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\title{``WE OWN WHAT YOU THINK'': SIDE PROJECTS AND HIGH-GROWTH
ENTREPRENEURSHIP-- EVIDENCE FROM A QUASI-NATURAL EXPERIMENT}



\author[1]{Ali Mohammadi}%
\author[2]{Sergio  Rodriguez-Garnica}%
\affil[1]{Copenhagen Business School}%
\affil[2]{Universidad Carlos III de Madrid}%


\vspace{-1em}



  
  \date{April 17, 2026}


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\selectlanguage{english}
\begin{abstract}
This paper provides causal evidence on how institutional constraints on
side projects affect high-growth entrepreneurship, measured by the rate
of VC-backed firms. We exploit the Alcatel v. Brown ruling, which
expanded employer ownership claims over employee side projects in states
lacking statutory protections. The ruling caused a significant decline
in VC activity---fewer deals, smaller investments, and lower exit rates.
It also reduced the number of hybrid entrepreneurs with graduate
education. These findings suggest that legal restrictions on side
projects deter entrepreneurial experimentation and shrink the pool of
high-quality startup founders.%
\end{abstract}%



\sloppy


\textbf{``WE OWN WHAT YOU THINK'': SIDE PROJECTS AND HIGH-GROWTH
ENTREPRENEURSHIP-- EVIDENCE FROM A QUASI-NATURAL EXPERIMENT}

jabbrv-ltwa-all.ldf jabbrv-ltwa-en.ldf\textbf{~}

\textbf{ABSTRACT}

This paper provides causal evidence on how institutional constraints on
side projects affect high-growth entrepreneurship, measured by the rate
of VC-backed firms. We exploit the Alcatel v. Brown ruling, which
expanded employer ownership claims over employee side projects in states
lacking statutory protections. The ruling led to a significant decline
in VC activity, characterized by fewer deals, smaller investments, and
lower exit rates. It also reduced the number of hybrid entrepreneurs
with graduate education. These findings suggest that legal restrictions
on side projects deter entrepreneurial experimentation and shrink the
pool of high-quality startup founders.

\textbf{Key words:} hybrid entrepreneurship, side projects, high-growth
entrepreneurship, entrepreneurial barriers, intellectual property
rights, venture capital, entrepreneurial experimentation.\selectlanguage{english}
\begin{longtable}[]{@{}ll@{}}
\toprule
& \emph{The best startups almost have to start as side projects, because
great ideas tend to be such outliers that your conscious mind would
reject them as ideas for companies.} \emph{Paul Graham, Founder, Y
Combinator}\tabularnewline
& \emph{Who owns your thoughts? According to the 219th Judicial District
Court of the State of Texas, your employer might.} \emph{Lai, J. C.
(2003)}\tabularnewline
\bottomrule
\end{longtable}

\textbf{INTRODUCTION}

Side projects have emerged as a fertile ground for the creation of
high-growth, disruptive businesses in the modern economy (Davis et al.,
2013). Their growing prevalence is fuelled by the rise of the gig
economy and the normalization of remote work arrangements (Kwan et al.,
2025). This trend is particularly pronounced in the Information
Technology (IT) sector, where a culture of experimentation fosters
widespread engagement in side projects (Stack Overflow, 2024). When
these initiatives demonstrate potential, their creators often formalize
them into business ventures while retaining their salaried
employment---a pathway referred to as hybrid
entrepreneurship.\textbf{Hybrid entrepreneurship offers a low-risk
environment to test, refine, and scale innovative ideas, serving as a
critical bridge between ideation and full-time entrepreneurial
commitment (Folta et al., 2010; Thorgren et al., 2014; Luc et al.,
2018).} Many successful firms\textbf{--including Apple, eBay, Twitter,
Slack, Craigslist, and Trello--originated as side projects developed
outside of working hours. Around 20\% of the CEOs on Inc. magazine's
list of the 500 fastest-growing companies started their ventures while
still employed (Wu et al., 2024; Inc. staff, 1997; Raffiee \& Feng,
2014).}

\textbf{Despite the growing prevalence of hybrid entrepreneurship
(Minniti, 2010), institutions and policy makers have largely overlooked
them or even hindered them (Schulz et al., 2016; Folta et al., 2010;
Welter, 2004).} A key institutional factor determining hybrid
entrepreneurship is the regulation of intellectual property (IP) rights
(Alyavi \& Schulz, 2024). For side projects to thrive, employees must be
confident they will retain ownership of independently developed ideas,
while employers need assurances that core proprietary knowledge is
protected. This delicate balance was disrupted by Alcatel v. Brown, a
Texas court case in which a software developer was required to assign
ownership of a personal project, created outside work hours and before
employment, to his employer, based on a broad IP clause in his contract
(Lobel, 2014a). The ruling significantly expanded the enforceability of
employer claims over employee ideas, introducing new legal uncertainty
around side ventures (Armstrong et al., 2024; Wu et al., 2024).

This institutional shift offers a unique opportunity to causally examine
whether constraints on side projects suppress or enhance the rate of
high-growth ventures in the economy, measured as Venture Capital (VC)
backed firms11Startups that receive venture capital (VC) financing are
widely recognized as a reliable proxy for high-growth firms. Venture
capitalists typically invest in startups with strong growth potential,
disruptive technologies, and a high likelihood of profitable exits
(Lerner \& Nanda, 2020). As a result, VC-backed firms are often
considered among the most valuable and scalable ventures in the broader
entrepreneurial population (Castellaneta et al., 2016). Empirical
evidence supports this view: VC-backed firms tend to grow more rapidly,
generate more patents, exhibit higher productivity, and are more likely
to go public than their non-VC-backed counterparts (Wright \& Robbie,
1998).. On the one hand, constraints on side projects may reduce the
prevalence of high-growth ventures, as side projects enable individuals
to explore and test new business ideas while retaining the security of
paid employment. This pathway is particularly important for developing
disruptive or uncertain innovations that may not emerge through
traditional entrepreneurial routes (Folta et al., 2010; \textbf{Raffiee
\& Feng, 2014} ). When legal risks discourage side ventures, this
experimentation process is curtailed. Moreover, hybrid pathways are
often used as a route into entrepreneurship for highly skilled
individuals with substantial opportunity costs--those in
well-compensated paid positions who are less likely to leave their jobs
to pursue unproven ideas. By deterring these individuals from engaging
in entrepreneurial activity, institutional barriers to side projects
could suppress the prevalence of high-growth ventures (Folta et al.,
2010; Raffiee and Feng, 2014; Panos et al., 2014).

jabbrv-ltwa-all.ldf jabbrv-ltwa-en.ldf\textbf{On the other hand, such
institutional constraints may serve as a filtering mechanism. By
increasing the costs and risks associated with entrepreneurship, they
can discourage marginal or low-commitment entrants while selectively
encouraging individuals with strong motivation, higher expected returns,
and more robust business models (Conti et al., 2022; Branstetter et al.,
2014). In this sense, legal barriers to engaging in side projects may
increase the prevalence of high-growth entrepreneurial ventures.}

\textbf{We find that institutional barriers to engaging in side
projects, particularly the Alcatel v. Brown ruling, had a pronounced
causal dampening effect on high-growth entrepreneurship. In states where
the ruling was adopted as legal precedent} 11A legal precedent refers to
a judicial decision that establishes a principle or rule of law, which
is then cited and followed in subsequent cases involving similar facts
or issues. This practice---central to the doctrine of stare
decisis---ensures consistency and predictability in legal
decision-making (Hart, 2012; Horwitz, 1977; Landes and Posner,
1976)\textbf{, VC activity declined significantly: the number of deals,
average and median investment amounts, and successful exits all
decreased. These effects were especially salient in early-stage
financing and within the IT sector, precisely the domains most closely
associated with side projects.}

jabbrv-ltwa-all.ldf jabbrv-ltwa-en.ldf\textbf{While our main analyses
are conducted at the state level to capture broad institutional effects,
we also complement this with individual-level analysis. At the
individual level, we find that the ruling led to a decline in the number
of hybrid entrepreneurs with graduate education, those particularly
likely to engage in innovative side projects.}

\textbf{Overall, our findings suggest that institutional barriers to
side projects disincentivize entrepreneurial experimentation and deter
capable individuals from entering hybrid entrepreneurship. The reduction
in early-stage experimentation likely contributes to the observed
decline in high-growth, VC-backed startups.}

This paper makes two main contributions. First, it advances the
literature on hybrid entrepreneurship and institutional constraints by
providing causal evidence on how institutional changes that deter
employees from engaging in side projects affect the rate of high-growth
startups, as proxied by VC activity. In doing so, we respond to calls
for greater attention to how hybrid entrepreneurs respond to
institutional change (Schulz et al., 2016) and demonstrate the
importance of regulatory clarity in employment contracts and IP law
(Alyavi \& Schulz, 2024). Our results underscore the need for
entrepreneurship policies that explicitly account for the institutional
environment facing hybrid entrepreneurs, a group that often operates in
a legal and regulatory gray zone despite its economic relevance. Since
side projects serve as a low-risk platform for experimentation, policies
that undermine this process risk dampening broader entrepreneurial
dynamism (Alyavi \& Schulz, 2024).

