vertical integration and firm boundaries · backward integration into input production (“make or...

IntroductionFirm boundaries

Consequences of vertical integration

Vertical integration and Firm BoundariesTheory and empirical evidence

Francine Lafontaine and Margaret Slade, JEL, 2007

Philippe Choné

May 2010

Advanced Industrial organization I, ENSAE and APE Master

Francine Lafontaine and Margareth Slade Vertical integration and Firm Boundaries



A fundamental issue in economics

Choice between interacting in a firm or a marketU.S. data: Value of transactions within firms roughly equalto those in marketsMore energy devoted on the workings of marketsUnder what circumstances good or service produced inhouse?Consequences of VI on prices, quantities, investment,profits?Inform managers’ decision as well as competition andmerger policy (vertical mergers and divestitures)




Outline

1 Introduction

2 Firm boundariesForward integration into retailingBackward integration into input production (“Make orBuy”)

The Transaction-Costs modelThe Property-Rights model

3 Consequences of vertical integrationMarket-power based theories of vertical integrationSome methodological issuesEvidence on the consequences of vertical mergers




Forward integration into retailingBackward integration into input production (“Make or Buy”)

Define vertical integration versus market transactionVI: ownership is joint and control rights are integratedContracts (vertical restraints) can achieve almostintegrationHere contracts equated as arm’s length transaction andcompared to VIRemark: Downward integration = “Make or buy”decision asregards retailing service.





Reaching consumers through premises she owns andoperates v. using independent retailersExamined in the case of exclusive dealing (franchising),not under common agency (department stores)Franchising can be

Business-format: the franchisor sells a way of doingbusiness to the franchisee (fast-food, hotel). Legallyindependent but transaction not completely arm’s length,because long-term contracts Royalties ρ and franchise feesf . Agent gets (1− ρ)q − f , where q is output. Studies focuson the proportion of company-owned outlets.Traditional (e.g. gasoline or car sales): the franchisor earnsa return on the product sold to franchisees. Some fixedpayment as well (rental fees in gasoline retailing). ExamineVI outlet by outlet





Stylized facts

Greater reliance on independent retailers whenthe franchisee’s effort are more importantthe firm’s operations are more geographically dispersedthe sales are more volatile (risk)the brand is less valuablethe outlets are smaller





Moral hazard (Old idea, 1920’!)

Risk is an important determinant of firm size and scopeTradeoff: Providing workers with

insurance. firms do well. Often fixed wages, do not dependon performances, at least in the short run.incentives to supply effort. Markets do that well, firms bad(low powered incentives). Independent contractor bearrisks. Fluctuation in response to both demand and costshocks





Principal agent framework. Moral hazard model of VI.Testable predictions

Principal: Manufacturer (effort eM ). Agent: Retailer (effort eR).Effort to produce output q: Advertising, point of sale services,etc.

q = β0 + βMeM + βReR + u

βM , βR > 0: marginal return of effort.u : random variable (uncertainty production process), N (0, σ2)q observable, but effort is not and cannot be inferred (due to u)Linear compensation scheme s(q) = αq + W .Cost of effort C(ei) = e2

i /2, i = M,R





Linear compensation scheme s(q) = αq + W

α: intensity of incentives, W : fixed wage

α = 0: salaried employee, perfectly insured (VI)α = 1: the agent is a residual claimant (gets profits oncecosts are paid), bears all of the risk (arm’s lengthtransactions)

Principal is risk neutral,agent risk averse, CARA utility

u(y) = −exp−ry , r ≥ 0

First-best efforts

maxeM ,eR

E(q)− e2M/2− e2

R/2 = β0 + βReR + βMeM − e2M/2− e2

R/2

yieldse∗∗

i = βi





Second-best

Principal maximizesE(q− s(q))− e2

M/2 = (1−α)(β0 + βReR + βMeM)−W − e2M/2,

Hence eM = (1− α)βM

Agent maximizes E{u[s(q)− e2R/2]} where

E(u(s(q))) = E ( −exp{−r [W + α(β0 + βReR + βMeM + u)]} )

