Competition and Innovation: An Inverted-U Relationship

1. 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)

2. 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)

3. 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”:

4. The framework of this paper • The new fact : an inverted-u relationshipuse 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

5. The structure • The empirics research • The model • Concludes

6. 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.

7. Measure of innovation • Average number of annual patents taken out by firms in an industry. • Weighted patents by citations received to measure innovation “quality”

8. 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

9. 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.

10. 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

11. 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)

12. 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

13. Results

14. The inverted-U shape is robust • Five –year average • R&D expenditure • Each of top four innovating industries

16. 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

17. 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

18. 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)

19. 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

20. They do not collude when the industry is unlevel. • Each firm in a level industry earns a profit of 0 if the firms areunable to collude. In Bertrandcompetition, each farm has maximun profit is . • is also the incremental profit of an innovator in a neck-and-neck industry, also indicates PMC

23. 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

24. 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

25. 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.

28. 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

29. 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

30. Some puzzles • Why the hazard rate is difference between a laggard frim and a firm in neck-and-neck industry? h? • FOC