Second, we contribute to the literature on IP and entrepreneurship by
shifting the focus from how IP protections benefit incumbent firms to
how they may inhibit employee-driven ventures. While prior studies
highlight how IP laws secure incentives for established innovators (Wu
et al., 2024; Png, 2015; Png \& Samila, 2015), our findings reveal that
the same legal instruments can suppress entrepreneurial
entry---especially among hybrid entrepreneurs---by limiting the
attractiveness of engaging in side projects. This trade-off emphasizes
that IP law is not neutral: rules that protect incumbents may
simultaneously hinder the prevalence of high-growth ventures,
particularly in innovation-driven sectors.

\textbf{THEORETICAL DEVELOPMENT AND HYPOTHESES}

This section develops the theoretical foundation for understanding how
institutional barriers to side projects can influence the rate of
high-growth ventures. We begin by outlining the importance of side
projects and hybrid entrepreneurship as a pathway for experimentation,
learning, and scalable business creation, emphasizing its prevalence
among professionals with high educational levels in the IT industry.
Next, we examine the role that institutions have either enabling or
constraining employees from pursuing side projects, with particular
attention to IP ownership. We then focus on the landmark Alcatel v.
Brown case, which significantly altered the legal treatment of side
projects by expanding employer claims over employee-generated
innovations. Finally, we theorize how such institutional constraints may
decrease or increase the rate of high-growth entrepreneurship.

jabbrv-ltwa-all.ldf jabbrv-ltwa-en.ldf\textbf{Hybrid entrepreneurship
and institutional barriers to side projects}

Some employees who engage in side projects eventually formalize these
efforts by launching ventures while continuing to hold their primary
job. These individuals are known as hybrid entrepreneurs (Folta et al.,
2010). While some may engage in hybrid entrepreneurship for supplemental
income or personal fulfilment, empirical evidence indicates that it is
primarily used as a transitional, low-risk pathway to full-time
self-employment (Folta et al., 2010). Rather than being driven by
necessity, hybrid entrepreneurship is often opportunity-driven, allowing
individuals to test and refine new business ideas while maintaining the
financial stability of salaried work (Schulz et al., 2016; Alyavi \&
Schulz, 2024). This dual arrangement offers the flexibility and security
needed to experiment before making a full entrepreneurial commitment
(Folta et al., 2010; Benitez et al., 2023; Thorgren et al., 2014; Luc et
al., 2018). Side projects are especially common in the IT sector; for
instance, 88\% of software developers report working on side projects
alongside their primary employment (\textbf{Stack Overflow, 2024} ).

Engagement in side projects provide employees with valuable
opportunities to acquire and apply new skills (Sonmez, 2017). Moreover,
such projects can serve as a source of groundbreaking innovation
(Burgelman 1983; Davis et al. 2013). As a result, they may generate
positive spillover effects for employers by enhancing employee
motivation, skill development, innovative capacity, and access to
broader professional networks (Ferreira, 2020; Marshall, 2019; Sessions
et al., 2021). However, concerns over misuse of proprietary knowledge
lead many firms, especially in IT, to require broad IP assignment
agreements, which often claim ownership of innovations developed outside
work. These contracts create legal uncertainty that may deter hybrid
entrepreneurship. Balancing IP protections with employee freedom to
innovate is crucial, and institutional frameworks play a key role in
shaping this balance. The next section explores Alcatel v. Brown, a
landmark case that redefined legal boundaries for side projects.

\textbf{The Alcatel v. Brown case}

The Alcatel v. Brown case marked a pivotal moment in the legal
interpretation of side project ownership, establishing a precedent with
far-reaching implications for entrepreneurship. The dispute involved
Evan Brown, a software developer in Texas, who claimed to have conceived
a software idea---- with potential to serve as the foundation for a new
venture---- before his employment at DSC Communications, a company later
acquired by Alcatel. Aware of the possible conflict with his employment
terms, Brown formally requested that DSC release him from his invention
disclosure obligations to independently pursue the project. Both Brown
and DSC acknowledged the commercial value of the idea, but after nearly
a year of unsuccessful negotiations, DSC terminated Brown's employment
and filed a lawsuit asserting full ownership. The company alleged that
Brown had violated the terms of his employment agreement by failing to
disclose the idea and sought a declaratory judgment that would not only
assign ownership to DSC but also compel Brown to fully disclose the
software concept (Lobel, 2014a; Armstrong et al., 2024). In 2002, the
Texas court ruled in Alcatel's favour, upholding the validity of the IP
assignment clause and establishing that even undeveloped or conceptual
ideas could be subject to employer ownership if contractually specified,
regardless of whether company resources were used (Armstrong et al.,
2024; Wu et al., 2024).

This ruling marked a significant decline in employer rights, shifting
the legal interpretation of ownership from tangible innovations (e.g.,
patents or trade secrets) to include early-stage and abstract ideas
(Lai, 2003; Lobel, 2014a). The Alcatel v. Brown decision thus created a
powerful, nationwide precedent that informed the future decisions of
other state and federal courts on employer claims. It introduced a
chilling effect on employee-led side projects, particularly in the IT
industry, where entrepreneurial ideas are often conceptual and portable.
The ruling attracted widespread media attention, with headlines such as
''We Own What You Think''11Nachtigal, J. (2004, August 18). We own what
you think. Salon. Retrieved May 30, 2025, from
https://www.salon.com/2004/08/18/evan\_brown/ or ``My Ideas, My Boss's
Property'' underscoring its controversial implications for potential
hybrid entrepreneurs (Armstrong et al., 2024; Wu et al., 2024; Lobel,
2014b).

\textbf{The impact of institutional barriers to side projects on
high-growth entrepreneurship}

Institutional constraints that limit side project activity, by
increasing the legal risks for employees, \textbf{particularly} the risk
of losing ownership over ideas developed outside of their primary
employment, may have opposing effects on high-growth entrepreneurship.
On one hand, such constraints may discourage early-stage experimentation
and deter highly capable individuals from engaging in hybrid
entrepreneurship. This should decrease the high-growth entrepreneurs. On
the other hand, these barriers may function as a filtering mechanism,
discouraging marginal or less-committed entrepreneurs while allowing
only the most promising, high-growth ventures to advance. Consequently,
the net effect of institutional barriers on high-growth entrepreneurship
remains theoretically ambiguous, highlighting the need for empirical
investigation.

First, we argue that institutional barriers to side projects may
decrease the rate of high-growth ventures because they limit
experimentation. Hybrid entrepreneurship serves as a critical
transitional pathway to full self-employment, \textbf{allowing founders
to test their entrepreneurial capabilities and refine their business
models while mitigating the financial risks associated with full-time
venture creation. In this sense, it serves as a low-risk experimentation
phase that can enhance the viability and effectiveness of
entrepreneurial ideas (Folta et al., 2010} ; Thorgren et al., 2014; Luc
et al., 2018\textbf{). This experimentation is particularly vital for
disruptive or novel business concepts, where uncertainty is high and
real-world implementation is often the only means of assessing value and
refining the model (Kerr et al., 2014). Without this transitional,
low-risk pathway to entrepreneurship, many promising and potentially
transformative ideas would likely remain unexplored (Folta et al., 2010;
Raffiee \& Feng, 2014).} Therefore\textbf{, when institutional barriers
restrict hybrid entrepreneurship, potential founders lose an essential
opportunity to try, acquire knowledge, and refine their ventures} ,

\textbf{particularly those that are more uncertain precisely because
they are more disruptive.}

\textbf{Institutional barriers that increase the risks associated with
engaging in side projects also affect the composition of the
entrepreneurial pool. When testing a business idea through hybrid
entrepreneurship becomes riskier, some individuals may choose not to
pursue entrepreneurship at all. High human capital individuals face
greater opportunity costs associated with leaving secure employment and
are therefore disproportionately deterred by such constraints (Folta et
al., 2010; Raffiee \& Feng, 2014). The IT sector may be especially
affected by these regulations, as it employs many highly skilled
professionals. As a result, institutional barriers to side projects may
exclude some of the most capable potential founders from the
entrepreneurial pipeline. Thus, regulations---particularly those that
restrict access to hybrid entrepreneurship---may inhibit entrepreneurial
activity among well-educated individuals seeking to test and refine
innovative ideas in the market, potentially preventing the ventures with
significant growth potential (Panos et al., 2014; Folta et al., 2010).}

\textbf{The legal risks of engaging in side projects are especially
pronounced for commercially valuable innovations. High-potential ideas
are more likely to attract employer claims, as firms have greater
incentives to assert ownership over ventures with significant value.
This uneven threat of litigation can lead individuals to abandon or
avoid their most promising entrepreneurial pursuits. As a result,
institutional barriers that elevate legal uncertainty around side
projects may systematically discourage ambitious innovation, ultimately
reducing the emergence of high-growth ventures. Based on these insights,
we hypothesize:}

\emph{H1a: Increases in institutional barriers to hybrid
entrepreneurship will lead to a decrease in the rate of high-growth
ventures.}