= −exp{−r [W + α(β0 + βReR + βMeM)] + r2α2σ2/2}

= −exp−r{E(s(q))− r2

V (s(q))}

Hence agent maximizes E(s(q))− r2V (s(q))− e2

R/2 or

W + α(β0 + βReR + βMeM)− r2α2σ2 − e2

R/2

Hence eR = αβRFrancine Lafontaine and Margareth Slade Vertical integration and Firm Boundaries




Principal chooses the power of incentives α

Making the retailer’s participation constraint binding (u = u0)

W =r2α2σ2 + e2

R/2− α(β0 + βReR + βMeM) + Cst

E(q − s(q))− e2M/2 = (1− α)(β0 + βReR + βMeM)−W − e2

M/2

= β0 + βReR + βMeM −r2α2σ2 − e2

R/2− e2M/2

= β0 + αβ2R + (1− α)β2

M −r2α2σ2

−α2β2R/2− (1− α)2β2

M/2= β0 + β2

M/2 + β2Rα− α2(β2

R + β2M + rσ2)/2

Principal chooses α∗ =β2

R

β2R + β2

M + rσ2

and gets E(π) = β0 + β2M/2 + 1

2β2Rα

∗





Deriving a reduced-form model of VI

Introducing unobserved factors ε, with cdf F :

α = α∗ + ε =β2

R

β2R + β2

M + rσ2+ ε

Reduced-form profit under vertical separation

E(πVS) = β0 + β2M/2 +

12β2

R(α∗ − ε)− T

where T transaction cost (writing and administrating contracts)

Under VI, α = 0, the agent (employee) makes no effort, eR = 0,W = 0 (due to normalization), the manufacturer maximizesE(q)− e2

M/2 = β0 + βMeM − e2M/2, getting

E(πVI) = β0 + β2M/2





Discrete choice model of VI

The principal chooses VI when

12β2

R(α∗ − ε)− T ≤ 0

or

−ε ≤ 2Tβ2

R−

β2R

β2R + β2

M + rσ2

Probability of vertical integration

prob(VI) = F

(2Tβ2

R−

β2R

β2R + β2

M + rσ2

)





Testable predictions of the moral hazard model

The probability of vertical integrationdecreases with the marginal return of the agent’s effort, βR

increases with the marginal return of M’s effort, βM

increases with risk σ2 = V (u) and/or R’s risk aversion rincreases with contracting costs

In practice, use observable variable x that influences βR, βM , oru

q = β0 + γx + (βM + βMxx)eM + (βR + βRxx)eM + (1 + βRux)u

x must interact with eM , eR or u to be relevant (γ plays no role).Risk aversion more difficult to identify in practice (not usedhere)





Extensions

Multi-tasking: design incentive schemes is more difficult. MoreVI (see below)

Team production: central in moral-hazard of levels of the firm.Many workers, with complementary effort.But team worm may induce free-riding and make monitoringharder. (On the other hand, under repeated interaction, peermonitoring may replace the principal’s supervision).Modeling issue: synergies creates nonlinearity, oftenuntractable.





Empirical evidence: Risk

Risk borne by the retailer (outlet). Data measure do not exist.Imperfect proxies:

Variation in detrended sales per outletfailure rates: fraction of discontinued outlets in a period oftime

Data often available at the level of the industry, not of the levelof the franchisorIn all but two of those studies, increased risk is associated withless integration.Moreover, the two positive findings are not significant.Unsupportive of the basic agency model.





Empirical evidence: Risk





Negative correlation between risk and VI : Puzzle!

Possible solutions:Franchisors shed risks onto franchisees. Optimal only iffranchisors more risk averse than franchisees But if that isthe case, franchisors could sell outlets to franchiseesoutright for a price: rarely observedRisk is endogenous. The power of incentives (large α)induces retailers to adjust to local market conditions,implying that we observe more variations under separation.Do not control for heterogenous risk aversion: more riskaverse agents select safer markets as well as lower-powerincentivesProperty right theory (see below)





Importance of downstream effort eR

When the agent’s job is more entrepreneurial in nature (eRmatters more), less VI.Proxies for the importance of agent’s effort:

labor intensity: employee/sales, capital/labor)agent’s value added (sales-franchisor’s input)discretion over input choiceslocation dummies capture the level of responsibility (ruralbank)full service versus self service in gasoline retailing

In all cases where the coefficient for the importance of eR issignificant, negative impact on VI, as predicted.





