Giving When Responsible For Others' Risks

The study will be a survey of several questions. Participants of the survey will be recruited from Amazon Mechanical Turk. The AMT workers will get access to the survey via a web link on the interface of AMT. They will be paid for finishing the survey. And they may get additional payment during the survey.

2017-03-27

2017-09-30

The key outcomes of this experiment include risk taking for self, risk taking for others and the proportion of participants who volunteer to take risks for others.

Risk taking for self and for others is constructed from decisions of participants in an investment game. They need to decide how to allocate the endowment given in the experiment (e.g. 100 tokens) between safe and risky asset. And proportion allocated into risky asset will be the measure for risk taking.

The proportion of volunteering will be constructed directly from how many participants among decision makers choose to voluntarily take risks for others.

The experimental design consists of four parts. First, participants finish a hypothetical dictator game. Second, they make risky decisions on their own behalf. Third, they make risky decisions for another participant matched with them. Last, they fill in a follow-up survey about demographic information.

Half participants in this experiment will be randomly chosen as decision makers, while the other half will be passive recipients. The following describes the procedure of experiment for all participants as decision makers.

First, all decision makers finish the task of ten hypothetical dictator games. This task will bring same workload to all decision makers so that it will create salience of payment. Moreover, answers of this task will deliver information of social preferences.

Second, all decision makers are rewarded 100 tokens for finishing the task and asked to play an investment game for themselves with the 100 tokens. The investment game needs them to choose a percentage of the 100 tokens that will be invested into a lottery which will return two and a half times invested with probability 33% or 0 with probability 67%.

Third, two thirds of decision makers will be randomly assigned into Voluntary frame and the other one third will be in Non-Voluntary frame. To balance the number of observations in both frames more participants are assigned into Voluntary frame. The proportion may be adjusted after the pilot. In Non-voluntary frame, decision makers are told that their randomly matched recipients who finished the same task as they did and they need to make the decision on behalf of the recipients. In Voluntary frame, decision makers are first asked to make binary choice between the following two options: either (i) make decisions in the investment game with 100 tokens so that the recipients matched with them will get payments based on the outcomes of their decisions and their final payment is still the outcome of the investment they have decided for themselves; or (ii) get twice as much as the outcome of the investment game they played for themselves previously but the recipients get nothing except the basic show-up fee which is paid for all participants.

Fourth, the decision makers who choose not to volunteer are asked to make decisions in the investment game with 100 tokens for different recipients re-matched with them.

Last, all decision makers need to complete a follow-up survey after the main experiment procedure. The follow-up survey will collect demographic information of age, gender, education level and political preferences.

Recipients in this experiment will only need to finish the task of ten hypothetical dictator games, a couple of hypothetical questions concerning their self- and other-regarding risk preferences, and the follow-up survey concerning gender, age and education. Payments of the recipients will be determined by the outcomes of decisions of decision makers matched with them, as well as the show-up fee. Participants will not know what is the subsequent steps and they will be informed of what they need to do only when they reach each step. And the outcomes of all their decisions will not be revealed throughout the experiment.

Participants of this experiment will be randomly recruited from online workers of Amazon Mechanical Turk (AMT).

Participants will be randomly assigned into two treatments by online software.

All participants will be randomly matching in pairs by programming software.

All participants will be paid a show-up fee. On top of the show-up fee, participants may earn from playing an investment game. The earning from the investment game will be randomly determined by programming software.

Unit of randomization is the individual participant.

No

There will be totally 2150 participants.

There will be totally 2150 participants.

Around 850 participants will be decision makers and the other 1300 participants will be passive recipients. In one treatment, there will be 289 participants as decision makers and 289 participants as recipients. In the other treatment, there will be 561 participants as decision makers and 1011 participants as recipients.

To achieve power 80%, the sample size needed for this experiment is 2150. Assumed parameters are mean of decision in investment game is 0.65 with standard deviation 0.25, and effect size 0.06. The calculation of sample size focuses on effect size in one research question of this project. (outcome)