1. ASYMMETRIC INFORMATION IN
R&D FOR PHARAMACUETICALS
By:-
KRITIKA GUPTA (34198)
PARTH YADAV (14266)
SANCHI VAHAL (10303)

2. By:
Kritika Gupta
Parth Yadav
Sanchi Vahal
ASYMMETRIC INFORMATION IN R&D FOR PHARAMACUETICALS
INTRODUCTION
Infectious diseases have been a major cause of death among people across countries.
They impose huge burden on the society. Lack of life saving essential medicines for the
neglected infectious diseases is one of the major reasons leading to large-scale public
health tragedy. The failure to use existing tools, insufficient knowledge of the disease
and inadequate or nonexistent tools are major reasons that intensify the burden. Despite
the ever increasing burden that these diseases pose on the society, the development of
specific drugs has almost been nonexistent. Pharmaceutical industry plays a crucial role
in improving the lives of people by developing new medicines, vaccines and
undertaking research. It is often characterized as a technology and science driven sector
where R& D develops new products and then hands over them to the government.
While the basic research takes place in the university or government laboratories, drug
development is done almost exclusively by the pharmaceutical industry (“pharma”).
Despite the progress made in both the basic knowledge of many infectious diseases and
towards the process of drug discovery and development, the past two and a half decades
have seen pharma develop only few new drugs for the treatment of infectious diseases
responsible for millions of deaths annually. Only 10% of expenditure on health
research is made on such diseases that account for 90% of the global burden of disease.
Existing treatments for killer infectious diseases are increasingly ineffective due to poor
diagnostic options. Despite challenging conditions the industry has been successful in
bringing numerous health benefits to the society. Lack of scientific knowledge is not the
major barrier to drug development, nor does the gap lie with technology, which has
greatly benefited from recent advances. Policy issues seem to be the main obstacle to
the translation of this knowledge into actual benefit for patients. The incentives for
pharmaceutical companies to invest in R&D of certain rare and often neglected
infectious diseases are low. According to “Acemoglu and Lin” pharmaceutical R&D is
directed towards profitable markets. The market for rare diseases is very small and thus

3. the expected returns from investing in R&D of medicines for such diseases is quite low
and insufficient to cover the cost.
A recent study by the Drugs for Neglected Diseases working and the Harvard School of
Public Health questioned the world’s top 20 pharmaceutical companies on their
research and development activities for malaria, tuberculosis, African trypanosomiasis,
Chagas’ disease, and leishmaniasis
. 11 companies responded, representing 29% of the worldwide pharmaceutical market
for 2002. Of these companies, seven reported spending less than 1% of their research
and development budget over the previous fiscal year on any of the five diseases.
(Drug development for neglected diseases: a deficient market and a public-health policy
failure
Patrice Trouiller, Piero Olliaro, Els Torreele, James Orbinski, Richard Laing, Nathan
Ford)
What is not realized is the difference between private and social returns. Even though
private expected benefits from such an investment are low, its social returns are
substantial. Thus there is a need to encourage R&D in such cases. Most of the
investment in the development of the drugs has been from the public sector. Public
spending of funds in the OECD countries has been around $239 per head per annum.
Most developing countries on the other hand spend less than $20 per year and per
annum. To deal with this, policymakers have come up with various policies, which
make these kinds of R&Ds more profitable for the firms to carry out. These policies can
be broadly characterized as push strategies and pull strategies. Basic mechanism of a
push program is to subsidize research inputs. They take the form of grants, tax credits
on R&D. On the other hand, under a pull program there is reward for success that is
given in addition to the private market value of the invention. They take the form of
prize, advance purchase commitments, orphan drugs, and patent buyouts.
OBJECTIVE
This study aims to analyze the problem of asymmetric information faced by the
government that occurs under a push strategy when it gives grants to the pharmaceutical
firms to promote R&D for development of drugs and vaccines for neglected infectious
diseases. The paper also aims to analyze the effectiveness of Pull strategy suggested as
possible solution by many scholars to overcome the problem of moral hazard.

