How can you be a more vigilant voter in elections?

 Given my research interests, I usually monitor the majority of the forms of contest; one of these forms is elections. From my point of view, when I see modern politics nowadays, I notice that candidates or political parties focus much more on criticizing or attacking their opponents rather than focusing on one’s positive attributes. This strategy has a clear definition. This is a Negative campaigning strategy. These campaigns often involve attacking the opponent's character, record, or position on issues. Negative campaigning can take various forms, including attack ads on television, radio, or social media, as well as negative messaging in speeches, debates, and campaign literature. The main purpose of the negative campaign is to seed doubt in the rival candidate's support regarding the opponent’s fit for office.

There are some reasons why this strategy is valuable for politicians:

Highlighting Contrasts: By focusing on the flaws or weaknesses of opponents, candidates can emphasize the differences between themselves and their rivals, making their own positions or qualities appear more favorable by comparison.

Mobilizing Supporters: Negative campaigns can energize a candidate's base by rallying them against a common enemy. Voters who are strongly opposed to the opponent may be more motivated to turn out and vote.

Undermining Opponents: Negative ads can damage an opponent's reputation and credibility, potentially reducing their support among undecided voters or causing supporters to reconsider their allegiance.

Shaping Perceptions: Negative campaigning can shape voters' perceptions of the opponent, framing them in a negative light and potentially influencing how they are viewed by the public.

However, there are a few reasons why negative campaigning also has its drawbacks:

Backlash: Voters may become disillusioned or turned off by negative campaigning, viewing it as petty or unproductive. This could lead to a backlash against the candidate employing such tactics. Some negative attacks may be seen as unfair or overly aggressive, causing sympathy for the opponent or leading voters to question the credibility of the attacker.

Damage to Civility: Negative campaigning can contribute to a decline in the overall tone of political discourse, fostering division and polarization within society.

Risk of Backfiring: Focus on Issues: Negative campaigning often detracts from substantive policy discussions, potentially depriving voters of important information about candidates' positions and proposals.

Here are some real-life examples of negative campaigning from various political contexts:

• In the 2012 U.S. presidential election, the Obama campaign ran ads criticizing Mitt Romney's record at Bain Capital, portraying him as a corporate raider who laid off workers for profit (link).
• During the 2016 U.S. presidential election, both Donald Trump and Hillary Clinton engaged in extensive negative campaigning against each other, with Trump labeling Clinton as "Crooked Hillary" and Clinton portraying Trump as unfit for office (link).
• In the UK, during the 2019 general election campaign, various political parties released attack ads targeting their opponents' policies and leadership qualities. For instance, the Conservative Party ran ads accusing Labour Party leader Jeremy Corbyn of being weak on national security (link).

These examples demonstrate how negative campaigning is a common strategy used in various political contexts around the world, from national elections to local races and referendums. Throw evidence of negative campaigns might have been found many years ago. In many cases, Richard M. Nixon’s 1968 presidential campaign started this form of negative campaign that we have now (link). Throw in our days is much more aggressive (from my point of view).

To understand the effect of the negative campaign, let’s look at this situation using game theoretical or proxies contest theoretical glasses. Regarding contest theory, we can look at the election as a contest where two forms of effort are exerted. The productive effort increases the contestant's (candidate or party) probability of winning, and the sabotaging effort decreases the probability of the consistent rival winning. The second form of effort is the effort exerted in a negative campaign.

The main question now is what contest theory can say about the effect of negative campaigns and how this campaign affects us, the voters.

These are the main insights from contest theoretical research in the field:

·         Adverse selection - Sabotage may lead to adverse selection of contestants. Namely, the best possible participants might refrain from participating altogether. In other words, the best politician might drop out of the election, and we will stay with the lower types of politicians (these results can be seen in many countries).

·         Information issues - Sabotage may prevent the contest organizer from allowing proper information flow and destroying valuable output. As voters, we are the contest organizers in case of an election, and thus, we won’t be able to choose the right candidate party because of the information issue.

·         Resources expended on sabotage behavior are unproductive and hence wasteful. Money is thrown in the garbage.

