1. What is the social impact of Marijuana use? Prashant Foneska Ana Kostioukova Dominic Lo Prashant Foneska Ana Kostioukova Dominic Lo

2. Arguments for Legalization F Largest cash crop in California, with annual revenues approaching $14 billion. F A 10% pot tax would yield $1.4 billion in California alone. F Thousands of new jobs in agriculture, packaging, marketing and advertising. F Largest cash crop in California, with annual revenues approaching $14 billion. F A 10% pot tax would yield $1.4 billion in California alone. F Thousands of new jobs in agriculture, packaging, marketing and advertising.

3. F $68 billion per year on corrections, 1/3 nonviolent drug crimes. F $150 billion on policing and courts, and 47.5% of all drug arrests are marijuana-related.  Resources spent on violent crime. Arguments for Legalization

4. Does a link between marijuana use and crime/unemployment exist? What is marijuana’s impact versus alcohol and other illicit drugs? F Factors we considered: F population density F Median income F Education F Median age F Population age 18 -24 F Children in low income families F Marijuana use F Alcohol use F Other Illicit drug use

5. Sources of Data Background: http://www.time.com/time/nation/article/0,8599,1889021,00.ht ml (Time Magazine, CNN News) http://www.time.com/time/nation/article/0,8599,1889021,00.ht ml http://www.oas.samhsa.gov/ (Office of Applied Studies: National Study on Drug Use and Health) http://www.oas.samhsa.gov/ http://www.sfgate.com/cgibin/article.cgi?f=/c/a/2009/02/23/BAO41635 4C.DTL&type=politics&tsp=1 (San Francisco Chronicle) http://www.sfgate.com/cgibin/article.cgi?f=/c/a/2009/02/23/BAO41635 4C.DTL&type=politics&tsp=1 Independent Variables: http://www.csac.countries.org/ ( California State Association of Counties)http://www.csac.countries.org/ http://www.labormarketinfo.edd.ca.gov/?pageid=1008 (California Employment Development Department) http://publications.childrennow.org/ (Children Now)http://www.labormarketinfo.edd.ca.gov/?pageid=1008 http://publications.childrennow.org/ http://censtats.census.gov/cgi-bin/usac/usacomp.pl(US Census)http://censtats.census.gov/cgi-bin/usac/usacomp.pl http://ca.rand.org/stats/ (Rand California Statistics)http://ca.rand.org/stats/ Background: http://www.time.com/time/nation/article/0,8599,1889021,00.ht ml (Time Magazine, CNN News) http://www.time.com/time/nation/article/0,8599,1889021,00.ht ml http://www.oas.samhsa.gov/ (Office of Applied Studies: National Study on Drug Use and Health) http://www.oas.samhsa.gov/ http://www.sfgate.com/cgibin/article.cgi?f=/c/a/2009/02/23/BAO41635 4C.DTL&type=politics&tsp=1 (San Francisco Chronicle) http://www.sfgate.com/cgibin/article.cgi?f=/c/a/2009/02/23/BAO41635 4C.DTL&type=politics&tsp=1 Independent Variables: http://www.csac.countries.org/ ( California State Association of Counties)http://www.csac.countries.org/ http://www.labormarketinfo.edd.ca.gov/?pageid=1008 (California Employment Development Department) http://publications.childrennow.org/ (Children Now)http://www.labormarketinfo.edd.ca.gov/?pageid=1008 http://publications.childrennow.org/ http://censtats.census.gov/cgi-bin/usac/usacomp.pl(US Census)http://censtats.census.gov/cgi-bin/usac/usacomp.pl http://ca.rand.org/stats/ (Rand California Statistics)http://ca.rand.org/stats/

