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Bargaining and social structure

Bargaining and social structure. Edoardo Gallo University of Oxford (Nuffield College) New Road, Oxford, OX1 1NF, UK Email: edoardo.gallo@economics.ox.ac.uk Webpage: http://users.ox.ac.uk/~scro0919/. Motivation and related literature Model Bargaining solution. Comparative statics

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Bargaining and social structure

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  1. Bargaining and social structure Edoardo Gallo University of Oxford (Nuffield College) New Road, Oxford, OX1 1NF, UK Email: edoardo.gallo@economics.ox.ac.uk Webpage: http://users.ox.ac.uk/~scro0919/

  2. Motivation and related literature Model Bargaining solution Comparative statics Application Extension and conclusions Motivation • Communities play an important role in perfectly competitive markets, e.g. Greif (AER, 1993), Rauch and Trindade (REStud, 2002), Kumagai (2007). • Greif (AER, 1993) argues that communities provide enforcement of sanctions that deter violation of contracts in an uncertain environment. • Here I argue that communities exist to give an informational advantage: the social structure of the community is a conduit of information that members use to learn about the market. • The paper investigates the role played by the structure of social networks for pricing in decentralized, perfectly competitive markets characterized by: • Incomplete information • Uncertainty on the price of the good • Private pairwise bargaining • Absence of a centralized coordination device • Relevant markets: developing countries, illegal commodities and wholesale.

  3. Motivation and related literature Model Bargaining solution Comparative statics Application Extension and conclusions Related literature • Bargaining models • Classical: Nash (Ecta, 1950); Rubinstein (Ecta, 1982); Rubinstein and Wolinsky (Ecta, 1985); Rubinstein and Wolinsky (RES, 1990). • Evolutionary: Young (JET, 1993), Binmore et al. (JET, 1998), Young (RES, 1998), Sáez-Martí and Weibull (JET, 1999). • On networks: Calvo-Armengol (2001, 2003); Corominas-Bosch (JET, 2004); Polanski (JET, 2008); Manea (2008); Abreu and Manea (2008). • Empirical evidence • Wholesale markets: Kirman and Vignes (1991); Hardle and Kirman (JE, 1995); Kirman et al. (JEBO, 2005); Vignes et al. (2008). • International trade: Rauch (JEL, 2001); Rauch and Trindade (REStud, 2002; AER, 2003); Kumagai (2007). • Illegal markets: Levitt and Venkatesh (QJE, 2000; 2007).

  4. Motivation and related literature Model Bargaining solution Comparative statics Application Extension and conclusions Nash demand game xt xt xt 0 yt yt yt 0 xt + yt ≤ 1 xt + yt > 1

  5. Motivation and related literature Model Bargaining solution Comparative statics Application Extension and conclusions Adaptive play bargaining process Buyers and sellers: B={1,…,nB} and S={1,…,nS} • Set-up is the same for buyers and sellers • b has concave and strictly increasing vN-M utility u(x), where x (0,1), u(0)=0 • b has memory m • b chooses an optimal reply to the cumulative probability distribution G(y) of the demands yjmade by sellers in his sample • Denote the utility of seller s by v(y)

  6. Motivation and related literature Model Bargaining solution Comparative statics Application Extension and conclusions Communication networks Poisson information arrival: the probability that buyer b receives a sample of past offers from buyer j is determined by a Poisson process with rate gij The rates of these Poisson processes form a weighted, undirected network g represented by a symmetric matrix [gij]n×n. For expositional purposes assume that gii=0 for all i B,S Let gi≡∑j є Li(g) gijbe the weighted degree of i A network is connected if there is a path connecting any pair of agents A complete network gCis a network where each agent is connected to all the other agents

  7. Motivation and related literature Model Bargaining solution Comparative statics Application Extension and conclusions Markov process s’ = {v1,…,v’b,…,v’s,…,vn} є S s’ = {v1,…,v’b,…,v’s,…,vn} є S s = {v1,…,vb,…,vs,…,vn} є S s = {v1,…,vb,…,vs,…,vn} є S vb = {yq-m+1,…,yq} v’b = {yq-m+2,…,yq+1} vs = {xq-m+1,…,xq} v’s = {xq-m+2,…,xq+1} xq+1 yq+1

  8. Motivation and related literature Model Bargaining solution Comparative statics Application Extension and conclusions Convergence Definition 1. A state is a convention if any vi  s with i B is such that vi = (1-x,...,1-x), and any vj s with j  S is such that vj= (x,...,x). Hereafter, denote this convention by x. Theorem 1. Assume both gBand gSare connected and they are not complete networks. The bargaining process converges almost surely to a convention.

