FDI spillovers and its impact on the innovation performance
of Latin America
Name: Lisette Meppelink
Student number: 11355999
Date: June 22, 2018
Qualification: MSc. in Business Administration – International Management
track
Institution: Amsterdam Business School, University of Amsterdam
Statement of originality
This document is written by Lisette Meppelink who declares to take full responsibility for the
contents of this document. I declare that the text and the work presented in this document is
original and that no sources other than those mentioned in the text and its references have
been used in creating it. The Faculty of Economics and Business is responsible solely for the
Table of contents
Abstract……….. 4
1. Introduction………...5
2. Literature review………...8
2.1 Inward FDI and spillover effects ... 8
2.2 Product and process innovation ...11
2.3 FDI, formal competition intensity and innovation outcomes ...13
2.4 Informal competition and innovation ...15
2.5 Institutions and imitation tolerance...17
3. Conceptual model and hypotheses……… 19
3.1 Inward FDI and product- and process innovation performance ...20
3.1.1 Inward FDI effect on product and process innovation... 22
3.2 Moderating effect of formal competition intensity ...23
3.3 Moderating effect of informal competition ...25
3.4 Moderating effect of imitation tolerance ...27
4. Methodology……… 29
4.1 Sample and data collection ...29
4.2 Estimation Methodology ...31
4.3 Variables and measures ...32
4.3.1 Dependent variable ... 32
4.3.2 Independent and moderating variables ... 34
4.3.3 Control variables ... 36
5. Findings……… 37
5.1 Negative binomial regression ...40
5.2 Binary logistic regression ...44
6. Discussion……….46
6.1 Scientific relevance...50
6.2 Practical relevance...51
6.3 Limitations and future research ...51
Abstract
Over the past years, Latin America has proven to be a world region with fast-growing flows
of both inward and outward Foreign Direct Investment (FDI). The area has shown great
economic growth and enhanced innovative capabilities. Several authors have pointed out the
high inflows of FDI as the source of economic growth, but does this also apply to the greater
innovation performance? Is the effect of knowledge spillovers apparent in Latin America?
This study aims to shed light on the phenomenon of positive externalities resulting from
inward FDI flows in the often-neglected area of Latin America. It thereby advances prior FDI
spillovers literature and does not only examine the effect of inward FDI on the innovation
performance of Latin America, but also explores how (in)formal competition and imitation
tolerance moderate this relationship. Moreover, the innovation performance outcome is
further analyzed and distinguished between product and process innovations. Secondary data
is collected for 22 Latin American countries for the year 2010. The findings reveal that the
FDI spillover effect is present in Latin America, as the innovation outcome improves when
FDI inflows are high. However, this positive relationship weakens when there are large levels
of informal competition present. The results resemble a first step towards the fulfillment of a
large gap in research concerning innovation activities in Latin America.
Keywords: FDI spillover effect, innovation performance, product innovations, process innovations, informal competition, competition intensity, imitation tolerance, Latin America.
1. Introduction
Multiple studies have acknowledged the growing potentials of emerging economies (e.g.
Brenes et al., 2016). These economies are developing quickly and have become interesting for
developed economy multinational enterprises (MNEs) to invest in (Martin et al., 2015). Latin
America is such an emerging economy and has only relatively recently been open to Foreign
Direct Investment (FDI). From mid 1970 onwards, many Latin American governments started
opening their markets (Trevino and Mixon Jr., 2004). Even though not all economies have
responded similarly to the opportunities and challenges of globalization, many countries
experienced a positive effect on the economic performance and managed to catch up to other
regions in the world (Castellacci and Natera, 2016). Accordingly, several countries in Latin
America have been regarded as new engines of economic growth and have proved to possess
innovative and entrepreneurial capabilities (Lederman et al. 2013). Brazil has been part of the
BRICS – the new emerging economic powers of the world – since 2010 (Stuenkel, 2014),
Mexico and Colombia have been acknowledged as fast growing emerging economies and are
included in the MIKTA and CIVETS groups (The Economist, 2013), and both Brazil and
Mexico are currently members of the OECD (Brenes et al., 2016).
