1. Llad Phillips1 Part I Strategies to Estimate Deterrence Part II Optimization of the Criminal Justice System

2. Llad Phillips2 Testing crime control

3. Llad Phillips3 Crime Generation Crime Control Offense Rate Per Capita Expected Cost of Punishment Schematic of the Criminal Justice System Causes ? (detention, deterrence) Expenditures Weak Link OF = f(CR, SV, CY, SE, MC CR = g(OF, X)

4. Llad Phillips4 Suicide AS A Proxy For Causes of Homicide

5. Llad Phillips5 FBI Vs. Vital Statistics

6. Llad Phillips6 Homicide Rate & Suicide Rate

7. Llad Phillips7 Homicides per 100, 000 = a + b*suicides per 100,000 + e, note suicides is significant, explains~76% OF= f( SE)

8. Llad Phillips8 Schematic Model Causes Homicide Controls: Imprisonment rate Clearance ratio

9. Llad Phillips9 The story over time

10. Llad Phillips10 A Control Story: US _ _ Clearance ratio for homicide was falling from 1960 0n _ _ This could explain the rising homicide rate from 1965-1975 _ _ Imprisonment rate was pretty stable until 1980 when it started rising _ _ This could explain the falling homicide rate from 1995-2009

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12. Llad Phillips12 Homicides per 100,000 = a + b*CR + e note: CR is significant, explains ~8.6% OF = f(CR)

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14. Llad Phillips14 Homicides per 100,000 =a + b*prisoners per 100,000 + e (note: prisoners not significant as the only explanatory variable)

15. Llad Phillips15 Homicides per 100,000 = a +b*CR +c* prisoners per 100,000 + e Note: CR and Prisoners together are significant, explain 83%

16. Llad Phillips16 OF = f(CR, SV)

17. Llad Phillips17 Homicides per 100, 000 = a + b*Suicides per 100,000 +c* CR + d* prisoners per 100,000 Note: all3 explanatory variables are significant & explain 87%

18. Llad Phillips18 Homicide Rate = a + b*CR +c*Prisoners + d*suicide rate + e The error e Or residual has a cycle. Indicates An explanatory variable is missing. Best to Find it. Next best, Model the error

19. Llad Phillips19 Homicide per 100,000 explained by suicides, clearance ratio, & prisoners with error modeled, explains 92.8 %

20. Llad Phillips20 Error modeled or cleaned up cleaned up

21. Llad Phillips21 Outline _ Human Capital & Other News _ Studying for the Midterm _ Deterrence: _ Evidence pro _ Evidence con

22. Llad Phillips22 Human Capital news

23. Llad Phillips23 About 60% Of 9 th graders Get a diploma somewhere

24. Llad Phillips24 The high Hurdle? Algebra

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30. Llad Phillips30 Deterrence: conceptual issues _ _ Controlling for causality _ _ Simultaneity

31. Llad Phillips31 Source: Report to the Nation on Crime and Justice Expect Get

32. Llad Phillips32 Crime Generation Crime Control Offense Rate Per Capita Expected Cost of Punishment Schematic of the Criminal Justice System Causes ? (detention, deterrence) Expenditures Weak Link Control for Causality

33. Llad Phillips33 Crime Generation Crime Control Offense Rate Per Capita Expected Cost of Punishment Schematic of the Criminal Justice System Causes ? (detention, deterrence) Expenditures Weak Link Recognize Simultaneity

34. Llad Phillips34 Greening the Earth _ Greening UCSB _ Rec-Cen

35. Llad Phillips35 Human development Index and Electricity Use

36. Llad Phillips36 Production Function

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40. Llad Phillips40 Policy Comment About Economic Development _ _ An Obama Keynesian strategy: invest in infrastructure _ _ Past investments in infrastructure _ _ Canals _ _ Railroads _ _ Paved roads _ _ Airways _ _ ?

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43. Llad Phillips43 Causality? Misery IndexOffense Rate Mystery Force

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45. Llad Phillips45 Crime Generation Crime Control Offense Rate Per Capita Expected Cost of Punishment Schematic of the Criminal Justice System Causes ? (detention, deterrence) Expenditures Weak Link Control for Causality

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47. Llad Phillips47 1851 1945 1900 1930

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50. Llad Phillips50 Part I Strategies to Estimate Deterrence

51. Llad Phillips51 Questions About Crime _ Why is it difficult to empirically demonstrate the control effect of deterrence on crime? _ What is the empirical evidence that raises questions about deterrence? _ What is the empirical evidence that supports deterrence?

