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Arbitration Experiments +. Cary Deck - University of Arkansas Amy Farmer - University of Arkansas Dao-Zhi Zeng – Kagawa University & Zhejiang University ”Arbitration and Bargaining Across the Pacific” ‚ “Amended Final Offer Arbitration Outperforms Final Offer Arbitration”
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Arbitration Experiments+ Cary Deck - University of Arkansas Amy Farmer - University of Arkansas Dao-Zhi Zeng – Kagawa University & Zhejiang University ”Arbitration and Bargaining Across the Pacific” ‚“Amended Final Offer Arbitration Outperforms Final Offer Arbitration” +Thank you NSF (SES0350709)
Roadmap for Talk Arbitration and Bargaining Across the Pacific AFOA Outperforms FOA Culture Japan US Mechanism Arbitrator Behavior
Dispute Resolution Two parties have a dispute regarding how to split a pie. - Litigation - Mediation - Arbitration C substantial cost savingsC restrictions on discoveryC shorter hearing length C information can remain private
Use of Arbitration Lipsky and Seeber (1998) surveyed the legal counsels of the 1000 largest US corporations and found that 79% of respondents had used arbitration. Dell Computer’s Online Policy States: “ANY CLAIM, DISPUTE, OR CONTROVERSY … SHALL BE RESOLVED EXCLUSIVELY AND FINALLY BY BINDING ARBITRATION…”http://www1.us.dell.com/content/topics/global.aspx/policy/en/policy?c=us&l=en&s=bsd&~section=012&cs=04 In Circuit City Stores Inc. vs. Saint Clair Adams, US Supreme Court ruled that employers can force employees to use arbitration to settle labor disputes.
Economics Approach to Arbitration Theoretical Modeling • Each party has a belief about the distribution of arbitrator’s preferred outcome, fi(z). • A disputant faces a cost ci of going to arbitration. • A party is willing to settle pre-arbitration for an outcome O if u(O) > u(A,ci) where A is what they expect to receive in arbitration and is dependent on fi(z).
Economics Approach to Arbitration Theoretical Modeling • Each party has a belief about the distribution of arbitrator’s preferred outcome, fi(z). • A disputant faces a cost ci of going to arbitration. • A party is willing to settle pre-arbitration for an outcome O if u(O) > u(A,ci) where A is what they expect to receive in arbitration and is dependent on fi(z). Under standard assumptions this yields a contract zone [A-c1,A+c2] which both parties prefer to arbitration.
Economics Approach to Arbitration Experimental Economics • Experimenter controls the institution (rules of the game, information flows) and the environment (payoffs, costs, arbitrator’s preferences) • Subjects make salient choices that are observed by the experimenter. • Enables replication and direct comparisons across institutions and environments.
Forms of Arbitration Conventional Arbitration (most commonly used)- arbitrator can implement any allocation - no strategic behavior by disputants- disputants should settle and save costs - many disputes are arbitrated - »50% agreement rates in the laboratory (Ashenfelter et al. 1992, Dickinson 2004, Deck and Farmer 2005)
Forms of Arbitration Final Offer Arbitration - each side proposes an allocation- arbitrator must pick one of the proposals - incentive to make an extreme offer- increases risk of going to arbitration
Final Offer Arbitration Widely Studied Empirically • Naturally Occurring World • Used in Major League Baseball • Laboratory • More Strategic than Conventional • Agreement Rates less than 50% But (almost) Exclusively in US even though arbitration is used to resolve international disputes as well.
Do Cultural Differences Matter? Bercovitch and Elgström (2001) find that cultural differences lower mediation success. Fu et al. (2002) find that Chinese and Americans exhibit differences in choosing mediators. Lew and Shore (1999) find cultural differences in cross examination procedures. Gans (1997) advocates informal procedures prior to invoking formal arbitration procedures due to cultural differences.
Cultural Differences Growing Experimental Literature on Culture(Roth et al. 1991, Henrich 2000, Buchan et al. 2004) Kilbourne et al. (2005) identify differences in materialism across cultures. Brandts et al. (2004) found differences in spite and cooperation behavior in voluntary contribution mechanisms. Buchan et al. (in press) examine the role that culture plays in trust, reciprocity and altruism.