Data provided by UNCTAD 2017 shows a growing interest of foreign investors in Latin
America: from 2010 to 2016 the inward FDI increased from respectively 70.869 stocks to
138.766. In particular South America, as opposed to Central America, is responsible for this
large increase. The Economic Commission for Latin America and the Caribbean (ECLAC)
reported that in 2010, Latin America showed great resilience to the international financial
the high inflows of FDI has yielded new opportunities for Latin America as inward FDI can
stimulate economic growth and support infrastructure development. However, despite the
growing potentials and almost doubling amount of inward FDI in Latin America, relatively
little research has been done in this area.
MNEs are increasingly expanding operations to turbulent economies, requiring the
understanding of non-traditional markets. Traditional developed market research and theories
do not properly fit the unique social, institutional and economic contexts of emerging
economies (Wright et al., 2005). Much attention has primarily been given to China and India
in non-traditional market research, neglecting the importance of Latin America. An additional
gap in research is the lack of insights on the relationship between inward FDI and innovation
performance. The majority of FDI spillover research has focused on productivity outcomes
solely (e.g. Blomstrom and Kokko, 1998; Liang, 2017). Moreover, previous findings appear
to be inconsistent; some found a positive effect of FDI on productivity performance (e.g.
Buckley et al., 2007) others a negative effect (e.g. Furman et al., 2002; Wang and Kafouros,
2009). Since FDI is often viewed as the engine for economic development and countries
increasingly compete to attract FDI, it is essential for managers and policymakers to
understand the impact of inward FDI not solely on productivity outcomes but on innovation
as well (Garcia et al., 2013).
This paper aims to fill the gap in research by investigating the effect of inward FDI on the
innovative capabilities of Latin American economies. Hence, the following research question
is addressed: What is the impact of inward FDI on the innovation performance of Latin
American economies? Does this impact differ for product innovations and process innovations?
In order to answer this question, data has been obtained for the year 2010 for 22 Latin
American economies from six different databases. The large numbers in economic growth
and FDI flows make Latin America a relevant region for enhancing previous (emerging
economy) FDI spillover literature.
This study contributes to existing literature in multiple ways. First, by shifting the focus from
productivity outcomes to innovative outcomes. There is currently little research investigating
whether FDI poses a negative or positive externality on the production of new ideas in the
host country, even though innovation has been considered one of the driving forces behind
growth (Al Azzawi, 2012). Second, more insight is being gained into the often-neglected but
fast-growing area of Latin America. It thereby advances non-traditional market studies that
mainly concern larger emerging economies such as China (e.g. Lew and Liu, 2016; Liu et al.,
2010) and India (e.g. Feinberg and Majumdar, 2001). Third, this study extends existing FDI
spillover literature by aiming to understand the context where the local condition can alter the
main relationship. Comparatively little is known about the contingent local contextual factors
that influence how FDI spillovers can be captured (Li et al., 2016). Specific local factors for
Latin America are therefore included, such as informal competition and growing levels of
inward FDI. Additionally, a divergent approach towards intellectual property rights (IPR) is
practiced. Most studies regard to IPR protection as indicator of successful innovation
outcomes (e.g. Segerstrom et al., 1990). Yet, this study suggests that, especially for emerging
markets, the proposed positive IPR effects might not always apply. Lastly, this research
advances previous innovation literature by not only using the amount of patents as innovation
The remainder of this paper is structured as follows. First, the main concepts are elaborated
upon in the literature review. Based on the discussed literature, hypotheses are constructed
and visualized in the conceptual model. After, the research methodology is justified and the
results of the research are discussed. The paper ends with a discussion, including a summary
of the findings, the scientific and practical relevance and limitations of the research.
2. Literature review
2.1 Inward FDI and spillover effects
One of the reasons why emerging economies try to attract foreign investment is the
opportunity of acquiring new technologies such as product and process innovations
(Blomström and Kokko, 1998). FDI is seen as a main source for diffusing such technological
advances (De Bondt, 1997). Emerging economies often aim to obtain advanced technologies
from developed countries through spillovers in order to gain a base for establishing domestic
innovation capabilities (Cheung and Lin, 2003).