Conversely, institutional barriers to side project/ hybrid
entrepreneurship may increase the rate of high-growth ventures.
Individuals who do not transition directly to full-time entrepreneurship
are often marginal entrepreneurs---those for whom expected returns are
relatively low (Schulz et al., 2016). By raising the cost of entry,
institutional constraints may act as a filter, deterring low-commitment
or ''hobbyist'' entrepreneurs who are less likely to build scalable
ventures. This view aligns with prior research suggesting that when the
attractiveness of wage employment rises (Conti et al., 2022) or the
costs of starting a business increase (Branstetter et al., 2014),
overall entry declines but the quality of ventures increases. Under such
constraints, only the most capable and committed individuals---those
with strong conviction in their ideas---may be willing to accept the
increased risk of launching a business, anticipating high returns.
Moreover, high-ability individuals may have more bargaining power to
negotiate favourable employment terms, such as exemptions from
restrictive IP clauses. As a result, they may be less affected by
institutional barriers and still be able to pursue entrepreneurial
opportunities despite legal constraints. \textbf{Building on this
reasoning, we propose that institutional constraints limiting side
projects may enhance the rate of high-growth entrepreneurship by
filtering out less committed individuals. This leads to our second
hypothesis:}

jabbrv-ltwa-all.ldf jabbrv-ltwa-en.ldf\emph{H1b: Increases in
institutional barriers to hybrid entrepreneurship lead to an increase in
the rate of high-growth ventures.}

\textbf{EMPIRICAL STRATEGY AND DATA}

\textbf{Research Design}

Identifying the causal impact of institutional barriers to engage in
side projects on high-growth entrepreneurship, specifically,
restrictions on side projects, presents significant empirical
challenges. Engagement in side project activity is not randomly
assigned; it is shaped by both firm-level policies and individual
characteristics. Some firms adopt more permissive attitudes toward side
projects, while others impose stringent IP restrictions. Similarly,
individuals differ in their motivations, skills, risk preferences, and
access to resources, all of which influence their likelihood of pursuing
side ventures (Wu et al., 2024). These firm- and individual-level
factors are also correlated with the propensity to engage in high-growth
entrepreneurship, making it difficult to isolate the effect of
institutional barriers on engaging in side projects on high-growth
entrepreneurship.

To address this, we exploit a quasi-natural experiment stemming from the
Alcatel USA, Inc. v. Evan Brown ruling, a landmark legal case that
redefined the enforceability of IP assignment clauses in employment
contracts. The ruling acted as an exogenous institutional shock,
altering the legal landscape for employee-initiated side projects in
states governed primarily by common law. Crucially, its impact varied
across states due to pre-existing statutory protections.

Specifically, eight states---California, Delaware, Illinois, Kansas,
Minnesota, North Carolina, Utah, and Washington---had already enacted
statutes protecting employee ownership of IP created outside the scope
of employment. In these states, the ruling had no material effect,
providing a natural control group. In contrast, the remaining states
were directly affected by the new precedent, forming the treatment
group. Table 1 summarizes the relevant statutory protections and their
enactment years.

\textbf{Table 1} . US States with Statutory Protection for Employees' IP
Ownership.\selectlanguage{english}
\begin{longtable}[]{@{}lll@{}}
\toprule
\textbf{State} & \textbf{Protection} & \textbf{Enacted
year}\tabularnewline
\midrule
\endhead
California & California Labor Code \selectlanguage{ngerman}§2870 \& §2872 & 1979\tabularnewline
Delaware & Delaware Code, 19 \selectlanguage{ngerman}§805 & 1984\tabularnewline
Illinois & Illinois Trade Secrets Act, 765 ILCS 1062/2 &
1983\tabularnewline
Kansas & Kansas Statutes Annotated \selectlanguage{ngerman}§44-130 & 1986\tabularnewline
Minnesota & Minn. Stat. \selectlanguage{ngerman}§ 181.78 & 1977\tabularnewline
North Carolina & North Carolina General Statutes \selectlanguage{ngerman}§ 66-57.1 &
1981\tabularnewline
Utah & Utah Code Annotated \selectlanguage{ngerman}§ 34-39-3 & 1989\tabularnewline
Washington & Washington Revised Code \selectlanguage{ngerman}§ 49.44.140-145 &
1979\tabularnewline
\bottomrule
\end{longtable}

This legal heterogeneity enables a Difference-in-Differences (DiD)
strategy, comparing entrepreneurial outcomes before and after the ruling
between affected and unaffected states. By leveraging this
jurisdictional variation, we isolate the causal effect of institutional
barriers to side projects on high-growth entrepreneurship.

\textbf{Data and Estimation Strategy}

To test our hypotheses, we use data from Refinitiv EIKON (formerly
VentureXpert), a comprehensive platform that tracks VC investment
activity. This dataset provides detailed information on VC backed deals
worldwide, making it well-suited for our analysis of high-growth
entrepreneurship. This database is used extensively in academic research
(Castellaneta et al., 2016; Conti et al. 2022; Hsu, 2007; Shafi et al.
2020). We transform our data to state-year level to capture VC
activities at the level of treatment (state).

Our sample consists of state-year-level US VC investments in the IT
industry11In supplementary analyses, we also examine VC investment
patterns in non-IT industries to provide a comparative perspective.,
which includes ''Computer Software and Services'' and ``Internet
Specific''. The focus in this sector is motivated by three primary
considerations. First, the IT industry exhibits a high prevalence of
side projects and hybrid entrepreneurship (Bretz et al., 2015; Wu et
al., 2024; Folta et al., 2010). Second, the IT industry was particularly
affected by the legal precedent set in Alcatel v. Brown. Prior to the
ruling, IP agreements in the sector were difficult to enforce due to the
abstract and intangible nature of software-based innovations. The
court's decision clarified that IP ownership agreements could indeed
extend to such intangible assets, making them legally enforceable and
significantly reshaping the regulatory environment for IT professionals
engaged in side-projects (Wu et al., 2024). Third, a substantial portion
of the US's most influential business ideas originates from IT-related
side projects (e.g. Slack and Twitter), illustrating the sector's
capacity to generate high-growth ventures.

Our main dependent variable, Deals, measures the total number of first
round VC deals in a each U.S. state-year. The key explanatory variable
is the interaction between Post and Treatment. The variable Post is a
binary indicator equal to 1 for years following 2002 (the year of
the\emph{Alcatel v. Brown} ruling), and 0 otherwise. Treatment is equal
to 1 for the 42 states that lacked preexisting legal protections for
employee-developed IP, and 0 for the 8 states that had such protections
in place prior to the ruling---namely, California, Delaware, Illinois,
Kansas, Minnesota, North Carolina, Utah, and Washington (see Table 1).

We estimate the effect of the ruling on VC activity using a Poisson
pseudo--maximum likelihood model (PPML), using the state-year as they
unit of analysis. The model is specified as follows:

Deals\textsubscript{st} = f (\selectlanguage{greek}β\selectlanguage{english}\textsubscript{0} +
\selectlanguage{greek}β\selectlanguage{english}\textsubscript{1}Treated\textsubscript{st} + \selectlanguage{greek}β\selectlanguage{english}\textsubscript{2}
Post\textsubscript{t} + \selectlanguage{greek}β\selectlanguage{english}\textsubscript{3} Treated\textsubscript{st}
Post\textsubscript{t} + \selectlanguage{greek}φ\selectlanguage{english}\textsubscript{s} + \selectlanguage{greek}τ\selectlanguage{english}\textsubscript{t} +
C\textsubscript{st} + \selectlanguage{greek}ε\selectlanguage{english}\textsubscript{st}) (1)

\selectlanguage{greek}φ\selectlanguage{english}\textsubscript{s} represents state fixed effects that control for
time-invariant state characteristics, and \selectlanguage{greek}τ\selectlanguage{english}\textsubscript{t} captures
year fixed effects, accounting for macroeconomic trends. The term
C\textsubscript{st} denotes a vector of time-varying state-level
controls sourced from the U.S. Census Bureau that has been extensively
used in state level data analysis (Conti et al., 2022; Conti \&
Valentini, 2018). First, we control for state population size (in log),
as state changes in the population size could influence the rate of
high-growth entrepreneurship. Second, we include state-level GDP growth
to reflect changes in macroeconomic conditions. Third, we control for
the tax burden, measured as the ratio of total state tax revenues to
GDP22Washington, D.C., is excluded from analyses involving this variable
due to data unavailability.. Finally, we include a measure of education
level, proxied by the share of the adult population holding at least a
college degree, to account for differences in the availability of human
capital across states and years. The term \selectlanguage{greek}ε\selectlanguage{english}\textsubscript{st} is the
error term. Standard errors are clustered at the state level to account
for serial correlation within states over time.

We assess the robustness of our findings using alternative measures of
high-growth entrepreneurship. Specifically, we estimate additional
models using (1) the number of successful exits, defined as the number
of VC-backed firms that underwent a M\&A or IPO; and (2) the
log-transformed average and median VC deal sizes33Number observations
drop for average and median investment size due to missing values..
These measures provide complementary insights into the quality and scale
of entrepreneurial outcomes beyond deal count and help validate the
consistency of our main results across a broader set of state-level
performance indicators. For the average and median deal size we use OLS
models with fixed effect. Tables 2 shows the definitions and Table 3
shows the descriptive statistics of these variables.

