On the Measurement of Subjective Apprehension Risk
Do people think about offending risk in verbal or numerical terms? Does the elicitation method affect reported subjective probabilities? Rational choice models require potential outcomes (e.g., benefits/costs) to be weighted by their probability of occurrence. Indeed, the subjective likelihood of being apprehended is the central construct in criminological deterrence theory—the so-called certainty principle. Yet, extant literature has measured the construct inconsistently and with little attention to potential consequences. Using a series of randomized experiments conducted with nationwide samples of American adults (aged 18 and over), this study examines the degree of correspondence between verbal and numeric measures of apprehension risk, assesses the durability of numeric estimates specifically, and attempts to elicit how respondents naturally think about apprehension risk. The findings suggest that laypeople are somewhat inconsistent in their use of both verbal and numeric descriptors of probability, their numeric estimates of probability are unlikely to be precise or durable, and many seem to prefer thinking of risk in verbal terms (compared to numeric terms). Researchers should consider including both verbal and numeric measures of probability and explore alternative measurement strategies, including anchoring vignettes, which have been valuable in standardizing verbal responses in other disciplines.
Such a study is needed, however, since scholars have often neglected a key potential trade-off of using subjective perceptions of certainty and severity of punishment rather than objective properties of sanction regimes. Objective sanction regime properties (e.g., police clearance rates, sentencing guidelines) may be unknown to or misunderstood by potential offenders, making subjective perceptions of risk more salient to decision making. Nevertheless, what perceived risk measures gain in salience, they may lose in durability over time, precision within respondents, and comparability across respondents. There is evidence to suggest this is the case. Decision makers have limited information, time, and cognitive abilities (e.g., “bounded rationality”; see Simon, 1955), are more sensitive to changes rather than absolute levels of the properties of their environment (e.g., “status quo bias” and “hedonic adaptation”; see Kahneman et al., 2006), and employ both analytical, cognitively intensive decision making and intuitive heuristic-based decision making (e.g., “dual-process decision making”; see Mamayek et al., 2015; van Gelder & de Vries, 2014). All of these factors are likely to affect subjective probabilities as well as self-reports of them in surveys.