4. STATEMENT OF PURPOSE
A major question that arises for the policy makers is, “is the push mechanism the most
effective way to induce the research firm to undertake R&D for such projects?” For
political reasons, the government prefers a push strategy, under which funds are
provided to the firm for the research irrespective the outcome. Push strategies often
gives the firms an incentive to deviate the funds provided by the government to other,
more profitable projects or future assignment. This creates an asymmetry of information
between the two parties. The paper evaluates the problem of moral hazard created by
the hidden actions of the firm and tries to analyze the effectiveness of Pull strategy
suggested as a solution to this problem.
PUSH PROGRMMES
 Under a push program the reward payments are not linked to the success or
failure of the research project. The researcher is awarded independent of the
outcome; the grants are given even before starting of the project. Push programs
thus lower the cost of development. The funders must offer a premium to the
pharma companies undertaking the R&D to overcome their skepticism for the
project.
 Publically funded research institutions help promote basic research and provide
the non-patentable public scientific knowledge and help reduce the research cost
incurred by pharmaceutical industry. They lay a base for downstream discoveries
and thereby incentives to invest in potential research. Another route for the
government to incentivize the pharmaceutical firms is, Targeted R&D tax credit.
This program subsidizes the research inputs and hence the contributions are made
directly to the pharmaceutical companies. Although push programs are suitable
for funding basic research, but if the market for these drugs is not viable then the
firms will have no incentive to invest in them. This program has certain
limitations.
Considering the case of publically funded research institutes a major problem that
arises is they are subject to informational asymmetry between the researcher and
the government. The inability of the government to monitor the research
activities of the researcher leads to the problem of moral hazard. Another
problem in the program is of adverse selection. This arises because the
government ex ante does not know the quality of the research activities whereas
the payments are made independent of the outcomes of the research. In the case
of targeted R&D tax credit, a similar problem of asymmetric information arises

5. because the efforts of the research firm are private knowledge to the firm and
thus the firm can ask for more claims for the same research project.
In the following paper we try to analyze is this incentive mechanism effective in
mitigating the problem of underinvestment in R&D for medicine of neglected infectious
diseases. In the next section we lay out the general framework of the model and
encounter the fact that within a push program, the firms putting high effort benefits
from diverting funds to other research activities.
FRAMEWORK OF THE MODEL
The general scheme of the problem that we will be analyzing is shown in the following
diagram:-
Chronologically, in the first place, principle (government) decides what contract (funds)
to offer the agent. Following this the agent decides whether or not to accept the
relationship according to the terms established by the principle. Finally if the contract
has been accepted, the agent must decides the effort level that he most desires, given
the contract that he has designed. This is a free decision be the agent since his action
(effort – High or Low) is not a contracted variable. Hence, when the government
designs the contract it must bear in mind that after signing the contract, the agent will
choose his effort to maximizes his expected profit.
Governmet(Principle)
designs the contract
Agent (Research firm)
either Accepts or
Rejects the contract
If accepted then agent
decides whether to
induce high or low
effort.
Nature's Play
Outcomes and Payoff

6. METHODOLOGY
We analyze the issue using a principal agent model, where the researcher i.e. the agent
undertakes costly research activity in order to develop a new product and the funder or
the principal who values the innovation more than the researcher encourages R&D by
providing incentives to the researcher. To address this related question we use a fairly
general version of a standard moral hazard problem. This paper seeks to investigate the
problem of moral hazard created by asymmetry of information between the firm (agent)
and the government (principle). The government is unable to monitor how the firm uses
grant and is also unable to monitor the effort level it exerts. Using one variable, i.e.
grant, the government can control only one of the two decisions of the firm, effort or
diversion. We assume that the government tries to induce high effort using the contract
and leaves the decision of diversion of funds on the firms based on their expected
profits.
ASSUMPTIONS OF THE MODEL
1. Government is risk neutral and research firm is risk averse.
2. Firms are identical and the government knows their type.
3. Output “x” is verifiable and hence can be written in the contract but firms actions
namely, high or low effort and whether it is deviating or non deviating funds cannot be
observed.
The model depicts a moral hazard problem since we have assumed that the firms are of
identical types and the regulator knows the types.