Four major spillover mechanisms have been identified by previous literature (Blomström and
Kokko, 1998; Spencer, 2008): demonstration effects, employee turnovers, domestic business
linkages, and competitive pressures. Demonstration effects occur because inward FDI enables
local firms to observe the technologies, organizational practices and strategies of the investing
MNE. Consequently, local firms can apply the observed techniques in their own operations
and develop innovative capabilities (Blomström and Kokko, 1998). Domestic business
linkages can cause both positive and negative spillovers. On the one hand, interactions
between local firms and MNEs through subcontracting, licensing and other types of
1998). Strong relationships between MNEs and local firms can lead to knowledge sharing.
The knowledge gained from MNEs can in return push local suppliers and distributors to raise
their quality and service standards (Brash, 1966). On the other hand, MNEs are able to lock in
the best local goods and service suppliers or distributors when fully utilizing their capacity
(Spencer, 2008). Additionally, an MNE’s entry can limit local firms’ access to scarce
resources and can raise prices of input goods. The employee turnover spillover mechanism
arises as MNEs often pay higher wages than local firms. MNEs are therefore able to hire
away the most qualified employees from the local firms. Yet, simultaneously, employees that
have worked at an MNE can switch jobs to a local firm and diffuse its knowledge gained at
the MNE (Meyer, 2004). The last spillover mechanism is related to competitive pressures.
Inward FDI increases competition as MNEs enter the local market. Since MNEs usually
possess a greater productivity rate than their local counterparts (Haddad and Harrison, 1993),
competition from an MNE will force local firms to increase their productivity in order to keep
up in the competitive challenge (Blomström and Kokko, 1998). Another important beneficial
externality when imitating an innovation is the cost and risk reduction for the imitator. Before
an innovation is widely adopted, potential adopters face great risks and costs since little is
known about the effectiveness of the innovation and much research needs to be done. These
risks and research costs are made by the first adopter but are spared to others who imitate the
first adopter. Spillover effects are argued to be more important for emerging economies as
these economies have a limited supply of technological skills and information (Blomström
and Kokko, 1998).
It must be recognized that spillover mechanisms do require a certain amount of time to effect
operationalizing the spillover benefits (Chen, 1996; Meyer and Sinani, 2009). However, this
effect is weakened for emerging economies facing a large technology gap compared to the
foreign investor. In such a scenario, local firms will be able to benefit even from standardized
knowledge that is easy to obtain. (Meyer and Sinani, 2009). The probability of knowledge
diffusion also relies on the type of knowledge. Polanyi (1966) made a distinction between
codified and tacit knowledge, also often referred to as tangible and intangible knowledge.
Whereas codified knowledge can be translated in formal, symbolic language, tacit knowledge
is hard to articulate and is acquired through experience. Thus, codified knowledge is more
easily transferable compared to tacit knowledge. Spencer (2008) developed five critical
principles regarding knowledge spillovers. First of all, knowledge – in particular more
codified forms of knowledge – can diffuse even to distant local firms with which the MNE
has had no direct contact. On the contrary, tacit knowledge diffuses far more slowly and
irresolute. Furthermore, knowledge tends to endure in complex systems and individual
components of knowledge decrease in value when separated from the complete system of knowledge and organizational practices. In addition, the local firm’s absorptive capacity does
not only depend on the volume of its existing internal knowledge, it also highly depends on
the amount of overlap in which the knowledge to be acquired resides, i.e. the level of
common knowledge. The final principle acknowledges that local firms are able to improve
their process by acquiring tacit knowledge or by adopting technologies or organizational
practices that manifest that knowledge.
Despite the fact that MNEs rarely aim to strengthen local competitors, many do tolerate
spillovers and avoid imposing strong barriers to prevent these spillovers from happening
(Spencer, 2008). In general, there are large differences in capabilities and market scope
MNE, even though spillovers may occur. Besides, overprotection of knowledge assets can be
as costly as underprotection (Liebeskind, 1999) and reversed spillover effects might occur
where MNEs and local firms learn from each other (Sartor and Beamish, 2014). Overall,
inward flows of FDI are suggested to increase the possibility of (technological) knowledge
diffusion needed for innovative activities.
2.2 Product and process innovation
Innovation is a highly researched topic in the International Business field as it is an important
asset for surviving todays’ highly competitive and globalized economy (Nieto and Rodriguez,
2011). It has been largely recognized as a crucial element of a competitive advantage
(Danneels, 2002; Porter, 1990) and essential for sustaining such competitive advantages.
