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Lecture 3 - The microeconomic foundations of the economic theory of innovation

From UNU.MERIT, 10 months ago

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Slide 1: R&D and competition Motivation: to investigate the relation between competition and R&D expenditures Schumpeterian hypotheses Incentives A case: steam engines Patent races Common pool problem Recent developments

Slide 2: Schumpeterian hypotheses: Monopoly power and firm size are conducive for R&D – A monopolist is well-placed (distribution, reaction to rivals) – Internal finance of innovation (moral hazard) – Advantage on labour market for engineers – More internal spillovers in a large R&D team – Technology push favours firms with large resources for R&D – Demand pull favours firms with a deep knowledge of market and large scope

Slide 3: Incentives Same context as in the patent length model: a process innovation Compare profits with and without innovation: the difference is what a firm would maximally pay to get the innovation (=maximum amount of R&D it is willing to spend)

Slide 4: Incentives – mathematics q A Bp, Monopolist: 2 qp 2 A1 1 1 (A Bc) p c, qp (A Bc), , 2B 2 2 4 B B c 1 1 B(c 2 c 2) (c) (c) q(p (c)) dc A(c c) 2 4 c Competitive firm: c minor q(c) dc (A Bc) (c c). c c q(c) dc. Social planner: c

Slide 5: Incentives: conclusion The incentive for a monopolist is strictly smaller than that for a competitive firm with a minor innovation, which is again strictly smaller than that for a social planner

Slide 6: Steam engines – An illustration Engine builders in Cornwall in 1800 could charge 1/3rd of the total fuel savings relative to a Newcomen engine P C × × HP × H , Fuel consumption: 240 2240 P=266 pence, HP=3250, H=4000 (Cornwall, 1800) Newcomen engine: C=24.3 266 (24.3 − 61) . × × 3250 × 4000 ≈ 117068 Watt engine: C=6.1 240 2240 266 (24.3 − 33) . × × 3250 × 4000 ≈ 135078 Woolf engine: C=3.3 240 2240 266 (24.3 − 4.3) × × 3250 × 4000 ≈ 128646 Trevithick engine: C=4.3 240 2240

Slide 7: Patent race Incumbent vs entrant Efficiency effect m d d (c) (c, c) (c, c). Incumbent: m d (c) (c, c) (R1 R2 ) m(c) V1 e e R1 R1 R2 0 m m d (c) R1 R1 (c) / R2 (c,c) / . R1 R2 Entrant: d d R2 (c,c) / R2 (c,c) (R1 R2 ) V2 e e R2 R2 . R1 R2 0

Slide 8: Patent race Incumbent vs entrant Nash equilibrium: 1 R1 [ m(c) m m d V1 [ R1 R2 ] (c) R2 [ (c) (c,c)] / R1] 0 R1 2 ( R1 R2 ) R2 1 [ d(c,c) R2 d V2 R1 R2 (c, c) / R2] 0. R2 2 ( R1 R2 ) Drastic innovation: π d (c, c ) = π m (c), π d (c , c,) = 0 1 1 R1 R2 R2 R1 1 1 1 m m (c) R1 (c) [R1 R2 ] R1 R2 .

Slide 9: Patent race Incumbent vs entrant

Slide 10: Symmetric patent race R1 R1 (R1 (n 1)R ) V e e (R1 R1) d . R1 (n 1) R 0 1 [(n 1) R ][ R1 1] R1 (1 ) 0. 1 [(n 1) R1 ][ R1 1] R1 (1 ) 0.

Slide 11: Symmetric patent race

Slide 12: Symmetric patent race Monopolist (centralized): Rm Rm (nRm) Vne e (Rm Rm) d n . nRm 0 nRm (1 ) 1 Rm 1 . Decentralized: R1 (1 ) 1 R1 1 . (n 1) R1

Slide 13: Patent race as a common pool problem Number of fishermen Catch per fisherman Total catch Marginal increase in total catch 0 - 0 - 1 100 100 100 2 90 180 80 3 80 240 60 4 70 280 40 5 60 300 20 6 50 300 0 7 40 280 -20

Slide 14: Recent developments Patent races with memory (leads to a single dominant firm) Mixed strategies repeated games: if leapfrogging is possible this favours a large number of firms undertaking R&D

Slide 15: recent developments Invariance theorem – if all players in a race are allowed to engage in multiple projects without externalities between them, it does not matter how many players there are (and otherwise it does!) Second-mover advantages (it may pay to wait, see inventing around example) Size of prize depends on R&D

Slide 16: R&D and competition An alternative view: technology regimes in a boundedly rational, evolutionary world When uncertainty is strong, the rational behaviour of patent race and patent protection models is not very realistic Nelson & Winter model

Slide 17: Technology regimes Basic idea is that the nature of the knowledge base has an impact on the way innovation and technological change takes place, and this influences market structure Schumpeter Mark I vs Mark II Different regimes within the same industry? (Saxenian) The Nelson & Winter model can generate technology regimes

Slide 18: A (more) realistic Model: Nelson & Winter Firms differ, they are characterized by – A labour coefficient (labour output ratio) – A capital coefficient (capital output ratio) – A capital stock Firms sell a homogenous output, and hire homogenous labour Rationality is bounded: based on rules of thumb and routines Firms engage in search (R&D) to improve their technology (input coefficients)

Slide 19: R&D in the Nelson & Winter model R&D can be imitative (trying to imitate technology of other firms) or innovative (trying to find new techniques R&D is local search, it starts from the technology that the firm has now; this is in line with the notion of a technological paradigm In one version of the model, R&D depends on the nature of the knowledge base

Slide 20: The market structure model Two technological regimes: – Routinized – Entrepreneurial This is modeled after Schumpeter Mark I vs Mark II

Slide 21: The routinized regime Lower probability of innovation (for equal levels of R&D spending) Innovative step depends on external (scientific) developments and the firm’s own performance (innovation in the past breeds more success): cumulativeness As a result outsiders (potential entrants) have a low probability of success (they have no experience)

Slide 22: The entrepreneurial regime A high probability for innovation Outsiders (potential entrants) are as good in innovation as incumbents

Slide 23: Simulation analysis The usual way of analysis of a model is to find the equilibrium The evolutionary Nelson and Winter model does not have a clear-cut equilibrium Outcomes of the model depend on random factors (e.g., innovative success) The model can be analyzed by running it on a computer

Slide 24: Guidance for simulation analysis A single simulation run is not enough to show a result Monte Carlo experiment: run multiple times with different parameter settings, and then compare the outcomes by means of a statistical analysis

Slide 25: Technology regimes – Nelson & Winter http://www.tm.tue.nl/ecis/bart/nwreg.zip

Slide 26: Simulation results – Nelson & Winter

Slide 27: Simulation results – a systematic comparison of the regimes

Slide 28: Technology regimes – Nelson & Winter A conclusion: differences in knowledge base cause differences in R&D spending and market structure Which regime generates which market structure? How can the changes between the regimes be influenced? – Explorations of parameter space