Human Capital and Innovation - Chris Parrish Dissertation Summary
DISSERTATION QUESTION
What role does human capital accumulation have in innovation? For example, are there
informational advantages for firms where venture capital (VC) is provided by VCs specializing in
the firm's industry or product type ? Is there a build-up of human capital at small/nascent firms
associated with "knowledgeable" VC companies, and are those businesses more likely to have
greater commercialization success, including initial public offerings?
EMPIRICAL APPROACH
The dissertation seeks to further the literature on the relationship between human capital and
innovation. Specifically, there are three dimensions of firm innovation that may be analyzed:
1.
likelihood of commercialization of a technology
2.
likelihood of receiving external funding to support the commercialization of the
technology (e.g., venture capital), and
3.
whether an initial public offering resulted from the commercialization of the technology
The foundation for this analysis is the role of human capital (e.g., education and/or experience)
in facilitating success in the development of technology. The expectation is to test this
relationship econometrically using data related to the Small Business Innovation Research
(SBIR) program. Those data are readily available for more than 1800 technology-based projects
undertaken in U.S. firms from 1992 through 2001. The form of the dissertation is expected to
be a modified unified format that includes a literature review related to human capital
formation and innovation, which motivates three distinct empirical analyses.
PERSONAL MOTIVATION FOR TOPIC
Experience as entrepreneur and in structuring financing arrangements has led to a keen
interest in evaluating the relationship between risk taking, skill set development, financing, and
product innovation.
Christopher (Chris) L Parrish, CFP®
9903 Liberty Bell Court Charlotte, NC 28269
p: 704-564-3026 email: chris@parrishhouse.net
WORK EXPERIENCE
Bank of America Merrill Lynch – 2010-2013
Senior Vice President – Risk Management
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Operational Risk Manager over Corporate Investments, Treasury, Private Equity and Corporate Strategy.
Identify and manage operational risks, including key process, systems, people and external risks.
Continuously challenge businesses and drive change to achieve operational risk management excellence.
Review and audit the Credit and Market Risk functions within the businesses to identify emerging risks as well as project
managing targeted reviews, including VaR methodology and enterprise stress testing.
ReSupply Industries, Inc. – 2009-2013
Executive Director
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Established 501(c)3 not-for-profit corporation to help local non-profits reduce operating costs.
ReSupply diverts office supplies that are bound for landfills to non-profits, free of charge.
Maintain relationships with 50+ non-profit organizations and numerous individual and corporate donors.
Execute business plan, including Infrastructure, Development, Outreach and Website.
Parrish Wealth Planning, LLC – 2008-2010
Founder, Owner and Wealth Manager
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Founded and managed an independent Registered Investment Advisor (RIA), which provided fee-only financial planning,
customized asset allocation and investment management services to clients.
Sourced assets through referrals and managed investments based on individualized investment policies.
Performed all duties related to maintaining RIA status, including compliance and regulatory requirements, setting
policies and procedures and record keeping.
Columbia Management Advisors – 2004-2008
Director – Senior Research Analyst
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Performed buy-side fundamental credit research, including due diligence, financial analysis, cash flow modeling and
relative value analysis to support buy/sell recommendations.
Published research to traders, portfolio managers, senior management, clients and fund board of directors.
Created comprehensive database of financial and asset performance information to supplement research.
Six Sigma Green Belt – project resulted in a US patent for a new Credit Research Measurement process.
Banc of America Securities – 1996-2004
Principal – Global Markets
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Senior Risk Manager covering credit risk within the Securitization Finance and Structured Rates units.
Reviewed, approved and risk managed structured loans and rates provided to bank clients.
Preceding role of Deal Team Leader in Securitization Finance business.
As Deal Team Leader, performed all aspects of loan origination, including due diligence, negotiating terms, structuring
credit support and managing the documentation process and monitored performance.
Began bank as a quantitative modeler using SAS to build loss forecasting models in an effort to develop a framework to
manage losses within the asset securitizations and consumer product lines.