Innovation has been defined by Damanpour and Gopalakrishnan (p.3, 2001) as ‘an organization’s means to adapt to the environment, or to preempt a change in the environment,
in order to increase or sustain its effectiveness and competiveness’. Two types of innovations
can be distinguished: product and process innovation (Abernathy & Utterback, 1978). Product innovation concerns the development of new products or services that meet markets’ needs.
Process innovation, on the other hand, regards the production or service operations of these
products and services (Damanpour and Gopalakrishnan, 2001). Both innovations can stem from two major sources: internal R&D and imitation of other firms’ innovations (Lewin and
Massini, 2004). Simply imitating other firms will not directly result in certain (cost)
advantages or capabilities. The imitator needs to improve the innovation in order to gain
advantages over the first mover. As such, process innovations are said to be important for the
requires firms to be capable of developing both product- and process innovations, which are
continuously being optimized and refined.
There is a difference in adopting product innovations and process innovations; each demands
a different organizational skill. Product innovations require meeting customers’ needs and
manufacturing the product, while process innovations require the ability to apply technologies
that can improve the efficiency of product development (Ettlie et al., 1984). According to
Damanpour and Gopalakrishnan (2001) product innovations occur more early on than process
innovations. Additionally, the process of translating knowledge to business practices is
generally less complicated for product innovations since product innovations tend to consist
of more codified knowledge compared to process innovations, which require complex and
tacit knowledge (Nieto and Rodriguez, 2011). Cimoli (2002) explains the different knowledge
requirements per innovation type by distinguishing between technology and information.
Information can be spread across firms as it can be written down and be reproduced by
individuals. Technology, on the other hand, includes tacit and specific knowledge and cannot
be diffused as a whole. Technology is embodied in individuals, organizations and networks
and is therefore much more complicated to reproduce.
All in all, product- and process innovations demand different inputs and produce contrasting
outcomes. They should therefore be treated as different processes as well. Though, literature
has primarily dealt with overall innovative activity, i.e. the totality of both product- and
process innovations, or focused on one innovation type solely, i.e. either product or process
innovation (Bonannoa and Haworthb, 1998). This study acknowledges the different
innovation types and aims to separate the effect of inward FDI for product innovations and for
2.3 FDI, formal competition intensity and innovation outcomes
The competitive intensity of firms is described by Barnett (1997) as the magnitude of effect
that a firm has on its competitors’ survival chances. Being a weak competitor means that the firm has only limited capabilities to ‘harm’ its competitors’ life chances, whereas strong
competitors reduce these life chances to a much larger extent. Auh and Menguc (2005)
describe a competitive intense market as a market that has a large number of competitors and a lack of potential growth opportunities. When competition further intensifies, firms’ behavior
will be greatly affected by the actions and contingencies of competitors. As a result, the
predictability and certainty of a competitive intense market reduces. These high levels of
uncertainty lead to incentives for firms to innovate in both products and processes, explore
new markets, find new ways to compete and learn how to differentiate from its competitors
(Zahra, 1993). Delbono and Denicolo (1990) explain competition intensity based on the
division between Cournot competition and Bertrand competition. Cournot competition applies when firms’ decision variables are output levels and Bertrand competition when firms’
decision variables are prices. Cournot competition generally leads to lower output and higher
prices than Bertrand competition, hence the former is said to be a situation where competition
is less intense. Assuming the competition of a homogeneous product, the incentive to
introduce an efficiency- or cost-reducing innovation is greater in conditions of Bertrand
competition. Bester and Petrakis (1993) further developed this theory by assuming the case
for differentiated products instead of homogeneous products. They found that for products
with low differentiation, high competition intensity increases the incentive to innovate. While
for products with high differentiation, low competition intensity increases the incentive to
When the international openness of an economy increases and inward FDI is attracted, the
competition intensity of the economy will increase. The exposure to larger competition from
MNEs may force local firms to be more productive and to enhance their innovation
performance (Kokko, 1996). Early economist such as Arrow (1962) and Delbono and
Denicolo (1990) already agreed upon that the more competitive an environment is, the greater the firm’s incentive to innovate will be. In addition, competition intensity can lead to mimetic
isomorphism (McKinsey et al., 2005), where local firms imitate the strategic behavior of
MNEs. Besides, emerging economies often try to increase competitiveness by acquiring and
developing new technologies (Wang and Kafouros, 2009). On the contrary, increased
competition in local markets may also have negative consequences for domestic economies.
