The analysis of the simultaneous voting results have been published in Bolle and Otto (2020).Footnote 7 Overall, the sequential voting behavior is rather different from the theoretical prediction and the comparison with simultaneous voting shows only small differences in true majority frequencies. Especially, sequential voting is investigated further to identify systematic deviations from equilibrium.
True majority results in simultaneous and sequential voting
Simultaneous voting for \(k=2\) with \(n^-=1\) in \(T_1\) and \(n^-=2\) in \(T_2\) has no pure strategy equilibria (Proposition 1). Eq. 3 delivers the two mixed strategy equilibria which are the same in \(T_1\) and \(T_2\).Footnote 8 This simplifies the theoretical prediction of results. Under the requirement that symmetric players should play the same strategy, mainly the two mixed strategies described by (4) remain. They are the same for \(T_1\) and \(T_2\). Therefore, we skip the pure/mixed equilibria as benchmarks for average behavior. The theoretical prediction for the sequential votes (derived from Proposition 3) are averages of the four sequences with which every treatment was played. The prediction for the negative players always voting Yes is clearly rejected. Table 2 shows that under simultaneous voting, true majority results were generated 11-12 percentage points more often and under sequential voting, 20 percentage points less often than predicted. Thus, the predicted difference between simultaneous voting (Eq. 3) and sequential voting (unique subgame perfection) largely vanishes when comparing experimental behavior.
Table 2 Percentages of Yes voting and true majority results Individual behavior in sequential voting
Contrary to simultaneous votes, the benchmark equilibrium for sequential votes is unique and—because it implies truthful results—also “fully satisfactory” from the perspective of mechanism design. Therefore, the major question is to which extent subjects stick to equilibrium behavior and, if not, what are possible reasons for deviations.
Deviations from the prediction might simply be “trembling hand” errors when applying the equilibrium strategy or might result from choosing a non-equilibrium strategy. Figure 1 shows frequency distributions of the number of individual Yes votes over the eight repetitions of one game. The U-shapes suggest that most voters play according to equilibrium predictions, that some play pure non-equilibrium strategies, and that there are deviations from equilibrium as well as pure non-equilibrium strategies. A first bounded rationality approach for explaining these errors is to assume that voters aim to follow Proposition 3 but incorrectly estimate \(k_i\) (number of previous Yes votes plus number remaining positive players). \(k_i\) can take integers from 0 to 3; for \(k_i=1\) a player should vote in line with true preferences (against true preferences otherwise). Under random errors, deviations from the equilibrium strategy should be independent of the position of a player. Alternatively, we might assume that subjects do not follow Proposition 3, but aim to apply backward induction if necessary. Backward induction is unnecessary if they are the last player; then they should know whether or not their vote is decisive. In positions one, two, and three they have to carry out respectively three steps, two steps, and one step of backward induction. Under this assumption, it appears plausible that the error rates decrease with the position in the decision sequence.
Table 3 Deviations from the unique subgame perfect equilibrium Average deviations from equilibrium in different player positions are reported in Table 3. Subjects seem to have increasing problems with backward induction the further they are away from the final position—especially in the first two positions. Kübler and Weizsäcker (2004) and Bolle (2017) find that backward induction in comparable games breaks down after two steps. This observation is clearly supported here. In sequential voting, even one-level reasoning (one step of backward induction in position 3 with deviation rates of 30.7% in \(T_1\) and 37.7% in \(T_2\)) is only weakly supported. However, deviations might as well originate from other sources like for example social preferences. A more complete picture concerning deviations for player types and separated for Yes versus No predictions are provided in Table 7 of Appendix A.
Social rules and static preferences
In the experimental voting games, we might expect two versions of ethical rules.Footnote 9 The first requires voting according to true preferences. The second is striving for efficiency (maximizing the sum of incomes): in \(T_1\) the equilibrium is efficient, but in \(T_2\) it requires never following true preferences. Some of the always Yes or always No voting subjects in Fig. 1 may be interpreted as a kind of voters who consistently follow a specific social rule. An alternative interpretation is that these voters follow opposite heuristics.
