1 The Economics of Crime and Justice

2

3 The News w Gangs w Drugs

4

5

6

7 Tu Feb 7, 07

8

California Government ANA Matasantos

UC Budget From CA General Fund

UC Budget from CA General Fund Arnie Davis

18

CA Government Vs. CA Economy

26 Outline w UCR Offenses Per Capita by State w The Meth Epidemic w Crime in California

UCR Offenses Per Capita By State w Crime Generation: OF = f(CR,SV, SE, MC) w OFPC = (PRPC, SE,MC), i.e offenses per capita varies with prisoners per capita, causal variables and moral compliance w SE: causal variables Human capital: % of students above basic grade 4 reading, deaths per 100,000 from heart disease,% of children below poverty w MC moral compliance % catholic, % weekly church attendance 27

28 No control Bad Health (low human capital) decreases crime

29

30 No Control Education Reduces crime Moral compliance ditto Less Poverty ditto Health insignificant

31 Expenditures Per Capita UCR Offenses Per Capita CCT Income Education Moral Compliance Less poverty

32 Front Line: The Meth Epidemic w Assignment for class 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

33 50 % of children In Oregon are there Because of meth- Addicted parents

34

35 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”

36 Four Periods: # except WWII, constancy # 2 WWII # , expansion #

37 Crime in California w Causality and Control w Corrections: Dynamics and Economics w Correctional Bureaucracy

39 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

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”

41 What are the facts? w Expenditures per capita on the CA criminal justice system

42

43

44 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

45 Trends In Crime in California Source: Crime and Delinquency in California, Social Welfare Lecture (#1 LP) Growth level

46 Crime in California 2007

47 Homicide in California 2007

48 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 relatively stable in this decade

49

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

51 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

52 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

53

54

55 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

Jobs and Crime

Jobs and Crime Lec #2 LP

Jobs and Crime

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

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”

61

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

63

64 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

65

66 What is Affecting Crime Rates? w Economic Conditions? w Imprisonment Rates? w Both?

67 Model Schematic Crime Generation: California Index Offenses Per Capita Causality: California Misery Index Crime Control: California Prisoners Per Capita

68 CA Crime Index Per Capita (t) = *Misery Index (t) – 3.60*Prisoners Per Capita (t) + e(t) where e(t) = 0.95*e(t-1)

69 Ln CA Crime Index Per Capita (t) = *ln Misery Index (t) ln Prisoners Per capita (t) +e(t) where e(t) = 0.93 e(t-1)

70 California Forecasts w Using the Fitted Model to Forecast Year CA Crime Index Per Capita

71

72

73

Institutional Population Projections

75

76 California Department of Corrections: Institutional Population

77 Crime in California w Causality and Control wCwCorrections: Dynamics and Economics

78 Prison Dynamics and Economics w Admissions * mean years served = prisoners

79 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

80 The Stock of Prisoners InflowOutflow Stock of Prisoners New Admissions from Court Released to Parole Coordinating CJS

81 45 degrees Constraint: Admits per year*Average years served = Prisoners Average Years Served Admits per Year Coordinating CJS

82 California Department of Corrections: Total Felon Admissions

83

84 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?

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

86 Consequence w Polly’s father campaigns for three strikes law

87 Consequence w More convicts are sent to prison

88

89 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

90 Prison Dynamics and Economics wAwAdmissions * mean years served = prisoners Dynamics wPwProduction Possibility Frontier Economics

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

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

93 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

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

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

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

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

98 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

100 Crime in California w Causality and Control wCwCorrections: Dynamics and Economics wCwCorrectional Bureaucracy

101 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

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

103 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

104

106 California Department of Corrections: Total Parole and Outpatient Population

108 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

110 “Charlie on the MTA” w Song: “Charlie on the MTA” w w IlU IlU w

111

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

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

114

115

116

117 CA Department of Corrections Projections

118 CA Department of Corrections Projections

119

120 CA Crime Rate Forecast 2006, 2007

121

122

126

128 Forecasting Prisoners Per Capita w Model Schematic Close the loop: 2-way causality

129 Causal Model Forecasts: OF Unemployment rate  inflation rate, prisoners per capita * Forecasts from Economic Forecasts, 2001-, # Forecasts from California Department of Corrections

130

131

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

133 Model Schematic Crime Generation: California Index Offenses Per Capita Causality: California Misery Index Crime Control: California Prisoners Per Capita

134

135

136 Brain scan study At UCLA Effect on The body

137

138