Hostname: page-component-8448b6f56d-sxzjt Total loading time: 0 Render date: 2024-04-24T08:10:28.550Z Has data issue: false hasContentIssue false

Psychologists should learn structural specification and experimental econometrics

Published online by Cambridge University Press:  10 February 2022

Don Ross*
Affiliation:
School of Society, Politics, and Ethics, University College Cork, Cork, T12 AW89, Ireland. don.ross931@gmail.com School of Economics, University of Cape Town, Rondebosch7701, South Africa. http://uct.academia.edu/DonRoss Center for Economic Analysis of Risk, J. Mack Robinson College of Business, Georgia State University, Atlanta, GA30303, USA

Abstract

The most plausible of Yarkoni's paths to recovery for psychology is the least radical one: psychologists need truly quantitative methods that exploit the informational power of variance and heterogeneity in multiple variables. If they drop ambitions to explain entire behaviors, they could find a box full of design and econometric tools in the parts of experimental economics that don't ape psychology.

Type
Open Peer Commentary
Copyright
Copyright © The Author(s), 2022. Published by Cambridge University Press

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Andersen, S., Harrison, G. W., Lau, M. I., & Rutström, E. E. (2010). Behavioral econometrics for psychologists. Journal of Economic Psychology, 31, 553576.CrossRefGoogle Scholar
Kruschke, J., & Liddell, T. (2018). The Bayesian new statistics: Hypothesis testing, estimation, meta-analysis, and power analysis from a Bayesian perspective. Psychonomic Bulletin and Review, 25, 178206.CrossRefGoogle ScholarPubMed
Lee, M., & Wagenmakers, E.-J. (2013). Bayesian cognitive modeling: A practical course. Cambridge University Press.CrossRefGoogle Scholar