Many economists have conducted experiments to analyze the preferences of different populations. In particular, many researchers have attempted to measure the degree of risk aversion or risk loving for a given population. The researcher hopes that his or her subjects are representative of the overall risk aversion composition of the population sampled.
A working paper by Harrison, Lau and Rutström looks at whether or not this will be the case. It is possible that a randomization bias will bias the results. For instance, if there is risk for individuals to be placed into control and treatment groups, more risk averse people will decide not to participate in the experiment. Thus, risk aversion estimates may be too low.
On the other hand, many experiments often give individuals show-up fees which are paid to the participants regardless of what their responses are in the given questionnaire. Harrison and co-authors hypothesize that more risk averse people will decide to participate when there is a guaranteed show-up fee.
To measure risk aversion, the authors use the Holt and Laury (2002) methodology. The find the following results:
- The average CRRA value for an experiment with a high show-up fee is 0.81 while the average is 0.67 in the experiment with a low show-up fee. Thus, a high show up fee increases the risk aversion of the population.
- The risk aversion parameters are also stronger when high lottery prizes compared to low ones (0.81 vs. 0.59).
It is important to take into account this randomization bias whenever you are conducting an experiment.
- Harrison GW, Lau, MI, Rutström EE (2007) “Risk Attitudes, Randomization to Treatment, and Self-Selection into Experiments” Working Paper.