\textbf{Table 2.} Variable definitions (Main Dataset).\selectlanguage{english}
\begin{longtable}[]{@{}lll@{}}
\toprule
Variable Name & Variable Description & Source\tabularnewline
\midrule
\endhead
Deals & Total number of first round VC deals per state-year & Refinitiv
EIKON\tabularnewline
Succ. exits & Total number of successful exits per state-year &
Refinitiv EIKON\tabularnewline
Avg/Med deal (ln) & Natural logarithm of the annual average/median VC
deal size (in thousands USD) per state-year & Refinitiv
EIKON\tabularnewline
Early-stage Deals & Total number of first round VC deals classified by
Refinitiv Eikon as early-stage (i.e., seed, early stage) per state-year
& Refinitiv EIKON\tabularnewline
Late-stage Deals & Total number of first round VC deals classified by
Refinitiv Eikon as late-stage (i.e., expansion and late-stage) per
state-year & Refinitiv EIKON\tabularnewline
Post & A binary variable equal to 1 if the year is after 2002, and 0
otherwise & Refinitiv EIKON\tabularnewline
Treatment & A binary variable equal to 1 for U.S. states without
statutory protections for employees' intellectual property (IP)
ownership (42 states); and 0 for states with such statutory protections,
namely: California, Delaware, Illinois, Kansas, Minnesota, North
Carolina, Utah, and Washington. & Refinitiv EIKON\tabularnewline
Population (ln) & Natural logarithm of the state population size per
state-year & U.S. Census Bureau\tabularnewline
GDP Growth & Annual percentage growth rate of real Gross Domestic
Product (GDP) per state-year & U.S. Census Bureau\tabularnewline
Taxation & Ratio of total state tax revenues to GDP per state-year &
U.S. Census Bureau\tabularnewline
College or above & Share of the adult population holding at least a
college degree per state-year & U.S. Census Bureau\tabularnewline
\bottomrule
\end{longtable}

\textbf{Table 3.} Descriptive Statistics for the Main Sample.

jabbrv-ltwa-all.ldf jabbrv-ltwa-en.ldf\selectlanguage{english}
\begin{longtable}[]{@{}lllllllll@{}}
\toprule
& N & SD & Mean & P10 & P25 & P50 & P75 & P99\tabularnewline
Deals & 391 & 61.01 & 21.22 & 1 & 2 & 5 & 15 & 267\tabularnewline
Succ. Exits & 391 & 16.393 & 5.013 & 0 & 0 & 1 & 3 & 87\tabularnewline
Avg deal (ln) & 382 & 1.001 & 8.199 & 7.048 & 7.824 & 8.367 & 8.829 &
10.101\tabularnewline
Median deal (ln) & 382 & 1.01 & 7.86 & 6.745 & 7.49 & 8.006 & 8.412 &
10.101\tabularnewline
Population & 391 & .88 & 15.429 & 14.077 & 14.89 & 15.508 & 15.973 &
17.387\tabularnewline
GDP Growth & 391 & .023 & .03 & .005 & .014 & .027 & .045 &
.094\tabularnewline
Taxation & 391 & 1.017 & 5.413 & 4.305 & 4.795 & 5.313 & 5.917 &
8.214\tabularnewline
College or above & 391 & 4.548 & 23.432 & 17.4 & 20.3 & 22.9 & 26.6 &
33.2\tabularnewline
\bottomrule
\end{longtable}

Note: the sample is restricted to IT-related industries. The table
displays the number of observations (N), standard deviation (SD), mean,
and selected percentiles (P10, P25, P50, P75, P99).

\textbf{RESULTS}

\textbf{Test of Parallel Trend Assumption}

A key identifying condition for the validity of the DiD research design
is the parallel trends assumption. This assumption requires that, in the
absence of treatment, the treated and control groups follow similar
pre-existing trends in the outcome variable. In our context, this
implies that---prior to the Alcatel v. Brown ruling---states ultimately
affected by the ruling (treated group) and those unaffected (control
group) would have exhibited parallel trajectories in the outcome
variable. Under this condition, any post-treatment divergence between
the two groups can be plausibly attributed to the legal intervention
rather than to pre-existing differences in trend dynamics.

To test the parallel trends assumption, we estimate an event-study
specification that interacts the treatment indicator with a full set of
year dummies, using the year 2002 as the reference period. Figure 1
presents the results, plotting the estimated coefficients for each year
relative to the treatment. Crucially, we find no statistically or
economically significant differences in the pre-treatment trends of the
total number of VC deals between treated and control states. The
treatment effect emerges only after the Alcatel v. Brown ruling in 2002,
reinforcing the causal interpretation of our findings.

\textbf{Figure 1.} Graph on parallel trends (DV: VC deals).

\textbf{Hosted file}

\verb`image1.emf`  available at \url{https://authorea.com/users/939111/articles/1309121--we-own-what-you-think-side-projects-and-high-growth-entrepreneurship-evidence-from-a-quasi-natural-experiment}

\textbf{Main Results:}

Table 4 reports the regression estimates for our main dependent
variable---the number of VC deals---as well as for three additional
state-level outcomes: the number of successful exits, and the
log-transformed average and median VC deal sizes. Columns 1--4 present
specifications that include state and year fixed effects but exclude
time-varying control variables to address concerns related to bad
controls. Columns 5--8 introduce state-level control variables that can
vary in every state over time, including population, GDP growth, tax
burden, and educational attainment.

Across all specifications, we observe a statistically significant
decline in entrepreneurial outcomes in treated states following the
legal shock, providing strong support for our hypothesis. Specifically,
the PPML estimates in Column 1 indicate that, relative to the control
states, treated states experienced a 25.1\% decline in the expected
number of VC deals after the Alcatel v. Brown ruling (IRR = e-0.289 =
0.749; \emph{p} \textless{} 0.001). When we include the full set of
control variables in Column 5, the estimated effect remains virtually
unchanged: a 24.6\% decline (IRR = e\textsuperscript{-0.284} =
0.753;\emph{p} = 0.005). These results confirm that the ruling
substantially dampened the total deal-making activity in states without
prior statutory protections for employees' ideas.

To evaluate the robustness of our findings across alternative dimensions
that reflect the prevalence of high-growth entrepreneurship, we include
additional dependent variables at the state level. Specifically, we
examine the number of successful exits, i.e., M\&A or IPOs, as well as
the log-transformed average and median VC deal sizes. The results show
that the ruling had a substantial dampening effect on all these
outcomes. Model 6 shows treated states experienced a 37.1\% decline in
successful exits relative to control states following the Alcatel v.
Brown ruling (IRR = e\textsuperscript{-0.486} = 0.629, \emph{p}
\textless{} 0.001), holding other factors constant11Results also hold
for the number of VC-backed firms that can have more than one round of
investments, follow-on VC Deals (Table A1 in the Appendix).. So,
startups that received investments are less likely to have a successful
exit after the shock. In addition, we find that the average deal size
declined by 33.2\% (p = 0.051), while the median deal size dropped by
54.4\% (p = 0.011) in treated states relative to controls. Results hold
when we include the control variables.

The consistent negative effects observed across all dependent variables
reinforce the conclusion that legal constraints on side project
ownership reduce the prevalence of high-growth entrepreneurial ventures.
These findings support Hypothesis 1a and reject the alternative view
that such institutional barriers might serve as a quality filter,
increasing the likelihood of high-growth outcomes by deterring only
low-commitment entrepreneurs.

\textbf{Table 4.} Main Regression Results: PPML and OLS Estimates on VC
Activity and Deal Size.\selectlanguage{english}
\begin{longtable}[]{@{}lllllllll@{}}
\toprule
& PPML & OLS & PPML & OLS & & & &\tabularnewline
\midrule
\endhead
& (1) & (2) & (3) & (4) & (5) & (6) & (7) & (8)\tabularnewline
& Deals & Succ. exits & Avg deal (ln) & Med deal (ln) & Deals & Succ.
exits & Avg deal (ln) & Med deal (ln)\tabularnewline
Post & 0.316*** & -2.213*** & 0.273 & 0.334 & 0.345*** & -2.592*** &
0.130 & 0.242\tabularnewline
& (0.088) & (0.229) & (0.183) & (0.201) & (0.127) & (0.377) & (0.752) &
(0.807)\tabularnewline
& (0.000) & (0.000) & (0.143) & (0.104) & (0.007) & (0.000) & (0.864) &
(0.766)\tabularnewline
Post * Treatment & -0.289*** & -0.471*** & -0.375** & -0.560*** &
-0.284*** & -0.486*** & -0.332* & -0.544**\tabularnewline
& (0.081) & (0.108) & (0.161) & (0.198) & (0.101) & (0.083) & (0.165) &
(0.206)\tabularnewline
& (0.000) & (0.000) & (0.024) & (0.007) & (0.005) & (0.000) & (0.051) &
(0.011)\tabularnewline
Population (ln) & & & & & -0.274 & 3.122** & 2.168 &
2.769*\tabularnewline
& & & & & (0.961) & (1.411) & (1.509) & (1.579)\tabularnewline
& & & & & (0.776) & (0.027) & (0.158) & (0.086)\tabularnewline
GDP Growth & & & & & 1.345 & 2.257* & -2.556 & -2.805\tabularnewline
& & & & & (1.012) & (1.347) & (2.494) & (2.703)\tabularnewline
& & & & & (0.184) & (0.094) & (0.311) & (0.305)\tabularnewline
Taxation & & & & & -0.131* & 0.087 & 0.077 & 0.152\tabularnewline
& & & & & (0.079) & (0.149) & (0.154) & (0.151)\tabularnewline
& & & & & (0.098) & (0.556) & (0.617) & (0.319)\tabularnewline
College or above & & & & & 0.016 & 0.020 & -0.036 &
-0.068\tabularnewline
& & & & & (0.035) & (0.030) & (0.132) & (0.147)\tabularnewline
& & & & & (0.649) & (0.515) & (0.785) & (0.644)\tabularnewline
Constant & 3.739*** & 2.930*** & 7.904*** & 7.693*** & 8.518 & -49.270**
& -24.936 & -34.136\tabularnewline
& (0.046) & (0.043) & (0.132) & (0.146) & (15.813) & (24.037) & (24.670)
& (25.444)\tabularnewline
& (0.000) & (0.000) & (0.000) & (0.000) & (0.590) & (0.040) & (0.317) &
(0.186)\tabularnewline
Year FE & YES & YES & YES & YES & YES & YES & YES & YES\tabularnewline
State FE & YES & YES & YES & YES & YES & YES & YES & YES\tabularnewline
N obs & 391 & 391 & 381 & 381 & 391 & 391 & 381 & 381\tabularnewline
N clust & 44 & 44 & 43 & 43 & 44 & 44 & 43 & 43\tabularnewline
F-stat & & & 11.151 & 4.816 & & & 11.293 & 5.763\tabularnewline
Adj. R-squared & & & 0.299 & 0.225 & & & 0.299 & 0.226\tabularnewline
Note: Analysis based on state-level data from Refinitiv EIKON,
restricted to the IT industry. The number of total VC deals and
successful exits (measured as the total number per U.S. state-year) are
estimated using a Poisson Pseudo-Maximum Likelihood (PPML) model. The
average and median VC deal sizes (in thousands of USD, annually per
state) are log-transformed and estimated using OLS regression. Standard
errors are clustered at the state level. Results are reported as:
coefficient (clustered standard error; p-value). Significance levels: *
p \textless{} 0.10, ** p \textless{} 0.05, *** p \textless{} 0.01. & & &
& & & & &\tabularnewline
\bottomrule
\end{longtable}