7. In this spirit we depart from what other scholars have done in their research papers. In
their papers they have analyzed the same problem, but have introduced the problem of
both moral hazard and adverse selection. The problem of adverse selection arises
because the researcher is privately informed about its own ability.
DESCRIBING THE MODEL
The paper takes a look at a two-stage game. As stated in the assumptions, all the agents
are identical in every aspect. Therefore the principle randomly selects one agent and
gives out the grant. Now in the first stage of the game Government designs the contract
and Agent has to decide whether to accept it or not . And in the second stage the firm
chooses an effort level. After choosing an effort level, it’s nature’s play to decide if the
agents get success or failure. Considering the two cases we assume that the probability
of success (p1) when the firm decides to not divert the funds which is higher than the
probability of success (p) when the firm diverts the funds. A possible reason for this
could be, with higher funds one can purchase better technology or conduct better
research than possible with low funds, which in turn increases the probability of
success. From the above given condition we can also say that the probability of failure
in case of a diverting firm is higher than that in case of a non-diverting firm. Now this
game can be solved by maximizing the utility function of the government subject to the
participation constraint and incentive compatibility constraint of the firm. After
obtaining the result for the same, we evaluate the expected pay offs of the firm and will
compute which strategy is more profitable for the firm.
THE MODEL
Push strategy
Under a push strategy, the government gives grant to the firm before the outcome is
observed. The grants are thus not dependent of the output of R&D
Utility of the government (Ug) is thus a function of grant and the output
Ug =U (G, x)
Utility of the firm is also a function of the grant
Uf =U (G)
For a deviating type firm:

8. Consider the firm to be a deviating type, i.e. whenever the government or the regulatory
authority enters into a contract with this kind of firm, it deviates the funds provided by
the funder to other profitable projects. The government wants to induce high effort from
the firm. The government maximizes its utility subject to the participation constraint
and incentive compatibility constraint of the firm. In the following setup we consider
TUs
Fe as the total utility in case of success for a given level of effort and TUf
Fe as the
total utility in case of failure. Whereas Us
F is the utility received when the firm is
successful and Uf
F is the utility of the firm when it faces failure. Therefore total utility
can be described as the utility the firm gets from success/failure minus the disutility (v)
it gets from exerting the efforts (high/low).
TUf
Fe = Uf
F - v
v = {a if e= h (high effort); b if e =l (low effort)}
a & b are constants and a > b
“p” is the probability of getting success and “(1-p)” probability of getting failure. Also
“r” is taken as the probability for the firm to extend high effort and “(1-r)” as the
probability of firm to extend low effort.
PC: r [p TUs
Fh + (1-p) TUf
Fh ] >= U , where U is the reservation
utility
ICC: r [p TUs
Fh + (1-p) TUf
Fh + ] >= (1-r) [p TUs
Fl + (1-p) TUf
Fl ] ; where is
benefit from diversion of portion of grant to other profitable project.
Setting up the Lagrange function
L = Ug + λ [ U – r {p TUs
Fh + (1-p) TUf
Fh }+ ] + μ [(1-r){p TUs
Fl + (1-p) TUf
Fl
}+ - r {p TUs
Fh + (1-p) TUf
Fh} ]
First order conditions,
∂L/ ∂G =0
 Ug’ λ [ -r{ p ’s
F + (1-p) ’f
F }] + μ[ (1-r){ p ’s
F + (1-p) ’f
F} – r{ p ’s
F
+ (1-p) ’f
F}]=0

9.  Let ’s
F = i and ’f
F =j
 Ug’ = λ r p i + λ(1-p) j – μ(1-r) p i – μ(1-r)(1-p) j + μ r p i + μ r (1-p) j
 = i[λ r p + μ(1-r) p + μ r p ] + j[λ r (1-p) + μ(1-r)(1-p) + μ r (1-p)]
 = i p [ λ r – μ (1-r) + μ r] + j (1-p) [λr – μ (1-r) + μ r]
 ’g / {i p + j(1-p)} = λ r - μ(1-r) + μ r
 ’g / r{i p + j(1-p)} = λ + 2 μ – μ/r
 ’g / r{i p + j(1-p)} = λ + μ{ 2- 1/r}
 ’g / r{ i p + j(1-p)} = λ + μ { 1- (1-r) p / r p}
 ’g / r{ ’s
F p ’f
F (1-p)} = λ + μ { 1- (1-r) p / r p}
It is easy to see from the equation that the agent’s effort varies in response to grant.
Thus in order to attain its objective to induce high effort the government has to pay a
high grant. The grant will be greater, the smaller the likelihood ratio, where the
likelihood ratio is given by
( )
It indicates the precision with which the result x depends on the effort level
The smaller the likelihood ratio, greater is ph
with respect to pl
. So the signal that the
effort supplied was eh
is stronger. Therefore grant must be higher if the government
needs the research firm to exert high effort.
From the results derived above, it is clear that under a push strategy, firm is better off in
deviating funds than not deviating as their expected profits are greater under diversion