Importance of upstream effort eM

MH in both sides. Franchisees expect franchisors to maintainbrand value: advertising, screen and police other franchisees.Proxies for eR:

Value of the tradename: amount of advertising, number ofoutlets, market value minus book value)amount of training provided by the franchisornumber of years developing the business format

In all cases, eM more important, more VI, as predicted.NB: Dynamics of franchising. The ownership rates decreasesfrom 100% to a target value (in typically 7 years), then remainsstable. The target rates is positively correlated with brand value.





Outlet size

q = β0 + γx + βMeM + βReM + (1 + βRux)u

Size has an effect onoutput (no effect on the franchising contract)on risk. The franchisee has more at stake in a larger outlet.Same risk, but more capital at risk (size effect)

Prediction: VI positively correlated with capital outlay. In all butone study, a larger outlet size increases company ownership.(Large outlets tend to be operated by salaried employees)

But size also increases retailer’s responsibility (βR + βRxx).Opposite prediction, contradicted by the data!





Costly monitoring

Simple model, without manufacturer’s effort. The manufacturerreceives an imperfect observation of effort: y = eR + εOutput q = β0 + βReR + uVariance of u: σ2

u. Variance of ε: σ2ε . To simplify: corr=0.

Schedule: s(q, y) = W + αqq + αyyThe retailer chooses effort so as to maximize Eu(s(q)− e2

R/2),or

−exp{−r [W + αq(β0 + βReR + u) + αy (eR + ε)− e2R/2]}

which is equal to

u [E(s(q, y))− r/2V (s(q, y))− e2R/2]





Costly monitoring

The agent maximizes

W + αq(β0 + eR) + αyeR − r/2[α2qσ

2u + α2

yσ2ε ]− e2

R/2

Second-best effort: eR = αq + αyThe principal maximizes

E(q − s(q, y)) = E [(1− αq)q −W − αyy ]

= E(q)− r2

(α2qσ

2u + α2

yσ2ε )− (αq + αy )2/2

The principal chooses (compare with the standard formula1/(1 + rσ2))

αq =1

1 + rσ2u + σ2

u/σ2ε

, αy =1

1 + rσ2ε + σ2

ε/σ2u





Costly monitoring

PredictionsHigher precision of sales data (lower σ2

u)→ moreoutcome-based compensation (higher αq), less VIHigher precision of the effort signal (lower σ2

ε )→ lower αq,more VI

When it is difficult to monitor sales, more VI [consistent withevidence]

difficult to measure equitably the results of individualsalespeople,team saleslong selling cycle make it difficult to attribute output to effortenvironmental uncertainty make it difficult for agents tocontrol sales





Costly monitoring

Proxies for the cost of direct monitoring of behaviorgeographic dispersiondistance from headquartersoutlet density (less costly)trucking: presence of onboard computer

Easier to monitor behavior, more VIConsistent with the empirical evidence





Multiple tasks

q1 = β0,1 + βR1eR1 + u1

q2 = β0,2 + βR2eR2 + u2

Symmetric case: V (u1) = V (u2) = σ2, correlation ρThe principal chooses

α∗i =1

1 + rσ∗2(1 + ρ)

Positive correlation (higher risk), lower αi , more VINegative correlation (risk diversification for the agent), higherαi , less VIOther linkages between tasks: costs of effort; cross-priceelasticity of demandWhen the agent is residual claimant for a complementary task,the incentives should be less powered (more VI).





Moral hazard: summary

Empirical evidence confirms thatImportance of local effort→ less VIImportance of company-wide effort→ more VIHard to monitor sales→ more VIHard to monitor behavior→ less VI

Outlet size, multitasking: more sensitive to specificationRisk: Evidence unsupportive of the MH theory

endogenous risk?but same in the sharecropping literature: the tenantunderreport output





Outline

1 Introduction



3 Consequences of vertical integration





The Transaction-Costs model

TC= cost of establishing and administering businessrelationships within and between firms, of writing and enforcingcontracts (Coase, 1937, Williamson, 70’)Parties often make investment that have grater value insidethan outside the relationship. Value of asset higher than inalternative use.