Wells Fargo Securities – 1994-1995
Junior Research Analyst – Fixed Income
Moody’s Investors Service – 1992-1994
Business Analyst – Financial Services
EDUCATION & CERTIFICATIONS
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Master of Science in Economics, University of North Carolina at Charlotte (1997)
Bachelor of Science in Business – Economics, Appalachian State University (1992)
CERTIFIED FINANCIAL PLANNER™
Six Sigma Greenbelt
Inventor, US Patent 7,720,753 B1 - Quantifying the Output of Credit Research Systems
Human Capital and Innovation - Chris Parrish Dissertation DRAFT
INTRODUCTION
Firms that are in the process of researching or developing a new product may find funding a
significant problem and impediment to success. In many cases, the cost of research and
development (R&D) can become so large that a firm may simply run out of money and
resources before it can bring the product to the point of realizing income or commercialization.
Even if the product is thought to have material commercialization potential, lack of access to
continued funding can preclude any meaningful outcome from R&D.
Given the high cost of R&D, firms are left with a minimal set of choices in determining how to
fund their product R&D. Additionally, funding sources are evolving due to changing market
conditions, changes in funding infrastructure, and government support. Broad categories of
funding R&D include traditional bank and alternative lending, peer-to-business funding, private
equity (including venture capital), and public-private partnerships, such as the Small Business
Innovation Research (SBIR) program.
In evaluating the funding options of their firms, managers must consider the costs and benefits
associated with each funding option. A key consideration for firms when seeking funding is the
benefit from advice, guidance and counseling available when engaging a potential lender or
investor. In particular, venture capital funding, which is generally an arrangement where a
venture capitalist provides a certain amount of money in return for an ownership interest in the
firm, can result in an infusion of business knowledge from the venture's principals. The
incremental knowledge that a firm obtains through a venture capital arrangement may increase
the overall human capital of the firm and the chances of product commercialization. A VC's
participation in a firm could also be a positive signal of future success as VCs draw upon their
own human capital to sort potential investments and invest in firms where they expect the
highest returns.
A theoretical model is developed within the paper to illustrate this transfer and the choices that
a firm faces with respect to venture capital participation. There is an assumed benefit to
production (commercialization) from knowledge transferred from venture capital firms and that
both firms and their venture capital investors will seek to find an equilibrium that maximizes
their respective utilities.
The remainder of the paper is organized as follows: Section 1 provides a literature review on
the intersection of human capital and innovation, how human capital may manifest itself within
funding options available for firms with nascent products, and initial public offering activity of
entrepreneurial firms; Section 2 outlines a theoretical model of the choices a firm faces in
funding R&D with a particular focus on the potential transfer of knowledge from venture
capitalists and accumulation of human capital at the firm; and Section 3 lays out the empirical
models to analyze the relationship between the build-up of human capital and
commercialization success.
SECTION 1: LITERATURE REVIEW
HUMAN CAPITAL AND INNOVATION
Human capital is a broad term that encompasses the cumulative amount of "knowhow"
associated with and individual (or group/unit) which is generally acquired through education,
experience, training, mentoring or some other source.
Innovation is generally considered the commercialization of a technology or some other new
knowledge.
[literature review to be completed with focus on intersection of human capital and innovation]
FIRM FUNDING OPTIONS AND VENTURE CAPITAL
While not exhaustive, there are four broad categories of funding options for firms to fund their
R&D: traditional bank and alternative lending, peer-to-business funding, private equity and
public-private partnerships. Other potential sources include other cash on hand, grants or
awards from foundations or other non-profits, and tax incentives, but since firms are generally
seeking to obtain longer-term, sustainable sources of funding for R&D and may not have profits
from which tax incentives are useful, the discussion is generally limited to the aforementioned
list of funding options.
