Department of Economics
Julis Romo Rabinowitz
Princeton, NJ 08540
NBER Program Affiliations:
NBER Affiliation: Research Associate
Institutional Affiliation: Princeton University
NBER Working Papers and Publications
|June 2018||Testing the Waters: Behavior across Participant Pools|
with Erik Snowberg: w24781
We leverage a large-scale incentivized survey eliciting behaviors from (almost) an entire university student population, a representative sample of the U.S. population, and Amazon Mechanical Turk (MTurk) to address concerns about the external validity of experiments with student participants. Behavior in the student population offers bounds on behaviors in other populations, and correlations between behaviors are largely similar across samples. Furthermore, non-student samples exhibit higher measurement error. Adding historical lab participation data, we find a small set of attributes over which lab participants differ from non-lab participants. Using an additional set of lab experiments, we see no evidence of observer effects.
|September 2015||Experimenting with Measurement Error: Techniques with Applications to the Caltech Cohort Study|
with Ben Gillen, Erik Snowberg: w21517
Measurement error is ubiquitous in experimental work. It leads to imperfect statistical controls, attenuated estimated effects of elicited behaviors, and biased correlations between characteristics. We develop simple statistical techniques for dealing with experimental measurement error. These techniques are applied to data from the Caltech Cohort Study, which conducts repeated incentivized surveys of the Caltech student body. We illustrate the impact of measurement error by replicating three classic experiments, and showing that results change substantially when measurement error is taken into account. Collectively, these results show that failing to properly account for measurement error may cause a field-wide bias: it may lead scholars to identify "new" effects and phenomena that are ac...
Published: Ben Gillen & Erik Snowberg & Leeat Yariv, 2019. "Experimenting with Measurement Error: Techniques with Applications to the Caltech Cohort Study," Journal of Political Economy, vol 127(4), pages 1826-1863.
|October 2010||Child-Adoption Matching: Preferences for Gender and Race|
with Mariagiovanna Baccara, Allan Collard-Wexler, Leonardo Felli: w16444
This paper uses a new data set on child-adoption matching to estimate the preferences of potential adoptive parents over U.S.-born and unborn children relinquished for adoption. We identify significant preferences favoring girls and unborn children close to birth, and against African-American children put up for adoption. These attitudes vary in magnitudes across different adoptive parents - heterosexual, same-sex couples, and single women. We also consider the effects of excluding single women and same-sex couples from the adoption process. In our data, such policies would substantially reduce the overall number of adopted children and have a disproportionate effect on African-American ones.
Published: Mariagiovanna Baccara & Allan Collard-Wexler & Leonardo Felli & Leeat Yariv, 2014. "Child-Adoption Matching: Preferences for Gender and Race," American Economic Journal: Applied Economics, American Economic Association, vol. 6(3), pages 133-58, July. citation courtesy of
|April 2009||Decentralized Matching with Aligned Preferences|
with Muriel Niederle: w14840
We study a simple model of a decentralized market game in which firms make directed offers to workers. We focus on markets in which agents have aligned preferences. When agents have complete information or when there are no frictions in the economy, there exists an equilibrium that yields the stable match. In the presence of market frictions and preference uncertainty, harsher assumptions on the richness of the economy have to be made in order for decentralized markets to generate stable outcomes in equilibrium.