Competition and Innovation; An inverted-u Relationship

Transcription

1 Competition and Innovation; An inverted-u Relationship by P. Aghion, N. Bloom, R. Blundell, R. Grith, P. Howitt, The Quarterly Journal of Economics (2005) 12 1 Department of Economics Ecole Polytechnique Course of Graduate Econometrics 3 - Denis Fougère

2 Outline 1 Problem Statement The problem Count Specication (Hausman et al - Econometrica 1984)

3 Outline Problem Statement 1 Problem Statement The problem Count Specication (Hausman et al - Econometrica 1984)

4 Competition and Innovation The possible Correlation The paper reexamines the possible relationship, literature predicts that innovation should decline with competition. However there exists an inverted-u shape curve. In their model, all players (leaders and the followers) can innovate in a step-by-step manner. Innovation incentives depend not so much upon postinnovation rents, but upon the dierence between postinnovation and preinnovation rents of rms.

5 Competition and Innovation The possible Correlation The paper reexamines the possible relationship, literature predicts that innovation should decline with competition. However there exists an inverted-u shape curve. In their model, all players (leaders and the followers) can innovate in a step-by-step manner. Innovation incentives depend not so much upon postinnovation rents, but upon the dierence between postinnovation and preinnovation rents of rms.

6 Competition and Innovation The possible Correlation The paper reexamines the possible relationship, literature predicts that innovation should decline with competition. However there exists an inverted-u shape curve. In their model, all players (leaders and the followers) can innovate in a step-by-step manner. Innovation incentives depend not so much upon postinnovation rents, but upon the dierence between postinnovation and preinnovation rents of rms.

7 Competition and Innovation The possible Correlation A priori there are two possibilities. Neck-and-neck situation where rms are operating at a similiar technological levels. Competition could reduce the preinnovation rent. In situation where neck-and-neck is not the case, the laggard rms with already low initial prots, product market competition will mainly aect postinnovation rents, and therefore the Schumpeterian eect of competition should dominate. The essence of the inverted-u relationship berween competition and innovation is that the fraction of sectors with neck-and-neck competitors is itself endogenous. When competition is low a larger equilibrium fraction of sectors involve neck-and-neck competing rms, so that overall the escape-competition condition would dominate the Schumpeterian eect. When competition is high it is the contrary which holds true.

8 Competition and Innovation The possible Correlation A priori there are two possibilities. Neck-and-neck situation where rms are operating at a similiar technological levels. Competition could reduce the preinnovation rent. In situation where neck-and-neck is not the case, the laggard rms with already low initial prots, product market competition will mainly aect postinnovation rents, and therefore the Schumpeterian eect of competition should dominate. The essence of the inverted-u relationship berween competition and innovation is that the fraction of sectors with neck-and-neck competitors is itself endogenous. When competition is low a larger equilibrium fraction of sectors involve neck-and-neck competing rms, so that overall the escape-competition condition would dominate the Schumpeterian eect. When competition is high it is the contrary which holds true.

9 Competition and Innovation The possible Correlation A priori there are two possibilities. Neck-and-neck situation where rms are operating at a similiar technological levels. Competition could reduce the preinnovation rent. In situation where neck-and-neck is not the case, the laggard rms with already low initial prots, product market competition will mainly aect postinnovation rents, and therefore the Schumpeterian eect of competition should dominate. The essence of the inverted-u relationship berween competition and innovation is that the fraction of sectors with neck-and-neck competitors is itself endogenous. When competition is low a larger equilibrium fraction of sectors involve neck-and-neck competing rms, so that overall the escape-competition condition would dominate the Schumpeterian eect. When competition is high it is the contrary which holds true.

10 Outline Problem Statement 1 Problem Statement The problem Count Specication (Hausman et al - Econometrica 1984)

11 Measuring the variables Measuring the variables Measuring Innovation: Average number of patents taken out by rms in an industry, and to reect the heterogeneous values of patents, weighted each patent by the number of times it has been cited. Measuring the competition: Lerner index (or price cost margin) operating prot nancial cost li it = hence c sales jt = 1 1 N (li it jt ) as measure of competition (value 1 means perfect competition)

12 Measuring the variables Measuring the variables Measuring Innovation: Average number of patents taken out by rms in an industry, and to reect the heterogeneous values of patents, weighted each patent by the number of times it has been cited. Measuring the competition: Lerner index (or price cost margin) operating prot nancial cost li it = hence c sales jt = 1 1 N (li it jt ) as measure of competition (value 1 means perfect competition)

