economics talking about the capital, innovation, and technology

1. INDUSTRIAL ORGANIZATION:
R&D and INNOVATION
PRODI S1 FEB UI 2020

2. 2
Introduction
• Technical/technology progress (innovation) is the
source of rising living standards over time. One of
indicators for economic growth
• Innovation is typically defined as a search for, and
the discovery, development, improvement,
adoption and commercialization of new process,
new products, new organizational structures and
procedures including new business model.
• Firms spend a lot of money on this activity.
Sometimes it is typically known as RnD

3. R&D and Innovation
• Some people often use the term R&D and Innovation
interchangeably. The fact, there is a slight different
• The relation is as follows:
Innovation = R&D (invention) ++ (e.g. customer value,
business model)
Research & Development Innovation
Technology/technical risk Including market risk
Create new knowledge/
knowhow
Create new value + business
from the knowledge

4. Introduction
• Innovation also brings about new concept of
efficiency
– Static efficiency—traditional allocation of resources
to produce existing goods and services so as to
maximize surplus and minimize dead weight loss
– Dynamic efficiency—creation of new goods and
services to raise potential surplus over time
• Thus far, it is assumed the production function
is exogenous to the firm and viewed as “black
box”. Innovation activities can influence this
box

5. Introduction: Dynamic efficiency
Efficiency
Time
T3
T2
T1
E3
E2
E1

6. Taxonomy of Innovation
Innovation
Type
Product
Process/
methods
Magnitude
of impact
Drastic
Non-
drastic

7. 7
Taxonomy of Innovations
By type: (i) Product Innovation; (ii) Process Innovations
– Product Innovations refer to the creation of new goods
and/or new services, e.g., DVD’s, PDA’s, and cellular
phones
– Process Innovations refer to the development of new
technologies for producing goods or new ways of
delivering services, e.g., robotics and CAD/CAM technology
We mainly focus on process innovations but the lines
of distinction are often blurred—a new product can
be the means of implementing a new process

8. Process innovations have two further categories
By magnitude of the impact:
(i) Drastic Innovations; and (ii) Non-Drastic
Innovations
– Drastic innovations have such great cost savings
that they permit the innovator to price as an
unconstrained monopolist
– Non-drastic innovations give the innovator a
cost advantage but not unconstrained monopoly
power
Taxonomy of Innovations

9. 9
Drastic v. Non-Drastic Innovations
Suppose that demand is given by: P = 120 – Q and
all firms have constant marginal cost of c = $80
• Let one firm have innovation that lowers cost to
cM = $20
• This is a Drastic innovation. Why?
– Marginal Revenue curve for monopolist is:
MR = 120 – 2Q
– If cM = $20, optimal monopoly output is:QM = 50
and PM = $70
– Innovator can charge optimal monopoly price
$70 and still undercut rivals whose unit cost is
$80

10. • If cost fell only to $60, the innovation is Non-drastic
– Marginal Revenue curve is: MR = 120 – 2Q
– Optimal Monopoly output and price: QM = 30;
PM = $90
– However, innovator cannot charge $90 because
rivals have unit cost of $80 and could under price it
– Innovator cannot act as an unconstrained
monopolist
– Best innovator can do is to set price of $80 (or just
under) and supply all 40 units demanded.
Drastic v. Non-Drastic Innovations

11. 11
Drastic v. Non-Drastic Innovations
Innovation is drastic if monopoly output QM at MR = new marginal
c’ exceeds the competitive output QC at old marginal cost c
$/unit = p
Quantity
c
QC
c’
QM
Demand
$/unit = p
c
PM
QC
QM
Demand
c’
PM
Drastic Innovation: QM > QC so
innovator can charge
monopoly price PM without
constraint
NonDrastic Innovation: QM < QC so
innovator cannot charge
monopoly price PM because rivals
can undercut that price
MR
Quantity
MR

12. Innovation and Market Structure
• Schumpeter (1883 – 1950) is a leading figure in
this topic. He postulates that:
– Perfect competition was not an efficient market
structure for creating incentives for innovation.
Rather, it is the lure of a monopoly position what
creates the strongest incentive to innovate
– Concentrated industries do more innovation of
new goods/services, thus, are more dynamically
efficient, than competitively structured industries
– Large firms do more innovation than small firms