·         Discouragement effect - The expectation of being sabotaged has a discouragement effect, which causes the participants to reduce their productive efforts. Namely, we will see politicians exert effort mainly in the negative campaigns (that is what indeed happens) and not in the positive campaigns. Namely, we will not know why to vote for a specific candidate, but we will know only why not to vote for him and since the information issue is also partial information.

·         Election attractiveness - Sabotage may reduce the attractiveness of the contest. In other words, fewer people will appear to vote on election day, and by that, will see more bias in the election outcome.

In the sum of all the bullets above, we can see that negative campaigns, in general, damage us as voters and hurt our decision-making to make the proper candidate choice.

The next question is what contest theory can teach us, the voters, how to reduce the level of negative campaigns. The most trivial is to reduce benefits from sabotaging or negative campaigns or to increase the cost of sabotaging. To pay attention to the campaign's narrative, punish the sabotaging politicians/parties by not choosing them, and reduce the incentives to be involved in negative campaigns.

In conclusion, contest theory provides valuable insights into the detrimental effects of negative campaigning on political contests and voter decision-making. By understanding these dynamics, voters can advocate for reforms to mitigate the prevalence of negative campaigns and uphold the principles of informed constructive democracy.

The pictures in this post were taken from Unsplash.

 

How do you divide a cake without regrets?

Consider a simple situation when two kids fight each other over a cookie. Let's assume that there is only one cookie. How do we divide the cookie so that both kids will be satisfied? This is not such an easy assignment. Now, let's consider a similar situation between adults. For example, assets acquired during the marriage must be divided fairly between spouses during divorce proceedings. This is also not such a simple assignment. Some will define it as a hard-to-do assignment. But, in some cases, science can help with relatively simple and straightforward roles. The rules are based on a well-known Cake-Cutting algorithm that is a part of the fair division concept.

Fair division is a concept in mathematics and economics that allocates goods or resources among individuals so that each person perceives their share as equitable or fair. This could involve dividing a cake, sharing property, assigning tasks, or distributing any other divisible item among multiple parties.

The history of the fair division concept goes back to the 1940s when Polish mathematician Hugo Steinhaus was considered the first to study the “cake-cutting procedure.” Since then, many studies have taken place in the field of fair division.  The formal research of fair division gained momentum in the 20th century with the emergence of game theory. The fair division became a central topic in cooperative game theory, where researchers developed algorithms and solution concepts for dividing resources among multiple parties.

Let’s go straight to the topic.

How can we apply this Cake-Cutting algorithm in real–life situations?

Simple. Consider dividing one small cake between two people. One person cuts the cake into two portions, and the other chooses which portion they want. This ensures fairness in the eyes of both parties.

This simple approach was mentioned in the Bible when Abraham and Lot divided the land of Cannan.

The next question is how to implement it in real-life situations. Here are two examples that will help with that.

Imagine two siblings, Alex and Sam, inheriting a collection of valuable vintage comics from their grandparents. Both siblings are interested in comics but have different preferences and values for each item in the collection.

To divide the collection fairly, Alex and Sam can use the "divide and choose" method:

1. Dividing: One sibling (Alex) divides the collection into two portions they believe to be of equal value. Alex carefully divides the comics, trying to make each portion as equal as possible, considering factors like rarity, condition, and personal preference.
2. Choosing: Sam, the other sibling, gets to choose which portion they want. Sam carefully examines both portions, assessing each comic's value and considering their preferences. After careful consideration, Sam decides the portion they believe to be more valuable or desirable.

This method ensures fairness because the sibling dividing the collection is incentivized to make the portions as equal as possible to prevent the other sibling from choosing the more valuable portion. Meanwhile, the other sibling can choose the portion they perceive to be more valuable, thereby ensuring both parties are satisfied with the outcome.

Another example:

Let's say two friends, Sarah and John, are planning a weekend road trip together. 

They must decide how to divide the driving responsibilities fairly since they'll share one car.

1. Dividing: Sarah suggests splitting the driving equally, with each person driving for half of the journey. However, John is concerned about driving through heavy traffic in a city they'll be passing through. To make the division fair, Sarah proposes dividing the driving based on time rather than distance. She suggests that they break the trip into two equal time segments, each driving for one segment.
2. Choosing: John agrees to Sarah's proposal. To determine who drives first, they flip a coin. Sarah wins the coin toss and gets to choose whether she wants to drive the first or second segment. After considering factors like traffic patterns and rest stops, Sarah drives the first segment.