13 Outline Problem Statement 1 Problem Statement The problem Count Specication (Hausman et al - Econometrica 1984)

14 Count Econometric Model n = exp(g (c)) where n is hazard function and c as the measure of competition Patent function has a Poisson distribution E [p c] = exp(g (c)) (Parametric model with strong assumption, relaxations could be found in Hausman et al- Econometrica-1984) To take into account the possible endogeneity caused by unobserved xed eect, the hasard function could be conditioned on industry and time ) dummies, E [p jt c jt, x jt ] = exp (g (c jt ) + x jtβ

15 Outline Problem Statement 1 Problem Statement The problem Count Specication (Hausman et al - Econometrica 1984)

16 Using Policy Instruments The major obstacle to empirical research in this area is that competition and innovation are mutually endogenous. Instruments dened by authors, Thatcher era privatization, the EU single market programme and Monopoly and Merger commission. c jt = π (z jt ) + x jt + ν jt

17 Outline Problem Statement 1 Problem Statement The problem Count Specication (Hausman et al - Econometrica 1984)

18 Explaining the Inverted-U Shape Many of the pre-existing models only take into account the decreasing part of the inverted-u (Refer to, Salop (1977), Dixit and Stiglitz (1977), Romer (1990), Aghion and Howitt (1992)), competition discourages innovation by reducing postentry rents. All the above models is based on prot maximization but Hart (1983) says that rms are runt by satiscing managers who do not value prots per se, but yet draw private interests from maintaining the rm aoat and thereby keeping their job! Then increased competition may induce otherwise reluctant managers to put more eort into reducing costs in order to avoid bankruptcy.

19 Outline 1 Problem Statement The problem Count Specication (Hausman et al - Econometrica 1984)

20 and Explanations A constant rate of intertemporal discounted function for consumption In the production side, authors dene a space (l,m) where l is the leader's technology and m is the gap between the laggard and the leader. This space leads to two already mentioned possibility, if m = 0 then we are in the neck-and-neck sector, otherwise there is a leader and laggard (m = 1) Hence they derive the necessary equations for the equilibrium research intensity by neck-and-neck and laggard rms (p )

21 Explanation When there is not much product market competition there is hardly any incentive for neck-and-neck rm to innovate, and therefore overall innovation rate will be highest when the sector is unleveled. On the other hand when competition is initially very high there is little incentive for the laggard in an unleveled state to innovate. As a result industry will spend most of the time in the unleveled state where the Schumeterian eect is at work on the laggard, while the leader never innovates.

22 Outline 1 Problem Statement The problem Count Specication (Hausman et al - Econometrica 1984)

23 Testing the s The rst key prediction on the technological spread is that, in the equilibrium the average technology gap between leaders and followers should be an increasing function of the overall level of industrywide competition. The second theoretical prediction is that the inverted-u shaped relationship between competition and growth should be more steeper in more neck-and-neck industries.

24 Outline 1 Problem Statement The problem Count Specication (Hausman et al - Econometrica 1984)

25 Ther is an inverted-u shape relationship between competition and innovation. Competition may increase the incremental prot from innovating labeled the escape-competition but competition may also reduce innovation incentives for laggards, labeled the Schumpeterian eect

26 Count Specication (Hausman et al - Econometrica 1984) Outline 1 Problem Statement The problem Count Specication (Hausman et al - Econometrica 1984)

27 Count Specication (Hausman et al - Econometrica 1984) Count Description Poisson model is the most convenient model of rare events (the limit law: n p 0 np λ ) This is also a reasonable description for events which occur both randomly and independently in time. As one of its properties, equi-dispersion could be mentioned E (y it x it ) = Var (y it x it ), which is not the case in real applications. Modication of Poisson distribution to take into account the overdispersion problem produces the Multivariate analysis such as Negative Binomial Model.

28 Count Specication (Hausman et al - Econometrica 1984) Count-Panel Formulation Fixed Eect Negative Binomial Regression, Gamma distribution used to capture the unobserved heterogeneity Fixed Eect since the unobserved heterogeneity could be correlated with covariates. Conditional Maximum Likelihood Conditional Fixed Eect NB Distribution ( f y i1,...,y it T t=1 y it ) = Γ( t λ it )Γ( t y it +1) Γ( t λ it + t y it ) T t=1 Γ(λ it +y it ) Γ(λ it )Γ(y it +1)

29 Count Specication (Hausman et al - Econometrica 1984) Count-Panel Formulation Fixed Eect Negative Binomial Regression, Gamma distribution used to capture the unobserved heterogeneity Fixed Eect since the unobserved heterogeneity could be correlated with covariates. Conditional Maximum Likelihood Conditional Fixed Eect NB Distribution ( f y i1,...,y it T t=1 y it ) = Γ( t λ it )Γ( t y it +1) Γ( t λ it + t y it ) T t=1 Γ(λ it +y it ) Γ(λ it )Γ(y it +1)