{"id":8999,"date":"2023-10-12T18:45:38","date_gmt":"2023-10-12T18:45:38","guid":{"rendered":"https:\/\/content.one.lumenlearning.com\/quantitativereasoning\/?post_type=chapter&#038;p=8999"},"modified":"2024-10-18T20:58:42","modified_gmt":"2024-10-18T20:58:42","slug":"weighted-voting-learn-it-4","status":"web-only","type":"chapter","link":"https:\/\/content.one.lumenlearning.com\/quantitativereasoning\/chapter\/weighted-voting-learn-it-4\/","title":{"raw":"Weighted Voting: Learn It 4","rendered":"Weighted Voting: Learn It 4"},"content":{"raw":"<h2>Calculating Power: Shapley-Shubik Power Index<\/h2>\r\n<p>The <strong>Shapley-Shubik power index<\/strong> was introduced in 1954 by economists Lloyd Shapley and Martin Shubik, and provides a different approach for calculating power.<\/p>\r\n<p>In situations like political alliances, the order in which players join an alliance could be considered the most important consideration. In particular, if a proposal is introduced, the player that joins the coalition and allows it to reach quota might be considered the most essential. The Shapley-Shubik power index counts how likely a player is to be pivotal. What does it mean for a player to be pivotal?<\/p>\r\n<p>First, we need to change our approach to coalitions. Previously, the coalition [latex]\\{P_1,P_2\\}[\/latex] and [latex]\\{P_2,P_1\\}[\/latex] would be considered equivalent, since they contain the same players. We now need to consider the order in which players join the coalition. For that, we will consider <strong>sequential coalitions<\/strong> \u2013 coalitions that contain all the players in which the order players are listed reflect the order they joined the coalition. For example, the sequential coalition [latex]&lt; P_2,P_1,P_3&gt;[\/latex] would mean that [latex]P_2[\/latex] joined the coalition first, then [latex]P_1[\/latex], and finally [latex]P_3[\/latex]. The angle brackets [latex]&lt; &gt;[\/latex] are used instead of curly brackets to distinguish sequential coalitions.<\/p>\r\n<section class=\"textbox keyTakeaway\">\r\n<div>\r\n<h3>pivotal player<\/h3>\r\n<p>A <strong>sequential coalition<\/strong> lists the players in the order in which they joined the coalition.<\/p>\r\n<p>&nbsp;<\/p>\r\n<p>A <strong>pivotal player<\/strong> is the player in a sequential coalition that changes a coalition from a losing coalition to a winning one. Notice there can only be one pivotal player in any sequential coalition.<\/p>\r\n<\/div>\r\n<\/section>\r\n<section class=\"textbox example\">In the weighted voting system [latex][8:6,4,3,2][\/latex], which player is pivotal in the sequential coalition [latex]&lt; P_3,P_2,P_4,P_1 &gt;[\/latex] ? [reveal-answer q=\"4331\"]Show Solution[\/reveal-answer] [hidden-answer a=\"4331\"]\r\n\r\n<p>The sequential coalition shows the order in which players joined the coalition. Consider the running totals as each player joins:<\/p>\r\n<p style=\"text-align: center;\">[latex]\\begin{array}{lll}P_{3} &amp; \\text { Total weight: } 3 &amp; \\text { Not winning } \\\\ P_{3}, P_{2} &amp; \\text { Total weight: } 3+4=7 &amp; \\text { Not winning } \\\\ P_{3}, P_{2}, P_{4} &amp; \\text { Total weight: } 3+4+2=9 &amp; \\text { Winning } \\\\ R_{2}, P_{3}, P_{4}, P_{1} &amp; \\text { Total weight: } 3+4+2+6=15 &amp; \\text { Winning }\\end{array}[\/latex]<\/p>\r\n<p>Since the coalition becomes winning when [latex]P_4[\/latex] joins, [latex]P_4[\/latex] is the pivotal player in this coalition.