10. than under non diversion.
A similar analysis can be done for a non-deviating firm:
PC: r [p TUs
Fh + (1-p) TUf
Fh ] >= U
ICC: r [p TUs
Fh + (1-p) TUf
Fh ] >= (1-r) [p TUs
Fl + (1-p) TUf
Fl ]
Setting up the Lagrange function
L = Ug + λ [ U – r {p TUs
Fh + (1-p) TUf
Fh }] + μ [(1-r){p TUs
Fl + (1-p) TUf
Fl } - r
{p TUs
Fh + (1-p) TUf
Fh}]
and we arrive at a similar result:
’g / r{ ’s
F p1 ’f
F (1-p1)} = λ + μ { 1- (1-r) p1 / r p1}
Given that in both cases, the firms will supply high effort, we now Calculate expected
profit that a firm obtains from deviating and non deviating the funds to other profitable
projects:
Expected profits from deviation:
π d = r p Us
F + r (1-p) Uf
F - I
Expected profit from non deviation:
π nd = r p1 Us
F + r (1-p1) Uf
F -II
 r p Us
F + r (1-p) Uf
F < r p1 Us
F + r (1-p1) Uf
F
 ( 1-p -1+ p1) Uf
F < ( p1 – p) Us
F
 ( p1 - p) Uf
F < ( p1 - p) Uf
F ;which holds since we have assumed P1>P
 Us
F > Uf
F ; assuming to be not too large
Therefore, from above result we can say that expected profit for a research firm from
diverting the funds is higher than the expected profit from not deviating. Hence the firm
will deviate the funds.

11. RESULTS
By working out the equations of the above problem, we infer that it is always more
beneficial for the firms to divert the government funding to other projects as they obtain
higher expected profits. Due to the lack of a proper monitoring mechanism the
government is not able to achieve the desired results.
POLICY IMPLICATIONS
A more useful policy from social point of view is the one, which induces firm not to
divert funds to other profitable research projects i.e. it, should reward the output instead
of subsidizing the inputs.
Pull program
Schemes under pull program induce the researcher to focus efforts on the development
of the desired product because payments are received only for a successful research.
This incentivizes the researcher to look for a potentially successful project. The aim of
the government is to make the drug or vaccine available at affordable prices to the
consumer, avoiding the situation of monopoly pricing. Pull programs could take the
form of a prize, an advance purchase commitments, and a patent buyouts and so on.
 Advanced purchase commitment: this refers to a contract under which a
government agency commits to purchase a specified quantity of drug or vaccine
at a specified price once research has led to successful development of the
particular drug. Such a program is beneficial for the funder as well as for the
society since it promotes successful research. It is a cost effective mechanism
mimicking market incentives.
 Prize: under this scheme also payment is made on the successful completion of
the project, thus not subject to moral hazard problem thereby reducing incentive
to shift research to other projects. Apart from the successful development of the
vaccine, the prize is received contingent on fulfillment of certain other
requirements.

12.  Patent buyouts: under this scheme, patents are purchased by the government at a
price higher than the private value of the researcher to promote R&D activities.
This price is determined using auctions. Most of the patents purchased by the
patent authority are made available to the public. Once the innovation is made
public, inefficiency losses due to monopoly pricing is eliminated.
Under a pull strategy, as the prize will be awarded to the firm only if there is a success,
thus the utility of the firm if it fails to develop the drug/vaccine is zero. It receives a
positive utility only if it is successful in developing the drug.
The aim of the government is to induce high effort by the firm. It maximizes its utility
subject to the participation constraint and the incentive compatibility constraint of the
firm.
Here we are assuming that firm either,
a) Has funds to invest in R&D, given that a certain proportion of the profits are invested
in R&D, or
b) The firm borrows from a bank to undertake R&D for a particular drug or the
government will later reward vaccine, successful invention of which.
For a Deviating type firm:
PC: r [p TUs
Fh + (1-p) TUf
F ] >= U
ICC: r [p TUs
Fh + (1-p) Uf
Fh ] >= (1-r) [p TUs
Fl + (1-p) TUf
Fl ]
Setting up the Lagrange function
L = Ug + λ [ U – r {p TUs
Fh + (1-p) TUf
Fh}+ ] + μ [(1-r){p TUs
Fl + (1-p) TUf
Fl}+
- r {p TUs
Fh + (1-p) TUf
Fh}+ ]
As TUf
Fe = 0 (because when the firm fails to develop the drug, it doesn’t get the grant
and as we don’t take negative utility hence its equal to zero)
L = Ug + λ [ U – r {p Us
F + (1-p) *0} ] + μ [(1-r){p Us
F + (1-p) *0} - r {p Us
F
+ (1-p) *0} ]
FOC’s:-
∂L/ ∂G =0

