BostonHomicide {strucchangeRcpp}

Youth Homicides in Boston

Description

Data about the number of youth homicides in Boston during the ‘Boston Gun Project’—a policing initiative aiming at lowering homicide victimization among young people in Boston.

Usage

data("BostonHomicide")

Format

A data frame containing 6 monthly time series and two factors coding seasonality and year, respectively.

homicides

time series. Number of youth homicides.

population

time series. Boston population (aged 25-44), linearly interpolated from annual data.

populationBM

time series. Population of black males (aged 15-24), linearly interpolated from annual data.

ahomicides25

time series. Number of adult homicides (aged 25 and older).

ahomicides35

time series. Number of adult homicides (aged 35-44).

unemploy

time series. Teen unemployment rate (in percent).

season

factor coding the month.

year

factor coding the year.

Details

The ‘Boston Gun Project’ is a policing initiative aiming at lowering youth homicides in Boston. The project began in early 1995 and implemented the so-called ‘Operation Ceasefire’ intervention which began in the late spring of 1996.

Source

Piehl et al. (2004), Figure 1, Figure 3, and Table 1.

From the table it is not clear how the data should be linearly interpolated. Here, it was chosen to use the given observations for July of the corresponding year and then use approx with rule = 2.

References

Piehl A.M., Cooper S.J., Braga A.A., Kennedy D.M. (2003), Testing for Structural Breaks in the Evaluation of Programs, The Review of Economics and Statistics, 85(3), 550-558.

Kennedy D.M., Piehl A.M., Braga A.A. (1996), Youth Violence in Boston: Gun Markets, Serious Youth Offenders, and a Use-Reduction Strategy, Law and Contemporary Problems, 59, 147-183.

Examples

data("BostonHomicide")
attach(BostonHomicide)

## data from Table 1
tapply(homicides, year, mean)
populationBM[0:6*12 + 7]
tapply(ahomicides25, year, mean)
tapply(ahomicides35, year, mean)
population[0:6*12 + 7]
unemploy[0:6*12 + 7]

## model A
## via OLS
fmA <- lm(homicides ~ populationBM + season)
anova(fmA)
## as GLM
fmA1 <- glm(homicides ~ populationBM + season, family = poisson)
anova(fmA1, test = "Chisq")

## model B & C
fmB <- lm(homicides ~ populationBM + season + ahomicides25)
fmC <- lm(homicides ~ populationBM + season + ahomicides25 + unemploy)

detach(BostonHomicide)