This method ensures fairness because Sarah, as the person dividing the driving time, is incentivized to create two segments of equal duration. Meanwhile, John, as the person choosing which segment to drive, can select the segment that best fits his preferences and concerns. They can reach a fair agreement that satisfies both parties by dividing and choosing.

Below is a more practical and sophisticated example that requires additional knowledge of the Cutting Cake algorithm.

Let's consider a hypothetical divorce settlement scenario between Alice and Bob, a married couple who are separating and need to divide their assets fairly. We'll use a little bit more sophisticated cake-cutting algorithm than described above to help them reach a fair distribution of their shared resources. 

Here's how the process might unfold:

1. Inventory of Assets:
• Alice and Bob create an inventory of all their shared assets, including property, savings, investments, vehicles, household items, and other valuable possessions.
2. Preferences and Priorities:
• Each of them lists their preferences and priorities regarding the division of assets. For example, Alice might prioritize keeping the family home for stability for their children, while Bob might prioritize retaining investments for long-term financial security.
3. Fair Division:
• They agree to use a cake-cutting algorithm to divide their assets fairly.
4. Ranking of Assets:
• Alice and Bob individually rank the assets in the inventory based on their preferences and perceived value. They may assign numerical values or rankings to each asset, indicating their relative importance.
5. Algorithm Execution:
• They input their rankings into the cake-cutting algorithm, which processes the data to determine a fair division of assets that minimizes envy between them. The algorithm aims to allocate assets to maximize the overall satisfaction of both parties.
6. Negotiation and Adjustments:
• After the algorithm generates a proposed division of assets, Alice and Bob review the results and negotiate any necessary adjustments or modifications. They may discuss trade-offs, compromises, or additional considerations to ensure the division meets their needs and preferences.
7. Final Agreement:
• Once they reach a consensus on the division of assets, Alice and Bob formalize their agreement in a legally binding document, such as a divorce settlement agreement. The document outlines the distribution of assets, liabilities, and any other relevant terms or provisions related to their separation.
8. Legal Approval:
• They may seek legal advice to review the settlement agreement and ensure its compliance with applicable laws and regulations. Once approved, they finalize the divorce proceedings, and the agreed-upon division of assets takes effect.

By using a cake-cutting algorithm in their divorce settlement process, Alice and Bob can achieve a fair and equitable distribution of their shared assets, minimizing conflicts and promoting a smoother transition to their new lives post-divorce. The algorithm helps them objectively navigate the complexities of asset division, considering their preferences and priorities.

If you want to widen your understanding of the field, link to one of the recommended books.

The pictures in this post were taken from Unsplash.

 

Tip on how to bid the right amount on eBay auctions

 As a researcher in game theory, auctions, and contests, I share your fascination with the practical application of research findings in real-life situations. While delving deeper into auction theory, I discovered that in certain cases, complex equations or sophisticated algorithms are not necessary to determine an optimal bidding strategy that balances the desire to win an item with avoiding overpaying. Surprisingly, a few straightforward rules and strategies apply to certain auction formats that any individual can implement strategically. In this article, we will explore the application of these simple bidding strategies in eBay auctions.

 eBay revolutionized the e-commerce industry as one of the pioneering companies that utilized the Internet to buy and sell goods and services. Founded by American entrepreneur Pierre Omidyar in 1995, eBay introduced online auctions, which became one of its signature features. By implementing a unique bidding mechanism, eBay created a platform where users could participate in competitive bidding for various items.

The bidding process on eBay involves individuals expressing their interest in purchasing a specific item by placing a bid. When a user decides to bid on an item, they enter the maximum amount they are willing to pay for it. This maximum bid remains confidential and is known only to the bidder. As other users place their bids, the auction system automatically increases the current price of the item, based on predefined bid increments, until the auction's end time.

The highest bid at the conclusion of the auction period determines the outcome of an eBay auction. However, the winning bidder does not pay their maximum bid; instead, they pay the price that surpasses the second-highest bid by the smallest increment. In essence, the winning bidder pays an amount equivalent to the second-highest bid plus a predefined increment.