13. Innovation and Market Structure
• Does market power favor or disfavor the introduction
of innovation?
• Arrow (1962) confronted this question. He questions
the social value of an innovation.
• Arrow’s (1962) analysis
– Innovative activity is likely to be too little because
innovators consider only profit that th e
innovation brings and not the additional
consumer surplus
– Monopoly provides less incentive to innovate than
competitive industry because of the Replacement
Effect

14. 14
Innovation and Market Structure
• Assume demand is: P = 120 – Q; MC= $80. At
competitive market (P = MC) Q is initially 40.
Innovator lowers cost to $60 and can sell all 40
units at P = $80.
• Profit Gain is $800–Less than Social Gain $1000
$/unit
Quantity
40 60
80
60
120
B
A
Initial Surplus is Yellow
Triangle--Social Gains from
Innovation are Areas A ($800)
and B ($200)
But Innovator Only Considers
Profit Area A ($800)
120

15. 15
Innovation and Market Structure
• Now consider innovation when market structure is monopoly
– Initially, the monopolist produces where MC = MR = $80 at
Q = 20 and P = $100, and earns profit (Area C) of $400
– Innovation allows monopolist to produce where MC = MR =
$60 at Q = 30 and P = $90 and earn profit of $900
– But this is a gain of only $700 over initial profit due to
Replacement Effect—new profits destroy old profits
$/unit
Quantity
90
120
100
80
60
C
20 60 120
A
30
MR Demand
Monopolist Initially Earns
Profit C—With Innovation it
Earns Profit A—Net Profit
Gain is Area A – Area C
Which is Less than the Gain
to a Competitive Firm

16. Innovation and Competition
• Schumpeter’s idea or Arrow’s analysis ?
• Dasgupta and Stiglitz (1980) attempts to provide
evidence. By employing model of Cournot competition
they came up with
(x* = optimal RnD level of each firm; n* = equilibrium number of
firms; ɳ = elasticity of demand)
• Industry’s RnD efforts decline as n* rise i.e. as industry
becomes less concentrated  fairly strong theoretical
support for Schumpeter’s hypothesis
 



*
1
*
*
*
*
n
Q
Q
P
x
n
Industry RnD as Share of Sales

17. 17
Innovation and Competition
• But empirical support for Schumpeterian view is mixed
– Need to control for science-based sectors (e.g., chemicals,
pharmaceuticals, and electronics) and non-technology based
sectors (e.g., restaurants and hair stylists)—RnD much more
likely in science-based sectors regardless of firm size
– Need also to distinguish between RnD expenditures and true
innovations. Common finding [e.g., Cohen and Klepper
(1996)], is that large firms do somewhat more RnD but
achieve less real innovative breakthroughs—e.g., Apple
produced the first PC
– Market structure is endogenous. Innovations might create
industry giants (e.g., Alcoa) not the other way around.

18. 18
Innovation and Spillovers
• Technological break-through by one firm often “spill
over” to other firms
– Spillover is unlikely to be complete but likely to arise to
some extent
– Dasgupta-Stiglitz try to model this by incorporating its
own and its rival’s RnD spending on each firm’s cost
function
• In this setting, response of firm 1’s RnD to firm 2’s RnD
depends on size of spillover term .
– When  is small, RnD expenditures are strategic
substitutes—the more firm 1 does the less firm 2 will do
– When  is large, RnD expenditures are strategic
complements—the more firm 1 does the more firm 2
will do

19. 19
Innovation and Spillovers
• However, determination of whether RnD efforts are strategic
substitutes or strategic complements is not sufficient to
determine what happens when there are spillovers
– Let Demand be given by: P = A – BQ
– Let ci = c – xi – xj; i = 1,2
– Each firm now chooses both production qi and research
intensity xi
– To make things simple, suppose that A = 100, B = 2; and that
firms have to choose between setting x at either 7.5 (low) or
10 (high)
• Now consider two cases
– First case: Low Spillovers;  = 0.25
– Second case: High Spillovers;  = 0.75

