Abstract
Using belief elicitation, the paper investigates the process of belief formation and evolution in a signaling game in which a common prior is not induced. Both prior and posterior beliefs of Receivers about Senders’ types are elicited, as well as beliefs of Senders about Receivers’ strategies. In the experiment, subjects often start with diffuse uniform beliefs and update them in view of observations. However, the speed of updating is influenced by the strength of initial beliefs. An interesting result is that beliefs about the prior distribution of types are updated slower than posterior beliefs, which incorporate Senders’ strategies. In the medium run, for some specifications of game parameters, this leads to outcomes being significantly different from the outcomes of the game in which a common prior is induced. It is also shown that elicitation of beliefs does not considerably change the pattern of play in this game.
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Notes
Decisions from experience, and their differences from decisions from description, have been reviewed and investigated in psychology literature by, among others, Hertwig and Erev (2009), Gonzalez and Dutt (2011) and Ludvig and Spetch (2011). Often an additional complication in those studies is that sampling size is endogenous; in contrast, in our case the sampling size is fixed and known.
Chen et al. (2007) also investigated a setting with incomplete information, an auction, with and without induced knowledge of the prior distribution of players’ valuations. They found differences in behavior between these two cases in initial rounds but not in later rounds.
There is also an equilibrium in partially mixed strategies, for each value of p. However, these equilibria are unstable under many specifications of adjustment dynamics and indeed are not observed in the data.
If risk- and ambiguity-neutral; these assumptions are maintained throughout the discussion, also for the Receiver.
The presence of players with a higher level of reasoning than level-1 would accelerate the process but not change the final outcome.
The stationarity of the distribution was emphasized in the experiment instructions.
Offerman et al. (2009) and Andersen et al. (2012), among others, propose corrections of belief reports to account for different attitudes to risk and ambiguity. These corrections, however, require participants to perform additional tasks. To avoid the additional complexity, and since the focus is on the comparison of beliefs, all likely affected by risk and ambiguity attitudes in a similar manner, no such corrections are applied in this paper.
See a sample of the experiment instructions in Section A of Supplementary Materials for more details.
Of course, eliciting beliefs more often would have allowed to collect more data; however, this can make the task routine and incentives would have to be smaller. Facing the trade-off between paying less every period or having a higher payment every few periods, the latter option was chosen since it gives the subjects more incentives to take the belief reporting task seriously.
One session, in treatment K3, had only 8 participants.
Detailed test results for these and other tests in this section are given in Section B.1 of Supplementary Materials.
For posterior beliefs in K2 and K3, observations similar to those about posterior beliefs in K1 can be made.
This is also evidence that hedging is not a large problem, since it would imply choosing the other action, not the best response.
For the game played, the worst-case scenario for the Sender after \(m_{1}\) is to get 15 and after \(m_{2}\) is to get 25. Thus, \(m_{2}\) is always consistent with best response since there always exists a belief that \(m_{1}\) leads to a lower payoff. After \(m_{1}\) the expected payoff is \(15\cdot \Pr (a_{1})+80\cdot (1-\Pr (a_{1}))\) for type \(t_{1}\) and \(80\cdot \Pr (a_{1})+15\cdot (1-\Pr (a_{1}))\) for type \(t_{2}\). The chosen message \(m_{1}\) would be inconsistent with best response if the reported beliefs \(\Pr (a_{1})\) in response to it were more than 11 / 13 for type \(t_{1}\) and less than 2 / 13 for type \(t_{2}\).
For N2, there is no statistically significant difference between beliefs in Periods 1 and 36. The test results for this and subsequent subsections are reported in Section B.2 of Supplementary Materials.
Since there are only a few observations per subject, estimating parameters for each subject is infeasible.
Scores are based on all treatments, not only on those with \(p=1/4\). The SSE score for the forgetting model is very similar to that of the baseline model; the score for the initial strength model without forgetting is similar to that of this model with forgetting (see Section B.2 of Supplementary Materials). Thus only the baseline and the full (initial strength and forgetting) scores are reported.
It is the predictions of the model with \(\gamma =0.97\) and \(A_\mathrm{Ps}=2.29\) that are also shown in Fig. 4 by dotted lines.
Scores are again based on all treatments, not only on those with \(p=1/4\). The SSE score for the forgetting model is very similar to that of the baseline model; the score for the initial strength model without forgetting is similar to that of this model with forgetting (see Section B.2 of Supplementary Materials). Thus only the baseline and the full (initial strength and forgetting) scores are reported.
The same results holds for tests based on all periods or on the last eight periods. The data on which the tests are based are given in Section B.3 of Supplementary Materials, also for other tests in this section.
The tests are reported in Section B.4 of Supplementary Materials.
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Acknowledgements
I would like to thank the School of Economics, University of Nottingham, for financial support and CeDEx for providing access to the infrastructure to run the experiment. At different stages of the project, the paper benefitted from presentations at various conferences, including Foundations of Utility and Risk (FUR) 2016 conference. I thank the editor of this special issue, Ganna Pogrebna, for providing an opportunity for papers presented at the 2016 FUR conference to be considered for publication. I am grateful to an anonymous referee for comments that led to improvements in the paper and to Maria Montero for suggestions to make the exposition better.
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Possajennikov, A. Belief formation in a signaling game without common prior: an experiment. Theory Decis 84, 483–505 (2018). https://doi.org/10.1007/s11238-017-9614-z
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DOI: https://doi.org/10.1007/s11238-017-9614-z