Department of Applied Economics
Erasmus School of Economics
PO Box 1738
3000 DR Rotterdam
Information about this author at RePEc
NBER Working Papers and Publications
|March 2017||Are the Rich More Selfish than the Poor, or Do They Just Have More Money? A Natural Field Experiment|
with James Andreoni, Nikos Nikiforakis: w23229
The growing concentration of resources among the rich has re-ignited a discussion about whether the rich are more selfish than others. While many recent studies show the rich behaving less pro-socially, endogeneity and selection problems prevent safe inferences about differences in social preferences. We present new evidence from a natural field experiment in which we “misdeliver” envelopes to rich and poor households in a Dutch city, varying their contents to identify motives for returning them. Our raw data indicate the rich behave more pro-socially. Controlling for pressures associated with poverty and the marginal utility of money, however, we find no difference in social preferences. The primary distinction between rich and poor is simply that the rich have more money.
|March 2014||On the Role of Group Size in Tournaments: Theory and Evidence from Lab and Field Experiments|
with John List, Daan Van Soest, Haiwen Zhou: w20008
Both private and public organizations constantly grapple with incentive schemes to induce maximum effort from agents. We begin with a theoretical exploration of optimal contest design, focusing on the number of competitors. Our theory reveals a critical link between the distribution of luck and the number of contestants. We find that if there is considerable (little) mass on good draws, equilibrium effort is an increasing (decreasing) function of the number of contestants. Our first test of the theory implements a laboratory experiment, where important features of the theory can be exogenously imposed. We complement our lab experiment with a field experiment, where we rely on biological models complemented by economic models to inform us of the relevant theoretical predictions. In bo...