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Bargaining Game Further Economic Analysis Dr. Keshab Bhattarai Hull Univ. Business School March 30, 2011 Dr. Bhattarai (Hull Univ. Business School) Bargaining March 30, 2011 1 / 14 Bargaining Game The very common example for bargaining game is splitting a pie between two individuals. The sum of the shares of the pie claimed by both cannot exceed more than 1, otherwise each will get zero. If we denote these shares by θ i and θ j then θ i + θ j 1 is required for a meaningful solution of the game where each get θ i 0 and θ j 0 payo¤. When θ i + θ j > 1 then and θ i = 0 and θ j = 0 . Standard technique to solve this problem is to use the concept of Nash Product. Dr. Bhattarai (Hull Univ. Business School) Bargaining March 30, 2011 2 / 14 Nash Product in Bargaining Game max U = (θ i 0) ( θ j 0) (1) subject to θi + θj 1 (2) or by non-satiation property θ i + θ j = 1 Using a Lagrangian function L (θ i , θ j , λ) = (θ i Dr. Bhattarai (Hull Univ. Business School) 0) ( θ j Bargaining 0) + λ [1 θi θj ] March 30, 2011 (3) 3 / 14 First Order Conditions First order conditions of this maximization problem are L (θ i , θ j , λ) = θj ∂θ i λ=0 (4) L (θ i , θ j , λ) = θi ∂θ j λ=0 (5) L (θ i , θ j , λ) = 1 θi θj = 0 (6) ∂λ From the …rst two …rst order conditions θ j λ = θ i λ implies θ j = θ i and putting this into the third …rst order condition θ j = θ i = 12 . This is called focal point. Thus Nash solution of this problem is to divide the pie symmetrically into two equal parts. Any other solution of this not stable. Roy Gardner (2003) and Charles Holt (2007) have a number of interesting examples on bargaining game. Dr. Bhattarai (Hull Univ. Business School) Bargaining March 30, 2011 4 / 14 Application of Bargaining Game Money to be divided between two players M = u1 + u2 (7) N = u1 u2 (8) Nash product The origin of this bargaining game is the disagreement point d (0, 0), the threat point. Here the utility of player one (u1 ) is plotted against the utility of player two u2 and the line u1 u2 is the utility possibility frontier (UPF). Starting of bargaining can be (0, M ) or (M, 0) where one player claims all but other nothing. But this is not stable. O¤ers and counter o¤ers will be made until the game is settled at u = 12 M, 12 M where each player gets equal share. Dr. Bhattarai (Hull Univ. Business School) Bargaining March 30, 2011 5 / 14 Numerical Example of Bargaining Game Suppose there is 1000 in the table to be split between two players. What is the optimal solution from a symmetric bargaining game if the threat point is given by d(0,0)? Using a Lagrangian function for constrained optimisation L (u1, u2 , λ) = u1 u2 + λ [1000 u1 u2 ] (9) First order conditions of this maximization problem are L (u1, u2 , λ) = u2 ∂u1 λ=0 (10) L (u1, u2 , λ) = u1 ∂u2 λ=0 (11) L (u1, u2 , λ) = 1000 u1 u2 = 0 (12) ∂λ From the …rst two …rst order conditions u2 λ = u1 λ implies u2 = u1 and putting this into the third …rst order condition u2 = u1 = 1000 2 = 500. Dr. Bhattarai (Hull Univ. Business School) Bargaining March 30, 2011 6 / 14 Numerical Example of Bargaining Game The Nash bargaining solution is the values of u1 and u2 that maximise the value of the Nash product u1 u2 subject to the resource allocation constraint,u1 + u2 = 1000. This bargaining solution ful…ls four di¤erent properties: 1) symmetry 2) e¢ ciency 3) linear invariance 4) independence of irrelevant alternatives (IIA). 1 Symmetry implies that equal division between two players 2 e¢ ciency implies no wastage of resources u1 + u2 = M or maximisation of the Nash product, u1 u2 . 