2. 1 The Economics of Crime and Justice

3. 2 The News w Gangs w Drugs

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7. 6 Tu Feb 7, 07

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9. 8 Outline w The Meth Epidemic w Crime in California

10. 9 Front Line: The Meth Epidemic w http://www.pbs.org Assignment for class http://www.pbs.org w 1.5 million addicts in the US Worldwide more addicts than for horse and coke, combined w Different than heroin and cocaine No natural supply Synthetic 9 factories in the world manufacture pseudoephedrin w Could focus on Supply Limit availability of pseudoephedrin Roadblock: pharmaceutical lobby

11. 10 50 % of children In Oregon are there Because of meth- Addicted parents

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13. 12 Prison Building since 80’s: Some Ideas w Death Penalty Controversy in the 70’s Was death penalty effective? Was death penalty moral? w Ignoring incentives Expected cost of punishment deters everybody Detention only controls those you catch w The law of unforeseen consequences Relying on detention means the gulag w The power of ideas The “Constancy of Imprisonment” hypothesis The “Serious Offender”

14. 13 Four Periods: #1 1930-1983 except WWII, constancy # 2 WWII #3 1984-1998, expansion #4 1999-

15. 14 Crime in California w Causality and Control w Corrections: Dynamics and Economics w Correctional Bureaucracy

16. 1952-2004

17. 16 Use the California Experience w Crime rates Have Fallen. Why Haven’t Imprisonment rates? w Apply the conceptual tools developed prior to the midterm Criminal justice system schematic crime control technology

18. Crime Generation Crime Control Offense Rate Per Capita Expected Cost of Punishment Schematic of the Criminal Justice System: Coordinating CJS Causes ?!! (detention, deterrence) Expenditures Weak Link “The Driving Force”

19. 18 What are the facts? w Expenditures per capita on the CA criminal justice system

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22. 21 What are the facts? w Expenditures per capita on the CA criminal justice system Expenditures per capita in real $ are rising steadily The big ticket items are enforcement and corrections w Offenses per capita

23. 22 Trends In Crime in California Source: Crime and Delinquency in California, 2002 http://caag.state.ca.us/ Social Welfare Lecture (#1 LP) Growth level 19801992

24. 23 Crime in California 2005

25. 24 Crime in California 2005

26. 25 What are the facts? w Offense rates per capita rose rapidly until 1980 w Leveled off in the 1980’s w Declined in the nineties w Are rising again

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28. 27 Can we identify the causes? w The factors that cause crime might have been getting better in the latter 90’s

29. 28 Crime Generation Crime Control Offense Rate Per Capita Expected Cost of Punishment Schematic of the Criminal Justice System; Death Penalty Causes ? (detention, deterrence) Expenditures Weak Link Variable, up & down Steady increase

30. 29 Crime Generation Crime Control Offense Rate Per Capita Expected Cost of Punishment Schematic of the Criminal Justice System; Jobs and Crime Causes ?:Economic Conditions (detention, deterrence) Expenditures Weak Link

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33. 32 Note: w The misery index bottoms out in 1998 and the crime rate bottoms out in 1999 w There is visual evidence that there may be a connection

34. Jobs and Crime

35. 34 2002 1952 1980 1954 Jobs and Crime Lec #2 LP

36. Jobs and Crime

37. 36 What are the facts? w Control variables Imprisonment as a measure of detention and deterrence

38. Crime Generation Crime Control Offense Rate Per Capita Expected Cost of Punishment Schematic of the Criminal Justice System: Coordinating CJS Causes ?!! (detention, deterrence) Expenditures Weak Link “The Driving Force”

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40. 39 The number of prisoners per capita is leveling off w Is this why the crime rate is turning up?

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42. 41 Note w When prisoners per capita was flat, offenses per capita was growing w When prisoners per capita started growing, offenses per capita leveled off and then declined

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44. 43 What is Affecting Crime Rates? w Economic Conditions? w Imprisonment Rates? w Both?

45. 44 Model Schematic Crime Generation: California Index Offenses Per Capita Causality: California Misery Index Crime Control: California Prisoners Per Capita

46. 45 CA Crime Index Per Capita (t) = 0.039 + 0.00034*Misery Index (t) – 3.726*Prisoners Per Capita (t) + e(t) where e(t) = 0.95*e(t-1)

47. 46 Ln CA Crime Index Per Capita (t) = -5.27 + 0.17*ln Misery Index (t) -0.22 ln Prisoners Per capita (t) +e(t) where e(t) = 0.93 e(t-1)

48. 47 California Forecasts w Using the Fitted Model to Forecast Year CA Crime Index Per Capita 120050.018882 220060.019424 320070.019416

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50. 49 California Department of Corrections: Institutional Population http://www.cdc.state.ca.us/reports/populatn.htm

51. 50 Crime in California w Causality and Control wCwCorrections: Dynamics and Economics

52. 51 Prison Dynamics and Economics w Admissions * mean years served = prisoners

53. 52 Relationships Between Stocks and Flows: Coordinating CJS w In equilibrium: Inflow = Outflow w The outflow is proportional to the stock Outflow = k * Stock constant of proportionality, k, equals one divided by mean time served –Admits * mean years served = stock of prisoners

54. 53 The Stock of Prisoners InflowOutflow Stock of Prisoners New Admissions from Court Released to Parole Coordinating CJS

55. 54 45 degrees Constraint: Admits per year*Average years served = Prisoners Average Years Served Admits per Year Coordinating CJS

56. 55 California Department of Corrections: Total Felon Admissions http://www.cdc.state.ca.us/reports/populatn.htm

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58. 57 Prison Realities w We can not build prisons fast enough to increase capacity soon enough w The public wants more convicts sent to prison w But prisons are full w So, what happens?

