice system.
  • Role of the police.
  • Processing and detention of youth offenders.
  • Transferring youths to the adult judicial system.
  • Residential placement of juveniles.

The book includes background on the American juvenile court system, useful comparisons with the juvenile justice systems of other nations, and other important information for assessing this problem.

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