| By: |
Ernst Fehr;
Thomas Epper;
Julien Senn |
| Abstract: |
Parsimony is a desirable feature of economic models but almost all human
behaviors are characterized by vast individual variation that appears to defy
parsimony. How much parsimony do we need to give up to capture the fundamental
aspects of a population’s distributional preferences and to maintain high
predictive ability? Using a Bayesian nonparametric clustering method that
makes the trade-off between parsimony and descriptive accuracy explicit, we
show that three preference types—an inequality averse, an altruistic and a
predominantly selfish type—capture the essence of behavioral heterogeneity.
These types independently emerge in four different data sets and are
strikingly stable over time. They predict out-of-sample behavior equally well
as a model that permits all individuals to differ and substantially better
than a representative agent model and a state-of-the-art machine learning
algorithm. Thus, a parsimonious model with three stable types captures key
characteristics of distributional preferences and has excellent predictive
power. |
| Keywords: |
Distributional preferences, altruism, inequality aversion, preference heterogeneity, stability, out-of-sample prediction, parsimony, bayesian nonparametrics |
| JEL: |
D31 D63 C49 C90 |
| Date: |
2023–10 |
| URL: |
http://d.repec.org/n?u=RePEc:zur:econwp:439&r=evo |