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1 The Economics of Crime and Justice 2 Outline w The Meth Epidemic w Crime in California.

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Presentation on theme: "1 The Economics of Crime and Justice 2 Outline w The Meth Epidemic w Crime in California."— Presentation transcript:

1

2 1 The Economics of Crime and Justice

3 2 Outline w The Meth Epidemic w Crime in California

4 3 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

5 4 Brain scan study At UCLA Effect on The body

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8 7 50 % of children In Oregon are there Because of meth- Addicted parents

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10 9 Crime in California w Causality and Control w Corrections: Dynamics and Economics w Correctional Bureaucracy

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12 11 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

13 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”

14 13 What are the facts? w Expenditures per capita on the CA criminal justice system

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17 16 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

18 17 Trends In Crime in California Source: Crime and Delinquency in California, 2002 http://caag.state.ca.us/ Social Welfare Lecture (#1 LP)

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20 19 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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22 21 Can we identify the causes? w The factors that cause crime might have been getting better in the latter 90’s

23 22 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

24 23 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

25 24 Misery Index, California 1952-2003 -5.00 0.00 5.00 10.00 15.00 20.00 25.00 1950196019701980199020002010 year Rate unemployment rate inflation rate misery index Jobs and Crime Lec(#2 LP)

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27 26 Note: w The misery rate is turning up and so is the crime rate in 2002 w There is visual evidence that there may be a connection

28 Jobs and Crime

29 28 2002 1952 1980 1954 Jobs and Crime Lec #2 LP

30 Jobs and Crime

31 30 What are the facts? w Control variables Imprisonment as a measure of detention and deterrence

32 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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34 33 The number of prisoners per capita is leveling off w Is this why the crime rate is turning up?

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36 35 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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38 37 What is Affecting Crime Rates? w Economic Conditions? w Imprisonment Rates?

39 38 Model Schematic Crime Generation: California Index Offenses Per Capita Causality: California Misery Index Crime Control: California Prisoners Per Capita

40 39 CA Crime Index Per Capita (t) = 0.039 + 0.00034*Misery Index (t) – 3.701*Prisoners Per Capita (t) + e(t) where e(t) = 0.954*e(t-1)

41 40 Ln CA Crime Index Per Capita (t) = -5.25 + 0.17*ln Misery Index (t) -0.22 ln Prisoners Per capita (t) +e(t) where e(t) = 0.93 e(t-1)

42 41 California Forecasts w Using the Fitted Model to Forecast

43 42 California Department of Corrections: Institutional Population http://www.cdc.state.ca.us/reports/populatn.htm

44 43 Crime in California w Causality and Control wCwCorrections: Dynamics and Economics

45 44 Prison Dynamics and Economics w Admissions * mean years served = prisoners

46 45 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

47 46 The Stock of Prisoners InflowOutflow Stock of Prisoners New Admissions from Court Released to Parole Coordinating CJS

48 47 45 degrees Constraint: Admits per year*Average years served = Prisoners Average Years Served Admits per Year Coordinating CJS

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50 49 California Department of Corrections: Total Felon Admissions http://www.cdc.state.ca.us/reports/populatn.htm

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52 51 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?

53 52 Consequence w Release violent offenders w Innocent children are kidnapped, raped and murdered: example-Polly Klass

54 53 Consequence w Polly’s father campaigns for three strikes law

55 54 Consequence w More convicts are sent to prison

56 55

57 56 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

58 57 Prison Dynamics and Economics wAwAdmissions * mean years served = prisoners Dynamics wPwProduction Possibility Frontier Economics

59 58 Abstraction (Model) of the Criminal Justice System Enforcement Prosecution Defense Courts State Prisons New Admits Mean Years Served

60 59 Admits per Year per capita average years served Tradeoff Between Criminal Justice System Outputs  tan  = admits per year per capita/average years served

61 60 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

62 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

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

64 63 Abstraction (Model) of the Criminal Justice System Enforcement Prosecution Defense Courts State Prisons New Admits Mean Years Served

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

66 65 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

67 1952 1986 1994 1975

68 67 Crime in California w Causality and Control wCwCorrections: Dynamics and Economics wCwCorrectional Bureaucracy

69 68 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

70 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

71 70 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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73 72 California Department of Corrections: Total Parole and Outpatient Population

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75 74 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

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77 76 Two Policy Issues w Composition of New Admissions from Court w Large Volume of Parole Violators Returned to Prison

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83 1955 1998 1980

84 1955 1998 1980

85 1955 1980 1998

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88 87 Forecasting Prisoners Per Capita w Model Schematic Close the loop: 2-way causality

89 88 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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92 91 Model Schematic Crime Generation: California Index Offenses Per Capita Causality: California Misery Index Causality: Time Trend Crime Control: California Prisoners Per Capita

93 92 Model Schematic Crime Generation: California Index Offenses Per Capita Causality: California Misery Index Crime Control: California Prisoners Per Capita

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