<\/p>\r\n\r\n[\/hidden-answer]<\/section>\r\n<section class=\"textbox questionHelp\">\r\n<p><strong>How To: Calculating Shapley-Shubik Power Index<\/strong><\/p>\r\n<p>To calculate the Shapley-Shubik Power Index:<\/p>\r\n<ol style=\"list-style-type: decimal;\">\r\n\t<li>List all sequential coalitions<\/li>\r\n\t<li>In each sequential coalition, determine the pivotal player<\/li>\r\n\t<li>Count up how many times each player is pivotal<\/li>\r\n\t<li>Convert these counts to fractions or decimals by dividing by the total number of sequential coalitions<\/li>\r\n<\/ol>\r\n<\/section>\r\n<p>How many sequential coalitions should we expect to have? If there are [latex]N[\/latex] players in the voting system, then there are [latex]N[\/latex] possibilities for the first player in the coalition, [latex]N\u20131[\/latex] possibilities for the second player in the coalition, and so on. Combining these possibilities, the total number of coalitions would be: [latex]N(N\u22121)(N\u22122)(N\u22123)\u22ef(3)(2)(1)[\/latex]. This calculation is called a <strong>factorial<\/strong>, and is notated [latex]N![\/latex] . The number of sequential coalitions with [latex]N[\/latex] players is [latex]N![\/latex] .<\/p>\r\n<section class=\"textbox recall\">\r\n<p><strong>Factorial<\/strong><\/p>\r\n\r\nCalculating the <strong>factorial <\/strong>is a way to calculate the product of all positive whole numbers up to a given number. <strong>Notation:<\/strong> A factorial is represented by an exclamation mark [latex](!)[\/latex] following a number.<\/section>\r\n<section class=\"textbox example\">How many sequential coalitions will there be in a voting system with [latex]7[\/latex] players? [reveal-answer q=\"4332\"]Show Solution[\/reveal-answer] [hidden-answer a=\"4332\"]\r\n\r\n<p>There will be [latex]7![\/latex] sequential coalitions. [latex]7!=7\u22c56\u22c55\u22c54\u22c53\u22c52\u22c51=5040[\/latex]<\/p>\r\n\r\n[\/hidden-answer]<\/section>\r\n<p>As you can see, computing the Shapley-Shubik power index by hand would be very difficult for voting systems that are not very small.<\/p>\r\n<section class=\"textbox example\">Consider the weighted voting system [latex][6:4,3,2][\/latex]. We will list all the sequential coalitions and identify the pivotal player. We will have [latex]3! = 6[\/latex] sequential coalitions. The coalitions are listed, and the pivotal player is underlined.\r\n\r\n<p style=\"text-align: center;\">[latex]\\begin{aligned} &amp;&lt; P_{1}, \\underline{P}_{2}, P_{3} &gt;\\quad&lt; P_{1}, \\underline{P}_{3}, P_{2} &gt;\\quad&lt; P_{2}, \\underline{P}_{1}, P_{3} &gt;\\\\ &amp;&lt; P_{2}, P_{3}, \\underline{P}_{1} &gt;\\quad&lt; P_{3}, P_{2}, \\underline{P}_{1} &gt;\\quad&lt; P_{3}, \\underline{P}_{1}, P_{2} &gt; \\end{aligned} [\/latex]<\/p>\r\n\r\n[reveal-answer q=\"4333\"]Show Solution[\/reveal-answer] [hidden-answer a=\"4333\"]\r\n\r\n<p>[latex]P_1[\/latex] is pivotal [latex]4[\/latex] times, [latex]P_2[\/latex] is pivotal [latex]1[\/latex] time, and [latex]P_3[\/latex] is pivotal [latex]1[\/latex] time.<\/p>\r\n<p style=\"text-align: center;\">[latex]\\begin{array}{|l|l|l|} \\hline \\textbf { Player } &amp; \\textbf { Times pivotal } &amp; \\textbf { Power index } \\\\ \\hline P_{1} &amp; 4 &amp; 4 \/ 6=66.7 \\% \\\\ \\hline P_{2} &amp; 1 &amp; 1 \/ 6=16.7 \\% \\\\ \\hline P_{3} &amp; 1 &amp; 1 \/ 6=16.7 \\% \\\\ \\hline \\end{array} [\/latex]<\/p>\r\n<p>For comparison, the Banzhaf power index for the same weighted voting system would be [latex]P_1:60\\%,P_2:20\\%,P_3:20\\%[\/latex]. While the Banzhaf power index and Shapley-Shubik power index are usually not terribly different, the two different approaches usually produce somewhat different results.