Special tools designed to produce a particular product(automobile dies)Training that increases worker or seller productivity in usingor selling the manufacturer productSupplier facility that have been located close to purchasers






Specific investment→ monopoly or monopsony powerParties are locked in ex postParties can sign long-term contracts to protect themselvesIf complete, no problem: under all possible contingencies, whatwill occur is specifies.But writing complete is costly, and not all contingencies can beforeseenReal-world contract are incompleteEx post opportunism and hold-up: The parties are likely tohaggle with one another,→↗ cost of writing and administeringthe contract, attempt to renegociateExacerbated in volatile environment






TC theory assume that these problem is mitigated inside thefirm. How does mitigation occur? Yet even inside the firms,workers having received special training can attempt to holdtheir employees up.Hierarchy and legal rules inside the firm reduce the hold-upcapacityTransaction with opportunism more likely to occur in houseFirms are likely to rely on in-house production when

transaction are complexspecific investmentquality of assets difficult to verifyenvironment is uncertainquasi-rents are large (more to earn by haggling)






Source of asset specificityPhysical capital specificity (higher value in intended use)Human capital specificity (training or on-the job learningthat is more valuable inside than outside a relationship)Dedicated assets (the buyer purchases a significantfraction of their product)Site specificity results from colocation. (savings ininventory and transport costs)Temporal specificity (assets must be used in a given order,so the unavailability of an asset can hold up production)

Measure specificity? complexity? Often qualitative, orquestionnaires, surveys of managers





Evidence on prediction from the Transaction-Costsmodel

Physical capital specificity0/1 depending on whether respondent thinks specificity isimportant0 “relatively standard” to n “design specificity”dummy for some imput (e.g. gas which requires pipelinesand storage tanks)

Effect on VI usually positive and significant (consistent with TC)






Human capital specificityAmount of training to produce or use an inputTechnical know how that must be acquired (can also be ameasure of complexity)

Positive and significant effect on VIOne exception (Woodruff) concerns forward integration intoretailing







chone

Rectangle





Dedicated assets. Proxies for dedicationDownstream firm’s share of purchasesdummy for whether one firm buy all the input

Positive effect on VI.






Site specificity or colocation. Proxiesanswers to questionsdummy for whether the two facilities are close to oneanother (plant generates electricity at the mouth of a coalmine)

Evidence not very conclusive. Only significant effort consistentwith TC theory






Temporal specificity: asset that can delay other aspects ofproduction

how important it is that an asset is on scheduledifficult to find an alternative supplier at the last minute

Positive effect on VI.






Complexity and uncertainty jointly make writing completecontracts more difficult. Effect have been studied together andseparatelyComplexity indicator

answers to question (0 to n)design costR&D intensityrenegotiation frequency

Positive and significant effect on VI (one exception, Acemogluet al. Upstream)







chone

Rectangle





Uncertainty indicatorsvariance of salesinstability of market shares downstream and upstreamfrequency of design changes

Whenever the effect on backward interaction is significant,higher uncertainty makes VI more likelyTrue whether uncertainty occurs upstream or downstream

NB: Difference with Table 1 that concerns forward integration






SummaryVirtually all predictions from TC theory are consistent withempirical evidencein particular for backward integration (between a manufacturerand its suppliers)





The Property-Rights model

Property rights: right to make decisions concerning the use ofan asset in case of unforeseen contingenciesA manufacturer M must decide whether

buys an input from a supplier Sproduces it herself (acquire S)

Specific investment, incomplete contract, ex post opportunismDifferences with TC theory

More recent (80’, 90’), more formal. Grossman, Hart, andMoore.Focus on ex ante investment incentivesHold up also inside the firm. VI does not necessarilymitigate the problem (which was postulated by TC theory)

MH: residual claims, PR: residual decision rights






Timing1 M and S agree on VI or separation2 Ex ante investment decisions. Non contractible investment

iM and iS, at cost i2M/2 and i2S/2. Under VI, investment iSmade by the upstream division of the firm (possiblehold-up)

3 Ex post sharing of the surplusEx post surplus when bargaining is successful:

π(iM , iS) = α0 + αM iM + αS iS

W (iM , iS) = π(iM , iS)− i2M/2− i2S/2

First best:i∗M = αM i∗S = αS






Asset ownership:Separation: S owns the upstream asset iS (k = 0)Backward VI: M owns the upstream asset iS (k = 1)

Asset ownership affects the the threat points (if bargaining fails)