A. Traditional Bank and Alternative Lending
While securing a loan from a local bank to fund a start-up company's new product is difficult,
the traditional bank lending route may be feasible for those firms who have a track record in
their business and are seeking to finance their next product. Small Business Administration
loans or asset-based loans are potential options under certain circumstances, but for the
majority of small firms seeking to fund R&D for a new or significant product, bank lending may
not be the best alternative. Further, obtaining loans from a third party is not likely to provide
meaningful additional human capital as small business lenders are not typically industry
experts.
However, there are gaps in the lending business that have drawn interest from alternative
lending firms. Firms like OnDeck, which provides small business lending, and Opportunity Fund,
a non-profit microlender, have been born out of the notion that small business lending is
underserved. Unfortunately, loans from these types of alternative lenders may not be available
on a large enough scale and at reasonable enough interest rates to justify the hassle and
expense of assembling multiple sources to fund R&D. Additionally, similar to traditional bank
lending, the firms seeking R&D funding are likely not generating any incremental human capital
benefit from engaging with alternative lenders.
B. Peer-to-Business Funding
Peer-to-business funding is a colloquial term to describe financial transactions between entities
(usually individuals) willing and able to invest or lend and those businesses seeking funds. This
sector is also generally referred to as "crowdfunding" or "crowdlending." Crowdfunding and
crowdlending are relatively new channels for businesses and provide an intriguing and
potentially significant source of capital for firms seeking to find relatively quick and easy
funding solutions.
With roots in raising money to support creative endeavors, crowdfunding has quickly evolved to
become a source of capital for innovative business prospects. The success of the firm Oculus
Rift, which was initially funded through Kickstarter and later acquired by Facebook, is widely
cited as an example of the power of crowdfunding (Profatilov 2014).
Furthering potential growth of small firm funding is the pending implementation of the
CROWDFUND Act section within the Jumpstart Our Business Startups (JOBS) Act of 2012.
Currently, the JOBS Act allows only investors of a certain net worth to acquire equity in
companies via crowdfunding. However, subject to further SEC review, the JOBS Act allows for
equity-based participation by the general public in "funding portal" channels, such as AngelList
or Crowdfunder. If implemented as written, firms can raise up to $1 million through this
method of solicitation and up to $50 million under a streamlined public issuance. Although the
rules are not yet final, the ability of firms to tap into significant capital directly from the general
public could be a transformative development that blurs the line between crowdfunding and
traditional venture capital.
According to Crowdnetic, a data aggregation source for the crowdfunding industry, the amount
of capital raised (measured in capital commitments) from 4Q14-4Q15 (5 quarters) is $482.5
million covering 5,122 offerings.
Source: Crowdnetic
Crowdlending is not a new concept, but the infrastructure to seek out lending options has
changed materially over the past few years. Companies such as Lending Club and Prosper
provide platforms to link borrowers with lenders. While initially structured for peer-to-peer
lending, the platforms have expanded to offer business loans. For those businesses seeking a
loan through this channel, these intermediaries provide a mechanism to allow lenders to
customize a loan portfolio by reviewing terms of the borrower, and businesses seeking a loan
may be able to appeal to a wider pool of lenders. From the borrower's perspective, there is
one lender to which payments are made, which creates a seamless transaction. From the
lender's perspective, they are issued registered notes by the issuing entity and payments are
deposited directly into their online account.
While crowdlending may grow to be a more formidable competitor to other types of lending
options in the future, the amounts generally available through this channel are not likely at a
level necessary to fund R&D.
Peer-to-business funding platforms are clearly growing and may become a truly important
source of R&D funding. As it stands today, however, crowdfunding/crowdlending are not
natural options for firms seeking longer-term financing. As well, it is unlikely this particular
channel would yield any increase in human capital by transacting. Nonetheless, this channel is
an important area to explore in the future to evaluate its potential impact on innovation and
commercialization.
C. PRIVATE EQUITY
Private equity is a broad category of investing that includes, but is not limited to, full company
purchases (through debt, equity or a combination), angel investing and venture capital.
