SUPPLY OF LEGAL AND ILLEGAL ACTIVITY - AN ECONOMETRIC MODEL - TECHNICAL REPORT

• NCJ Number: 59668
• Author(s): J M HEINEKE
• Date Published: 1978
• Length: 35 pages
• Grant Number(s): TECH REPORT ESCD-1-78; 75-NI-99-0123; 77-NI-99-0071
• Sponsoring Agency: US Dept of Justice; US Dept of Justice NIJ Pub
• Corporate Author: Hoover Institution
• Sale Source: National Institute of Justice/
• Language: English
• Country: United States of America

Annotation

AN ECONOMETRIC MODEL OF LEGAL AND ILLEGAL LABOR SUPPLY IS DERIVED AND ITS IMPLICATIONS FOR ESTIMATING CRIMINAL ACTIVITIES AND EFFECTS OF CHANGES IN CRIMINAL JUSTICE VARIABLES ARE EXPLORED.

Abstract

THE MODEL IS BASED ON RECENT INVESTIGATIONS SUPPORTING THE HYPOTHESIS THAT INCREASES OR DECREASES IN ILLEGAL ACTIVITIES RESULT FROM CORRESPONDING INCREASES OR DECREASES IN EXPECTED BENEFITS RESULTING FROM SUCH ACTIVITIES. THESE INVESTIGATIONS DO NOT, HOWEVER, CLARIFY THE EXTENT TO WHICH INDIVIDUALS CHANGE FROM ONE SOURCE OF INCOME TO ANOTHER IN RESPONSE TO CHANGES IN EXPECTED RETURNS. RESULTS FORM MODERN DUALITY THEORY ARE USED TO MAKE THE PRESENT ECONOMETRIC MODEL CORRESPOND AS CLOSELY AS POSSIBLE TO THE UNDERLYING ECONOMIC MODEL. THE MODEL BEGINS WITH AN INDIVIDUAL'S SUPPLY CHOICES DETERMINING THE MIX OF LEGAL AND ILLEGAL ACTIVITIES PROVIDED. THE MODEL TREATS DECISIONS AS A CHOICE AMONG COMPETING SOURCES OF INCOME AND/OR SATISFACTION. VARIABLES INCLUDED IN THE INDIVIDUAL'S SUPPLY AND DEMAND FUNCTIONS ARE WEALTH, TIME ALLOTTED TO EACH ACTIVITY, RETURN FOR THE ACTIVITY, COST OF A PRISON SENTENCE, AND SUBJECTIVE PROBABILITIES OF BEING ARRESTED, AND OF BEING CONVICTED IF ARRESTED. BOTH INDIVIDUAL AND AGGREGATE SUPPLY AND DEMAND FUNCTIONS AND SUPPLY ELASTICITIES ARE THEN DERIVED. FOUR ACTIVITIES ARE CONSIDERED: A GENERIC LEGAL ACTIVITY, LARCENY, BURGLARY, AND ROBBERY. THE MODEL ESTIMATES THE DEGREE OF CAPACITY FOR SUBSTITUTION OR COMPLEMENTING BETWEEN THE COMBINATIONS OF ACTIVITIES AS WELL AS LEVELS OF PARTICIPATION IN EACH ACTIVITY IN RELATION TO VARIATIONS IN EXPECTED RETURNS AND COSTS. IT ALSO PERMITS SIMPLE EMPIRICAL MEASURES FOR ASSESSING EFFECTS OF CHANGES IN SUCH VARIABLES AS ARREST RATES, CONVICTION RATES, AND SENTENCING PRACTICES. ONE PREDICTION, FOR EXAMPLE, IT THAT POLICY CHANGES DESIGNED TO REDUCE CRIME WILL HAVE LESS EFFECT IN JURISDICTIONS WITH LOW ENFORCEMENT AND SANCTION RATES THAN IN OTHER JURISDICTIONS. DETAILED EQUATIONS, FOOTNOTES, AND A BIBLIOGRAPHY ARE INCLUDED. (CFW)