  9. Motivation and related literature Model Bargaining solution Comparative statics Application Extension and conclusions Proof: Intuition • b ands are picked to play the game • they receive samplesσandσ’ respectively • they demand best replies x andy respectively • repeat steps (1)-(3) for m-1 periods to obtain • b’ ands’ are picked to play the game • they receive samplesfromvbandvs respectively • they demand best replies 1-y and1-x respectively • repeat steps (1)-(3) for m-1 periods to obtain • b’’ ands’’ are picked to play the game • they receive samplesfromvbandvs’ respectively • they demand best replies 1-y andy respectively • repeat steps (1)-(3) for m-1 periods to obtain vb = {y,…,y} vs = {x,…,x} vb’ = {1-x,…,1-x} vs’ = {1-y,…,1-y} vb’’ = {y,…,y} vs’’ = {1-y,…,1-y}

  10. Motivation and related literature Model Bargaining solution Comparative statics Application Extension and conclusions Markov process with mistakes Definition 2. The demand xb(t) by buyer b at time t is a mistake if it is not a best response to the sample b has received before playing. A mistake ys(t) by seller s is defined analogously. Definition 3. The stochastically stable states are the states that are most likely to be observed in the long-run when the random mistakes are small. Mathematically, let μєbe the stationary distribution of the Markov process (with mistakes), then a state s is stochastically stable if limє →0μє(s)>0

  11. Motivation and related literature Model Bargaining solution Comparative statics Application Extension and conclusions Further assumptions and notation Two further assumptions are needed to make the model more tractable. (i) Mean-field assumption: the size of the information sample of the buyer b is constant and equal to gb, i.e. the sum of the amount of information b receives in expectation from each one of his neighbors. The same assumption holds for the seller s. (ii) Large memory: assume that the individual memory m ≥ max{gb, gs} Some additional notation: Let Bmin = {j B|gj ≤gb , b B}be the subset of buyers with the least integer weighted degree. Let gbmin ≡ gj for jBmin . Equivalent definitions apply to the sellers.

  12. Motivation and related literature Model Bargaining solution Comparative statics Application Extension and conclusions Asymmetric Nash bargaining solution (ANB) Theorem 2. There exists a unique stochastically stable division (x*,1-x*) . The division is the asymmetric Nash bargaining solution which maximizes uβ(x) vσ(1-x) where β≡gbminand σ ≡gsmin

  13. Motivation and related literature Model Bargaining solution Comparative statics Application Extension and conclusions ANB: Interpretation A weighted network with n=32 players and two types of links: strong links (in bold) with weight 1 and weak links with weight 0.5. Color-coded nodes denote the players belonging to the subset of least connected players.

  14. Motivation and related literature Model Bargaining solution Comparative statics Application Extension and conclusions Quasi-regular networks Definition 4. Consider the set G of undirected networks with n nodes and at most L links. Let gd,abe the regular network with degree d=2L/n, i.e. the largest regular network in G, and link strength a. The network g є G is a quasi-regular network generated by gd,aif it can be obtained by randomly adding k links of any strength to gd,abe where k  [0, L-nd/2]. Examples of quasi-regular networks for n=5 and L=7.

  15. Motivation and related literature Model Bargaining solution Comparative statics Application Extension and conclusions Quasi-regular networks (cont’d) Corollary 1. Fix a communication network gSfor the sellers. Consider the set G of all possible communication structures gBamong the nbbuyers such that the total number of links is L< (nb-1)nb/2 and that the strength of each links is in the [s, s] range where s, s є R+. The subset of networks GB G that gives the highest share to buyers are the quasi-regular networks generated by the regular network gd,abe where d=2L/ nb. The same statement holds reversing the roles of buyers and sellers.

  16. Motivation and related literature Model Bargaining solution Comparative statics Application Extension and conclusions Changing the network: Definitions Let ρ(g) denote the weighted degree distribution of network g. Definition 5. A distribution ρ’ strictly first order stochastically dominates (FOSD) another distribution ρif ρ’(d) < ρ(d) (for all d  {1,...,D}), where ρ(d)=∑d p(d) is the cumulative distribution of p(d). Definition 6. A distribution ρ’’ strictly second order stochastically dominates (SOSD) another distribution ρif ∑dρ’’(d) <∑dρ(d) (for all d  {1,...,D}).

  17. Motivation and related literature Model Bargaining solution Comparative statics Application Extension and conclusions Changing the network and the ANB Denser and more homogenous social groups obtain a higher share of the pie in equilibrium. Theorem 3. Let (x*,1-x*) be the ANB for sets of agents B and S that communicate through networks gBand gS. Let ρ(g’B) FOSD ρ(gB) and ρ(g’’B) SOSD ρ(gB). (i) Let (x’*B, 1- x’*B) be the ANB for sets of agents B and S with degree distributions ρ(g’B) and ρ(gS). Then x’*B > x*. (ii) Let (x’’*B, 1- x’*B) be the ANB for sets of agents B and S with degree distributions ρ(g’’B) and ρ(gS). Then x’’*B > x*. The same statement holds reversing the roles of buyers and sellers.

  18. Motivation and related literature Model Bargaining solution Comparative statics Application Extension and conclusions The Fulton fish market (FFM) • Graddy (RAND, 1995) tracked all (n=489) transactions of whiting by one dealer over 19 days, recording: price, quantity, exact time, type of buyer and quality of fish. • No posted prices and dealer is free to charge a different price to each customer. • “Spread of prices throughout the day is very high, and the interday volatility is large” (Graddy, p. 78). • Types of buyers: • Three ethnic groups: whites, Asians and blacks (small sample). • Locations: Manhattan, Brooklyn, New Brunswick, Princeton. • Establishments: restaurants, stores, shippers, dealers, fry shops.