52. Llad Phillips52 Evidence Against the Death Penalty Being a Deterrent _ Contiguous States _ Maine: no death penalty _ Vermont: death penalty _ New Hampshire: death penalty _ Little Variation in the Homicide Rate _ Source: Study by Thorsten Sellin in Hugo Bedau, The Death Penalty in America

54. Llad Phillips54 Isaac Ehrlich Study of the Death Penalty: 1933-1969 _ Homicide Rate Per Capita _ Control Variables _ probability of arrest _ probability of conviction given charged _ Probability of execution given conviction _ Causal Variables _ labor force participation rate _ unemployment rate _ percent population aged 14-24 years _ permanent income _ trend

55. Ehrlich Results: Elasticities of Homicide with respect to Controls Source: Isaac Ehrlich, “The Deterrent Effect of Capital Punishment

56. Llad Phillips56 Critique of Ehrlich by Death Penalty Opponents _ Time period used: 1933-1968 _ period of declining probability of execution _ Ehrlich did not include probability of imprisonment given conviction as a control variable _ Causal variables included are unconvincing as causes of homicide

57. Llad Phillips57 U.S. United States Bureau of Justice Statistics http://www.ojp.usdoj.gov/bjs/

58. Llad Phillips58 U.S. United States Bureau of Justice Statistics http://www.ojp.usdoj.gov/bjs/

59. Llad Phillips59 What is the Empirical Evidence that Supports Deterrence? _ Domestic violence and police intervention _ Experiments with control groups _ Traffic Black Spots _ Focused enforcement efforts

60. Llad Phillips60 Traffic Black Spots _ Blood Alley _ Highway 126 _ San Marcos Pass _ Highway 154

61. Llad Phillips61 San Marcos Pass Experiment _ Increase Highway Patrols _ Increase Arrests _ Total accidents decrease _ Injury accidents decrease _ Accidents involving drinking under the influence decrease

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63. Los Angeles Traffic Map

64. Llad Phillips64 Domestic Violence & Police Intervention

65. Llad Phillips65 1993-2005

66. Llad Phillips66 Female Victims of Violent Crime, 1973-2003

67. Llad Phillips67 Homicides of Intimates, 1976-2005

68. Llad Phillips68 Female Victims of Violent Crime _ In 1994 _ 1 homicide for every 23,000 women (12 or older) _ females represented 23% of homicide victims in US _ 9 out of 10 female victims were murdered by males _ 1 rape for every 270 women _ 1 robbery for every 240 women _ 1 assault for every 29 women

69. Victims of Lone Offenders* Annual Average Numbers

70. Llad Phillips70 United States Bureau of Justice Statistics http://www.ojp.usdoj.gov/bjs/

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72. Llad Phillips72 Average Annual Rate of Violent Victimizations Per 1000 Females

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74. Llad Phillips74 United States Bureau of Justice Statistics http://www.ojp.usdoj.gov/bjs/

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76. Llad Phillips76 Female victimization rates by relationship

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78. Llad Phillips78 Domestic Violence in California http://caag.state.ca.us/

79. Llad Phillips79 Domestic Violence Rates in California: 1988-1998 1988: 113.6 per 100.000 1998: 169.9 per 100,000

80. Llad Phillips80 Domestic Violence in California 1988: 94% Male Arrests 1998: 83.5% Male Arrests

81. Llad Phillips81 Police Intervention with Experimental Controls _ A 911 call from a family member _ the case is randomly assigned for “treatment” _ A police patrol responds and visits the household _ police calm down the family members _ based on the treatment randomly assigned, the police carry out the sanctions

82. Llad Phillips82 Why is Treatment Assigned Randomly? _ To control for unknown causal factors _ assign known numbers of cases, for example equal numbers, to each treatment _ with this procedure, there should be an even distribution of difficult cases in each treatment group

83. Llad Phillips83 911 call (characteristics of household Participants unknown) Random Assignment code blue code gold patrol responds settles the household verbally warn the husbandtake the husband to jail for the night

84. Llad Phillips84 Part II Optimization of the Criminal Justice System

85. Llad Phillips85 Questions About Statistical Studies of Deterrence _ Do we know enough about the factors that cause crime? _ Can we find variables that will control for variation in crime generation? _ We have better measures for the factors that control crime than for the factors that cause crime. _ Unknown variation in crime generation may mask the effects of crime control.

