Law in Regression? Impacts of Quantitative Research on Law and Regulation

Abstract

Quantitative research (“QR”) has undeniably improved the quality of law- and rulemaking, but it can also present risks for these activities. On the one hand, replacing anecdotal assertions regarding behavior or the effects of rules in an area to be regulated with objective, statistical evidence has advanced the quality of regulatory discourse. On the other hand, because the construction of such evidence often depends on bringing the complex realities of both human behavior and rules designed to govern it into simple, quantified variables, QR findings can at times camouflage complexity, masking real problems. Deceptively objective findings can in this way prevent the kind of deep, difficult, granular investigation a problem needs. This Article examines the methodology of QR, highlighting points where objectivity and verifiability can be threatened. It discusses a number of case studies where common patterns emerge in the interaction between QR and policymaking. These include the displacement of qualitative problems with inaccurate quantification, the release of powerful, statistical or otherwise quantitative “sound bites” that immediately move policy but are later found to be incorrect, deflating like a “bubble,” and the abdication of governance duties by regulators in favor of quantitative indicia like the performance benchmarks of an “efficient market.” These case studies reveal a particularly troubling tension between the strength of QR in reaching generalized findings and the uniquely context-specific nature and operation of most laws and regulations. This Article recommends a number of measures to improve the use of QR in policymaking, including increasing the transparency of data generation and analysis within the academic community, putting more emphasis on interdisciplinary creation and validation of findings, using certain cautionary disclosure when making “public offerings” of quantitative findings, and holding policymakers more strictly to their statutory mandates, even if not complementary with quantitative analysis.