\textbf{Additional Analysis:}

Having found strong support for Hypothesis 1a that institutional
constraints on side projects, i.e the Alcatel v. Brown ruling,
significantly reduced the rate of high-growth ventures---we next turn to
a set of supplementary analyses aimed at unpacking the underlying
mechanisms. While individual-level data linking VC-backed firms to
hybrid entrepreneurs are unavailable, we draw on additional sources and
empirical strategies to explore whether the observed effects plausibly
stem from a decline in hybrid entrepreneurship. Moreover, we conduct a
series of robustness checks to rule out alternative explanations and to
strengthen the causal interpretation of our findings, ensuring that the
estimated effects are attributable to the Alcatel v. Brown decision
rather than to other contemporaneous events or trends.

First, we examine whether early-stage investments---which are more
likely to be affected from experimental efforts of side projects---were
more negatively affected by the legal change than late-stage
investments. Second, we assess whether the observed effects are
concentrated in the IT sector, where side projects are especially
prevalent and often serve as a pipeline for innovative ideas. Third, we
add individual data from Current Population Data to check whether the
ruling that constrained side projects affects entrepreneurship in the
expected way, i.e. reducing the rate of hybrid entrepreneurship.
Finally, we examine whether the negative effect on hybrid
entrepreneurship is concentrated among individuals with higher
opportunity costs---specifically, those with elevated levels of human
capital. If the deterrent effect of the legal shock is
disproportionately borne by this group, it would suggest that the ruling
discouraged precisely the type of individuals most likely to initiate
high-potential, growth-oriented startups. Such a finding would further
support the interpretation that institutional constraints on side
projects undermine not only the quantity but also the quality of
entrepreneurial entry, that could eventually impact the rate of
high-growth firms.

\emph{Differential Impact on Early- vs. Late-Stage Investments}

Our first theoretical argument posits that institutional constraints on
side projects could hinder high-growth entrepreneurship by limiting
opportunities for early experimentation. Hybrid entrepreneurship often
serves as a platform for testing and refining business ideas before full
commitment, effectively functioning as an experimentation phase for new
ventures (Folta et al., 2010; Thorgren et al., 2014; Luc et al., 2018).
If this mechanism is disrupted, we expect the negative effects to be
more pronounced for nascent firms----which rely more on early
experimentation with their business idea, than for more mature,
established companies.

To test this prediction, we examine whether the impact of the Alcatel v.
Brown ruling varies across different phases of the investment cycle.
Specifically, we compare early-stage deals, which target newly formed
ventures, with late-stage deals, which typically involve firms that have
already achieved a certain level of operational maturity.11In an
alternative analysis we used the age of start-ups instead of stage of
development. In this case we compared VC investment in young firms (two
years old or younger at the time of investment) and older firm. The
results remain consistent and shows that institutional constraints on
side project ownership disproportionately hinder the younger high-growth
entrepreneurship.

The findings, presented in Table 5, support our argumentation. The
ruling had a significantly stronger negative effect on early-stage deals
(IRR = e\textsuperscript{-0.330} = 0.719), representing a 28.1\% decline
(p = 0.011), compared to a smaller and marginally significant effect on
late-stage deals (IRR = e\textsuperscript{-0.187} = 0.829),
corresponding to a 17.1\% decline (p = 0.067). These results suggest
that institutional restrictions on side projects disproportionately
hinder high-growth ventures at the earliest stages of development, when
experimentation is most critical.

\textbf{Table 5.} OLS Estimates on the Differential Effects Across VC
Investment Stages.\selectlanguage{english}
\begin{longtable}[]{@{}lll@{}}
\toprule
& (1) & (2)\tabularnewline
\midrule
\endhead
& Early stage deals & Late stage deals\tabularnewline
Post & 0.539*** & -0.059\tabularnewline
& (0.197) & (0.232)\tabularnewline
& (0.006) & (0.800)\tabularnewline
Post * Treatment & -0.330** & -0.183*\tabularnewline
& (0.129) & (0.101)\tabularnewline
& (0.011) & (0.069)\tabularnewline
Population (ln) & -1.316 & 1.729*\tabularnewline
& (1.155) & (1.026)\tabularnewline
& (0.254) & (0.092)\tabularnewline
GDP Growth & 0.073 & 4.003**\tabularnewline
& (1.076) & (1.672)\tabularnewline
& (0.946) & (0.017)\tabularnewline
Taxation & -0.098 & -0.194*\tabularnewline
& (0.102) & (0.116)\tabularnewline
& (0.340) & (0.095)\tabularnewline
College or above & 0.035 & -0.014\tabularnewline
& (0.051) & (0.033)\tabularnewline
& (0.498) & (0.660)\tabularnewline
Constant & 24.687 & -24.405\tabularnewline
& (19.113) & (16.529)\tabularnewline
& (0.196) & (0.140)\tabularnewline
Year FE & YES & YES\tabularnewline
State FE & YES & YES\tabularnewline
N & 402 & 400\tabularnewline
N\_clust & 48 & 47\tabularnewline
Note: Analysis is based on state-level data from Refinitiv EIKON,
restricted to the IT industry. Control variables are sourced from the
U.S. Census Bureau. Early-Stage Deals refer to the total number of VC
deals classified by Refinitiv EIKON as early-stage (i.e., seed or
early-stage) per state-year. Late-Stage Deals refer to the total number
of VC deals classified as late-stage (e.g., expansion and late-stage)
per state-year. Estimates are obtained using OLS regression, with
standard errors clustered at the state level. Results are reported as:
coefficient (clustered standard error; p-value). Significance levels: *
p \textless{} 0.10, ** p \textless{} 0.05, *** p \textless{} 0.01. &
&\tabularnewline
\bottomrule
\end{longtable}

jabbrv-ltwa-all.ldf jabbrv-ltwa-en.ldf\emph{Main Analysis Excluding the
IT Industry}

To strengthen the causal interpretation of our results, we next aim to
rule out alternative explanations and assess whether the observed
effects are indeed driven by the Alcatel v. Brown ruling, rather than by
other contemporaneous factors. If the ruling, which expanded employers'
rights to claim ownership over employees' side projects, primarily
affected hybrid entrepreneurs, its impact should be most pronounced in
industries where side project activity is particularly common. Hybrid
entrepreneurship is especially prevalent in IT industry, where employees
frequently engage in side ventures while maintaining full-time
employment (Schulz et al, 2016; Bretz et al., 2015; Folta et al., 2010).
As previously noted, approximately 88\% of software developers report
participating in side projects (Stack Overflow, 2024), underscoring the
centrality of such activity in this domain. Moreover, the Alcatel v.
Brown case itself involved a software developer, directly implicating
the IT sector and reinforcing expectations that the ruling would exert
its strongest effects in this industry (Wu et al., 2024). Our main
regression analysis (Table 4) confirmed a significant negative effect on
the VC activity of the IT industry.

If this effect is indeed driven by the legal shock, we should observe
negligible or statistically insignificant effects outside the IT
industry. To test this, we conduct a falsification test by restricting
the sample to non-IT industries. As shown in Table 6, none of the
interaction terms between Post and Treatment are statistically
significant in the non-IT subsample. This null result suggests that the
ruling's impact was largely confined to the IT sector, lending further
support to our interpretation that the Alcatel v. Brown decision was the
key institutional driver behind the observed decline in high-growth
entrepreneurial activity, and that the mechanism driving our results is
a reduction of side projects.

