1 / 72

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

Part I Strategies to Estimate Deterrence Part II Optimization of the Criminal Justice System. Studying For the Midterm. http://econ.ucsb.edu/. Part I Strategies to Estimate Deterrence. Questions About Crime.

petra
Download Presentation

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

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript


  1. Part IStrategies to Estimate DeterrencePart IIOptimization of the Criminal Justice System

  2. Studying For the Midterm • http://econ.ucsb.edu/

  3. Part IStrategies to Estimate Deterrence

  4. 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?

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

  6. Female Victims of Violent Crime

  7. 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

  8. Victims of Lone Offenders*Annual Average Numbers

  9. United States Bureau of Justice Statistics http://www.ojp.usdoj.gov/bjs/

  10. Average Annual Rate of Violent Victimizations Per 1000 Females

  11. Declining Trends in Intimate Violence: Homicide

  12. United States Bureau of Justice Statistics

  13. United States Bureau of Justice Statistics http://www.ojp.usdoj.gov/bjs/

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

  15. United States Bureau of Justice Statistics http://www.ojp.usdoj.gov/bjs/

  16. Domestic Violence in California http://caag.state.ca.us/

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

  18. Domestic Violence in California 1988: 94% Male Arrests 1998: 83.5% Male Arrests

  19. 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

  20. 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

  21. 911 call (characteristics of household Participants unknown) Random Assignment code blue code gold patrol responds patrol responds settles the household settles the household verbally warn the husband take the husband to jail for the night

  22. Traffic Black Spots • Blood Alley • Highway 126 • San Marcos Pass • Highway 154

  23. Los Angeles Traffic Map

  24. San Marcos Pass Experiment • Increase Highway Patrols • Increase Arrests • Total accidents decrease • Injury accidents decrease • Accidents involving drinking under the influence decrease

  25. 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

  26. 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

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

  28. 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

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

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

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

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

  33. Part IIOptimization of the Criminal Justice System

  34. 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.

  35. Schematic of the Criminal Justice System Causes ? Weak Link Offense Rate Per Capita Crime Generation Expected Cost of Punishment (detention, deterrence) Expenditures Crime Control

  36. 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 crime generation function Expected cost(severity) of punishment

  37. 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 crime generation function High causal conditions Low causal conditions Expected cost(severity) of punishment

  38. 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 production function Criminal Justice System expenditures per capita

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

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

More Related