Foreign firms that possess greater capabilities than local firms may steal market from the local
players and thereby force local firms to reduce output and increase costs (Aitken and
Harrison, 1999; Konings, 2001). Furthermore, increased competition causes saturated
markets, which leads to downward pressures on prices and a lower profitability (Hanson,
2001).
The conflicting findings regarding the effect of competition intensity on innovation
performance could be explained by the theory of Aghion et al. (2005). Their research found
an inverted-U relationship between competitive pressure and innovation activities. Thus, for
low levels of competitive pressure, an increase in competition causes an increase in
innovative activities. This is referred to as the escape competition effect; where
neck-and-neck firms innovate in order to escape competition. However, when competition becomes too
intense, the incentives to innovate are diminished as the rent-dissipation effect comes into
play. The increased competition generates lower post entry rents, which discourages
Overall, earlier studies show that there is no consensus concerning the competitive pressures’
impact on innovation outcomes. The one thing that researchers do agree upon is that
innovation is an interactive process (Freeman, 1987) and the result of a social process that
develops best when there is an intensive interaction between the suppliers and buyers of
goods, services, knowledge and technology (Cimoli, 2002). Firms do not compete in
isolation. Especially not in todays’ globalized world where technological developments are
taking place at an ever-increase pace. These developments force firms to respond quickly and
it makes it challenging for firms to produce and covert knowledge into innovations all by
themselves.
2.4 Informal competition and innovation
In emerging markets, firms typically face competitive threats from three groups: formal
domestic firms, foreign MNEs and informal firms (Iriyama et al., 2016). The informal sector
is an economy circuit where the activities related to the production and trade of goods and
services are not registered or conducted by unregistered entities. Such activities operate
outside of government regulation and tax systems (Heredia et al., 2017). The informal
economy circuit is especially large in emerging economies. According to Schneider (2002),
more than 50% of the gross domestic product of emerging economies is connected to the
informal economy. In the 2010 World Bank Enterprise Survey of firms in 22 Latin American
and Caribbean countries, 63.3 percent competes against informal firms and 31.4 percent
ranked competition from informal firms as one of their top three obstacles of doing business.
government institutions, causing the growth of the informal sector (Loayza, 1999). The large
informal sector is fostered by the complicated procedures and burdensome regulations that are
present in Latin America. The region scores significantly low on Ease of Doing Business
indicators, as Latin American economies require the largest numbers of procedures (12) and
days (66) to start a new business (González and Lamanna, 2007). An increase in informal
competition negatively affects economic growth in two ways. First, it reduces the availability
of public services for everyone in the economy. Second, it increases the totality of activities
that use some of the existing public services less efficiently or not at all (Loayza, 1999).
Informal competitors enjoy relative cost advantages as they usually fail to comply with
economic regulations and tax obligations. These cost advantages allow informal competitors to undervalue their products and steal market share from formal firms (OECD, 2009). Therefore, even though competition is considered to be the engine of economic growth in
most markets as it induces higher rates of productivity growth, competition between formal
and informal firms is not necessarily productive (González and Lamanna, 2007).
Formal and informal firms differ on many aspects.First of all, the type of products offered by
informal firms is typically of lower quality than those produced by formal firms (Amaral and
Quintin, 2006). Secondly, informal firms are much smaller and much less productive than
formal firms (La Porta and Shleifer, 2008). Informal firms serve different customers, mostly
low-income consumers. They do not advertise, have less capital and rely to a smaller extent
on public goods. Furthermore, managers of informal firms are less educated and have less
human capital than managers of formal firms (La Porta and Shleifer, 2008). Additionally, the
average education level is considerably lower in the informal sector compared to the formal
sector (Funkhouser, 1996). Very few formal firms have been previously informal, inconsistent with the theory that formality is a later stage of a firm’s life cycle when the firm is growing.
The vast majority of informal firms begin and end their existence as unproductive informal
firms (La porta and Shleifer, 2014). Informal firms are argued to be so inefficient that taxing
them or forcing them to comply with government regulations would most likely put them out
of business (La Porta and Shleifer, 2008). There is no inducement from available evidence for
assuming that informal firms would increase their productivity if they register. Entrepreneurs
are thus not likely to use the informal sector as a method of acquiring knowledge at lower
costs.
