The Promise and Success of Lab-Field Generalizability in Experimental Economics: A Critical Reply to Levitt and List

By Colin F. Camerer. 2011

316 citations recorded by the source corpus.

Subfields: Demography, General Decision Sciences, Safety Research

View Paper: https://www.semanticscholar.org/paper/7c5b4c8d03bc95ac914b9e125b73df160043c3a9

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Citations in the corpus

Reference-Dependent Preferences: Evidence from Marathon Runners (2014, background): “Camerer et al. (1997) argued that taxi drivers have a downward-sloping labor supply curve due to referencedependent preferences defined by daily income targets (see also Fehr and Goette, 2007, and Mas, 2006).”
Representative evidence on lying costs (2014, background): “For an overview and critical discussion, see Falk and Heckman (2009), Camerer (2011), or Coppock and Green (2013).”
On the External Validity of Laboratory Tax Compliance Experiments (2015, unknown): “See Falk and Heckman (2009), Camerer (2011), Armentier and Boly (2012), Kagel (forthcoming), Harrison, Lau, and Rutström (forthcoming), and Frechette (forthcoming). students.”
On doing relevant and rigorous experiments: Review and recommendations (2018, background): “the skepticism regarding the generalizability of laboratory evidence is based on misunderstandings about existing evidence on the topic (Camerer, 2015; Falk & Heckman, 2009; Kessler & Vesterlund, 2015).”
Do short-term laboratory experiments provide valid descriptions of long-term economic interactions? A study of Cournot markets (2013, unknown): “…it does not answer the question of how duration itself affects the course of play 1Levitt and List (2007) argue that external validity is crucial regarding the relevance of laboratory experiments, whereas Falk and Heckman (2009) and Camerer (2011) contend that external validity is not central.”
The external validity of giving in the dictator game (2012, background): “8Field settings will probably always differ in some aspect from in-lab experiments, which limits the expected correlations (see Camerer 2011).”
Nudging in education (2018, background): “For policy design it is crucial to understand whether results from one intervention are externally valid (Camerer, 2015) and under what circumstances interventions are scalable.”