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

63 Pages Posted: 4 Nov 2014 Last revised: 20 Oct 2015

See all articles by David C. Donald

David C. Donald

Chinese University of Hong Kong - Faculty of Law

Date Written: November 3, 2014

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.

In this paper, I examine the methodology of QR, highlighting points where objectivity and verifiability can be threatened. I then discuss 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 favour 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.

I recommend 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 inter-disciplinary 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.

Keywords: Law, Economics, Empirical Research, Quantitative Research, Corporate Law, Comparative Law, Securities Regulation

JEL Classification: B23, C25, D61, E62, G14, G28, G38, H30, K10, K22, L50, O20

Suggested Citation

Donald, David C., Law in Regression? Impacts of Quantitative Research on Law and Regulation (November 3, 2014). Available at SSRN: https://ssrn.com/abstract=2518109 or http://dx.doi.org/10.2139/ssrn.2518109

David C. Donald (Contact Author)

Chinese University of Hong Kong - Faculty of Law ( email )

Faculty of Law
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852 2696 1040 (Fax)

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