Two of the standard forms of static social preferences are linear altruism/spite and inequality aversion (formal representation in Appendix C). For both types of social preferences (with plausible parameter restrictions), a voter who is not decisive would never incur costs; i.e. positive voters would not vote Yes and negative voters would not vote No. Concerning altruism, the only effect is that i’s own income decreases; for inequality aversion, the value of reduced inequality is smaller than the loss of income. Only for strong altruism directed to negative voters, a positive voter who is decisive might vote No in order to save costs for himself and negative benefits for the negative voters. But under normal assumptions (in particular, stronger altruism for fellow positive voters than for negative voters), these gains cannot compensate the loss of the positive benefits of the positive players. Regarding strong enough inequality aversion, deviations from the equilibrium strategy of Proposition 3 are possible. Imagine a decisive positive voter whose fellow positive voter has or is expected to vote No. Voting against true preferences may prevent having less income than the fellow positive voter, but reduces own income and causes less income than negative voters. At least in \(T_2\), such a deviation from Proposition 3 requires inequality aversion to fellow positive players to be stronger than to negative players. This makes the explanation of deviations from the unique strategy of Proposition 3 rather implausible.
Emotional responses
There are various experiments which find (i) in-group subjects to be favored against out-group subjects (Ahmed 2007; Ben-Ner et al. 2009; Yan and Li 2009) and (ii) inequality aversion or altruism (Bellemare et al. 2008; Visser and Roelofs 2011). It is plausible, however, that magnitudes and relations of “social feelings” as in (i) and (ii) change when people interact. We want to keep things non-formal and call the changing preferences “emotional responses.” Subjects may become disappointed or thankful toward another player, in particular with respect to an in-group player. Let us introduce this hypotheses with an example: If there is a sequence (\(-,+,+,-\)), the equilibrium result of following the strategy from Proposition 3 is a sequence of votes (Yes, No, Yes, Yes). The positive voter in position 3 is disadvantaged compared with his fellow voter in position 2 who saves the costs of voting Yes. Although position 2 plays equilibrium, position 3 may become angry about this attempt to free ride or, in other words, about passing the buck.Footnote 10 Position 3 may punish position 2 by voting No, thus making the negative player in position 4 decisive. We call such a decision “anger” driven. Alternatively, position 3 may honor position 2 voting Yes (according to true preferences but against equilibrium) by own costly voting (also according to true preferences and against equilibrium). We say that, in the latter case, the voter at position 3 expresses “solidarity” with the voter at position 2. As a consequence of anger and solidarity, both positive players are not worse or better off than their exploitative or altruistic predecessor. This can be considered as a form of extreme inequity aversion (usually excluded) concerning the players with the same sign (compare Bolton 1997; Otto 2020).
The frequencies of individual choices in two (out of the eight) sequences are given in Appendix A. An example of solidarity is given in Fig. 3 with 48% (non-equilibrium) true preference votes after three No-votes. An example of anger driven votes are the \(51\%\) No votes of the positive player in position 2 in Fig. 4 after a No vote of the positive player in position 1. For statistical inferences, however, we need a clear definition of such kind of “emotional responses.”
Definition 4
A node or information set is called a solidarity node or solidarity information set if
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(i)
the positive (negative) player i whose turn it is has a predecessor with the same sign,
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(ii)
a current number of previous Yes (No) votes is larger than zero \(z_{Yes}>0\) (\(z_{No}>0\)) and implies the equilibrium move No (Yes) by player i,
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(iii)
the equilibrium move would have been Yes (No) for \(z_{Yes}-1\) (\(z_{No}-1\)).
If, in addition, \(z_{Yes}\) (\(z_{No}\)) is equal to the number of predecessors then the node is called a strong solidarity node, and otherwise a weak solidarity information set.