<\/p>\r\n\r\n[\/hidden-answer]<\/section>\r\n<section class=\"textbox tryIt\">[ohm2_question hide_question_numbers=1]13340[\/ohm2_question]<\/section>","rendered":"<h2>Calculating Power: Shapley-Shubik Power Index<\/h2>\n<p>The <strong>Shapley-Shubik power index<\/strong> was introduced in 1954 by economists Lloyd Shapley and Martin Shubik, and provides a different approach for calculating power.<\/p>\n<p>In situations like political alliances, the order in which players join an alliance could be considered the most important consideration. In particular, if a proposal is introduced, the player that joins the coalition and allows it to reach quota might be considered the most essential. The Shapley-Shubik power index counts how likely a player is to be pivotal. What does it mean for a player to be pivotal?<\/p>\n<p>First, we need to change our approach to coalitions. Previously, the coalition [latex]\\{P_1,P_2\\}[\/latex] and [latex]\\{P_2,P_1\\}[\/latex] would be considered equivalent, since they contain the same players. We now need to consider the order in which players join the coalition. For that, we will consider <strong>sequential coalitions<\/strong> \u2013 coalitions that contain all the players in which the order players are listed reflect the order they joined the coalition. For example, the sequential coalition [latex]< P_2,P_1,P_3>[\/latex] would mean that [latex]P_2[\/latex] joined the coalition first, then [latex]P_1[\/latex], and finally [latex]P_3[\/latex]. The angle brackets [latex]< >[\/latex] are used instead of curly brackets to distinguish sequential coalitions.<\/p>\n<section class=\"textbox keyTakeaway\">\n<div>\n<h3>pivotal player<\/h3>\n<p>A <strong>sequential coalition<\/strong> lists the players in the order in which they joined the coalition.<\/p>\n<p>&nbsp;<\/p>\n<p>A <strong>pivotal player<\/strong> is the player in a sequential coalition that changes a coalition from a losing coalition to a winning one. Notice there can only be one pivotal player in any sequential coalition.<\/p>\n<\/div>\n<\/section>\n<section class=\"textbox example\">In the weighted voting system [latex][8:6,4,3,2][\/latex], which player is pivotal in the sequential coalition [latex]< P_3,P_2,P_4,P_1 >[\/latex] ? <\/p>\n<div class=\"qa-wrapper\" style=\"display: block\"><button class=\"show-answer show-answer-button collapsed\" data-target=\"q4331\">Show Solution<\/button> <\/p>\n<div id=\"q4331\" class=\"hidden-answer\" style=\"display: none\">\n<p>The sequential coalition shows the order in which players joined the coalition. Consider the running totals as each player joins:<\/p>\n<p style=\"text-align: center;\">[latex]\\begin{array}{lll}P_{3} & \\text { Total weight: } 3 & \\text { Not winning } \\\\ P_{3}, P_{2} & \\text { Total weight: } 3+4=7 & \\text { Not winning } \\\\ P_{3}, P_{2}, P_{4} & \\text { Total weight: } 3+4+2=9 & \\text { Winning } \\\\ R_{2}, P_{3}, P_{4}, P_{1} & \\text { Total weight: } 3+4+2+6=15 & \\text { Winning }\\end{array}[\/latex]<\/p>\n<p>Since the coalition becomes winning when [latex]P_4[\/latex] joins, [latex]P_4[\/latex] is the pivotal player in this coalition.