US and Japan • Similar Economies Both Modern Industrialized Economies Major Trading Partners for Several Decades (Graham and Sano, 1989) Societies exhibit high levels of trust (Slemrod and Katuščák 2005) 2) Culturally Diverse “collectivism” to “individualism” (Hofstede 1991, Oyserman et al. 2002) Differing views of fairness and power (Buchan et al. 2004)
Shares of Imports by Country of Origin Data from Feenstra et al. (2004)
Hofstede’s Scales PDI - Power Distance Index , IDV –Individualism, MAS – Masculinity, UAI- Uncertainty Avoidance Index, LTO-Long-Term Orientation
Experimental Design A pair of subjects had $EXP 100 to allocate. Treatments: UU- both subjects from University of Arkansas JJ- both subjects from Kagawa University in Japan UJ- one subject from each university Show up fee of $EXP 500 $EXP 100 = $US 1 & $EXP 100 = ¥100
Experimental Design Written Directions Comprehension Handout Periods 1-15 forced arbitration Bargaining Directions Periods 16-25 bargaining prior to arbitration Random rematching of anonymous counterparts each period.
Experimental Design Arbitrator's preferred outcome ~U[0,100]. Let x and y denote the shares for disputant 1 by disputants 1 and 2 respectively if x<y then offers are compatible payoffs are (x+y)/2 and 100 - (x+y)/2 if x>y then offers are incompatible payoffs are x and 100-x if |z-x|<|z-y| and y and 100-y otherwise Brams and Merrill (1983) show that unique Nash Equilibrium is x=100 and y=0.
Experimental Design Þ Expected Payoff in Arbitration = 50 Periods 1-15 (arbitration only): c = 0 Periods 16-25 (pre-arbitration bargaining): c = 15 Þ Contract Zone [35,65] 4 replicates of each treatment (12 total sessions) 4 subjects in UU & JJ 6 subjects in UJ Sessions lasted one hour.
Experimental Design Cultural Concerns Same experimenters present for each session. Web cameras employed in UJ treatment as described by Eckel and Wilson (2006). Pictorial screen for UJ and JJ treatments. Directions written in English and translated into Japanese.
Linear Mixed Effects Model of Offers in Periods 5-15 Variable Parameter Value t-value p-value Constant b0 56.3895 19.9404 <.0001 JapSub b1 4.1366 0.9604 0.3424 JapCount b2 10.5445 2.4480 0.0186 JapSub´JapCount b3 –12.5770 –2.0472 0.0678
Hypotheses of Lituchy (1997) As America is individualistic and Japan is a collective society, Lituchy argues that Japanese - Ho: b2+b3 = 0 will be rejected in favor of Ha: b2+b3 < 0. Americans - Ho: b2= 0 will not be rejected in favor of Ha: b2 ¹ 0. We do not find support for either claim hypothetical payments subject pool bias
Self-Negotiated Settlement Rate by Session Wilcoxon Rank-Sum Tests UU v JJ W = 19.5 UU v UJ W = 20 JJ v UJ W = 25*
Self-Negotiated Settlement Rate by Session Wilcoxon Rank-Sum Tests UU v JJ W = 19.5 UU v UJ W = 20 JJ v UJ W = 25* We find substantially more agreement than previous laboratory studies.
Let’s Play Name That Distribution Distribution #2 Distribution #1 Distribution #3
Random Effects Probit Model of Settlements in Periods 16-25. F(b0+b1UJj+b2JJj+b3AvgPayjp+b4UJj´AvgPayjp+b5JJj´AvgPayjp+ zj)
Allocation in Self-Negotiated Settlements Contract Zone: 35-65
Further Exploration Risk Attitudes and Strategic Bidding First Price Sealed Bid and Dutch Auctionsn = 5 biddersvalues ~ U[0,15] 6 sessions (3 in each treatment ordering) Observed Price/Risk Neutral Expected Price
Further Exploration Cooperation and Other Regarding Preferences Public Goods- n=4MPCR=.3,.75 w=10periods = 104 sessions (2 per MPCR order)
Cultural Conclusions JJ and UU treatments yield similar behavior But, intercultural disputes differ from domestic ones Þ Americans become more aggressive in international arbitration. (UU v UJ) Þ Japanese become more willing to settle in international bargaining. (JJ v UJ) Explanations: Social Distance? (Cox and Deck 2005, Buchan in press)Cultural Representation?
Improving Arbitration Performance of Mechanism is measured by how often it is not used! • Social welfare is higher when parties save arbitration costs. • Preference for self-negotiated settlements. Can we do better than FOA?
