Competition and Innovation:An Inverted-U Relationship

Philippe Aghion (Harvard & UCL)Nick Bloom (CEP, LSE)

Richard Blundell (IFS & UCL)Rachel Griffith (IFS & UCL)

Peter Howitt (Brown)

The fact

• The theories of industrial organization typically predict the negative relationshiip between competition and innovation

• a positive effect – i.e. Geroski (1995 OUP), Nickell (1996 JPE) and Blundell, Griffith and Van Reenen (1999 RES), Mohen and ten Raa (2002, WP)

The two effects

• “Competition effect”:– “... from Adam Smith to Richard Caves: the

belief that competition is good, rests on the idea that competition exerts downward pressure on costs, reduces slack and provides incentives for efficient organisation of production...” (Nickell, 1996 JPE)

• “Schumpeterian effect”:

The framework of this paper

• The new fact : an inverted-u relationship use a panel data and find a robust inverted U-shape between competition and innovation (patenting)

• Combining agency models with Schumpeterian models– At low levels of competition the “competition effect”

dominates leading to a positive relationship– At high levels of competition the “Schumpeterian effect”

dominates leading to a negative effect

The structure

• The empirics research

• The model

• Concludes

The data

• UK firm level accounting data , the firms list on the London Stock Exchang.

• Our sample includes all firms with names beginning A to L plus all large R&D firms

• An unbalanced panel of 311 firms spanning seventeen industries over the period 1973-1994.

Measure of innovation

• Average number of annual patents taken out by firms in an industry.

• Weighted patents by citations received to measure innovation “quality”

Measure of Product Market Competition

• Traditional measures based on market share– But problem defining the product & location

market.– For the UK international markets important – i.e.

Glaxo has 7% global market but 70% share of UK market as defined by sales of UK listed firms

• So we use the Lerner Index

Our competition measure is the average of this across firms within the industry

• A value of 1 indicates perfect competition, while values below 1 indicates some degree of market power.

• The entire sample of Stock Market Listed firms in each industry.

Passion regression(p527-p531)

• 因变量是计数变量（ count varible ），非负整数值。确保 y的预测值也总是正数，将其期望值模型化为一个指数函数。

• MLE(QMLE): 不管泊松分布成立与否，仍然可以得到待估系数的一致和渐进正态的估计量

),...,(exp),...,,|( 121 kk xxGxxxyE

!/)])][exp(exp(exp[)|( hxxxhyP h

• Estimate the key moment condition E[P|C] = exp(g(C))– P is the patent count, C the competition measure, and g(.) a

flexible function

– We use an exponential `Poisson style’ model

– g(.) is non-parametrically approximated using a quadratic spline-function (see Ai and Chen, 2002 Econometrica)

• To allow for industry and time variables effects these are parametrically included in addition to yield a final estimating equation E[Pit|Cit] = exp(g(Cit) + Xit’b)

Endogeneity • PMC may be endogenous as higher patenting firms

may gain higher rents• Firstly, we include time and industry dummies

– changes in competition identify changes in patenting

Secondly, we instrument changes in competition using the large number of competition changes that have occurred in the UK since 1970:– Differential changes in competition across industries

following the 1992 EU single market program– Changes in competition following major privatizations– Change in completion following structural and behavioural

remedies imposed on industries after a Monopolies and Mergers Commission

Results

The inverted-U shape is robust

• Five –year average

• R&D expenditure

• Each of top four innovating industries

Assumptions• Sturcture assumption:• The economy contains many industries, with (for

simplicity) two firms, which are either:– “neck-and-neck” as firms have the same technology– “leader-follower” as firms have different technologies

Technonlogy is step-by-step

Innovation depends on difference between postinnovation and preinnovation rents for incumbent firms

The model

• A logarithmic instantaneous utility function

• A continuum of intermediate sectors

• Doupolists in sector j

• Max xAj + xBj st pAj*xAj +pBj*xBj =1

• Each firm produces using labor as only input, a constant –returns production function, and take the wage rate as given.

• The unit costs of production cA and cB of the two firms in an industry are independent of the quantities produced.

• let k denote the technology level of duopoly firm i in some industry j . One units labor generates an output flow equal to

• The state of an industry is then fully characterized by a pair of integers (l,m)

• For simplicity,we assume knowledge spillovers between leader and follower in any intermediate industry are such that the maximun sustainable gap is m=1.

• Two kinds of intermediate sectors in the economy:– Leveled or neck-and-neck sectors, m=0.– Unleveled sectors, m=1.

R&D cost is in units of labor ,with a passion hazard rate n. ----innovation rate or R&D intensity

• Leader firm moves one technological step ahead with a hazard rate n

• a follower firm can move one step ahead with hazard rate h, even if it spends nothing on R&D ,by copy the leader’s technology . Then,a follower firm moves ahead with a hazard rete n+h

• They do not collude when the industry is unlevel.

• Each firm in a level industry earns a profit of 0 if the firms are unable to collude. In Bertrand competition, each farm has maximun profit is .

• is also the incremental profit of an innovator in a neck-and-neck industry, also indicates PMC

Escape competition

• Under low competition “neck-and-neck” firms earn moderate profits, yielding little gain from innovation, so– “neck-and-neck” firms undertake little innovation– leading to an equilibrium with mainly “neck-and-

neck” industries– so increasing competition raises innovation as

“neck-and-neck” firms increase innovation

Schumpeterian effect

• Under high competition “neck-and-neck” profits are low, so the rewards to innovating to become a leader are high, so:– “neck-and-neck” firms undertake a lot of

innovation– leading to an equilibrium with mainly “leader-

follower” industries– so further increases in competition lower the

profits for followers to innovate and become “neck-and-neck”, reducing innovation

Schumpeterian effect vs escape-competition effect

• On average, an increase in product market competition will thus have an ambiguous effect on growth.

• The overall effect on growth will thus depend on the (steady-state) fraction of leveled versus unleveled sectors.

• But this steady-state fraction is itself endogenous, since it depends upon equilibrium R&D intensities in both types of sectors.

Conclusions

• the competitioninnovation relationship takes the form of an inverted-U shape.This result is robust.

• Extend the current theoretical literature on step-by-step innovation to produce a model that delivers an inverted-U prediction.

• the equilibrium degree of technological neck-and-neckness among firms should decrease with PMC

• the higher the average degree of neck-and-neckness in an industry, the steeper the inverted-U relationship between PMC and innovation

• All innovations equal in the model

• Lerner index ? More profit doesnot mean less competitive.

• Which is the cause? Innavation or compitition ? What determints the initial conditions

Some puzzles

• Why the hazard rate is difference between a laggard frim and a firm in neck-and-neck industry? h?

• FOC