Quantifying Equilibrium Network Externalities In The ACH Banking Industry

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1 Quantifying Equilibrium Network Externalities In The ACH Banking Industry Ackerberg and Gowrisankaran (2006) Presented By Yang YU FEB 14, 2013

2 Outline Summary of the paper The paper s contribution and weakness Suggestions for further research

3 Introduction The goal of this paper is to estimate the size and importance of network externalities for the automated clearinghouse (ACH) banking industry using an equilibrium model of ACH usage and adoption. ACH is an electronic payment mechanism developed by the Federal Reserve and used by banks and customers It is an electronic alternative to paper checks

4 Introduction ACH is a two-sided market (bank and customers) and is characterized by network effects. Two types of transaction. one-way transaction which is passively accepted by receiving customers. two-way transaction requires receiving customers to adopt ACH actively.

5 The implications of the model depend on parameters that specify bank and customer costs and benefits, the proportion of two way transactions, and other details including scales and time trends. The paper estimate these parameters by applying an indirect inference estimator to bank level panel data on ACH adoption and the number of ACH transactions. The idea of the estimator is to simulate data from the model to find the parameters for simulated data most closely match observed data

6 2. Model Set up A simple, static, two-sided market model Market m consists of J banks at time t Game: In first stage, local banks decide adopt ACH or not. A mt =(A 1mt A jmt ) bank adoption decisions. Second stage, customers decide adopt ACH for their individual transactions or not.

7 Adoption decision for customers: Customer i s net expected utility: EU ijmt =Nu mt (V ACH -V CHK )+F ijmt =β 0 +Nu mt (β 11 +β 22 (p t ACH -p t CHK ))+β 3 t+α jmt +ε ijmt =β 0 +β 1 u mt +β 2 p t ACH u mt +β 3 t+α jmt +ε ijmt Customer net utility: V ACH -V CHK =β 11 +β 22 (p t ACH -p t CHK ) Expected proportion of a customer s transaction if he adopts: u mt =δ[ A jmt P jmt x jmt / x jmt ]+(1-δ)[ A jmt x jmt / x jmt ) P jmt : proportion of customers adopting ACH δ : proportion of two-way transaction F ijmt =β 0 +β 3 t+α jmt +ε ijmt is the negative of fixed costs of adopting ε ijmt is an iid customer level logit error, T is time trend, α jmt is bank-level unobservable common knowledge

8 Adoption decision for local banks Local bank Profit from adopting ACH: Total number of transactions originated through bank j : T jmt ACH =T jmt P jmt u mt where T jmt =λx jmt where markup is a parameter to estimate FC jmt =FC+α jmt E is a per period fixed cost

9 Multiple Equilibrium Multiple equilibrium when network externality sufficient large, the adoption game is supermodular There exists at least one pure strategy subgame perfect equilibrium, and exists one Pareto-best or Pareto-worst subgame perfect equilibrium. let ω m < Ω be a frequency being best. Ω is the probability of being in Pareto-best equilibrium

10 3. Estimation Estimate the model using indirect inference ( Ⅱ) estimator. Ⅱis a variant of the method of simulated moments (MSM) estimator The model based on a vector of unknown parameters θ=(λ,β,ω,fc,markup,δ) and econometric unobservable v=(α,ω) Exogenous data:z m ={x 1t x jt, t, p t, A j1+1,t A J,t } t T =1 Endogenous variable: y m ={T 1mt ACH.T j1mt ACH } T=1 T

11 Construct estimator 1 st : estimation on true data, get a parameter vector μ (y, z), 2 nd : simulate data according to the model at various parameter vector. Take S simulation draws v sm from distribution of unobservables for each m. Compute Nash Equilibrium (either Pareto-best or worst, depending on w ) for each market given v sm and θ. Call this NE vector ŷ sm (v sm, θ, z sm ) Let ŷ s (v s, θ, z )=(ŷ s1. ŷ sm ), then perform same indirect inference on NE data.

12 The Ⅱestimator Need to specify norm using efficient weight matrix=inverse of variance of G Ⅱ (θ) is weight matrix

13 Compute Nash Equilibrium Compute NE, ŷ sm (v sm, θ, z sm ), this involves solving for either Pareto-best or Pareto-worst subgame perfect equilibrium. Solve for Pareto-best SPE, start iterative at a point all customers and local banks adopt ACH, while Pareto-worst SPE start at no one use ACH

14 Choice of indirect inference moments 1. capture bank and customer adoption decisions within a network 2. examine relationship between market concentration (HHI) and adoption 3. relationship between local bank and nonlocal bank adoption decisions These three group of regression coefficients give us 31 Ⅱmoments Add additional 11 moments to examine the robustness of parameter to an alternative choice of moments

15 Identification Network effects captured by 5 parameters 1. Customer fixed cost of adoption (utility, δ, T) 2. bank fixed cost of adoption (relative markup,% of bank adoption) 3. Bank marginal benefits 4. Customer marginal benefits (β 1 ) 5. Proportion of two-way transactions (δ) β 1 and δ will be identified by the shape of local bank ACH transactions in response to exogenous nonlocal bank adoption

16 4. Results and implication Table 1: parameter estimates

17 5. Results and implications

18 Table 2: indirect inference moments at estimated parameters A comparison of the differences in simulated moments and data moments suggest the model fits well. The estimated model overstate the level of network externalities

19 Table 3: Economic significance of parameters

20

21 Eliminate mean bank fixed cost, change for customer adoption is small Eliminate mean customer fixed cost, big changes Row 4 and Row 5, the results across the two equilibria are similar. Ω not particularly meaningful Row 6 and Row 7,bank maximize joint profit not change much, customers maximize joint utility nothing changed

22 Policy experiments Customer fixed cost preventing adoption of ACH government can have two types of fixed cost subsides: gov. pays a fixed amount to customers gov. pays a fixed amount to local banks Table 4: policy experiment

23

24 Column 2 and 3, customer subsidy is more effective Column 4, large customer subsidy, generate more ACH transactions and firm profits, but even larger utility cost Column 5, largest customer subsidy, total utils are unchanged, total profits increased

25 5.conclusion The paper estimate a static structural equilibrium model of network externalities in ACH banking industry to estimate causes and magnitudes of network externalities for this industry. The parameters are reasonable well. Bank fixed costs from ACH adoption are low, while customer fixed costs are high. Most ACH transactions are one-way Pareto best and worst equilibrium are not identical but similar to ACH adoption decision Adding large bank and customer subsidies will increase welfare

26 Section 2: Paper s contribution and weakness

27 Contribution Previous paper (Gowrisankaran and Stavins 2004) just test for the network externality; this paper estimate the magnitudes and source of network effect Develop the method on structural estimation of network games with potential multiple equilibrium The model will not not identify network effects from within-market correlations, instead it allows for unobservable shocks that are time varying and correlated between banks in a market

28 Weakness For the multiple equilibrium part, the restriction to only the two extreme equilibria (Pareto-best and Pareto-worst) is a simplicafication

29 Section 3: Suggestions for further research

30 The model here is fairly simple and static, future research can be to extend to allow for sunk costs (this model use per period cost) and dynamic optimization

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