Generally, both angel investing and venture capital focus on purchases of equity in businesses
seeking to fund activities related to a new innovation or product. Angel investors, who may be
individuals or families, may have more flexibility in timing or repayment while venture
capitalists generally have specific investment goals and return expectations over a set period
time. Further, venture capitalists often look to the public stock market to monetize their
investments. With volume, this disciplined approach allows venture capital firms to potentially
acquire key industry expertise related to product development and commercialization. As such,
for firms seeking R&D funding, venture capital is an appealing source of both information and
capital.
Venture capital, which is generally funding provided to firms in exchange for some amount of
private equity ownership, has been a significant source of capital to firms where traditional
financing sources, such as public equity and debt-financing, are limited or not available. The
amount of available venture capital and the types of firm in which capital is deployed varies
considerably.
According to The MoneyTree™ Report by PricewaterhouseCoopers and the National Venture
Capital Association based on data from Thomson Reuters, the amount of venture capital
invested in 2014 was over $48 billion in 4,356 deals. While software is the clear leader in
venture capital funding, total investments in the biotechnology industry are the next largest.
Industry
Biotechnology
Business Products and Services
Computers and Peripherals
Consumer Products and
Services
Electronics/Instrumentation
Financial Services
Healthcare Services
Industrial/Energy
IT Services
Media and Entertainment
Medical Devices and Equipment
Networking and Equipment
Other
Retailing/Distribution
Semiconductors
Software
Telecommunications
Grand Total
2014
5,966,376,500
377,092,800
1,456,265,900
12%
1%
3%
2,230,140,400
694,643,700
1,068,473,400
360,187,000
2,406,730,600
3,259,005,500
5,747,918,500
2,661,741,400
467,742,700
6,150,000
789,905,300
727,936,000
19,803,561,000
324,715,700
48,348,586,400
5%
1%
2%
1%
5%
7%
12%
6%
1%
0%
2%
2%
41%
1%
100%
Source: PricewaterhouseCoopers/National Venture Capital Association MoneyTree™ Report, Data: Thomson Reuters
While recent venture capital investments have been the strongest since the early 2000's,
returns on venture capital are a mixed story. Cochrane (2005) found returns to vary
significantly given selection bias since it is common for venture capitalists to spread out their
risk among a portfolio of investments, due to overall high level of failures. Further, Gompers et
al. (2008) assert that investments can be influenced by several factors, such as venture capital
firm experience and IPO valuations, which creates a level of cyclicality with this type of funding
source.
It is precisely this type of selection by venture capital firms that can provide small firms with a
key informational advantage. It is very typical for venture capital firms to invest as well as
participate in the management of the firms in which they take an equity position (generally in
the form of a board position(s) and/or special consultant). Thus, start-up firms with venture
capital financing often find access to skilled individuals who may provide critical information
transfers to firms, thereby building start-up firms' overall human capital and potentially
increasing the likelihood of commercialization success.
Offsetting that advantage to some extent is the historically high failure rate of firms with
venture capital financing (vs. those with longer-term funding - Lerner 2002) as well as wide
variations in the rate of innovation. The potential for this outcome could have material
implications if policymakers hold a view that innovation is necessary to generate economic
growth. If there are uncertain returns in venture capital given the relatively high rate of
venture capital firm failures, then the natural question is whether venture capital financing
works for all parties.
D. PUBLIC-PRIVATE PARTNERSHIPS
There are multiple mechanisms to promote innovation and the acceleration of
commercialization by the federal government. To expand R&D research, the government can
support universities and research centers, use the tax code to stimulate private sector R&D
spending, and provide direct government funding in a private-public partnership arrangement.