There are alternatives to these definitions. For example, a player may reduce incomplete information by the assumption that, in most cases, the voters from the other group had played equilibrium. Another possibility is to mitigate the third requirement by substituting prY-1 by prY-h where h is between 1 and the number of players from one’s own group. We think, however, that the restriction to prY-1 is that with the strongest signal: with one Yes-vote less, the equilibrium reply would have changed.
Definition 5
A node or information set of a player in position m is called an anger node or anger information set if
-
(i)
the positive (negative) player whose turn it is has a predecessor with the same sign
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(ii)
the current number of previous Yes votes \(z_{Yes}<m\) (\(z_{No}<m\)) implies the equilibrium move Yes (No)
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(iii)
the equilibrium move would have been No (Yes) for \(z_{Yes}+1\) (\(z_{No}+1\))
If, in addition, \(z_{Yes}\) (\(z_{No}\)) is equal to zero then the node is called a strong anger node, and otherwise a weak anger information set.
Strong solidarity or strong anger can be found in nodes, weak solidarity or weak anger in information sets. In the latter cases the current voter is not sure how the predecessors with the same sign have voted. Every game has seven separate nodes and three information sets with two nodes, i.e. in the eight different games (treatments times sequences), there are 80 different decision situations. 27 (34%) of them are classified as anger or solidarity nodes/information sets. In the regression analysis below, we find that, in these situations, there is a stronger tendency to deviate from equilibrium behavior than in other situations. Because several influences (position in the sequence, decision according or against true preferences) overlap, a regression analysis is better suited to investigate these "emotional responses" than non-parametric tests. In Section 4.6 we will test the following hypotheses with a regression analysis.
Hypothesis 1—Prevalence of true preferences: Deviations from equilibrium moves are more frequent in the direction of true preferences than away from true preferences.
Hypothesis 2—Emotional responses: Deviations from equilibrium moves are more frequent in solidarity and anger nodes/information sets than otherwise.
Hypothesis 3—Strong versus weak: Deviations from equilibrium moves are larger in strong solidarity (anger) nodes than in weak solidarity (anger) information sets.
Hypothesis 4—In dubio pro reo: Deviations from equilibrium moves are larger in solidarity information sets than in anger information sets.
All four hypotheses are evaluated jointly as regression parameters in our overall results predicting Yes versus No votes. Appendix D reports non-parametric tests concerning these individual hypotheses. The last hypothesis states that, in doubt (in information sets) we tend to believe that our co-player with the same sign has acted nicely.
Emotional evaluations
Emotions are influenced by others’ and own decisions in the process of a game and by the (anticipated or experienced) final result. In the previous sub-section, we investigated hypothetical emotional responses in certain states of the game—usually not the final state. In the experiment subjects were asked to self-evaluate their emotions after each game (round) according to their perceived happiness, anger, and fairness. Are the hypothetical emotions reflected by the subjectively reported emotions? Table 5 shows that, in strong anger situations, costly retaliation helps to decrease anger and to increase the perceived satisfaction as well as fairness. In other cases, also the decisions of later acting players and the result of a game may play a decisive role. This supports the assumption of emotion venting (e.g., Dickinson and Masclet 2015): After taking revenge, anger dwindles and satisfaction increases.
Table 4 Reported emotions separated for pivot-situations While emotional responses are defined for situations where previous players put the current player into a pivot player situation or not, you may look back from the end of the game and ask whether your decision has been decisive, i.e. whether it turned out ex post that you have been a pivot player or not. It might be satisfactory to have made the reward maximizing decision and you might feel anger if not. Three significant regularities are observed:
-
(i)
Wasted contributions: If players of my own sign have contributed less than \(k-1\) Yes votes (positive players) or \(4-k-1\) No votes (negative players) then my emotions are worse if I have followed true preferences instead of deciding opposite to them.
-
(ii)
Superfluous contributions: If there would have been enough votes for their preferred result, on average players regret their “solidarity decisions” but not as much as in (i).