13.  Ug’ λ [ -r{ p ’s
F }] + μ[ (1-r){ p ’s
F } – r{ p ’s
F }]=0
Using the similar notation; i = ’s
F
 Ug’ = λ r p i – μ(1-r) p i + μ r p i
 = i p [ λ r – μ (1-r) + μ r]
 ’g / r i p = λ + μ{ 2- 1/r}
 ’g / r.i.p = λ + μ { 1- (1-r) p / r p}
 ’g / r. ’s
F.p = λ + μ { 1- (1-r) p / r p}
A similar analysis can be done for a non-diverting firm :
PC: r [p TUs
Fh + (1-p) TUf
F ] >= U
ICC: r [p TUs
Fh + (1-p) Uf
Fh ] >= (1-r) [p TUs
Fl + (1-p) TUf
Fl ]
Setting up the Lagrange function
L = Ug λ [ U – r {p TUs
Fh + (1-p) TUf
Fh}] μ [(1-r){p TUs
Fl + (1-p) TUf
Fl} - r {p
TUs
Fh + (1-p) TUf
Fh}]
and we get the same results:
 ’g / r. ’s
F.p1 = λ + μ { 1- (1-r) p1 / r p1}
We can see that the firm will supply high effort irrespective of whether or not it diverts
the funds. Now we look at the expected profits that the firm may receive from diverting
the funds and not diverting the funds.
Expected profits from diverting the funds:
π d = r p Us
F - III

14. Expected profit from not deviating:
π nd = r p1 Us
F -IV
Here result is ambiguous. Expected profit will be greater in non deviating case only
for a small ̅.
Result: Pull Strategy is not necessarily better than a push strategy to induce non diversion of
funds. Thus even though a pull strategy is theoretically better than a push strategy, this
need not necessarily be the case. One needs to look for other alternatives or a
combination of both strategies.
CONCLUSION
From above it is clear, Push strategy, which is usually adopted by the government,
come with a set of its own drawbacks. Push strategy induces the firms to divert the
resources in lieu of maximizing their own private benefits and not the benefit of the
society. This paper suggests that the use of pull strategy, as theoretically suggested in
many scholarly articles as strategy which optimizes the efforts of the firm and will give
no or very little incentives to the firms to divert the funds allocated to a particular R&D
of a drug/ vaccine may not be better than a push strategy. Therefore by adopting the
pull strategies the government may not do away with the problem of asymmetry of
information created by the hidden actions of the firm and may not get the output more
efficiently and promptly. Hence the paper provides a brief overview on how the pull
strategy may not work for better provisions of the drugs and vaccines.
LIMITATIONS
This paper takes some simplifying assumptions, which may not be applicable in the real
world. The paper assumes that all the firms are identical and of a similar type and the
type is known to the government, whereas in the real world the government might not
be able to segregate between efficient and non-efficient type firms. By relaxing this
assumption we can incorporate the problem of adverse selection in the model.
Pull mechanism are an improvement over push mechanisms in promoting R&D and
thereby eliminates the problem of moral hazard. However, schemes under this program
come with their own set of limitations. nder APC’S and PRIZE, once investment is
made by the researcher, the government or the regulatory authority has incentives to

15. deviate from its commitment made earlier regarding the purchase price,. The incentive
for the researcher/firm to invest in costly projects is thus reduced. Another problem
with the same issue is that the reward could be under or overpriced, as output is variable
and can’t be determined beforehand. Patent buyouts are subject to limitations of second
price bid auction.
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 Monique F. Mrazek, Elias Mossialos, (2002),” Stimulating pharmaceutical
research and development for neglected diseases”, Health Policy 64 (2003), pp:
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 David Henry, Joel Lexchin, (2002), “The pharmaceutical industry as a medicines
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 Frank Mueller-Langer, (2011), “Neglected infectious diseases: are push and pull
incentive mechanisms suitable for promoting research?” MPRA Paper No.
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