59. 58 Consequence w Release violent offenders w Innocent children are kidnapped, raped and murdered: example-Polly Klass

60. 59 Consequence w Polly’s father campaigns for three strikes law

61. 60 Consequence w More convicts are sent to prison

62. 61

63. 62 Capital constraint: Coordinating CJS w admits per capita per year * average years served = prisoners per capita w Prisoners per capita is limited by prison capacity w If you increase admits per capita per year, then average years served decreases until prison capacity catches up

64. 63 Prison Dynamics and Economics wAwAdmissions * mean years served = prisoners Dynamics wPwProduction Possibility Frontier Economics

65. 64 Abstraction (Model) of the Criminal Justice System Enforcement Prosecution Defense Courts State Prisons New Admits Mean Years Served

66. 65 Admits per Year per capita average years served Tradeoff Between Criminal Justice System Outputs  tan  = admits per year per capita/average years served

67. 66 Resource constraint w expenditure per capita on CJS = expenditure per capita on enforcement, prosecution, and adjudication plus expenditure per capita on corrections w admits per year per capita depends on expenditures per capita on enforcement, etc. w average years served depends on expenditures per capita on corrections

68. Admits per Capita Expenditures per capita on Enforcement Average Years Served Expenditures per capita on Corrections production function production function Expenditures per capita on Corrections Expenditures per capita on Enforcement Total Expenditures per capita on Criminal Justice System

69. Total Expenditure per capita on CJScapita on CJS Expenditures per capita, Corrections Expenditures per capita, Enforcement Admits per capita Average Years Served Production Function

70. 69 Abstraction (Model) of the Criminal Justice System Enforcement Prosecution Defense Courts State Prisons New Admits Mean Years Served

71. Total Expenditure per capita on CJScapita on CJS Expenditures per capita, Corrections Expenditures per capita, Enforcement Admits per capita Average Years Served Production Function

72. 71 Admits per Year per capita, AD average years served, S A Shifting Mix In Criminal Justice System Outputs  tan  = admits per year per capita/average years served  Facts 1. spend more 2. Admit more 3. shorter time served   Prison Capacity Constraint

73. 1952 1986 1994 1975

74. 73 Crime in California w Causality and Control wCwCorrections: Dynamics and Economics wCwCorrectional Bureaucracy

75. 74 California Corrections Bureaucracy w Prisoner and Parole Populations Stocks w Felon New Admissions From Court Inflow to Prison w Prisoners Released to Parole Outflow from Prison/Inflow to Parole w Parole Violators Outflow from Parole w Discharges from Parole and Deaths Outflow from Parole

76. California Department of Corrections 1996 Prisoners 145,565 Parolees 100,935 Felon New Admits 46,487 Releases to Parole 111,532 Discharged and Died 27,691 57,984 Parole Violators Returned to Custody Parole Violators With a New Term 17,525 Parolees At Large 18,034 Discharged and Died 3,984 Absconded 29,376

77. 76 Correctional Trends in California: Custodial Populations w Prisoners Per Capita Institutional Population Felons Civil Narcotics Addicts w Parolees Per Capita Parole and Outpatient Population Supervised in California

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80. 79 California Department of Corrections: Total Parole and Outpatient Population

82. 81 Correctional Trends in California: Inflows to Prison w Felon New Admissions from Court w Parole Violators Returned to Custody w Parole Violators With a New Term

84. 83 “Charlie on the MTA” w http://www.google.com http://www.google.com Song: “Charlie on the MTA” w www.youtube.com/watch?v=HXgo2GTKPEg www.youtube.com/watch?v=HXgo2GTKPEg w http://www.youtube.com/watch?v=3VMSGrY- IlU http://www.youtube.com/watch?v=3VMSGrY- IlU w www.youtube.com/watch?v=HXgo2GTKPEg www.youtube.com/watch?v=HXgo2GTKPEg

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86. California Department of Corrections 1996 Prisoners 145,565 Parolees 100,935 Felon New Admits 46,487 Releases to Parole 111,532 Discharged and Died 27,691 57,984 Parole Violators Returned to Custody Parole Violators With a New Term 17,525 Parolees At Large 18,034 Discharged and Died 3,984 Absconded 29,376

87. 86 Two Policy Issues w Composition of New Admissions from Court w Large Volume of Parole Violators Returned to Prison

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91. 90 CA Department of Corrections Projections

92. 91 CA Department of Corrections Projections

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94. 93 CA Crime Rate Forecast 2006, 2007

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97. 1955 1998 1980

98. 1955 1998 1980

99. 1955 1980 1998

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102. 101 Forecasting Prisoners Per Capita w Model Schematic Close the loop: 2-way causality

103. 102 Causal Model Forecasts: OF Unemployment rate  inflation rate, prisoners per capita * Forecasts from Economic Forecasts, 2001-, www.dof.ca.gov # Forecasts from California Department of Corrections

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106. 105 Model Schematic Crime Generation: California Index Offenses Per Capita Causality: California Misery Index Causality: Time Trend Crime Control: California Prisoners Per Capita

107. 106 Model Schematic Crime Generation: California Index Offenses Per Capita Causality: California Misery Index Crime Control: California Prisoners Per Capita

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110. 109 Brain scan study At UCLA Effect on The body

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