-
(iii)
Pivot player contributions: If, in the end, players turn out to be pivot players they enjoy having made the reward maximizing decision.
The first two rows in Table 4 for \(T_1\) and for \(T_2\) support (i). Positive players feel worse if they voted Yes when compared to No (negative players vice versa). Differences between the fifth and the sixth row support (ii). The two middle rows of Table 4 for \(T_1\) and \(T_2\), support (iii).
Table 5 Emotions in sequential situations with emotional responses Tables 4 and 5 seem partly contradictory, but note that in Table 4 the pivot player status is determined ex post and in Table 5 the status was expected. The relevant sets of decisions/emotions overlap but are largely different.
The structure of emotions does not seem to be much different between sequential and simultaneous votes. The overall level, however, is a bit more “pleasant” for sequential votes. On average, fairness and satisfaction are rated by 0.3 points higher and anger by 0.2 points lower. In simultaneous games, our subjects knew about their pivot situation only ex post, and the same applies for the subjects in positions 1, 2, or 3 in the sequential games. Therefore, it is difficult to connect their ex post emotions with their ex ante decisions. The pivot position (possibly the emotions) in the current round of simultaneous games influence, however, the behavior in the following round (Bolle and Otto 2020; Bolle and Spiller 2021).
Regression analysis
The significance of equilibrium behavior and deviations according to the proposed hypotheses are tested within a regression analysis. Instead of running separate regressions for positive and negative players, we assume that deviations from equilibrium are symmetric, and for negative voters only into the opposite direction of deviations by positive voters. Therefore, all variables indicating behavioral predictions have been transformed by multiplication with the sign of the respective player. The intercept and the dummy \(P^+\) for a positive player measures autonomous (asymmetric) tendencies for positive versus negative players to vote Yes. Equilibrium behavior (variable “predict”) has a higher weight for decisions in positions 3 and 4, but not in position 2 (confirming the conclusion from Table 7). In all regressions, the respective dummy term for strong backward induction (predict\(\times\)position 2) was never significant and it has therefore been dropped in the presented Table 6. Hypotheses 1, 2, 3, and 4 are generally confirmed with one surprising exception, namely the coefficient of the weak anger dummy. Positive (negative) players in a weak anger situation are more probable to play equilibrium by voting Yes (No) than players in a no-anger situation. Our explanation is a more intensive decision process under the uncertainty whether or not a co-player with the same sign has “passed the buck,” thus making fewer mistakes when determining the equilibrium strategy. Otherwise Hypothesis 2 is confirmed. Generally strong hypothetical emotions cause a higher deviations from equilibrium than weak emotions, which is in favor of Hypothesis 3. The difference between the dummies for weak anger and weak solidarity is explained by “in dubio pro reo.” Hypothesis 4 is supported as the propensity to neglect solidarity in cases of doubt is far lower than the propensity to neglect anger. The significantly negative effect of the intercept is to be interpreted with caution. This aggregated residual reflects an overall tendency to deviate from the prediction into the direction No. In regressions which include \(P^+\), this strong tendency to vote No only holds for negative players, who are more likely to vote according to their true preference. The sum of intercept and the \(P^+\) coefficient depicts the tendency to follow true preferences for positive players. In the most differentiated regression, this sum is close to zero. With this differentiation, Hypothesis 1 is confirmed only for negative players. Furthermore, temporal influences over game repetitions have a significant effect, namely round (1–8) and period (1–32) negatively influencing the propensity to vote according to true preferences. \(T_1\) is only weakly significant. Other influences like the sequences of positive and negative players, reported emotions, or demographic variables (29 variables including personality questions not included in Table 6) are not significant. The only exception is Sequence 5 (\(+,+,+,-\)) potentially supporting an extreme form of solidarity or confirmative behavior (compare Fig. 4.
Table 6 Logit regression for voting Yes with random effects for session and subject