PREDICTING THE 2013 SAINT LOUIS CITY HOMICIDE RATE SPENCER SCHNEIDENBACH SHAILESH LANJEWAR XUN ZHOU...
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Transcript of PREDICTING THE 2013 SAINT LOUIS CITY HOMICIDE RATE SPENCER SCHNEIDENBACH SHAILESH LANJEWAR XUN ZHOU...
PREDIC
TING T
HE
2013 SAIN
T LO
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CITY
HOMICID
E RAT
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I DE
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BACKGROUND
• Annual homicide rates for 157 large US cities
• Analyzed for 30 years – 1976 to 2005
• Factors
Resource deprivation/concentrated poverty
Higher income inequality
Higher percentage of divorced adult male population
Higher unemployment rates
• Study in 30 nations
• Significant association between poverty and homicide
Sources: http://www.sciencedirect.com/science/article/pii/S0049089X10001882http://www.sciencedirect.com/science/article/pii/S0049089X12002554
DIVERSITY
• Characteristics of neighborhoods
• Very significant in predicting homicide
• Conclusion:• immigrant concentration unrelated or inversely related
to homicide• language diversity consistently linked to lower homicide
• 15 years of data (1980-1994)• St. Louis• Homicide rate related to neighborhood characteristics• Patterns differ according to homicide subtypes – general
altercation, felony and domestic
Sources: http://hsx.sagepub.com/content/13/3/242.shorthttp://onlinelibrary.wiley.com/doi/10.1111/j.1533-8525.2003.tb00536.x/abstract
NATIONAL GANG TRENDS
Source: FBI 2011 National Gang Threat Assessment – Emerging Trends
MISSOURI GANG TRENDS
Source: FBI 2011 National Gang Threat Assessment – Emerging Trends
MISSOURI GANG TRENDS
Seems to be lower than other states with only 0-2 members per 1000 people
Rise in gang “promotional teams”
Increased gang use of social media directed towards youth
Presence small as it may be of 490 gangs according to the FBI Gang Threat Assessment
Source: FBI 2011 National Gang Threat Assessment – Emerging Trends
DATA SELECTION PRINCIPLETimeliness
- Annually? Quarterly? Monthly?
Sufficiency
- Sample size – St Louis City, at least 5 years, the factors can have potential impact on criminal
Level of detail or aggregation
- Amount for reported criminal annually, criminal ratio distribute by district and possible influence factors such as poverty level, education attainment, population, Income etc
Understandability
- Readable for the crime data.
Freedom from bias
- How to avoid that? Keep it simple
Decision relevance
- How to determine the boundary? Geographical? How many factors are relevant to the criminal occurs geographically?
DATA SELECTION PRINCIPLE
Comparability
- Each city is individual case for analytic, avoid comparing the other cites’ data and cut off the data which influenced by abnormal factors.
Reliability
- We can not control, however there may be un-reported and un- detected crime which can influence the analysis
Redundancy
- Mulit-resources?
Cost efficiency
- Costs concern update data annually
Quantifiability
- Use Ratio level data
Appropriateness of format
- Which is the appropriate way to demonstrate
DIMENSIONALITY OF MODELS
Representation
- Reported crime
Time Dimension
- How much of the activity of decision environment is being considered
Linearity of the Relationship
- Determine if categorized data are linear or nonlinear
Deterministic Versus Stochastic
- Linear regression , Stochastic modeling
Descriptive Versus Normative
- Descriptive - used for prediction
DIMENSIONALITY OF MODELS
Causality versus correlation
- How to determine? - use criminal distribution graph and the other possible factor which has the positive or negative relate on them
Methodology Dimension
- Complete enumeration, algorithmic, heuristic simulations and analytical
- Complete enumeration – large sample amounts required
- Algorithmic – extremeness' value method
- Heuristic - if math would not help
- Simulation – external influence? Hard to identify
- Analytical – speared parts for the whole process
MODELS WE CONSIDERED
Linear regression Model based on Census, American Community Survey
data Predict crime based on population factors
- Saint Louis Police Department Neighborhood Statistics- U.S. Census American Fact Finder Statistics
- American Community Survey- Poverty Level- Educational Attainment- Lack of Core Family Stability Single Parent Families – Mothers with
no husband present- Income- Race
MODELS WE CONSIDERED (CONT)
Linear Regression Census data
Research only occurs once a decade Hard to measure trends for predictions
American Community Survey Broken down at the macro level (entire city) Can’t measure by neighborhood, district
Conclusion: Still useful for identifying problem areas inside a city Best for a one-time “snapshot” to see what correlations exist and
attack those problems Largely outside the scope of what the SLMPD does
MODELS WE CONSIDERED (CONT)
Rolling average Model based on past homicides Weighs more recent data higher than other data
Pros Data is easily accessible and accurate Model is simple and pretty accurate
Cons Does not predict big, one time events Model data varies the more homicides are committed
MODELS WE CONSIDERED (CONT)
Rolling average District vs. neighborhood
SLMPD uses districts Most crime seems to be concentrated in several large
areas Districts it is
Quarters, months, years? Years – too macro Months – too micro – data is too wildly distributed Measuring by quarters provides a nice balance between
micro vs. macro and data accuracy
DECISION POINT
Rolling average it isRegression model can’t be trendedBest model based on all available data
EXAMPLE MODEL
Rolling average it is Best model based on all available dataOur model:
Prediction based on last 4 quarters Last quarter: weighted by 0.4 2nd last: 0.4 3rd last: 0.1 4th last: 0.1
MEASURING THE MODEL
1 2 3 4 5 6 7 8 90.0
1.0
2.0
3.0
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5.0
6.0
7.0
8.0
9.0
Homicide Predictions vs. Actual for Q4-2012
Pred Actual
Districts
Hom
icid
es
Microsoft Excel Worksheet
OUR PREDICTIONS
1 2 3 4 5 6 7 8 90.0
1.0
2.0
3.0
4.0
5.0
6.0
7.0
8.0
9.0
Homicide Predictions for Q1-2013
Districts
Pre
dic
ted H
om
icid
es
CONCLUSION
Prediction is difficult
QUESTIONS?
SOURCES• FBI 2011 National Gang Threat Assessment – Emerging Trends. http://
www.fbi.gov/stats-services/publications/2011-national-gang-threat-assessment
• Saint Louis Police Department Statistics - http://www.slmpd.org/Crimereports.shtml
• American Fact Finder - http://factfinder2.census.gov/faces/nav/jsf/pages/guided_search.xhtml
• Saint Louis Homicide Map - http://blogs.riverfronttimes.com/dailyrft/2013/01/st_louis_city_homicide_map_nextstl.php