\textbf{Table 6.} Non-IT Sector Analysis: PPML and OLS Estimates on VC
Activity and Deal Size.\selectlanguage{english}
\begin{longtable}[]{@{}lllllllll@{}}
\toprule
& PPML & OLS & PPML & OLS & & & &\tabularnewline
\midrule
\endhead
& (1) & (2) & (3) & (4) & (5) & (6) & (7) & (8)\tabularnewline
& Deals & Succ. exits & Avg deal (ln) & Med deal (ln) & Deals & Succ.
exits & Avg deal (ln) & Med deal (ln)\tabularnewline
Post & 0.053 & -1.648*** & -0.109 & 0.027 & 0.330 & -1.483*** & -1.586**
& -1.128*\tabularnewline
& (0.072) & (0.137) & (0.349) & (0.343) & (0.205) & (0.265) & (0.663) &
(0.639)\tabularnewline
& (0.461) & (0.000) & (0.756) & (0.937) & (0.107) & (0.000) & (0.021) &
(0.084)\tabularnewline
Post * Treatment & -0.051 & -0.037 & 0.397 & 0.122 & -0.075 & -0.036 &
0.438 & 0.165\tabularnewline
& (0.073) & (0.116) & (0.321) & (0.318) & (0.070) & (0.107) & (0.319) &
(0.307)\tabularnewline
& (0.482) & (0.749) & (0.222) & (0.702) & (0.286) & (0.739) & (0.176) &
(0.593)\tabularnewline
Population (ln) & & & & & -1.672** & -1.461 & 2.904 &
4.080**\tabularnewline
& & & & & (0.696) & (1.169) & (2.399) & (1.903)\tabularnewline
& & & & & (0.016) & (0.211) & (0.232) & (0.037)\tabularnewline
GDP Growth & & & & & 2.174*** & 1.782 & 3.377 & 3.770\tabularnewline
& & & & & (0.811) & (1.432) & (2.932) & (2.658)\tabularnewline
& & & & & (0.007) & (0.213) & (0.255) & (0.163)\tabularnewline
Taxation & & & & & 0.027 & -0.116 & 0.141 & -0.042\tabularnewline
& & & & & (0.079) & (0.129) & (0.145) & (0.112)\tabularnewline
& & & & & (0.738) & (0.367) & (0.334) & (0.707)\tabularnewline
College or above & & & & & -0.004 & 0.018 & 0.289** &
0.177\tabularnewline
& & & & & (0.036) & (0.033) & (0.139) & (0.135)\tabularnewline
& & & & & (0.909) & (0.586) & (0.043) & (0.197)\tabularnewline
Constant & 4.003*** & 3.044*** & 8.096*** & 7.513*** & 31.083*** &
27.000 & -42.869 & -58.116**\tabularnewline
& (0.056) & (0.043) & (0.100) & (0.104) & (11.604) & (19.217) & (35.513)
& (27.975)\tabularnewline
& (0.000) & (0.000) & (0.000) & (0.000) & (0.007) & (0.160) & (0.233) &
(0.043)\tabularnewline
Year FE & YES & YES & YES & YES & YES & YES & YES & YES\tabularnewline
State FE & YES & YES & YES & YES & YES & YES & YES & YES\tabularnewline
N obs & 508 & 508 & 482 & 482 & 483 & 483 & 459 & 459\tabularnewline
N clust & 50 & 50 & 50 & 50 & 49 & 49 & 49 & 49\tabularnewline
F-stat & & & 6.172 & 5.732 & & & 6.988 & 5.275\tabularnewline
Adj. R-squared & & & 0.249 & 0.169 & & & 0.253 & 0.151\tabularnewline
Note: Analysis based on state-level data from Refinitiv EIKON,
restricted to the non-IT industries. Control variables are sourced from
the U.S. Census Bureau. The number of total VC deals and successful
exits (measured as the total number per U.S. state-year) are estimated
using a Poisson Pseudo-Maximum Likelihood (PPML) model. The average and
median VC deal sizes (in thousands of USD, annually per state) are
log-transformed and estimated using OLS regression. Standard errors are
clustered at the state level. Results are reported as: coefficient
(clustered standard error; p-value). Significance levels: * p
\textless{} 0.10, ** p \textless{} 0.05, *** p \textless{} 0.01. & & & &
& & & &\tabularnewline
\bottomrule
\end{longtable}

\emph{Impact of the Ruling on Hybrid Entrepreneurship Among
College-Educated Employees}

The following analysis demonstrates that the Alcatel v. Brown
ruling---stemming from a legal dispute concerning employee-led side
projects---has tangible effects on hybrid entrepreneurship. Hybrid
entrepreneurship typically represents a formalization stage in which
employees, having initially explored new ideas through informal side
projects, formalize these efforts constituting a venture while
maintaining their primary employment. This pathway allows individuals to
further commit to promising ideas without immediately foregoing the
security of a salaried position (Folta et al., 2010). Although side
projects are often informal and unreported, hybrid entrepreneurship
serves as a measurable proxy for these activities done outside of their
employment. We thus expect the Alcatel v. Brown ruling to
disproportionately discourages hybrid entrepreneurship compared to other
forms of entrepreneurship.

To empirically examine whether the ruling disproportionately affected
hybrid entrepreneurs within the overall pool of entrepreneurs, we
utilize individual-level data from the Current Population Survey (CPS),
accessed through IPUMS (Floods et al., 2021). The CPS is a nationally
representative monthly survey that covers approximately 65,000
households and 130,000 individuals. Each respondent is interviewed eight
times over a 16-month period (in four consecutive months, followed by an
eight-month gap, and then four additional monthly interviews). This
rotating panel structure allows us to track transitions in employment
status and entrepreneurial activity over time. This data has been used
in research on hybrid entrepreneurship11This adds some complexities to
create the hybrid entrepreneurship variable. We overcome them by
following the steps suggested by G\selectlanguage{ngerman}änser-Stickler et al. (2022) in their
Appendix. (e.g., Gänser-Stickler et al., 2022; Schulz et al., 2021). We
create hybrid entrepreneurship as a binary variable equal to 1 if an
individual was in full-time paid employment during the previous wave and
reports multiple job holdings in the current wave---specifically,
full-time employment as the primary job and self-employment as a
secondary activity22This definition explicitly designates
self-employment as a secondary job. In this paper, we adhere to Folta et
al.'s (2010) original definition that is frequently used in the
literature (e.g. Schulz et al., 2021), considering only those whose
self-employment constitutes a secondary job. However, some scholars
adopt a broader perspective, classifying individuals as hybrid
entrepreneurs regardless of whether self-employment serves as their
primary or secondary occupation (e.g., Raffiee \& Feng, 2014; Schulz et
al., 2016). Results hold when we do not differentiate whether
individuals report being self-employed in the primary or secondary job..
The variable is coded as 0 for self-employed, non-hybrid individuals,
i.e. those that report self-employment without maintaining a wage job.

To control for factors influencing entrepreneurial behaviour, we include
a set of individual-level covariates: age, gender, marital status, race
(white, black), parental status, and a binary indicator for high
household income (above \$75,000). These controls account for
demographic and socioeconomic characteristics that may shape both the
likelihood of entrepreneurial engagement and the opportunity costs
associated with it. Descriptive statistics of the CPS variables used are
reported in the Appendix, Table A2.

We estimate the effect of the Alcatel v. Brown ruling on transitions
into entrepreneurship using a linear probability model. Columns 1 and 2
of Table 7 report estimates of the likelihood that individuals
transition from full-time employment to any form of self-employment,
while Columns 3 and 4 isolate transitions specifically into hybrid
entrepreneurship, using transitions into other forms of entrepreneurship
as the reference category. To address concerns regarding bad controls,
we present results both without the full set of controls (Columns 1 and
3) and with them (Columns 2 and 4).

Importantly, Table 7 restricts the analysis to individuals with at least
a college degree. This subgroup is of particular interest given
theoretical expectations that the ruling would disproportionately affect
more educated individuals for two reasons. First, the legal change
specifically concerns ownership over innovative outputs, and its
consequences are therefore most salient among knowledge workers---those
with higher educational attainment and a greater likelihood of
generating IP (Wu et al., 2024). Second, hybrid entrepreneurship is
commonly employed as a strategy to reduce the risks associated with
entrepreneurial entry for individuals facing higher opportunity costs,
such as those with higher levels of human capital (Folta et al., 2010;
Panos et al., 2014). We therefore expect the ruling's effects to be
especially pronounced within this segment of the workforce.

Consistent with this expectation, we find a statistically significant
decline in entrepreneurial entry following the ruling. Specifically, the
probability that a full-time employee transitions into any form of
self-employment falls by approximately 0.1 percentage points (p = 0.046)
in treated states after the ruling. Given a baseline entry rate of
0.6\%, this corresponds to a relative decline of roughly 16.7\%. This
result remains robust when controlling for a rich set of demographic and
socioeconomic characteristics. These findings offer initial evidence
that the institutional constraints introduced by the ruling
significantly dampened entrepreneurial activity among college-educated
workers.