One of the initial moves by the U.S. government to accelerate commercialization was passing
legislation (Bayh-Dole Act of 1980 and the Stevenson-Wydler Act of 1980) to promote the
movement of existing research and innovation into the private sector. Although this legislation
was aimed at universities and government agencies and not in direct support of private sector
R&D, it spurred the creation of Technology Transfer Offices across the U.S. university system
and National Laboratories, advancing the awareness and potential of financial incentives to
promote commercialization from the government. Empirically, analyses evaluating the
effectiveness of the legislation shows mixed results, however. Mowery et al. (2001), Mowery
and Sampat (2005), Jaffe et al. (1998), Jaffe and Lerner (2001) and Link et al. (2011), generally
find that while patenting and licensing activity increased after 1980, there is not clear evidence
of a correlation between passage of the legislation and knowledge transfer, which would
presumably lead to commercialization.
To expand private R&D, the government enacted the Research and Experimentation (R&E) Tax
Credit in 1981, which initially provided partial credits on incremental research and was later
expanded to accommodate smaller firms with no meaningful base of R&D. The motivation for
the credit is based on the theory that tax credits are market neutral (as companies can decide
whether or not to engage versus direct government funding that is more targeted and
potentially favors certain industries or technologies) and thus can provide an indiscriminate
incentive to potentially increase research investments. Bozeman and Link (1984) reviewed tax
incentives as policy tools for increasing R&D spending and found that tax incentives can be one
of several tools to stimulate spending, but it is not likely a viable singular tool. Additionally,
Tassey (2007) and Atkinson (2007) assert the structure and the implementation of any tax
credits can mute or distort any potential benefits. They both make arguments about the
efficacy of the R&E Tax Credit, and while they take somewhat opposing views of its current
impact, both suggest significant changes to the credit in order to increase private sector R&D
spending. Overall, tax credits are one tool available for private companies to fund their
research and product development, but they likely do not provide the key longer-term
sustainable funding necessary to bring a large scale project to commercialization.
The government has also been involved with supporting private sector advancement in R&D
through accommodative policy and direct financial support. Programs such as the National
Cooperative Research Act (NCRA) of 1984 (and further amended) and the American Technology
Preeminence Act of 1991 were implemented to relax certain legal restrictions around research
participation by private firms and provide direct funding for joint research ventures,
respectively. Link and Scott (2001) reviewed the impact of public/private partnerships and
showed that social returns were higher under the partnership than would have been otherwise.
These results imply it is possible for small firms that participate in strategic ventures and
partnerships to reap benefits not only for themselves but also can increase social rates of
return. While participating in research joint ventures can increase overall knowledge through
collaboration, there are risks of spillover effects which can diminish firm-specific benefits. In
the case of firms seeking R&D funding to support commercialization of a product, joint ventures
may not provide the same level of human capital accumulation as through direct support, such
as venture capital participation.
Incorporating the potential informational advantages of venture capital with public/private
partnerships is the Small Business Innovation Research (SBIR) program (and similar but smaller
Small Business Technology Transfer (STTR) program, which is focused on collaboration with
research institutions). As SBIR.gov notes, the SBIR program was developed in 1982 and is
designed to provide funding directly to firms unable to financially sustain themselves while
transitioning from idea development to product commercialization. Recognizing that research
intensive projects require longer-term funding to carry research across the "valley of death"
and into the commercialization stage, the government requires federal agencies with
extramural budgets in excess of $100 million to allocate 2.8% of their R&D budgets to SBIR
grants. Applicants apply to the federal agencies directly.
If awarded, SBIR has three distinct phases:
1. Phase I: develop the technical specifications and commercial viability of the project (up
to $150m for 1 year)
2. Phase II: further the development of the research and commercialization potential
(usually up to $1mm for 2 years)
3. Phase III: (unfunded) expects businesses to acquire additional funding (including venture
capital) to commercialize product(s) supported by SBIR
SBIR is available to U.S. small firms (<500 employees) where U.S. individuals own 51% or more
of the firm. SBIR also allows venture capital firms (through joint ventures) to own the
businesses seeking the award if the venture capital firm itself is majority-owned by individuals,
which is still a relatively stringent requirement. However, venture capital, hedge funds and
private equity firms are allowed to hold minority shares of business so long as they do not have
control of the award applicant. The Department of Health and Human Services/NIH is one of
the few participating agencies to fund businesses that are majority-owned by venture
capitalists, which makes it an interesting case study of the potential benefits of firms with
venture capital participation seeking SBIR funding.