Forms of Arbitration Tri Offer Arbitration - each side (and a neutral third party) proposes an allocation- arbitrator must pick one of the 3 proposals- designed to lower the likelihood of extreme outcomes in arbitration - increases incentive to be extreme - used to settle public sector disputes in Iowa- lower agreement rate in laboratory than CA (Ashenfelter, et al. 1992)
Forms of Arbitration Combined Offer Arbitration (Brams and Merril 1986) -like FOA except that extreme choices by arbitrator are implemented - theoretically encourages convergent offers - agreement rates in the laboratory lower than FOA (Dickinson 2001) 0 100 C Y
Forms of Arbitration Amended Final Offer Arbitration (Zeng 2003) - each side proposes an allocation- arbitrator picks preferred proposal as in FOA- person placing relatively extreme proposal pays penalty to the more reasonable party - allocation is 2 x arbitrators preferred outcome minus the “extreme” proposal
} } 100 0 } } Allocation Random Draw Counterpart’s Offer Your Offer 100 0 Random Draw =z Allocation=p1 Counterpart’s Offer =y Your Offer=x Amended Final Offer Arbitration If z > (x + y)/2), then p1 = z + | z - y| = 2z – y and p2=100 – (2z – y) If z < (x + y)/2), then p1 = z + | z - x| = 2z – x and p2=100 – (2z – x)
Amended Final Offer Arbitration -Like a 2nd price auction while FOA is like a first price auction -Allocation is based upon arbitrator’s preference and loser’s offer -Own offer impacts 1) the probability that you win2) your payoff if you looseÞ incentive to bid “reasonably”
Distribution of Arbitrator Previous experiments (and most theory) dealing with arbitration have utilized nice continuous distributions. • nice mathematical properties • appropriate in many situations • amount of alimony • appropriate pain and suffering • level of wages • inappropriate for other situations • is the defendant liable? • who should receive custody?
Distribution of Arbitrator FOA • Centered about median if density is continuous and has mass about the median. • Kilgore (1994) showed that with a binary distribution there is no pure strategy equilibrium (unless further restrictions are imposed). AFOA • Centered about mean of distribution. • Zeng (2003) showed that optimal offer = mzand this is robust to distribution.
Comparison of AFOA and FOA ûFOA strategy depends on the shape of the distribution (Kilgour 1994) üAFOA strategy is robust to distribution ûFOA offers should diverge üAFOA offers should converge ûFOA does not induce settlement AFOA
Experimental Design 2x2 design 1) mechanism: FOA vs AFOA 2) f(z): u[0,100] vs 25 w/p =.5 and 75 w/p =.5 Þ E(z)=50 UU treatment = FOA with Uniform distribution Mechanism Arbitrator Behavior
Optimal Offers FOA with uniform distribution x=100, y=0 as before FOA with binary distribution forcing offers to be Î[0,100]if x=100, when yÎ[0, 50)then2’s profit is (100-y)/2 if x=100, when y=50 then 2’s profit is (.5+.25)*50+.25*(0) if x=100, when yÎ(50, 100]then 2’s profit is 100-y. Best choice for disputant 2 is y=0, and similarly for disputant 1’s best choice is x=100. Expected payoff in arbitration is 50. Contract Zone is [50-c,50+c]
Optimal Offers AFOA with uniform distribution x=50, y=50 AFOA with binary distribution x=50, y=50 Expected payoff in arbitration is 50. Contract Zone is [50-c,50+c]
Experimental Design 4 sessions (replicates) per cell 4 subjects per session random pairing each periodaverage payoff = $12.26 + $5.00subjects recruited for 1 hour 2 phases per session -15 periods of arbitration (c=0)-10 periods with pre-arbitration bargaining (c=15) Þ Contract Zone = E(z) ± c = [35,65]
Experimental Results FOA with Binary Optimal Offer =100 AFOA with Binary Optimal Offer =50
Experimental Results FOA with Uniform Optimal Offer =100 AFOA with Uniform Optimal Offer =50
Experimental Results FINDING 1. Observed behavior in AFOA is consistent with the theoretical predications of the model. However, behavior in FOA is not consistent with the theoretical prediction for the mechanism. Parameter Value Std. Error DF t-value p-value m 51.58480 2.966176 576 17.39101 <0.0001 b1 4.65417 4.253991 12 1.09407 0.2954 b2 -0.99731 4.202240 12 -0.23733 0.8164 b3 1.08503 6.118946 12 0.17732 0.8622
Experimental Results FINDING 2. AFOA generates greater pre-arbitration settlement than does FOA. (p-value is 0.014) Statistical Significance based on Mack Skillings test