  19. Motivation and related literature Model Bargaining solution Comparative statics Application Extension and conclusions A puzzling finding • Key finding: white sellers charge white buyers significantly (~7%) more than Asian buyers for the same homogeneous product. • Graddy (p. 87) concludes that “the reason behind the price discrimination is less clear.” • Not a typical setting for 3rd degree price discrimination: competitive industry, no search costs, homogeneous products, no barriers to entry, no significant difference in elasticity for Asians vs white buyers. • Graddy (1995) shows that difference is not due to differences in purchase times, product quality, mode of payment and volume of transactions.

  20. Motivation and related literature Model Bargaining solution Comparative statics Application Extension and conclusions Applying the model to the FFM A potential explanation: Asian buyers’ communication network is denser/more homogeneous than white buyers’. Therefore, the group of Asian buyers is better at sharing information on today’s price and this informational advantage leads to the observed price difference. • Graddy (p. 84): “very little social contact appears to take place between groups of Asian buyers and groups of white buyers” • Graddy (p. 87): “Asian buyers appear to be more organized than white buyers” • Graddy: “Asian buyers certainly spoke to one another and congregated much more frequently than white buyers” • Homophily is a powerful determinant of social networks, and racial/ethnic homophily is much stronger than other types (e.g., McPherson et al., 2001) • Evidence that Asian immigrant groups form very close-knit networks (e.g., Sanders et al., 2002; McCabe, 2006)

  21. Motivation and related literature Model Bargaining solution Comparative statics Application Extension and conclusions A look at the FFM dataset (1) Asians obtain a better price only after the first 1-2 hours of the market, presumably due to learning. Regression analysis shows that the “Asian” dummy is negatively correlated (p=0.01) with prices in the 6-7am time period, but it is statistically insignificant (and positively correlated) in the 4-5am time period.

  22. Motivation and related literature Model Bargaining solution Comparative statics Application Extension and conclusions A look at the FFM dataset (2) The variability of prices paid by Asians decreases faster than the variability of prices paid by Whites pointing to faster learning among Asians of the current value of fish. ■Asians □Whites • A two-sample variance comparison test rejects (99% c.f.) the null hypothesis that VarASIAN(4-5)=VarASIAN(6-7). • But the same test cannot reject (90% c.f.) the null hypotheses that VarWHITE(4-5)=VarWHITE(6-7) and VarASIAN(4-5)=VarWHITE(4-5).

  23. Motivation and related literature Model Bargaining solution Comparative statics Application Extension and conclusions Evidence on Asians’ social networks Social connections play a key role in business transactions in the overseas Asian community: • Redding, Overseas Chinese Networks: Understanding the Enigma, 1995: • "[p]ersonalism does in Asia what law does in the West [...] [w]ithout [what is termed guanxi or connections] nothing can be made to happen [...] the instinct of the Overseas Chinese to trust friends but no-one else is very deep-rooted.“ • “For the Overseas Chinese the uncertainties of the business environment mean that playing fields are not level. […] So the Chinese rules are: put your trust primarily in 'your own' people; seek the opportunities by trading rare information; share that information to build allegiances” • Xie, Asian Americans: A Demographic Portrait, 2004:. • “Asian American communities offer many practical resources to immigrants, including [...] information in native languages, and entrepreneurial opportunities.“ See, e.g., additional references in Rauch and Trindade (REStud, 2002), Rauch and Casella (EJ,2003), Kumagai (2007).

  24. Motivation and related literature Model Bargaining solution Comparative statics Application Extension and conclusions Extension Assume that the two groups share the same network, i.e. buyers receive information from other buyers and sellers about past sellers’ demands, then: • The stochastically stable division is unchanged. • Core-periphery networks maximize the share for a group. • A more homogeneous network narrows down the difference between the two groups. • In a regular network with homogeneous agents 50-50 is the stable division.

  25. Motivation and related literature Model Bargaining solution Comparative statics Application Extension and conclusions Further research • Theoretical • How sensitive are the results to the assumptions of a very small ε? • Can we say anything on the speed to convergence? • Empirical • How do we test the model empirically? • Field experiment? • Lab experiment?

  26. Motivation and related literature Model Bargaining solution Comparative statics Application Extension and conclusions Conclusions Main results: • The unique stochastically stable division is the ANB with weights determined by the players with the least weighted degree in each group. • Quasi-regular networks maximize the share for a group. • Denser and more homogeneous networks fare better. • An empirical analysis of the observed price differential between Asian and white buyers in the FFM is consistent with these predictions If the two groups share the same network, then: • The stochastically stable division is unchanged. • Core-periphery networks maximize the share for a group. • A more homogeneous network narrows down the difference between the two groups. • In a regular network with homogeneous agents 50-50 is the stable division.

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