<\/p>\n<\/div>\n<\/div>\n<\/section>\n<section class=\"textbox questionHelp\">\n<p><strong>How To: Calculating Shapley-Shubik Power Index<\/strong><\/p>\n<p>To calculate the Shapley-Shubik Power Index:<\/p>\n<ol style=\"list-style-type: decimal;\">\n<li>List all sequential coalitions<\/li>\n<li>In each sequential coalition, determine the pivotal player<\/li>\n<li>Count up how many times each player is pivotal<\/li>\n<li>Convert these counts to fractions or decimals by dividing by the total number of sequential coalitions<\/li>\n<\/ol>\n<\/section>\n<p>How many sequential coalitions should we expect to have? If there are [latex]N[\/latex] players in the voting system, then there are [latex]N[\/latex] possibilities for the first player in the coalition, [latex]N\u20131[\/latex] possibilities for the second player in the coalition, and so on. Combining these possibilities, the total number of coalitions would be: [latex]N(N\u22121)(N\u22122)(N\u22123)\u22ef(3)(2)(1)[\/latex]. This calculation is called a <strong>factorial<\/strong>, and is notated [latex]N![\/latex] . The number of sequential coalitions with [latex]N[\/latex] players is [latex]N![\/latex] .<\/p>\n<section class=\"textbox recall\">\n<p><strong>Factorial<\/strong><\/p>\n<p>Calculating the <strong>factorial <\/strong>is a way to calculate the product of all positive whole numbers up to a given number. <strong>Notation:<\/strong> A factorial is represented by an exclamation mark [latex](!)[\/latex] following a number.<\/section>\n<section class=\"textbox example\">How many sequential coalitions will there be in a voting system with [latex]7[\/latex] players? <\/p>\n<div class=\"qa-wrapper\" style=\"display: block\"><button class=\"show-answer show-answer-button collapsed\" data-target=\"q4332\">Show Solution<\/button> <\/p>\n<div id=\"q4332\" class=\"hidden-answer\" style=\"display: none\">\n<p>There will be [latex]7![\/latex] sequential coalitions. [latex]7!=7\u22c56\u22c55\u22c54\u22c53\u22c52\u22c51=5040[\/latex]<\/p>\n<\/div>\n<\/div>\n<\/section>\n<p>As you can see, computing the Shapley-Shubik power index by hand would be very difficult for voting systems that are not very small.<\/p>\n<section class=\"textbox example\">Consider the weighted voting system [latex][6:4,3,2][\/latex]. We will list all the sequential coalitions and identify the pivotal player. We will have [latex]3! = 6[\/latex] sequential coalitions. The coalitions are listed, and the pivotal player is underlined.<\/p>\n<p style=\"text-align: center;\">[latex]\\begin{aligned} &< P_{1}, \\underline{P}_{2}, P_{3} >\\quad< P_{1}, \\underline{P}_{3}, P_{2} >\\quad< P_{2}, \\underline{P}_{1}, P_{3} >\\\\ &< P_{2}, P_{3}, \\underline{P}_{1} >\\quad< P_{3}, P_{2}, \\underline{P}_{1} >\\quad< P_{3}, \\underline{P}_{1}, P_{2} > \\end{aligned}[\/latex]<\/p>\n<div class=\"qa-wrapper\" style=\"display: block\"><button class=\"show-answer show-answer-button collapsed\" data-target=\"q4333\">Show Solution<\/button> <\/p>\n<div id=\"q4333\" class=\"hidden-answer\" style=\"display: none\">\n<p>[latex]P_1[\/latex] is pivotal [latex]4[\/latex] times, [latex]P_2[\/latex] is pivotal [latex]1[\/latex] time, and [latex]P_3[\/latex] is pivotal [latex]1[\/latex] time.<\/p>\n<p style=\"text-align: center;\">[latex]\\begin{array}{|l|l|l|} \\hline \\textbf { Player } & \\textbf { Times pivotal } & \\textbf { Power index } \\\\ \\hline P_{1} & 4 & 4 \/ 6=66.7 \\% \\\\ \\hline P_{2} & 1 & 1 \/ 6=16.7 \\% \\\\ \\hline P_{3} & 1 & 1 \/ 6=16.7 \\% \\\\ \\hline \\end{array}[\/latex]<\/p>\n<p>For comparison, the Banzhaf power index for the same weighted voting system would be [latex]P_1:60\\%,P_2:20\\%,P_3:20\\%[\/latex]. While the Banzhaf power index and Shapley-Shubik power index are usually not terribly different, the two different approaches usually produce somewhat different results.