We then examine whether the ruling disproportionately affected hybrid
entrepreneurship---defined as self-employment concurrent with wage
employment. The results show a pronounced decline: the probability of
transitioning into hybrid entrepreneurship falls by 4.1 percentage
points (p = 0.031) in treated states. This effect also remains robust to
the inclusion of covariates. Given a baseline rate of hybrid entry of
6.3\%, the estimate reflects a substantial relative decline of
approximately 65\%.

Taken together, the CPS-based results provide compelling support for our
theoretical argument: the Alcatel v. Brown ruling constrained
entrepreneurship, particularly among hybrid entrepreneurs with higher
levels of human capital. These individuals, who typically leverage
hybrid entry to manage risk and opportunity costs, appear to have been
disproportionately deterred by the increased legal uncertainty
surrounding side project ownership. While we cannot directly demonstrate
that the Alcatel v. Brown ruling reduced high-growth entrepreneurship by
shrinking the pool of individuals with high levels of education from
entering into entrepreneurship, the findings offer suggestive evidence
that this mechanism may play an important role.

jabbrv-ltwa-all.ldf jabbrv-ltwa-en.ldf \textbf{}

\textbf{Table 7. OLS Estimates of the Probability of Transitioning from
Full-Time Employment to Self-Employment or Hybrid
Entrepreneurship----CPS Sample.}\selectlanguage{english}
\begin{longtable}[]{@{}lllll@{}}
\toprule
& (1) & (2) & (3) & (4)\tabularnewline
\midrule
\endhead
& Self-Employment & Self-Employment & Hybrid Entrepreneurship & Hybrid
Entrepreneurship\tabularnewline
Post & -0.001* & -0.001* & -0.087*** & -0.087***\tabularnewline
& (0.001) & (0.001) & (0.015) & (0.016)\tabularnewline
& (0.089) & (0.065) & (0.000) & (0.000)\tabularnewline
Post*Treatment & -0.001** & -0.001* & -0.041** & -0.041**\tabularnewline
& (0.000) & (0.000) & (0.018) & (0.019)\tabularnewline
& (0.046) & (0.077) & (0.031) & (0.039)\tabularnewline
Age & & 0.000*** & & 0.000\tabularnewline
& & (0.000) & & (0.000)\tabularnewline
& & (0.000) & & (0.848)\tabularnewline
Female & & -0.003*** & & -0.000\tabularnewline
& & (0.000) & & (0.010)\tabularnewline
& & (0.000) & & (0.975)\tabularnewline
Married & & 0.001** & & -0.013\tabularnewline
& & (0.000) & & (0.011)\tabularnewline
& & (0.039) & & (0.268)\tabularnewline
White & & 0.000 & & 0.028***\tabularnewline
& & (0.000) & & (0.010)\tabularnewline
& & (0.551) & & (0.007)\tabularnewline
Black & & -0.000 & & 0.031\tabularnewline
& & (0.001) & & (0.024)\tabularnewline
& & (0.974) & & (0.201)\tabularnewline
With children & & 0.000 & & -0.006\tabularnewline
& & (0.000) & & (0.011)\tabularnewline
& & (0.387) & & (0.572)\tabularnewline
Fam income over 75,000\$ & & 0.001*** & & -0.001\tabularnewline
& & (0.000) & & (0.010)\tabularnewline
& & (0.005) & & (0.933)\tabularnewline
Fam income missing & & 0.004*** & & -0.030*\tabularnewline
& & (0.000) & & (0.017)\tabularnewline
& & (0.000) & & (0.073)\tabularnewline
Constant & 0.006*** & -0.001** & 0.126*** & 0.115***\tabularnewline
& (0.000) & (0.001) & (0.009) & (0.027)\tabularnewline
& (0.000) & (0.022) & (0.000) & (0.000)\tabularnewline
State, Industry \& Year FE & Yes & Yes & Yes & Yes\tabularnewline
N & 483087 & 483087 & 2677 & 2677\tabularnewline
N clust & 50 & 50 & 50 & 50\tabularnewline
Adj. R-squared & 0.004 & 0.005 & 0.127 & 0.127\tabularnewline
Note: Analysis is based on Current Population Survey (CPS)
individual-level data. Sample is restricted to respondents with a
college degree or higher and individuals between 25 and 59 years old to
mitigates confounding influences that are specific to younger
individuals who are still in their qualification phase and older
individuals who are approaching retirement (Schulz et al., 2021;
G\selectlanguage{ngerman}änser-Stickler et al., 2022). OLS models estimate: (1) the probability
of becoming any type of self-employed (base category: not
self-employed), and (2) the probability of becoming a hybrid
entrepreneur (base category: non-hybrid entrepreneurs). Both outcomes
are conditional on individuals being full-time, paid employees in the
previous period (t\selectlanguage{english} --\selectlanguage{english} 1). All control variables---except for age are
binary indicators. Fam Income Over \$75,000 is a dummy variable equal to
1 if the respondent's household income falls into the highest income
category provided by CPS across the full sample, and 0 otherwise. Due to
approximately 15\% of income values being missing, Fam Income Missing
equals 1 if a respondent's income is missing but was assigned a value of
0 in Fam Income Over \$75,000, and 0 otherwise. The results remain
robust when excluding either or both of the income controls. Results are
reported as: coefficient (clustered standard error; p-value).
Significance levels: * p \textless{} 0.10, ** p \textless{} 0.05, *** p
\textless{} 0.01. & & & &\tabularnewline
\bottomrule
\end{longtable}

jabbrv-ltwa-all.ldf jabbrv-ltwa-en.ldf\emph{Impact of the Ruling on
Hybrid Entrepreneurship Among Non-College-Educated Employees}

We conduct a falsification test by repeating our analysis for
individuals without a college degree. Unlike the significant negative
effects observed for college-educated hybrid entrepreneurs, we find no
impact of the ruling---neither on overall entrepreneurship nor on hybrid
entrepreneurship---for less educated individuals (in Appendix, Table
A3). This reinforces our argument that the Alcatel v. Brown ruling
primarily constrained high human capital employees, who are more likely
to pursue high-growth ventures through hybrid entrepreneurship. While we
cannot directly link this mechanism to the observed decline in VC-backed
startups due to data limitations, our findings suggest that reduced
participation of educated hybrid entrepreneurs likely contributed to the
drop in high-growth entrepreneurial activity.

jabbrv-ltwa-all.ldf jabbrv-ltwa-en.ldf\textbf{DISCUSSION AND CONCLUSION}

Side projects---and their eventual evolution into hybrid
entrepreneurship--- have become increasingly common, accompanied by a
growing body of research recognizing their importance (Folta et al.,
2010; Schulz et al., 2016; Petrova, 2012; Burke et al., 2008). These
side efforts allow individuals to test and refine innovative ideas while
retaining the financial security of salaried employment. Employers may
benefit from such activity through enhanced motivation, creativity, and
expanded networks among their employees (Ferreira, 2020; Marshall,
2019). However, they may also attempt to restrict side projects due to
concerns over IP loss. In this context, institutional factors that
define the boundaries of employer-employee IP rights are crucial (Alyavi
\& Schulz, 2024).

This paper leverages a quasi-natural experiment---the Alcatel v. Brown
ruling in the U.S.---to provide causal evidence on how institutional
constraints on side projects affect high-growth firms, measured as VC
backed firms. We find that in states where the ruling became binding
precedent (i.e., those lacking prior statutory protection for employee
IP rights), there was a significant decline in the prevalence of VC
backed firms. This includes reductions in the number of deals, average
and median investment amounts, and successful exits. These effects are
especially pronounced in the IT sector and in early-stage financing,
both areas where side projects are more prevalent. Our findings suggest
that restricting side projects undermines low-risk experimentation and
narrows the pipeline of high-potential ventures.

We acknowledge the limitation posed by the absence of individual-level
data that would allow us to identify which VC backed startups were
founded by hybrid entrepreneurs. However, we try to causally assess the
impact of the Alcatel v. Brown ruling---which restricted side project
activity---on hybrid entrepreneurship. Our findings show that the ruling
significantly reduced entrepreneurial activity among hybrid
entrepreneurs with graduate level education. This suggests that
institutional constraints discourage high human capital individuals from
experimenting with new business ideas through side ventures.

