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Storable votes with a “pay as you win” mechanism

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Abstract

This paper introduces a new storable vote mechanism (Storable Votes-Pay as you win, SV-PAYW) where a fixed number of votes is cast among different alternatives, and the votes spent (and redistributed) on each election depend only on the number cast for the winning alternative. The mechanism is expected to deliver more enfranchisement, efficiency and a reduction of uncertainty and strategic behavior with respect to previously known voting systems. To compare the pure storable votes with the SV-PAYW implementations, two key characteristics are monitored: the “enfranchisement gap”, which measures the proportionality between political influence and electoral victories, and the “efficiency ratio”, which assesses the utility derived from the allocation of electoral victories on a scale from random allocation (zero) to the social optimum (one). SV-PAYW consistently outperforms pure storable votes in terms of enfranchisement in all cases. Additionally, as a general rule (there are some exceptions), the “efficiency ratio” tends to be higher for SV-PAYW, hovering around 0.7.

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Notes

  1. The combination of multiple alternatives and vote buying and redistribution inspired this article; however, we propose a storable votes mechanism instead of a “votes-for-numeraire” one.

  2. That is, the stock of path of past electoral results does not impact the current period utility; only each period election matters for that period utility.

  3. When the one-man one-vote principle is applied the number of people belonging to A and B groups determine political weight; in firms, shares are the unit of political power, etc.

  4. An important notational issue is that \(k_{A}\) determines \(k_{B}\); consequently, it is the same that a given variable or function depends on \(k_{A}\) or on \(k_{B}\) or on both \(k_{A}\) and \(k_{B}\). As a general rule, functions and variables related to a player are indexed on her own vote endowment.

  5. In the general case (multiple alternatives) this pure SV implementation cannot be defined: the number of votes casted is not uniquely defined in a multi-alternative case.

  6. If the winner in case of draw were the player with more votes, when one player hits the zero votes level, the other would win all remaining rounds, leading to an “absorbent state" that distort all the games decisions. We avoid that by awarding the electoral victory in case of draw to the player with less votes.

  7. The straightforward discretization of the Vickrey implementation from the divisible votes case implies that if a player has zero votes, the other player wins the election by simply casting one vote and paying none. To avoid this absorbent state in the discretized version of the Vickrey implementation, if the player with the larger number of votes wins the election, she has to pay the maximum between the number of votes cast by the loser and one.

  8. Given that \(V^{j}(.)\) is a function ranging from {0.. N} to \(\mathbb {R}\), its representation is a vector with N+1 real numbers representing the expected utility of having k votes in the next period.

  9. The binomial distribution is \(Bin(w,s,i)=\left( \begin{array}{c} s\\ i \end{array}\right) w^{i}(1-w)^{s-i}\)

  10. As commented in Sect.  5, utilities are normalized for its use, so the normalized utility vector for Hv is (0.553, 1.66, 5.533), for Lg is (0.7, 1.4, 2.8).

  11. The 120 graphs are included in the replication materials: folder “GRAPHS/CONVERGENCE/INCOM” for the classical (incomplete information) setting, folder “GRAPHS/CONVERGENCE/COM” for the simplified (complete information) setting.

  12. The ratio was inspired by the receiving operational characteristic (ROC) curve used to assess the fit of predictive models for binary outcomes.

  13. The discrepancies between lines summary graph and the boxplots are explained because they present different statistics: the summary graph presents the means while the central trend statistic in the boxplots is the median.

  14. The discrepancies between lines summary graph and the boxplots are explained because they present different statistics: the summary graph presents the means while the central trend statistic in the boxplots is the median.

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Acknowledgement

I want to thank the Financial Risk Department of Banco de España for an exceptional intellectual and professional environment. Additionally, I would like to thank my Ph. D directors (Marc Vorsatz and Mariano Matilla Garcia, UNED) for training me on the techniques and research perspectives now applied in a surprisingly different research field. Rene Guerra Millet lent his selfless help to implement the calculations in a virtual machine. I am solely responsible for any errors. The opinions in this article do not necessarily coincide with those of the Banco de España or the Eurosystem.

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Correspondence to Arturo Macías.

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Social optimum equation transformation

Social optimum equation transformation

$$\begin{aligned} w_{A}\sum _{i=1}^{I^{A}}\sum _{j=1}^{I^{B}}\gamma _{ij}p_{ij}u_{i}^{A}+(1-w_{A})\sum _{i=1}^{I^{A}}\sum _{j=1}^{I^{B}}(1-\gamma _{ij})p_{ij}u_{j}^{B} \end{aligned}$$
(A1)

Some terms re-arrangement leaves the following expression:

$$\begin{aligned} \sum _{i=1}^{I^{A}}\sum _{j=1}^{I^{B}}\left[ w_{A}\gamma _{ij}p_{ij}u_{i}^{A}+(1-w_{A})(1-\gamma _{ij})p_{ij}u_{j}^{B}\right] \end{aligned}$$
(A2)

Then:

$$\begin{aligned} \sum _{i=1}^{I^{A}}\sum _{j=1}^{I^{B}}\left[ w_{A}\gamma _{ij}p_{ij}u_{i}^{A}+p_{ij}u_{j}^{B}-w_{A}p_{ij}u_{j}^{B}-\gamma _{ij}p_{ij}u_{j}^{B}+w_{A}\gamma _{ij}p_{ij}u_{j}^{B}\right] \end{aligned}$$
(A3)

The terms without controls are grouped on one side and the terms that include controls are grouped on the other:

$$\begin{aligned} \sum _{i=1}^{I^{A}}\sum _{j=1}^{I^{B}}\left[ p_{ij}u_{j}^{B}-w_{A}p_{ij}u_{j}^{B}\right] +\sum _{i=1}^{I^{A}}\sum _{j=1}^{I^{B}}\left[ w_{A}\gamma _{ij}p_{ij}u_{i}^{A}-\gamma _{ij}p_{ij}u_{j}^{B}+w_{A}\gamma _{ij}p_{ij}u_{j}^{B}\right] \end{aligned}$$
(A4)

And simplifying the last term:

$$\begin{aligned} \sum _{i=1}^{I^{A}}\sum _{j=1}^{I^{B}}\left[ p_{ij}u_{j}^{B}-w_{A}p_{ij}u_{j}^{B}\right] + \sum _{i=1}^{I^{A}}\sum _{j=1}^{I^{B}}\gamma _{ij}p_{ij}(w_{A}u_{i}^{A}-(1-w_{A})u_{j}^{B}) \end{aligned}$$
(A5)

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Macías, A. Storable votes with a “pay as you win” mechanism. J Econ Interact Coord 19, 121–150 (2024). https://doi.org/10.1007/s11403-024-00407-1

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