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

2. Llad Phillips2 Studying For the Midterm _ http://econ.ucsb.edu/ http://econ.ucsb.edu/

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8. 8 Part I Strategies to Estimate Deterrence

9. Llad Phillips9 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?

10. Llad Phillips10 What is the Empirical Evidence that Supports Deterrence? _ Domestic violence and police intervention _ Experiments with control groups _ Traffic Black Spots _ Focused enforcement efforts

11. Llad Phillips11 Female Victims of Violent Crime

12. Llad Phillips12 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

13. Victims of Lone Offenders* Annual Average Numbers

14. Llad Phillips14 United States Bureau of Justice Statistics http://www.ojp.usdoj.gov/bjs/

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16. Llad Phillips16 Average Annual Rate of Violent Victimizations Per 1000 Females

17. Llad Phillips17 Declining Trends in Intimate Violence: Homicide

18. Llad Phillips18 United States Bureau of Justice Statistics

19. Llad Phillips19 United States Bureau of Justice Statistics http://www.ojp.usdoj.gov/bjs/

20. Llad Phillips20 United States Bureau of Justice Statistics http://www.ojp.usdoj.gov/bjs/

21. Llad Phillips21 United States Bureau of Justice Statistics http://www.ojp.usdoj.gov/bjs/

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23. Llad Phillips23 Domestic Violence in California http://caag.state.ca.us/

24. Llad Phillips24 Domestic Violence Rates in California: 1988-1998 1988: 113.6 per 100.000 1998: 169.9 per 100,000

25. Llad Phillips25 Domestic Violence in California 1988: 94% Male Arrests 1998: 83.5% Male Arrests

26. Llad Phillips26 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

27. Llad Phillips27 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

28. Llad Phillips28 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

29. Llad Phillips29 Traffic Black Spots _ Blood Alley _ Highway 126 _ San Marcos Pass _ Highway 154

30. Los Angeles Traffic Map

31. Llad Phillips31 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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33. Llad Phillips33 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

35. Llad Phillips35 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

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

37. Llad Phillips37 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

38. Llad Phillips38 U.S. United States Bureau of Justice Statistics http://www.ojp.usdoj.gov/bjs/

39. Llad Phillips39 U.S. United States Bureau of Justice Statistics http://www.ojp.usdoj.gov/bjs/

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

41. Llad Phillips41 United States Bureau of Justice Statistics http://www.ojp.usdoj.gov/bjs/ Long Swings in The Homicide Rate

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43. Llad Phillips43 Part II Optimization of the Criminal Justice System

44. Llad Phillips44 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.

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

46. 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

47. 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

48. 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

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

50. 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

51. 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

52. 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

53. 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

54. 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

55. 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

56. 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

57. 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

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

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

60. 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

61. Source: Report to the Nation on Crime and Justice control Causal factors

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

63. Llad Phillips63 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

64. 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

65. 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

66. Llad Phillips66 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

67. Source: Phillips: Lecture One

68. Llad Phillips68 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

69. Llad Phillips69 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

70. Llad Phillips70 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

72. Llad Phillips72 Female Victims of Violent Crime