6. 15 California Regions Included in the Analysis

7. Descriptive Statistics Populati on % Unemp. Pop./sq mi Med. Inc % HS Grad Med. Age% 18- 24 0-17 LowMj. UseAlc. UseIllicit Use Mean656025. 2069 0.06275 8621 498.5517 241 53158. 7069 78.7396 5517 36.115517 24 9.1431 03448 0.444482 759 0.0827758 62 0.5249448 28 0.041625 862 Std. Error194799. 6796 0.00298 0813 169.8759 577 2236.3 53696 1.05336 4212 0.6080415 03 0.3251 14453 0.015614 403 0.0026831 46 0.0059512 43 0.000512 821 Median1809790.05798.550525. 5 80.935.49.20.430.08230.53230.0421 Mode#N/A0.0824848982.336.410.30.430.11430.53230.046 Std. Dev.148355 0.161 0.02270 1194 1293.736 75 17031. 56233 8.02218 2834 4.6307061 23 2.4759 97908 0.118915 751 0.0204342 27 0.0453233 19 0.003905 532 S. Variance 2.20092 E+12 0.00051 5344 1673754. 778 290074 115.5 64.3554 1742 21.443439 2 6.1305 65638 0.014140 956 0.0004175 58 0.0020542 03 1.52532E- 05 Kurtosis32.9371 7297 3.58105 6355 29.59782 899 1.3445 90518 - 0.51438 2955 - 1.0314828 06 2.0731 73024 - 0.557338 498 - 1.0606293 47 0.0367692 99 - 0.283866 649 Skewness 5.27068 8787 1.46506 1916 5.053458 472 1.0108 67219 - 0.62281 6024 0.3754243 46 0.7765 84806 - 0.030547 283 0.4882043 07 - 0.7526100 56 - 0.641289 2 Range103626 28 0.1287128179932.215.613.50.490.06190.17170.0145 Minimum12220.03423035659294.80.160.05240.42740.0315 Maximum103638 50 0.154871411215591.244.618.30.650.11430.59910.046 Sum380494 62 3.6428916308320 5 4566.92094.7530.325.784.80130.44682.4143 Count58

8. Predictions Type of VariablesExpected Sign for Crime Expected Sign for Unemployment Population per square mile (2005 estimate) + + Median Family Income – – % High School Graduates – – Median Age – + % population age 18-24 + + Children ( age 0-17) in low income families + + Marijuana + + Alcohol + + Other Illicit Drugs + +

9. Crime Regression

10. CoefficientsStandard Errort Stat Intercept4798.397251996.938172.40287 Pop./sq mi (2005 estimates)* 0.023480.042180.55670 Median Family Income-0.0165950.01026-1.61707 % of HS Graduates 2000 Census -10.3161315.06715-0.68467 Median Age-33.4932929.31520-1.14252 % Population 18-24-56.7788135.50606-1.59913 Children 0-17 in Low Income Families -1063.100661385.77276-0.76715 Marijuana Use (Past Month) -902.184984231.57732-0.21320 Alcohol Use (Past Month) 344.066542218.298460.15510 Illicit Drug Use12087.9812524232.668050.49882

11. Crime Findings F 1% increase in Marijuana use leads to 9 less felonies per 100,000 people F 1% increase in Alcohol use leads to 3-4 more felonies per 100,000 people F 1% increase in Other Illicit Drug use leads to 120 more felonies per 100,000 people. F 1% increase in Marijuana use leads to 9 less felonies per 100,000 people F 1% increase in Alcohol use leads to 3-4 more felonies per 100,000 people F 1% increase in Other Illicit Drug use leads to 120 more felonies per 100,000 people.

12. Unemployment Regression

13. CoefficientsStandard Errort Stat Intercept0.134570.075161.79033 Pop./sq mi (2005 estimates)* 2.12572E-061.58781E-061.33877 Median Family Income-3.51997E-073.86263E-07-0.91128 % of HS Graduates 2000 Census -0.002460.00057-4.33176 Median Age0.001580.001111.43563 % Population 18-24-0.000290.00134-0.22113 Children 0-17 in Low Income Families 0.002120.052160.04059 Marijuana Use (Past Month) -0.069840.15927-0.43848 Alcohol Use (Past Month)0.093220.083491.11642 Illicit Drug Use0.977170.912101.07134

14. Unemployment Findings F 1% increase in Marijuana use leads to.07% decrease in unemployment F 1% increase in Alcohol use leads to.09% increase in unemployment F 1% increase in Other Illicit Drug use leads to.97% increase in unemployment F 1% increase in Marijuana use leads to.07% decrease in unemployment F 1% increase in Alcohol use leads to.09% increase in unemployment F 1% increase in Other Illicit Drug use leads to.97% increase in unemployment

15. Conclusion F According to our model marijuana does not increase serious crime or unemployment rates. F Alcohol and other illicit drugs pose a much worse problem F Marijuana slightly decreases serious crime and unemployment rates F Possible limitations in our model F Accuracy of data F Other significant factors not included in our model F Most recent 2000 Census data F According to our model marijuana does not increase serious crime or unemployment rates. F Alcohol and other illicit drugs pose a much worse problem F Marijuana slightly decreases serious crime and unemployment rates F Possible limitations in our model F Accuracy of data F Other significant factors not included in our model F Most recent 2000 Census data