Which Measures of Time Preference Best Predict Outcomes? Evidence from a Large-Scale Field Experiment

By Stephen V. Burks, Jeffrey P. Carpenter, Lorenz F. Goette, Aldo Rustichini. Social Science Research Network, 2011

110 citations recorded by the source corpus.

Economists and psychologists have devised numerous instruments to measure time preferences and have generated a rich literature examining the extent to which time preferences predict important outcomes; however, we still do not know which measures work best. With the help of a large sample of non-student participants (truck driver trainees) and administrative data on outcomes, we gather four different time preference measures and test the extent to which they predict both on their own and when they are all forced to compete head-to-head. Our results suggest that the now familiar (β, δ) formulation of present bias and exponential discounting predicts best, especially when both parameters are used.

Subfields: Economics and Econometrics, General Decision Sciences

View Paper: https://www.semanticscholar.org/paper/20430f263542c8e2df823441dd0b5621276280f3

How researchers see this paper

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

In Economics and Econometrics

1. S. Angerer
2. Matthias Sutter
3. Daniela Glätzle-Rützler
4. Philipp Lergetporer
5. Seda Ertac
6. Sule Alan

In General Decision Sciences

1. Daniela Glätzle-Rützler
2. S. Angerer
3. Matthias Sutter
4. Philipp Lergetporer
5. Martin G. Kocher
6. Seda Ertac
7. Sule Alan
8. Roman M. Sheremeta

Citations in the corpus

• Financial Literacy, Present Bias and Alternative Mortgage Products (2017, unknown): “We also contribute to the expanding literature on investigating behavioral characteristics in representative surveys (Ameriks et al., 2007; Dohmen et al., 2010; Burks et al., 2012), as well as the potential interaction between time preferences and financial literacy (Meier and Sprenger, 2013).”
• How to measure time preferences in children: a comparison of two methods (2015, methodology): “In fact, Burks et al. (2012) find that simple exponential discounting (i.e. ignoring present bias) successfully predicts three out of six outcomes (smoking, credit score and going absent without leave) while four outcomes can be predicted when also considering present bias (washing out of job…”