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Abstract

Saying that the probability (P) of punishment is more important in reducing crime (C) than severity (S) of punishment is largely meaningless unless one takes into consideration at least eight factors that relate to (1) diminishing returns between S and C, (2) diminishing returns between P and C, (3) the lowness of S in conjunction with P, (4) the lowness of P in conjunction with S, (5) the highness of crime benefits (B) in conjunction with P and S, (6) the dollar cost per unit of P versus S, (7) the non-monetary costs of P versus S, and (8) the liberal versus the conservative interpretation of P and S. One must also consider such relevant matters as (1) the interaction between probability and severity, (2) the feedback effect of crime on both severity and probability, and (3) the role of criminal benefits, which is a key variable in crime-committing decisions, along with punishment and its probability. The analysis lends itself to three equilibrium models regarding the reciprocal causation between severity/crime, probability/crime, and benefits/crime. Variations on the ideas from the two figures also lend themselves to two optimizing models regarding optimum crime levels for criminals and society. The main value of such causal and optimizing theory is its potential for pointing to the need for various types of data and how the data might be processed and the results used.

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Punishment and Probability in Crime Reduction Research Needs for Policy Making

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