M’s outside option under separation and under VI

µ0k + µk iM , k = 0,1

S’s outside options under separation and under VI

σ0k + σk iS, k = 0,1

VI improves (deteriorates ) M(S)’s bargaining position

µ0 < µ1 < αM and σ1 < σ0 < αS

Players have an incentives to use their investment to bettertheir positions in the ex post game






Sharing of the surplus: each party gets its outside option plushalf of the surplus from tradeManufacturer gets

µ0k + µk iM +12

[α0 + αM iM + αS iS − (µ0k + µk iM)]

or12

[µ0k + µk iM + α0 + αM iM + αS iS]

Manufacturer maximizes the above minus i2M/2, soiM = (αM + µk )/2 under kSimilarly the supplier chooses iS = (αS + σk )/2






Ex ante total surplus as a function of asset ownership(separation (k=0)or VI (k=1))

W (k) = α0 + αM iM + αS iS − i2M/2− i2S/2= α0 + αM(αM + µk )/2− (αM + µk )2/8 + same for S= Cst + αMµk/4− µ2

k/8 + +αSσk/4− σ2k/8

M and S agree on VI if W (1) ≥W (0)W (1)−W (0) depends on αM through (µ1 − µ0)αM/8,increasing in αM .The marginal return of the manufacturer’s investment makesbackward integration MORE likely






W (1)−W (0) depends on αS through (σ1 − σ0)αS/8,decreasing in αS.The marginal return of the supplier’s investment makesbackward integration LESS likely

Similar to MH

W (k) increasing in µk and σk : the marginal return of oneparty’s investment in a disagreement payoff under assetownership k increases the likelihood of k





Evidence on prediction from Property-Rights model

Few studies deal with PR predictions, distinguish TC and PREvidence seems supportive of TCE more than PR as assetspecificity always make VI more likelyBut the following supports PR (or, admittedly MH):

Acemoglu et al., Table 13: Complexity upstream(downstream) decreases (increases) VIWoodruff (Table 8): also forward integration retailing (Rinvestment make VI less likely)Table 2 (effect of R effort) support PR vis-à-vis TCE: Reffort can also be seen as R investment (franchisee ownsfuture profits and even the right to sell the outlet)Table 1: When risk increases, R investment become moreproductive. PR predicts LESS VI, not more, which wouldexplain the negative between risk and VI




Market-power based theories of vertical integrationSome methodological issuesEvidence on the consequences of vertical mergers

Outline

1 Introduction



3 Consequences of vertical integrationMarket-power based theories of vertical integrationSome methodological issuesEvidence on the consequences of vertical mergers





Introduction

Identify the benefits from VI? The winners and the losers?What about consumers?

First part has emphasized that when firms choose VI, it isefficient for them to do so

Should vertical merger policy even exist? In the antitrusthistory, many reversals with lenient or stringent policies.

There exist anticompetitive motives for VI: Creation orexploitation of market power through collusion, exclusion





Introduction

Studies focus on concentrated marketsHalf of the studies do not find exclusionWhen they do, they also document efficiencies. Overall,not necessarily for consumers

Literature suggest thatmost voluntary VI benefit consumersdivorcement requirements from authorities (e.g. to protectlocal dealers) harm consumers through higher prices andlower service levels





Double marginalization

Fixed proportion. Unintegrated firms ignore the reduction inprofits they inflict on other stages of production when theirprices increaseVI benefit consumersDM can easily be eliminated through VR

Variable factors proportionsUpstream monopolist sells an input x1Downstream firms substitute other input x2 from x1, consumingtoo much of x2 and too little of x1Production inefficiency gives to monopolist an incentive tointegrate forward. Ambiguous effect on consumers.





Foreclosure and Raising Rival’s costs

Consumer or input foreclosure: main worry of competitionauthoritiesBarrier to entry or to growth, eviction, competitivedisadvantage, raising rivals costsSalinger (1988), Hart and Tirole (1990), Ordover, Saloner,Salop (1990)Absent double marginalization, VI often causes prices torise





Strategic delegation and CollusionUnder price competition, price higher under separation thanunder VI.Under separation, the manufacturers delegate the pricedecision to retailers which soften competitionUnder VI, neck-to-neck, fiercer competitionSo manufacturers prefer separation, all the more than theproducts are substitutableDoes not hold under Cournot competitionDoes not hold if agent risk averse (then VI is better)VI chosen when products not highly substitutable and agentrisk averse

Slade (1988) in the retail-gasoline sales, shows that VI is lesslikely when rival reaction function are steep.





