Risk Preferences and Outcome Bias in the Delegation Process

When evaluating the past performance of politicians, voters tend to focus on policy outcomes rather than on the political decisions and the circumstances under which they were taken. In this study, we take this so-called outcome bias as a starting point and go one step further to examine the role of risk in political delegation processes. More specifically, we aim to understand on an abstract level whether (I) subjects are more likely to vote for representatives who take the same level of risk as they take for themselves, (II) their (re-)election decision is affected by the outcome bias even if it is clear that the outcome is only determined by chance, and (III) whether representatives adapt to the risk preferences of the represented and anticipate the potential outcome bias among them.

To answer our research questions, we employ a 2x2 between-subject design, where we systematically vary the immediacy of the outcome as well as the lottery of the risky policy in an online experiment (see details under 'Experimental Design' below).

Intervention 1: Immediacy of the outcome. In the 'long-term' treatment, the allocation decision takes effect in the long run, and voters get informed about the outcome of the first terms’ lottery only after their voting decision. In the 'short-term' treatment, the allocation decision takes effect in the short run, and voters get informed about the outcome of the first terms’ lottery before their voting decision. This implies that in the long-term treatment, the voting decision can be affected by the politicians’ allocation decision (but not by the outcome of the first term’s lottery, because it is still unknown), whereas in the short-term treatment, the voting decision can be affected by the politicians’ allocation decision and the outcome of the first terms’ lottery. This enables us to measure the causal influence of the outcome on the voting decision of the represented. Furthermore, it enables us to assess whether politicians anticipate an outcome bias among voters and act differently under the short-term treatment than under the long-term treatment.

Intervention 2: Lottery of the risky policy. The safe policy always has a return of 1 and the return of the risky policy in case of a downswing is always 0. In the 'high risk-reward' treatment, the probability of an upswing is 1/3 and the return 3.5 times the allocated points, whereas the probability of a downswing is 2/3. In the 'low risk-reward' treatment, the probability of an upswing is 2/3 and the return 1.75, whereas the probability of a downswing is 1/3. Note that the expected payoff of the risky policy is in both cases 1.16 times the allocated points. The two treatments enable us to infer via a difference-in-difference analysis whether the lottery affects the allocation decision of politicians due to the anticipated outcome bias.

2021-05-21

2021-12-13

Through the experimental design, we obtain two main variables of interest. First, we can observe the representatives’ allocation decision between the safe and risky policy. Second, we observe the voting decision of the represented.

We programme an online experiment using otree (Chen, Schonger, and Wickens 2016). In the first and second part of the experiment, we elicit individuals’ risk preferences through allocation tasks similar to the one developed by Gneezy and Potters (1997). In these tasks, subjects have to allocate a certain amount of points between two policies, called ‘safe’ and ‘risky’ policy, which differ regarding their payoffs in case of two possible outcomes, which are called ‘upswing’ and ‘downswing’. The risky policy gives a higher return in case of an upswing and no return in case of a downswing, whereas the safe policy gives the same intermediate return in case of an upswing or downswing. The difference between the first and the second part of the experiment is that in the first part, subjects need to take one single allocation decision which takes effect for two consecutive terms (in each of which an upswing or a downswing may occur), while in the second part, subjects take two (potentially different) allocation decisions, one in the first term and one in the second term.

In the third and main part of the experiment, we randomly assign participants to the roles of politicians (incumbents and challengers) and voters. Subjects are assigned to groups of three: one voter, one incumbent, and one challenger. Both politicians must decide how to allocate the same amount of points as in the previous parts between the two policies on behalf of the voter for two consecutive terms. Additionally, we ask them which risk preferences they expect the voter to have. In the first term, the allocation decision of the incumbent is implemented. After the first term, the voter is informed about the politicians’ decision and then must decide whether to re-elect the incumbent or to elect the challenger for the second term. The politicians’ payoff depends on the voter’s voting decision. If a politician is elected for the second term, she earns a fixed payoff, otherwise, she does not receive any payoff in this part of the experiment. The voter’s payoff depends on the decisive politician’s allocation decision and the outcome of the lottery in each term.

In a final part, we gather information on personal characteristics of the subjects and ask about general and specific preferences regarding risk decisions and political representation.

randomization done in office by a computer

experimental sessions (between-subject design)

No

353 groups

1059 subjects, 3 per group

122 groups in the 'long-term' treatment and 231 groups in the 'short-term' treatment (in the 'short-term' treatment approximately half of the participants face a positive and half a negative outcome) with 353 incumbents, 353 challenger and 353 voters in total