<\/p>\n<\/div>\n<\/div>\n<\/section>\n<section class=\"textbox tryIt\"><iframe loading=\"lazy\" id=\"ohm13340\" class=\"resizable\" src=\"https:\/\/ohm.one.lumenlearning.com\/multiembedq.php?id=13340&theme=lumen&iframe_resize_id=ohm13340&source=tnh\" width=\"100%\" height=\"150\"><\/iframe><\/section>\n","protected":false},"author":15,"menu_order":26,"template":"","meta":{"_candela_citation":"[{\"type\":\"cc-attribution\",\"description\":\"Math in Society (Lippman)\",\"author\":\"David Lippman\",\"organization\":\"LibreTexts Mathematics\",\"url\":\"https:\/\/math.libretexts.org\/Bookshelves\/Applied_Mathematics\/Math_in_Society_(Lippman)\/03%3A_Weighted_Voting\/3.05%3A_Calculating_Power-__Shapley-Shubik_Power_Index\",\"project\":\"3.5: Calculating Power- Shapley-Shubik Power Index\",\"license\":\"cc-by-sa\",\"license_terms\":\"Access for free at https:\/\/math.libretexts.org\/Bookshelves\/Applied_Mathematics\/Math_in_Society_(Lippman)\"}]","pb_show_title":"on","pb_short_title":"","pb_subtitle":"","pb_authors":[],"pb_section_license":""},"chapter-type":[],"contributor":[],"license":[],"part":90,"module-header":"learn_it","content_attributions":[{"type":"cc-attribution","description":"Math in Society (Lippman)","author":"David Lippman","organization":"LibreTexts Mathematics","url":"https:\/\/math.libretexts.org\/Bookshelves\/Applied_Mathematics\/Math_in_Society_(Lippman)\/03%3A_Weighted_Voting\/3.05%3A_Calculating_Power-__Shapley-Shubik_Power_Index","project":"3.5: Calculating Power- Shapley-Shubik Power Index","license":"cc-by-sa","license_terms":"Access for free at https:\/\/math.libretexts.org\/Bookshelves\/Applied_Mathematics\/Math_in_Society_(Lippman)"}],"internal_book_links":[],"video_content":null,"cc_video_embed_content":{"cc_scripts":"","media_targets":[]},"try_it_collection":null,"_links":{"self":[{"href":"https:\/\/content.one.lumenlearning.com\/quantitativereasoning\/wp-json\/pressbooks\/v2\/chapters\/8999"}],"collection":[{"href":"https:\/\/content.one.lumenlearning.com\/quantitativereasoning\/wp-json\/pressbooks\/v2\/chapters"}],"about":[{"href":"https:\/\/content.one.lumenlearning.com\/quantitativereasoning\/wp-json\/wp\/v2\/types\/chapter"}],"author":[{"embeddable":true,"href":"https:\/\/content.one.lumenlearning.com\/quantitativereasoning\/wp-json\/wp\/v2\/users\/15"}],"version-history":[{"count":22,"href":"https:\/\/content.one.lumenlearning.com\/quantitativereasoning\/wp-json\/pressbooks\/v2\/chapters\/8999\/revisions"}],"predecessor-version":[{"id":14896,"href":"https:\/\/content.one.lumenlearning.com\/quantitativereasoning\/wp-json\/pressbooks\/v2\/chapters\/8999\/revisions\/14896"}],"part":[{"href":"https:\/\/content.one.lumenlearning.com\/quantitativereasoning\/wp-json\/pressbooks\/v2\/parts\/90"}],"metadata":[{"href":"https:\/\/content.one.lumenlearning.com\/quantitativereasoning\/wp-json\/pressbooks\/v2\/chapters\/8999\/metadata\/"}],"wp:attachment":[{"href":"https:\/\/content.one.lumenlearning.com\/quantitativereasoning\/wp-json\/wp\/v2\/media?parent=8999"}],"wp:term":[{"taxonomy":"chapter-type","embeddable":true,"href":"https:\/\/content.one.lumenlearning.com\/quantitativereasoning\/wp-json\/pressbooks\/v2\/chapter-type?post=8999"},{"taxonomy":"contributor","embeddable":true,"href":"https:\/\/content.one.lumenlearning.com\/quantitativereasoning\/wp-json\/wp\/v2\/contributor?post=8999"},{"taxonomy":"license","embeddable":true,"href":"https:\/\/content.one.lumenlearning.com\/quantitativereasoning\/wp-json\/wp\/v2\/license?post=8999"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}