20. 20
Innovation and Spillovers
The Pay-Off Matrix for  = 0.25
Firm 1
Firm 2
Low Research
Intensity
High Research
Intensity
$107.31, $107.31
Low Research
Intensity
High Research
Intensity
$100.54, $110.50
$110.50, $100.54 $103.13, $103.13
Nash Equilibrium is for both firms to
choose the high level of research
intensity (x = 10). Why? When degree
of spillovers  is small, firm know that
if its rival can do RnD knowing that it
will get most of the benefits. Since this
would advantage the rival, each firm
tries to avoid being left behind by
doing lots of RnD

21. Innovation and Spillovers
21
The Pay-Off Matrix for  = 0.75
Firm 1
Firm 2
Low Research
Intensity
High Research
Intensity
$128.67, $128.671,
Low Research
Intensity
High Research
Intensity
$136.13, $125.78
$125.78, $136.13 $133.68, $133.68
Nash Equilibrium is for both firms to
choose the low level of research intensity
(x = 7.5). Why? When degree of
spillovers  is large, firm knows that it
will benefit from technical advance of its
rival even if it doesn’t do any RnD itself.
So, each firm tries to free-ride off its rival
and each does little RnD
MORAL of the story: the Outcome of non-cooperative RnD spending
(x) depends critically on the extent of spillovers (β).

22. 22
Spillovers and Cooperative RnD
• What if RnD spending is cooperative?
• RnD cooperation can take two forms:
– 1. Do RnD independently but choose x1 and x2 jointly to
maximize combined profits, given competition in product
market is maintained.
– 2. Do RnD together as one firm, (Research Joint Venture).
That is, effectively operate as though the degree of spillovers
is  = 1, again though, continue to maintain product market
competition.
• The two types have very different implications.

23. 23
Spillovers and Cooperative RnD
• Consider first the case of coordinated but not centralized
RnD using our generalized demand and cost equations
– Total RnD spending now rises unambiguously as  increases.
– To see this note that given our earlier demand and cost
assumptions, and given the fact that x1 and x2 are chosen to
maximize joint profits, the optimal values for x1 and x2 are:
  
 2
2
1
1
2
9
1
2









c
A
x
x
– This is unambiguously increasing in  but this is a good news/bad
news story.
– The good news is that for the high spillover case ( >1), the free-
riding problem is no longer an issue and firms now do more RnD
– The bad news is that for the low spillover case ( < 1), there is no
longer a fear of being left behind by one’s rival. So in this case firms
do less RnD which means costs (and consumer prices) are higher.

24. 24
Spillovers and Cooperative RnD
• What about a Research Joint Venture?
– As noted, this effectively changes  to 1.
– For our general demand and cost equations, it can be shown that:
– This is clearly more RnD than occurred with simple coordination for any
given value of 
– As a result, it leads to lower costs and more output to the benefit of
consumers
– Profits are also higher. Thus, in the presence of spillovers, Research Joint
Ventures are unambiguously beneficial.
– The only trick is to make sure that cooperation is limited to research and
does not spill over to other dimensions of competition
 
8
9
4
2
1




B
c
A
x
x
 
8
9
3
2
1




B
c
A
q
q

25. Government and R&D Race
• Strategic Trade Policy (Krugman 1986) – government
enhance its international strategic position of the firms in
their countries by subsidizing their R&D
• Profit Boeing v. Airbus with no Government Intervention
Airbus
Produce No Produce
Boeing
Produce -10 -10 50 0
No Produce 0 50 0 0
• Nash Eq. = (Produce, No Produce) & (No Produce, Produce)

26. • Now suppose EU provide subsidy for Airbus as much as
€15 for the development of megacarrier.
• Nash Eq. unique, Airbus – Boeing (Produce, No Produce)
• Thus, by subsidizing R&D, Airbus can secure world
dominance of megacarrier.
Government and R&D Race
Airbus
Produce No Produce
Boeing
Produce -10 5 50 0
No Produce 0 65 0 0

27. Thank you