This type of auction is commonly called a second-price auction or a Vickrey auction. To illustrate the auction outcome, consider the bids that are posted in the auction as 100$, 50$, 75$, and 64$. The winner is the bidder that placed a 100$ bid, but he will pay the second highest bid, 75$.

 

The second-price auction is called the Vickery Auction because of a well-known researcher in economics and Nobel Laureate William Vickery. Professor Vickery was the first to study and analyze the auction with game theoretical tools. William Vickrey's pioneering work on auctions, particularly the second-price auction, provided important insights into the optimal bidding strategies and outcomes in various auction formats. His research shed light on bidders’ behavior and the implications of different auction rules on efficiency and revenue generation.

The game theoretical analysis of the second-price auction provides insights into the optimal bidding strategy for participants. In this type of auction, the dominant strategy for bidders is to place their true valuations on an item. By doing so, bidders can maximize their chances of winning while ensuring that they pay an amount that aligns with their actual willingness to pay.

Placing a bid equal to their true valuation allows bidders to avoid overpaying for an item. Since the winning bidder pays the second-highest bid, bidders who accurately assess the item’s value can secure it at a price that reflects the market's consensus. This mechanism creates a fair and efficient outcome, encouraging participants to bid sincerely and avoid artificially inflating the prices.

The simplicity of calculating the bid is another advantage of the second-price auction. Bidders can refrain from engaging in complex calculations or strategic maneuvers. Instead, they can rely on straightforward logic and bid the maximum amount they genuinely want to pay. This transparency and ease of calculation contribute to a level playing field and promote participant trust.

eBay's utilization of the second-price auction mechanism aligns with the principles of fairness and efficiency. By implementing this bidding system, eBay ensures that the winning bidder is the one who values the item the most, as reflected by their bid. This encourages a genuine and competitive bidding environment where participants can confidently express their valuation without fearing overpaying.

Overall, the game’s theoretical analysis of the second-price auction supports eBay’s use of this mechanism. It provides a strategic rationale for bidders to bid truthfully, promotes fairness in determining the winning bid, and offers a straightforward approach to calculating bids. Through these means, eBay fosters an environment where buyers and sellers can engage in auctions with confidence and trust in the process.

The main question: How much should you bid on eBay? 

The answer is quite simple. Ask yourself how much you are willing to pay for the current item that is sold in the auction and place this value as a bid.

This can be challenging. You might say, what if I don’t know my valuation for the item at the auction? What should I do? This is a common challenge in auctions when you are unsure about your valuation for the sold item. In such cases, there is a strategy you can consider:

Begin with a guested value that you can easily pay for the item on sale in the auction. Rise it up by small amounts until the price is too high for you and you don’t want to apply the last increase; this is the amount that you should bid. Important to determine that the possible budget that you are willing to pay will be, at most, that value.

For example, you start with 50$, and you ask yourself, would you agree to pay for the item 51$? If the answer is yes, you continue to rise. 52$? The answer again is yes; we are rising to 53$, and asking ourselves again, 53$ is ok? If the answer is no. We are stopping to raise the amount and placing a bid of 52$ on the eBay auction.

By applying these simple rules and strategies rooted in game theory, you can enhance your chances of winning eBay auctions while maintaining control over your spending. Each auction is unique; factors like item popularity and bidder behavior can vary. Continuously learning and adapting your approach based on observed outcomes will refine your bidding skills over time. Good luck with your future eBay bidding endeavors!

The pictures in this post were taken from Unsplash.

 

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Backward induction concept: How can it help us in real-life decisions?

In the current post, I will write about a concept from game theory that could make a decision-making process more manageable. Game theory, in general, is the study of mathematical models that model interaction between rational agents. This game theory concept is also applied in decision theory and is entitled backward induction. Backward induction is a concept often used to solve sequential games, where players make decisions one after another. It involves working backward from the end of a game to its beginning, considering each player's optimal choices at each stage. This technique helps players determine the best strategies by considering the potential outcomes of different decisions.

The first to introduce the concept was Arthur Cayley in 1887, who discovered the method while trying to solve the infamous Commissioner Problem.  John von Neumann and Oskar Morgenstern, the game theory pioneers, introduced the backward induction concept as a game-solving process in their book Theory of Games and Economic Behavior (1944).  There have been many academic works done in that field since then. Kreps and Wilson did the first and more solid definition of this concept in terms of game theory in 1982.