There has been interest in determining the SBIR program's effectiveness. Link and Scott (2012)
and Qian and Haynes (2014) have each studied the SBIR, but since the focus of their analyses
related to employment growth and the promotion of entrepreneurship, respectively, there was
not a direct measurement of SBIR and commercialization. The difficulty in measuring its
effectiveness is a combination of developing rich enough data to evaluate the relationship
between funding and commercialization and the potential different definitions of success (or
lack thereof). Further, agencies providing the funding do not track the performance of those
businesses that were not given awards, which does not allow for a control group comparison.
ENTREPRENEURIAL IPOs
[literature review on initial public offerings of entrepreneurial firms]
SECTION 2: THEORETICAL MODEL
To evaluate the potential for marginal informational advantages obtained through engagement
with a venture capital firm specializing in industry- or product-specific investments, a
theoretical model of human capital accumulation through venture capital funding is developed
below.
Assume Firm S is a start-up firm that is in the process of developing product G. There is 1
venture capital firm (VC1) interested in investing in Firm S. It is assumed that if VC1 invests in
Firm S, they could transfer some portion of their specialized human capital to Firm S in order
increase production of G, potentially increasing their return on investment. The actual level of
knowledge transfer will be a function of VC1's ability and willingness to impart that knowledge
(𝜎) to Firm S as mentoring and advising by VC1 takes time and is costly.
Borrowing the principal/agent construct from Macho-Stadler and Perez-Castrillo (2001), Firm S
seeks to maximize their profit with a venture capital investment subject to VC1 participating. In
this sense, Firm S is the principal and is deciding whether or not to offer an equity contract to
VC1 based on the effort level exerted to transfer knowledge (i.e., incremental human capital) to
Firm S.
In a basic 1-period model, the following assumptions are asserted:
Firm S has the following utility function:
•
•
𝐹(𝐺 − 𝑐)
where 𝐺 is the monetary value of observable production and 𝑐 is a return to VC1
Firm S's objective is to obtain the greatest possible profit
The probability of any particular production output 𝐺𝑖 :
𝑝𝑖 (𝜎)
•
is due to a random component to production
•
•
and based on the effort 𝜎 exerted by VC1 to transfer knowledge to Firm S
•
and Firm S will dictate effort level consistent with profit objectives of the contract
under a base (perfect information) model, 𝜎 is verifiable by Firm S
The set of possible results 𝐺 = {𝑔1 , … , 𝑔𝑛 } follows a distribution such that ∑𝑛𝑖=1 𝑝𝑖 (𝜎) = 1
•
probability density function of results:
•
worst result out of distribution:
•
best result out of distribution:
𝑔
𝑔
VC1 has the following utility function:
•
𝑓(𝑔|𝜎)
𝑈(𝑐, 𝜎) = 𝑢(𝑐) − 𝑣(𝜎)
where total utility is positively affected by higher returns and negatively affected by
more effort to transfer knowledge
•
•
VC1 has a reservation utility value of 𝑈 which drives contract accept/reject decision
VC1 wants to maximize utility
Both Firm S and VC1 have concave utility functions (linear or diminishing marginal utility)
•
Concavity of utility functions allows for risk-neutral or risk-averse preferences
•
Assumes VC1's risk-aversion does not vary with the level of effort exerted
•
Conflicts of interest are inherent in model in a strict manner:
o Firm S cares about 𝑔 since their motives are profit driven; VC1 does not
o VC1 cares about effort (more effort lowers utility); Firm S does not
o However, the larger the effort, the better the results
The von Neumann-Morgenstern expected utility functions can be used to solve for the optimal
equity participation contract.
𝑛
𝐸𝑈(𝑔) = � 𝑝𝑖 (𝜎) ∗ 𝑢(𝑔𝑖 )
𝑖=1
An optimal return to VC1 is the function which maximizes the utility (profit) of Firm S subject to
VC1 accepting the offer to participate in the equity of Firm S that meets VC1's reservation
utility.
