Predicting the 2013 Saint Louis City Homicide Rate

1. Predicting the 2013 Saint Louis City Homicide Rate Spencer Schneidenbach ShaileshLanjewar Xun Zhou Ben Holtman

2. 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/S0049089X10001882 http://www.sciencedirect.com/science/article/pii/S0049089X12002554

3. 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.short http://onlinelibrary.wiley.com/doi/10.1111/j.1533-8525.2003.tb00536.x/abstract

4. National gang trends Source: FBI 2011 National Gang Threat Assessment – Emerging Trends

5. Missouri gang trends Source: FBI 2011 National Gang Threat Assessment – Emerging Trends

6. 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

8. Data selection principle • Timeliness • - 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?

9. 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

10. 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

11. 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

12. 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

13. 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

14. 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

15. 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

16. Decision point • Rolling average it is • Regression model can’t be trended • Best model based on all available data

17. Example model • Rolling average it is • Best model based on all available data • Our 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

18. Measuring the Model

19. Our Predictions

20. Conclusion • Prediction is difficult

21. QUESTIONS?

22. 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