3 Linear invariance refers to the location of threat point as (200, 200). If u is a solution to the bargaining game then u + d is a solution to the bargaining problem with disagreement point d. 4 IIA implies irrelevant alternatives are not discussed in the game. Dr. Bhattarai (Hull Univ. Business School) Bargaining March 30, 2011 7 / 14 Another example Dr. Bhattarai (Hull Univ. Business School) Bargaining March 30, 2011 8 / 14 Numerical Example of Bargaining Game L (u1, u2 , λ) = (u1 d1 ) (u2 d2 ) + λ [50000 u1 u2 ] (13) u1 u2 ] (14) Suppose the player 1 has side payment d1 = 15000 L (u1, u2 , λ) = (u1 15000) (u2 d2 ) + λ [50000 First order conditions of this maximization problem are L (u1, u2 , λ) = u2 ∂u1 L (u1, u2 , λ) = u1 ∂u2 15000 L (u1, u2 , λ) = 50000 ∂λ Dr. Bhattarai (Hull Univ. Business School) λ=0 Bargaining u1 (15) λ=0 (16) u2 = 0 (17) March 30, 2011 9 / 14 Numerical Example of Bargaining Game From the …rst two …rst order conditions u2 implies u2 = u1 λ = u1 15000 λ 15000 and putting this into the third …rst order condition u2 + 15000 = u1 ; u2 = 32500. 50000 15000 2 = 17500; u1 = 15000 + u2 = Then u1 + u2 = 17500 + 32500 = 50000. Dr. Bhattarai (Hull Univ. Business School) Bargaining March 30, 2011 10 / 14 Risk and Bargaining A risk averse person loses in bargaining but the risk neutral person gains. Suppose the utility functions of risk averse person is given byu2 = (m2 )0.5 but the risk neutral person has a linear utility u1 = m1 . m 1 + m2 = M .u1 + u22 = 100 Using a Lagrangian function for constrained optimisation L (u1, u2 , λ) = u1 u2 + λ 100 u1 u22 (18) First order conditions of this maximization problem are L (u1, u2 , λ) = u2 ∂u1 L (u1, u2 , λ) = u1 ∂u2 L (u1, u2 , λ) = 100 ∂λ Dr. Bhattarai (Hull Univ. Business School) λ=0 (19) 2λu2 = 0 (20) u1 Bargaining u22 = 0 (21) March 30, 2011 11 / 14 Numerical Example of Bargaining Game λ From the …rst two …rst order conditions uu1,2 = 2λu implies u1 2u22 and 2 putting this into the third …rst order condition .3u22 = 100 ; u22 = 100 3 = 33.3 ; u2 = 5.77 u1 = 2u22 = 2 (5.77)2 = 66.6 u1 + u22 = 66.6 + 33.3 = 100 Thus the risk neutral player’s utility is 66.7 and risk averse player’s utility is only 5.7. Morale: do not reveal anyone if you are risk averse, otherwise you will lose in the bargaining. Dr. Bhattarai (Hull Univ. Business School) Bargaining March 30, 2011 12 / 14 Coalition Possibilities 2N -1 rule for possible coalition Consider Four Players A,B,C,D A, B, C, D AB, AC, AD BC, BD, CD ABC, ABD,ACD, BCD, ABCD 16 -1=15 What is core of a coalition? It is a coalition that cannot be blocked by any coalition. Detected by the shapley value. Shapley value is the amount a particular player can bring in the team di¤erence a particular player makes in the game. Weakest link game. What is empty core? When non-cooperatively playing coalition partners all end up in a zero payo¤. Examples of empty core. Global warming game; Why no constitution in Nepal? Dr. Bhattarai (Hull Univ. Business School) Bargaining March 30, 2011 13 / 14 References Binmore K. (1990) Fun and Games: A text on Game Theory, Lexington, Heath. Cripps, M.W.(1997) Bargaining and the Timing of Investment, International Economic Review, 38:3 :Aug.:527-546 Dixit A., S. Skeath and D. F. Reiley (2009) Games of Strategy, Norton. Gardener R (2003) Games of Business and Economics, Wiley, Second Edition. Holt Charles (2007) Markets, Games and Strategic Behaviour, Pearson, . Mailath G. J. and L. Samuelson (2006) Repeated Games and Reputations: long run relationship, Oxford. Kreps D. M. (1990) A Course in Microeconomic Theory, Princeton. Osborne M.J. and A. Robinstein (1994) A course in game theory, MIT Press. Perlo¤ J. M. (2008) Microeconomics: Theory and Applications with Calculus, Pearson. Rasmusen E(2007) Games and Information, Blackwell. Varian HR (2010) Intermediate Microeconomics: A Modern Approach, Norton,8th ed.. Dr. Bhattarai (Hull Univ. Business School) Bargaining March 30, 2011 14 / 14