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

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Presentation on theme: "Llad Phillips1 Part I Strategies to Estimate Deterrence Part II Optimization of the Criminal Justice System."— Presentation transcript:

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

2 Llad Phillips2 Outline _ Human Capital & Other News _ Studying for the Midterm _ Deterrence: _ Evidence pro _ Evidence con

3 Llad Phillips3 Human Capital news

4 Llad Phillips4 About 60% Of 9 th graders Get a diploma somewhere

5 Llad Phillips5 The high Hurdle? Algebra

6 Llad Phillips6 Studying For the Midterm _ http://econ.ucsb.edu/ http://econ.ucsb.edu/

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12 Llad Phillips12 Deterrence: conceptual issues _ _ Controlling for causality _ _ Simultaneity

13 Llad Phillips13 Source: Report to the Nation on Crime and Justice Expect Get

14 Llad Phillips14 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

15 Llad Phillips15 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

16 Llad Phillips16 News Over the Weekend _ Deep Recession high Unemployment rate Keynesian Economics drop money from a helicopter? Or invest in infrastructure? TransportationEnergyindependencegreen

17 Llad Phillips17 Greening the Earth _ Greening UCSB _ Rec-Cen

18 Llad Phillips18 Human development Index and Electricity Use

19 Llad Phillips19 Production Function

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23 Llad Phillips23 Policy Comment About Economic Development _ _ An Obama Keynesian strategy: invest in infrastructure _ _ Past investments in infrastructure _ _ Canals _ _ Railroads _ _ Paved roads _ _ Airways _ _ ?

24 Llad Phillips24 Cesare Marchetti “Fifty-Year Pulsation In Human Affairs” Futures 17(3):376-388 (1986) www.cesaremarchetti.org/archive/scan/ MARCHETTI-069.pdf www.cesaremarchetti.org/archive/scan/ MARCHETTI-069.pdf Cesare Marchetti “Fifty-Year Pulsation In Human Affairs” Futures 17(3):376-388 (1986) www.cesaremarchetti.org/archive/scan/ MARCHETTI-069.pdf www.cesaremarchetti.org/archive/scan/ MARCHETTI-069.pdf _ _ Example: the construction of railroad miles is logistically distributed

25 Llad Phillips25 90%10% 1859 1890 1921

26 Llad Phillips26 Cesare Marchetti

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28 Llad Phillips28 Cesare Marchetti: Energy Technology: Coal, Oil, Gas, Nuclear 52 years57 years56 years

29 Llad Phillips29 Cesare Marchetti

30 Llad Phillips30 Theodore Modis Figure 4. The data points represent the percentage deviation of energy consumption in the US from the natural growth-trend indicated by a fitted S-curve. The gray band is an 8% interval around a sine wave with period 56 years. The black dots and black triangles show what happened after the graph was first put together in 1988.[7] Presently we are entering a “spring” season. WWI occurred in late “summer” whereas WWII in late “winter”.

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33 Llad Phillips33 Causality? Misery IndexOffense Rate Mystery Force

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35 Llad Phillips35 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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37 Llad Phillips37 1851 1945 1900 1930

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40 Llad Phillips40 Part I Strategies to Estimate Deterrence

41 Llad Phillips41 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?

42 Llad Phillips42 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

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44 Llad Phillips44 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

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

46 Llad Phillips46 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

47 Llad Phillips47 U.S. United States Bureau of Justice Statistics http://www.ojp.usdoj.gov/bjs/

48 Llad Phillips48 U.S. United States Bureau of Justice Statistics http://www.ojp.usdoj.gov/bjs/

49 Llad Phillips49 What is the Empirical Evidence that Supports Deterrence? _ Domestic violence and police intervention _ Experiments with control groups _ Traffic Black Spots _ Focused enforcement efforts

50 Llad Phillips50 Traffic Black Spots _ Blood Alley _ Highway 126 _ San Marcos Pass _ Highway 154

51 Llad Phillips51 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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53 Los Angeles Traffic Map

54 Llad Phillips54 Domestic Violence & Police Intervention

55 Llad Phillips55 1993-2005

56 Llad Phillips56 Female Victims of Violent Crime, 1973-2003

57 Llad Phillips57 Homicides of Intimates, 1976-2005

58 Llad Phillips58 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

59 Victims of Lone Offenders* Annual Average Numbers

60 Llad Phillips60 United States Bureau of Justice Statistics http://www.ojp.usdoj.gov/bjs/

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62 Llad Phillips62 Average Annual Rate of Violent Victimizations Per 1000 Females

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64 Llad Phillips64 Declining Trends in Intimate Violence: Homicide

65 Llad Phillips65 Nonfatal Violent victimization Rates

66 Llad Phillips66 United States Bureau of Justice Statistics http://www.ojp.usdoj.gov/bjs/

67 Llad Phillips67 United States Bureau of Justice Statistics http://www.ojp.usdoj.gov/bjs/

68 Llad Phillips68 United States Bureau of Justice Statistics http://www.ojp.usdoj.gov/bjs/

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70 Llad Phillips70 Nonfatal intimate Victimization Rates By Age

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72 Llad Phillips72 Female victimization rates by relationship

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76 Llad Phillips76 Intimate homicides by weapon type

77 Llad Phillips77 Domestic Violence in California http://caag.state.ca.us/

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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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