\textbf{Taken together, our findings demonstrate that the Alcatel v.
Brown ruling causally reduced both the prevalence of hybrid
entrepreneurship and VC-backed startups in affected states. This
contradicts the ''filtering effect'' hypothesis, which suggests that
stricter legal barriers would elevate the high-growth ventures in
affected states. Instead, we show that such constraints
disproportionately discourage educated individuals from entering
entrepreneurship via hybrid entrepreneurship, and that these legal
barriers to join in side projects ultimately stifling the prevalence of
high-growth, VC backed firms. The contraction in early-stage VC
activity, particularly within the IT sector, points to a broader
chilling effect on entrepreneurial ecosystem, with potential long-term
consequences for innovation and economic dynamism.}

jabbrv-ltwa-all.ldf jabbrv-ltwa-en.ldf\textbf{This paper makes several
contributions to the literature on hybrid entrepreneurship and
institutional constraints. First, by leveraging a quasi-natural
experiment---the Alcatel v. Brown ruling---we provide causal evidence
that institutional barriers to side projects significantly reduce
high-growth entrepreneurial activity, measuring it as VC backed
ventures. While we cannot directly observe whether VC backed firms were
founded by hybrid entrepreneurs, the pronounced decline in VC activity
in industries and regions where hybrid entrepreneurship is more
prevalent offers suggestive evidence that such entrepreneurs play a
meaningful role in seeding scalable startups. This supports the view
that hybrid entrepreneurs' ability to experiment and de-risk ideas may
make them especially attractive to early-stage investors (Cumming \&
Zhang, 2023; Petty et al., 2023), countering claims that their ongoing
wage employment may signal low commitment. Hybrid entrepreneurship
remains a valuable, often overlooked mechanism for innovation and
economic growth---especially in knowledge intensive sectors and among
individuals with high levels of education. Recognizing and supporting
this form of entrepreneurial activity is essential for building a more
inclusive, dynamic, and resilient entrepreneurial ecosystem (Schulz et
al., 2016; Folta et al., 2010).}

\textbf{Second, we contribute to the literature on the role of IP
protection in shaping entrepreneurial ecosystems (} Alyavi \& Schulz,
2024\textbf{). Our results highlight a critical policy trade-off: while
IP rules are designed to protect employers, they may also
unintentionally hinder innovation by reducing the entrepreneurial
options of ambitious and highly skilled individuals. Legal frameworks
that fail to account for the realities of hybrid entrepreneurship risk
suppressing the experimentation of highly capable individuals that could
fuel the entrepreneurial landscape.}

Third, our analysis complements emerging work on the broader
consequences of employer IP control. While Wu et al. (2024) examine the
effects of such constraints on innovation performance, and Armstrong et
al. (2024) explore their impact on disclosure behavior and
inventor-employer matching, we focus on the effect on entrepreneurship
and VC. Our study extends this literature by documenting how
institutional constraints influence the prevalence of high-growth
startups, thereby connecting employment law with entrepreneurial
ecosystem dynamics.

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\textbf{APPENDIX}

\textbf{Table A1.} PPML Regression Results on Follow-On Venture Capital
Deals\selectlanguage{english}
\begin{longtable}[]{@{}llll@{}}
\toprule
& Follow-on Deals & &\tabularnewline
\midrule
\endhead
& Coefficients & Standard errors & P-value\tabularnewline
Post & 0.274 & (0.170) & (0.106)\tabularnewline
Post * Treatment & -0.342*** & (0.097) & (0.000)\tabularnewline
Population (ln) & -1.004 & (1.109) & (0.365)\tabularnewline
GDP Growth & 1.285 & (1.001) & (0.199)\tabularnewline
Taxation & -0.051 & (0.083) & (0.541)\tabularnewline
College or above & 0.018 & (0.035) & (0.595)\tabularnewline
Constant & 19.845 & (18.423) & (0.281)\tabularnewline
Year \& State FE & YES & &\tabularnewline
N & 402 & &\tabularnewline
N Clusters & 48 & &\tabularnewline
Note: Analysis is based on state-level data from Refinitiv EIKON,
restricted to the IT industries. Control variables are sourced from the
U.S. Census Bureau. Follow-on Deals refer to the number of second or
later rounds of VC investment per state-year. Estimates are obtained
using a Poisson Pseudo-Maximum Likelihood (PPML) regression. Standard
errors are clustered at the state level. Significance levels: * p
\textless{} 0.10, ** p \textless{} 0.05, *** p \textless{} 0.01. & &
&\tabularnewline
\bottomrule
\end{longtable}

\textbf{Table A2.} Descriptive Statistics of CPS Data\selectlanguage{english}
\begin{longtable}[]{@{}lllllllll@{}}
\toprule
& N & Mean & SD & p10 & p25 & p50 & p75 & p99\tabularnewline
Self-employment & 504055 & .006 & 0.075 & 0 & 0 & 0 & 0 &
0\tabularnewline
Hybrid entrepreneurship11This includes only sample of individuals that
transitioned to self-employment. & 2826 & .063 & 0.243 & 0 & 0 & 0 & 0 &
1\tabularnewline
Treated & 949860 & .773 & 0.419 & 0 & 1 & 1 & 1 & 1\tabularnewline
Age & 989391 & 41.482 & 9.257 & 29 & 34 & 42 & 49 & 58\tabularnewline
Female & 989391 & .477 & 0.499 & 0 & 0 & 0 & 1 & 1\tabularnewline
Married & 989391 & .699 & 0.459 & 0 & 0 & 1 & 1 & 1\tabularnewline
White & 989391 & .866 & 0.341 & 0 & 1 & 1 & 1 & 1\tabularnewline
Black & 989391 & .062 & 0.241 & 0 & 0 & 0 & 0 & 1\tabularnewline
Fam income \textgreater{}75,000\$ & 989391 & .461 & 0.498 & 0 & 0 & 0 &
1 & 1\tabularnewline
\bottomrule
\end{longtable}

Note: sample restricted to individuals with college degree or above; and
individuals between 25 and 59 years old to mitigates confounding
influences that are specific to younger individuals who are still in
their qualification phase and older individuals who are approaching
retirement (Schulz et al., 2021; G\selectlanguage{ngerman}änser-Stickler et al., 2022).



\textbf{Table A3. OLS Estimates of the Probability of Transitioning from
Full-Time Employment to Any Self-Employment or Hybrid Entrepreneurship
(Below College Degree)}\selectlanguage{english}
\begin{longtable}[]{@{}lllll@{}}
\toprule
& (1) & (2) & (3) & (4)\tabularnewline
\midrule
\endhead
& Self-Employment & Self-Employment & Hybrid Entrepreneurship & Hybrid
Entrepreneurship\tabularnewline
Post & -0.001* & -0.001* & -0.104*** & -0.105***\tabularnewline
& (0.000) & (0.000) & (0.021) & (0.021)\tabularnewline
& (0.099) & (0.090) & (0.000) & (0.000)\tabularnewline
Treated*Post & 0.000 & 0.000 & 0.000 & 0.001\tabularnewline
& (0.000) & (0.000) & (0.016) & (0.016)\tabularnewline
& (0.704) & (0.765) & (0.979) & (0.956)\tabularnewline
Age & & 0.000*** & & 0.001\tabularnewline
& & (0.000) & & (0.000)\tabularnewline
& & (0.000) & & (0.139)\tabularnewline
Female & & -0.002*** & & -0.002\tabularnewline
& & (0.000) & & (0.008)\tabularnewline
& & (0.000) & & (0.835)\tabularnewline
Married & & 0.001*** & & 0.020***\tabularnewline
& & (0.000) & & (0.007)\tabularnewline
& & (0.000) & & (0.005)\tabularnewline
White & & 0.000 & & 0.037***\tabularnewline
& & (0.000) & & (0.010)\tabularnewline
& & (0.705) & & (0.001)\tabularnewline
Black & & -0.000 & & 0.035**\tabularnewline
& & (0.000) & & (0.016)\tabularnewline
& & (0.453) & & (0.032)\tabularnewline
With children & & 0.000 & & -0.002\tabularnewline
& & (0.000) & & (0.006)\tabularnewline
& & (0.712) & & (0.777)\tabularnewline
Fam income \textgreater{}75,000\$ & & 0.002*** & & -0.006\tabularnewline
& & (0.000) & & (0.007)\tabularnewline
& & (0.000) & & (0.397)\tabularnewline
Fam income missing & & 0.003*** & & -0.031***\tabularnewline
& & (0.000) & & (0.008)\tabularnewline
& & (0.000) & & (0.000)\tabularnewline
Constant & 0.005*** & 0.002*** & 0.106*** & 0.043**\tabularnewline
& (0.000) & (0.001) & (0.009) & (0.019)\tabularnewline
& (0.000) & (0.002) & (0.000) & (0.024)\tabularnewline
State, Industry, Year FE & Yes & Yes & Yes & Yes\tabularnewline
N & 995585 & 995585 & 4662 & 4662\tabularnewline
N clusters & 50 & 50 & 50 & 50\tabularnewline
Adj R-squared & 0.003 & 0.004 & 0.100 & 0.105\tabularnewline
Note: Analysis is based on Current Population Survey (CPS)
individual-level data. Sample is restricted to respondents without a
college degree; and individuals between 25 and 59 years old to mitigates
confounding influences that are specific to younger individuals who are
still in their qualification phase and older individuals who are
approaching retirement (Schulz et al., 2021; G\selectlanguage{ngerman}änser-Stickler et al.,
2022). OLS models estimate: (1) the probability of becoming any type of
self-employed (base category: not self-employed), and (2) the
probability of becoming a hybrid entrepreneur (base category: non-hybrid
entrepreneurs). Both outcomes are conditional on individuals being
full-time, paid employees in the previous period (t\selectlanguage{english} --\selectlanguage{english} 1). All control
variables---except for age and fixed effects---are binary indicators.
Fam Income Over \$75,000 is a dummy variable equal to 1 if the
respondent's household income falls into the highest income category
provided by CPS across the full sample, and 0 otherwise. Due to
approximately 15\% of income values being missing, Fam Income Missing
equals 1 if a respondent's income is missing but was assigned a value of
0 in Fam Income Over \$75,000, and 0 otherwise. The results remain
robust when excluding either or both of the income controls. Results are
reported as: coefficient (clustered standard error; p-value).
Significance levels: * p \textless{} 0.10, ** p \textless{} 0.05, *** p
\textless{} 0.01. & & & &\tabularnewline
\bottomrule
\end{longtable}

\selectlanguage{english}
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