Data and Code for: Fair Shares and Selective Attention
Principal Investigator(s): View help for Principal Investigator(s) Dianna Amasino, Tilburg University (Netherlands); Davide Pace, LMU Munich; Joël van der Weele, University of Amsterdam
Version: View help for Version V1
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| Analysis | 01/05/2024 07:49:AM | ||
| Data | 01/05/2024 07:58:AM | ||
| Experiment Materials | 01/05/2024 08:12:AM | ||
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Project Citation:
Amasino, Dianna, Pace, Davide, and van der Weele, Joël. Data and Code for: Fair Shares and Selective Attention. Nashville, TN: American Economic Association [publisher], 2024. Ann Arbor, MI: Inter-university Consortium for Political and Social Research [distributor], 2024-10-09. https://doi.org/10.3886/E196781V1
Project Description
Summary:
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Attitudes towards fairness and redistribution differ along socio-economic lines. To under-
stand their formation, we conduct a large-scale experiment on attention to merit and luck
and the effect of attention on fairness decisions. Randomly advantaged subjects pay less
attention to information about true merit and retain more economic surplus, and this effect
persists in subsequent impartial decisions. Attention also has a causal role: encouraging
subjects to look at merit reduces the effect of an advantaged position on allocations. This
suggests that attention-based policy interventions may be effective in reducing polarized
views on inequality.
stand their formation, we conduct a large-scale experiment on attention to merit and luck
and the effect of attention on fairness decisions. Randomly advantaged subjects pay less
attention to information about true merit and retain more economic surplus, and this effect
persists in subsequent impartial decisions. Attention also has a causal role: encouraging
subjects to look at merit reduces the effect of an advantaged position on allocations. This
suggests that attention-based policy interventions may be effective in reducing polarized
views on inequality.
Scope of Project
Subject Terms:
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Redistribution;
attention;
self-serving bias;
fairness;
mouse-tracking
JEL Classification:
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C91 Design of Experiments: Laboratory, Individual
D83 Search; Learning; Information and Knowledge; Communication; Belief; Unawareness
D87 Neuroeconomics
C91 Design of Experiments: Laboratory, Individual
D83 Search; Learning; Information and Knowledge; Communication; Belief; Unawareness
D87 Neuroeconomics
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