So the function would take the form:
𝑔
𝑚𝑎𝑥 𝐸𝑈(𝐹𝑖𝑟𝑚 𝑆) 𝑠. 𝑡. 𝐸𝑈(𝑉𝐶1) ≥ 𝑈
𝑔
𝑚𝑎𝑥 � 𝐹(𝑔𝑖 − 𝑐) ∗ 𝑓(𝑔𝑖 |𝜎) 𝑑𝑔 𝑠. 𝑡. � [𝑢(𝑐) − 𝑣(𝜎)] ∗ 𝑓(𝑔𝑖 |𝜎) 𝑑𝑔 ≥ 𝑈
𝑔
𝑔
Since the density function for the results is conditional on VC1s' efforts, 𝑣(𝜎) can be treated as
a constant and pulled out of the integration.
Also, Firm S decides upfront the level of effort of knowledge transfer it demands and provides a
return according to results. Thus, the returns to VC1 will be function of the result:
𝑔
𝑔
𝑚𝑎𝑥
� 𝐹(𝑔𝑖 − 𝑐(𝑔𝑖 )) ∗ 𝑓(𝑔𝑖 |𝜎) 𝑑𝑔 𝑠. 𝑡. � [𝑢(𝑐(𝑔𝑖 ))] ∗ 𝑓(𝑔𝑖 |𝜎) 𝑑𝑔 − 𝑣(𝜎) ≥ 𝑈
𝑐(𝑔𝑖 ) , 𝜎 𝑔
𝑔
Lagrangian:
𝑔
𝑔
ℒ
= � 𝐹(𝑔𝑖 − 𝑐(𝑔𝑖 )) ∗ 𝑓(𝑔𝑖 |𝜎) 𝑑𝑔 + 𝜆[ � [𝑢(𝑐(𝑔𝑖 ))] ∗ 𝑓(𝑔𝑖 |𝜎) 𝑑𝑔 − 𝑣(𝜎) − 𝑈 ]
𝑐(𝑔𝑖 ) , 𝜎
𝑔
𝑔
To calculate the optimal return for VC1, the objective function is differentiated with respect to
investor return 𝑐. However, each return is dependent on each level of output 𝑔, and each level
of output is based on a level of effort of knowledge transfer demanded, so there is a circular
issue. To resolve this, there is an assumed fixed level of optimal effort to transfer knowledge
noted as 𝜎 𝑜 .
Therefore, the Lagrangian will be differentiated with respect to 𝑐 𝑜 (𝑔𝑖 ). Since this is a partial
derivative of an integration of a function that includes the choice variable (itself a function), the
Chain Rule will be used.
𝜕ℒ
= −𝐹′�𝑔𝑖 − 𝑐 𝑜 (𝑔𝑖 )� ∗ 𝑓(𝑔𝑖 |𝜎 𝑜 ) + 𝜆𝑜 ∗ 𝑢′�𝑐 𝑜 (𝑔𝑖 )� ∗ 𝑓(𝑔𝑖 |𝜎 𝑜 ) ≤ 0 , 𝑐 𝑜 (𝑔𝑖 ) ≥ 0 𝑐. 𝑠.
𝜕𝑐 𝑜 (𝑔𝑖 )
Solving in terms of 𝜆𝑜 :
𝑜
𝜆 =
𝐹′�𝑔𝑖 − 𝑐 𝑜 (𝑔𝑖 )� ∗ 𝑓(𝑔𝑖 |𝜎 𝑜 )
𝑢′�𝑐 𝑜 (𝑔𝑖 )� ∗ 𝑓(𝑔𝑖 |𝜎 𝑜 )
The multiplier in this case shows the ratio of expected marginal utility of Firm S to the expected
marginal utility of VC1. Canceling out the densities shows that the optimal investment contract
is the ratio of marginal utilities.