Price discriminationAn upstream monopolist sells an input to two industrieswith different demand elasticitiesIf arbitrage impossible, higher price for less elastic industryIf arbitrage possible, single price, upstream profit lower.To remedy that, the monopolist may acquire the moreelastic industry, suppressing the low price market andpreventing arbitrage.Ambiguous effect: less elastic consumers pay more, moreelastic consumers pay less





Start with descriptive statistics: before and after, but VIdecisions are endogenous/ hard to find instruments/ structuralmethods

Cross-section, Time-series, and Panel2 subgroups of firms in a given industry, VI (m) and firmstransact with independent trade partners (m)measure of performance y (profits, sales, etc.)VI = Treatment undergone by the firmsIdentify the counterfactual: yvm hypothetical y the firmwould have experienced if no treatment

∆∗ = yv ,T − yvm,T





Cross-section, Time-series, and Panel (ct’ed)Most useful data is panel with both cross-sectional andtime-series variations in firm organizationsm1 firms undergoes an organizational change between periods1 and 2, m2 remain untreatedDifference in differences

∆DD = (yv ,T2 − ym1,T1)− (ym2,T2 − ym2,T1)

DD removes both firm and time fixed-effects. Attribute the DDto the treatment.Possible to control for time-varying individual variablesPurge common causal factors provided that differ by firm (overtime) but not over time (by firm)





Cross-section, Time-series, and Panel (ct’ed)Time-series data: hard to control for other changes than VICross-section: hard to control for endogenous treatment(selection bias)

What if the organizational is imposed, e.g. by regulation? Doesnot mitigate the problem if the law has targeted special firms,supposed to differ in terms of the relevant competitive concern.





Event studiesFor publicly traded firms, use the market forecasts of the effectsAssumption: stock markets are efficient, share prices reflect allcurrently available infoReturn on asset i as a function of market return:

Rit = αi + βiRMt + uit

It is important the event is a surprise to attribute the change inthe share price to the eventMarket might not react instantaneously, use a window aroundthe event





Event studiesAssess the abnormal returns due to the merger

ARit = R̂it − Rit = α̂i + β̂iRMt − Rit

where α̂i and β̂i are estimate before the eventOften AR summed over observations in the window.

Window too narrow misses the eventWith too broad a window, averaging can remove the effect.





Event studiesHorizontal merger, look at the rivals’ share prices

Market power effect dominates: good for rivalEfficiency effects dominates: bad for rivals

More complicated for vertical merger, that can harmdownstream rivals

because downstream units becomes more efficient(pro-competitive)because of input foreclosure (anti-competitive)

Look at the share price of buyers, if possible





Structural methodsWith reduced-form method, no ex ante forecast of a policychange, no merger simulationQuite common for horizontal mergers, but very few structuralworks for non-horizontal mergers, because it is hard to capture

efficiencies (better alignment of incentives)better ability to collude (“coordinated effects”)strategic incentives, bargaining with suppliers orcustomers, etc.





Foreclosure and Raising rival costs

Industries under scrutiny from authorities: media, cementand concrete, oil refining and distributionSome paper find foreclosure, but not necessarilyanticompetitive foreclosure (need to balance efficiencygains)Two papers assess the tradeoff, concluding that EGdominateEvidence for anticompetitive foreclosure is weak





Other consequencesVariables of interest: price, cost, investment, profit, stockratings, abnormal returnsLiterature suggest efficiencies.Does not find welfare reductions due to VI (even thoughmarkets are concentrated)





DivorcementAgencies sometimes mandate divestitures

Gasoline (US states:) from company owned companyoperated to company owned dealer operatedBeer UK: from company owned dealer operated to dealerowned dealer operated

Literature conclude that divorcement policy is misguided.

Gasoline US: The choice of an arrangement (e.g.company operated versus company owned dealeroperated for outlets owned by the company) is based onefficiency consideration. Why would the company want todisadvantage its affiliated retailers?Beer UK: Introduction of double marginalization


vertical integration and firm boundaries · backward integration into input production (“make or...

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