The concept of backward induction is a fundamental idea in game theory and decision-making, and its development can be attributed to multiple researchers over time. While it's challenging to pinpoint a single individual as the "first" to introduce the concept, its foundations have been built upon the works of various mathematicians, economists, and scholars.

How can the concept help in everyday decision-making? I will try to answer that in detail.

Remember that real-life decisions can be more complex and uncertain than simplified examples and unexpected factors might arise. However, the backward induction approach can provide a structured way to think about decisions and their potential consequences in a strategic manner.

Here's how backward induction can be applied as a decision-making tool:

1. Define the End Goal: Clearly identify your ultimate objective or desired outcome. This could be achieving a career milestone, maximizing profits in a business venture, or any other goal involving a series of decisions.
2. Identify Intermediate Steps: Break down the journey toward your goal into intermediate steps or stages. Consider what needs to be accomplished at each stage to move closer to your end goal.
3. Evaluate Options at Each Stage: Consider each intermediate stage's available options or choices. Analyze the potential outcomes of each choice, including the impact on future stages and the overall goal.
4. Consider Consequences: Analyze the consequences of each option on future decisions and outcomes. Think about how each choice will influence subsequent choices and whether it will move you closer to or farther from your ultimate goal.
5. Work Backward: Start from the final stage and work backward through the stages, considering the optimal choices at each step. This involves considering what decision you would make if you were at the last stage, given the best choices made in the subsequent stages.
6. Choose the Best Path: Select the option that leads to the most favorable outcomes at every stage, ultimately aligning with your end goal.

Here's the first example of how it might be used:

Example: Job Offer Decision

Imagine you are a recent college graduate who has received multiple job offers. You need to decide which job to accept. Each job has different salary packages, work environments, and potential career paths. You decide to use the backward induction approach.

1. Identify the End Point: Start by clearly defining your ultimate objective or desired outcome. This could be a long-term goal, a project completion, a career milestone, or any decision-making situation with multiple steps. For example, what do you ultimately want to achieve in your career? This could be becoming a manager, working in a specific industry, or starting your own business.
2. Work Backward: Think about the path that will best lead you to your long-term goals. Consider the potential career progression at each job, the skills you will acquire, and the network you will build.
3. Consider Intermediate Goals: Break down your long-term goal into intermediate goals. For example, if your goal is to become a manager, you might need to first gain experience in a certain role and develop specific skills.
4. Evaluate Job Offers: Compare the job offers based on how well they align with your intermediate and long-term goals. Consider factors like salary, benefits, location, opportunities for growth, and alignment with your values.
5. Select the Best Option: Choose the job offer that best aligns with your goals and offers the most promising path toward achieving them.

By using backward induction, you've thoughtfully analyzed each job offer in the context of your long-term objectives. This approach helps you make a decision that aligns with your aspirations and maximizes your chances of success.

Here's a simplified second example to illustrate these steps:

Example: Vacation Planning

1. Define the End Goal: Plan a memorable vacation.

2. Identify Intermediate Steps: Choose a destination, book accommodations, plan activities, pack, and travel.

3. List Available Options: Destination A, Destination B, etc. Different accommodations, activity options, etc.

4. Analyze Potential Outcomes: Consider costs, available attractions, weather, convenience, etc.

5. Consider Interactions: Booking accommodations might depend on the chosen destination.

6. Determine Optimal Choices: Choose a destination that aligns with your preferences and offers the best experience.

7. Evaluate Alignment: Ensure that the chosen destination and planned activities align with your vacation goal.

8. Select the Best Path: Make decisions that lead to a well-planned vacation.

9. Contingency Planning: Plan for unexpected weather or activity cancellations.

10. Execute and Monitor: Book accommodations, plan activities, and track progress.

11. Adapt and Update: Adjust plans if weather conditions change or new activities become available.

In conclusion, backward induction is a valuable concept in game theory and decision-making that involves working backward through a sequence of decisions or stages to determine optimal strategies or outcomes. It is a powerful tool for analyzing strategic interactions in various contexts, from simple games to complex real-life situations. In essence, backward induction provides a structured and forward-thinking approach to decision-making, allowing individuals to make rational choices by considering the long-term implications of their actions.

 The pictures in this post were taken from Unsplash.