Also, 𝜆𝑜 must be positive and binds the constraint of a minimum reservation utility. If 𝜆𝑜 = 0,
then Firm S's marginal utility would be zero or VC1's marginal utility would be positive infinity,
both of which are not possible under the assumptions. Under this basic scenario of perfect
information, Firm S demands a level of effort in knowledge transfer to achieve a desired
production and VC1 accepts the contract for a return commensurate with that level of output.
It follow then that the ratio of marginal utilities will be constant under these contracts.
While simplistic, this theoretical model assumes firms see value in venture capital knowledge,
and incremental knowledge transfers increase production through human capital accumulation.
This model could be extended to consider increasing levels of asymmetric information and
moral hazard, but the intent is to illustrate on a very basic level the potential for increases in
human capital with venture capital involvement and its potential effect on production
(commercialization).
SECTION 3: EMPIRICAL MODELS
The basic framework of the empirical analysis is to evaluate the relationship between human
capital and innovation within firms engaged in research to develop a new product or
innovation. It has been established that firms engaged in R&D need capital to overcome the
"valley of death," and one potential source of funding is from venture capital. Venture capital
participation can also result in the accumulation of human capital at the firm. It follows then
that firms with venture capital funding may be more commercially successful than those firms
without venture capital participation.
SBIR provides an opportunity to study the interaction of human capital and innovation since the
SBIR program allows for awards to be given to firms that are minority or majority owned by
venture capital entities. Therefore, survey data from SBIR recipients are used to evaluate the
potential impact of human capital build-up from venture capital and commercialization success
relative to those who have received SBIR awards without venture capital investments.
A basic model for the relationship is proposed to have the following form:
𝑐𝑜𝑚𝑚𝑒𝑟𝑐𝑖𝑎𝑙𝑖𝑧𝑎𝑡𝑖𝑜𝑛 = 𝑉𝐶 𝑝𝑎𝑟𝑡𝑖𝑐𝑖𝑝𝑎𝑡𝑖𝑜𝑛 + 𝑉𝐶 𝑚𝑎𝑗𝑜𝑟𝑖𝑡𝑦 + 𝑋𝑖 𝛽 + 𝜀𝑖
Commercialization is defined as whether a product has been brought to market and is
generating revenue. VC Participation may be a binary variable or an actual level/category of
funding to indicate whether a venture capital firm has invested in the firm. This variable also
encapsulates the incremental human capital provided to the firm by way of venture capital
participation. VC Majority is a binary variable equity to 1 if the firm is 51% or more owned by
one or more venture capitalists and is intended to control for those firms with significant
venture capital participation.
The proposed model also controls for other factors represented by the 𝑋 vector, including
whether the firm received prior SBIR funding at either the Phase I or Phase II state.
It could also be suggested that there is an unobserved omitted variable related to firm
heterogeneity, potentially creating endogeneity in the model as venture capital firms are likely
selecting investments based on commercial viability. However, that argument would only hold
if there is some belief that venture capitalists are more correct in their assessment of
commercial success. Studies performed on active asset management indicate (Malkiel 2005),
active managers do not consistently beat market returns and therefore do not hold any special
skill sets that allow for a more accurate prediction of payoffs. However, venture capital is a
different type of investment strategy and generally involves some level of active board of
directors participation. As such, the issue of endogeneity will need to be further evaluated
within the model.
An extension of the model includes evaluating the implications of receiving Phase I and/or
Phase II funding on commercialization. Given the potential for different distribution
assumptions at each stage of funding, conditional on Phase I funding, the probability of Phase II
funding with/without venture capital could be evaluated. Firms that apply for Phase II funding
have already received Phase I funding, so it may make the probability of commercialization
success more likely than simply assuming any particular firm can receive Phase II funds. Other
models to be considered include: conditional on Phase I and Phase II funding, the probability of
commercialization with/without venture capital, and conditional on Phase I and Phase II
funding, the probability of an initial public offering (IPO) with/without venture capital.
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