Field Experiments: A Bridge between Lab and Naturally Occurring Data

By John A. List. 2007

231 citations recorded by the source corpus.

Laboratory experiments have been used extensively in economics in the past several decades to lend both positive and normative insights into a myriad of important economic issues. This study discusses a related approach that has increasingly grown in prominence of late—field experiments. I argue that field experiments serve as a useful bridge between data generated in the lab and empirical studies using naturally-occurring data. In discussing this relationship, I highlight that field experiments can yield important insights into economic theory and provide useful guidance to policymakers. I also draw attention to an important methodological contribution of field experiments: they provide an empirical account of behavioral principles that are shared across different domains. In this regard, at odds with conventional wisdom, I argue that representativeness of the environment, rather than representative of the sampled population, is the most crucial variable in determining generalizability of results for a large class of experimental laboratory games.

View Paper: https://www.semanticscholar.org/paper/5bcd5a60296ceec9afa3c9699eafcf4eeaadf093

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

1. Matthias Sutter
2. Jeffrey P. Carpenter
3. Catherine C. Eckel
4. Robert Metcalfe
5. Loukas Balafoutas
6. Shivaram Rajgopal
7. Henry S. Schneider
8. Philip J. Grossman

Citations in the corpus

• Agency Problems and Reputation in Expert Services: Evidence from Auto Repair (2012, background): “2 See List [2006a] for a discussion of field experiments in economics.”
• What Drives Taxi Drivers? A Field Experiment on Fraud in a Market for Credence Goods (2013, background): “22 See, for instance, the article “Your Wheels.”
• Subsidizing charitable contributions: a natural field experiment comparing matching and rebate subsidies (2008, background): “This point is made by List (2006), who argues that there is a risk of overdeveloping ideas based on laboratory data, when these concepts have little parallel in the field; if a result holds up in the field, this legitimizes the lab results.”
• Instruments, Randomization, and Learning about Development (2010, background): “In all of this work, the project, when it exists at all, is an embodiment of the theory that is being tested and refined, not the object of evaluation in its own right, and the field experiments are a bridge between the laboratory and the analysis of " natural " data (List 2006).”
• Altruistic behavior in a representative dictator experiment (2008, background): “1Harrison and List (2004) refer to these as “artefactual” field experiments. 2Although our experiment is best categorized as artefactual by the Harrison and List (2004) system of classification, we do not think that if fits neatly in this category for this reason.”
• The Behavioralist as Tax Collector: Using Natural Field Experiments to Enhance Tax Compliance (2017, background): “The inspiration for our treatments comes from the growing literature suggesting that moral costs can be an important mechanism for changing human behavior (Levitt & List, 2007).”
• Field experiments in labor economics (2010, methodology): “Harrison and List (2004), List (2006) and List and Reiley (2008) provide recent overviews of this literature.”
• Violent conflict and behavior: A field experiment in Burundi (2012, background): “Analysts routinely trade off control versus relevance when conducting experiments (e.g., List 2007).”
• Temporal Patterns of Happiness and Information in a Global Social Network: Hedonometrics and Twitter (2011, methodology): “As such, we avoid the many difficulties associated with self-report [64–66].”
• Earnings quality: Evidence from the field (2013, methodology): “Following the recommendation by List (2007), we benchmark our survey sample to Compustat in Table 1, panel C.6 While the survey firms span most of the universe of Compustat firms on the indicated variables, they tilt away from the benchmark averages in some directions.”
• Managerial Attitudes and Corporate Actions (2013, methodology): “Following the recommendation by List (2007), we benchmark to Compustat, a frequently used database for corporate finance research.”
• Going green: does it depend on education, gender or income? (2014, methodology): “Following List (2006), we analyse the trade-off S as a”