86. Llad Phillips86 Crime Generation Crime Control Offense Rate Per Capita Expected Cost of Punishment Schematic of the Criminal Justice System Causes ? (detention, deterrence) Expenditures Weak Link

87. per capita expenditures on CJS offense rate per capita Four-Way Diagram: Crime Generation & Crime Control 1 2 3

88. Source: Report to the Nation on Crime and Justice

89. control Causal factors

90. Expenditures per Capita Offenses Per Capita Crime Control Technology South Dakota North Dakota 2500 Index crimes per 100,000 people $100 $0 0

91. Llad Phillips91 Optimization of the Criminal Justice System (CJS) _ Minimize damages to victims plus the costs of control, subject to the crime control technology _ damages to victims per capita = loss rate per offense * offense rate per capita _ Costs of control = per capita expenditures on CJS _ Total cost = damages + expenditures

92. Expenditures per Capita Offenses Per Capita Crime Control Technology South Dakota North Dakota 2500 Index crimes per 100,000 people $100 Total cost = expenditures per capita $200 $0 0

93. Expenditures per Capita Offenses Per Capita Crime Control Technology South Dakota North Dakota 2500 Index crimes per 100,000 people $100 Total cost = expenditures per capita Total cost = damages to victims $200 $0 0 5000 Index offenses per 100,000 people = 0.05 per capita

94. Llad Phillips94 Expenditures per Capita Offenses Per Capita Crime Control Technology South Dakota North Dakota 0.025 Index crimes per capita $100 Total cost = expenditures per capita Total cost = damages to victims 0.050 Total cost = $200 per capita = damages to victims = loss rate*0.05 so loss rate = $4,000 per Index Crime in South Dakota $200 $0 0

95. Source: Phillips: Lecture One

96. Llad Phillips96 Expenditures per capita Offenses Per Capita 2500 Index crimes per 100,000 people $100 Total cost = expenditures per capita Total cost = damages to victims Family of Total Cost Curves High Low

97. Llad Phillips97 Expenditures per Capita Offenses Per Capita Crime Control Technology South Dakota North Dakota 2500 Index crimes per 100,000 people $100 Total cost = expenditures per capita Total cost = damages to victims

98. Llad Phillips98 Application of the Economic Paradigm _ Specify the feasible options _ the states of the world: Crime control technology _ Value the options _ loss rate per offense _ Optimize _ Pick the lowest cost point on the crime control technology

99. That’s all folks!

100. Crime Generation 1. variation of offense rate per capita with expected cost of punishment 2. Shift in the relationship with a change in causal factors Offense rate per capita Expected cost(severity) of punishment crime generation function

101. Crime Generation 1. variation of offense rate per capita with expected cost of punishment 2. Shift in the relationship with a change in causal factors Offense rate per capita Expected cost(severity) of punishment crime generation function High causal conditions Low causal conditions

102. Production Function for the Criminal Justice System (CJS) 1. Variation in expected costs of punishment with criminal justice system expenditure per capita Expected costs of punishment Criminal Justice System expenditures per capita production function

103. per capita expenditures on CJS offense rate per capita expected cost of punishment Crime Generation Four-Way Diagram: Crime Generation & Crime Control

104. per capita expenditures on CJS offense rate per capita expected cost of punishment Crime Generation Four-Way Diagram: Crime Generation & Crime Control per capita expenditures on CJS Production Function

105. per capita expenditures on CJS offense rate per capita expected cost of punishment Crime Generation Four-Way Diagram: Crime Generation & Crime Control per capita expenditures on CJS Production Function square 45 0

106. per capita expenditures on CJS offense rate per capita expected cost of punishment Crime Generation Four-Way Diagram: Crime Generation & Crime Control per capita expenditures on CJS Production Function square 45 0 1 1

107. per capita expenditures on CJS offense rate per capita expected cost of punishment Crime Generation Four-Way Diagram: Crime Generation & Crime Control per capita expenditures on CJS Production Function square 45 0 1 1

108. per capita expenditures on CJS offense rate per capita expected cost of punishment Crime Generation Four-Way Diagram: Crime Generation & Crime Control per capita expenditures on CJS Production Function square 45 0 1 1

109. per capita expenditures on CJS offense rate per capita expected cost of punishment Crime Generation Four-Way Diagram: Crime Generation & Crime Control per capita expenditures on CJS Production Function square 45 0 1 1

110. per capita expenditures on CJS offense rate per capita expected cost of punishment Crime Generation Four-Way Diagram: Crime Generation & Crime Control per capita expenditures on CJS Production Function square 45 0 1 1 2 2

111. per capita expenditures on CJS offense rate per capita expected cost of punishment Crime Generation Four-Way Diagram: Crime Generation & Crime Control per capita expenditures on CJS Production Function square 45 0 1 1 2 2 3

112. per capita expenditures on CJS offense rate per capita expected cost of punishment Crime Generation Four-Way Diagram: Crime Generation & Crime Control per capita expenditures on CJS Production Function square 45 0 1 1 2 2 3

113. Llad Phillips113 Female Victims of Violent Crime

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117. Long Swings in the Homicide Rate in the US: 1900-1980 Source: Report to the Nation on Crime and Justice

118. Llad Phillips118 United States Bureau of Justice Statistics http://www.ojp.usdoj.gov/bjs/ Long Swings in The Homicide Rate

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120. Llad Phillips120 Empirical Study of Certainty and Severity