1. Small area estimation of violent crime victim rates in the Netherlands
Bart Buelens, Thijs Benschop
Statistics Netherlands
NTTS, Brussels Feb 2009

2. National Safety Monitor (NSM)
Crime, satisfaction with police, feelings of unsafety
Annual survey conducted in 1st quarter among people aged 15+ living in NL
Mixed mode telephone – personal interviews
Target response 750 per Police Zone (PZ)
Equal fractions per municipality in each PZ
25 PZs, target pop size approx. 13 mln.
sample size approx. 19,000
Property and violent crime, used as a performance measure for police
Chief of police corps
Equal inclusion weights per PZ
About half a million people per PZ

3. NSM estimation Generalized regression estimator (GREG)
Age, gender, ethnicity, marital status, income, household size, urbanisation
Publication at various levels:
national
5 clusters of police zones ~ urbanization
police zones
high variance

4. Violent crime victim rate
victim at least once in last 12 months, of
physical assaults, sexual offences, intentional threats
using 2007 survey
higher or lower than country-wide average?
better or worse than last year?

5. Small area estimation
PZs are “small areas”: design based estimates not precise enough due to small sample size
Use models to borrow strength from other PZs
Area level linear mixed model
matching of register and survey data problematic so no unit level models possible at this stage
Area level is much better than no model, improvement from unit over area level models is smaller,
Matching of register and survey data problematic so no unit level possible at this stage
Random area effects do help

6. Linear Mixed Model (Fay-Herriot)
Estimation using EBLUP (Rao 2003)
Combination of direct and model based, asymptotically design based hence unbiased
MSE estimates available

7. Covariates Known for all PZs (from registers)
Police Register of Reported Offences
Violent crimes, property crimes, vandalism, traffic offences
Municipal Administration
Age, ethnicity, (gender)
Address density
Registered violent crimes different from surveyed violent crime: not all are reported, and survey answer to question whether reported is unreliable
Gender is not useful as we are using area level models: distribution male/female is approx the same everywhere.

9. Model selection Which model is best? Which measure is best?
log(m=25) = 3.2 so BIC gives higher penalty to more complex models
Which measure is best?

10. Model selection results

11. Model with 2 covariates: not very complex, yet good predictive power
Note there are only 25 areas so over fitting seems to occur at 3 covariates

12. Results Model estimates within margins of direct
Model estimates have lower margins
Something about 95% conf intervals: 1 in 20 true values expected to be out of c.i.

13. Conclusions & future work
Model based SAE: improved precision
Unit level models: matching of register and survey data required
Survey variables other than victim rates
Temporal change, stability
New Integral Safety Monitor with local oversampling: possibilities using SAE methods