Related research performed by Mendi and Costamagna (2017) showed that informal
competition has a negative effect on both product and process innovations. The informal sector typically disrupts formal firms’ innovation practices due to cost-cutting pressures. This
makes informal firms a great obstacle to formal firms’ performances and innovation
capabilities. Since excessive regulations are proposed to be the main reason for the existence
of a large informal sector, informal sectors and institutions are closely connected in the sense that the informal sector can be partly explained by a country it’s institutional efficiency and
vice versa (Mendi and Costamagna, 2017). Overall, the informal sector is proposed to play a
large role in emerging economies hence its influence cannot be overlooked.
2.5 Institutions and imitation tolerance
Institutions are defined by North (1991, p. 97) as ‘the humanly devised constraints that structure political, economic and social interaction.’ Three main institutional pillars are
identified by previous research (e.g. Scott, 1995; Kostova, 1997): regulative, cognitive and
systems. Castellacci and Natera (2016) highlighted the importance of combining imitation
policy and innovation policy for increasing the growth rate of emerging economies. These
institutional factors, both normative and regulatory, have had a strong influence in the
catching up process of emerging economies. Governments often protect local firms from
initial failures and encourage them to learn from MNEs (Li and Kozhikode, 2009).
Cerqueti et al. (2016) describe imitation as an inverse measure of Intellectual Property Rights
(IPR) protection. According to the authors, there must be a balance between innovation and
imitation as an unbalance between the two will be costly to society. Too many imitations will
hinder economic growth while too little imitations decrease the number of innovation
diffusions. Conversely, governments should seek to balance the ratio between innovations and
imitations and should intervene when needed. However, this is not always practiced, as the
innovation and imitation ratio is highly dynamic and uncertain. It is impossible to establish
beforehand whether the ratio will go up or down.
Multiple authors have agreed upon the fact that imitations can benefit the society on the
whole by leading to a larger number of innovations (e.g. Sohn, 2008; Bessen and Maskin,
2009).Although imitation can weaken the incentive to innovate as it reduces the current profit
of the innovator, it raises the probability of further innovation, which could lead to new
profitable discoveries (Bessen and Maskin, 2009). Furthermore, Cerqueti et al. (2016) state
that imitations can mitigate damages introduced by monopolies and hasten the innovation
diffusion process. Fershtman and Markovich (2010) argue that imitation may be particularly
beneficial when firms have different innovative capabilities and are able to combine these
different capabilities by imitating. According to the authors this could eventually lead to a higher consumers’ surplus and higher value for firms than a strong patent protection regime.
Imitation is said to be especially important in economies that are far from the technological
frontier, as imitation can help these economies grow quickly. Besides, the diffusion of already
existing technologies is relatively easy. Thus, when a country is on the technological frontier
it can grow quickly by only imitating innovations (Hikino and Amsden, 1994).
3. Conceptual model and hypotheses
Figure 1 visualizes the conceptual model of this study by showing the main concepts and its
proposed effects. The next section will further explain this conceptual model and the motives
behind the hypotheses.
Figure 1. Conceptual model
H1: Inward FDI LA Innovation performance
LA (+)
H1a: Product innovation over process innovation (+)
Competition LA H2: Formal competition intensity (+) H3: Informal competition (-) Institutions LA H4: Imitation tolerance (+)
3.1 Inward FDI and product- and process innovation performance
Emerging economy firms are in general not likely to possess greater innovative technology
advantages over their equivalents in developed economies (Peng et al., 2008), but the
presence of foreign investors can enhance the innovative performance of local emerging
economy firms operating in the same sector (Crescenzi et al., 2015). Due to the (often) long
histories of economic and political uncertainty, Latin America has traditionally suffered from
low levels of entrepreneurship and innovation (Aguilera et al., 2017). However, during the
end of the twentieth century several structural reforms were adopted in many Latin American
countries. This period of economic crisis and reforms induced firms to rethink their activities,
improve their competitiveness and seek for opportunities outside of the domestic market
(Dominguez and Brenes, 1997). The changes eventually led to a new period of stability and
economic growth (Cuervo-Cazurra, 2008). The structural reforms caused the adoption of
pro-market reforms and a greater international openness, which stabilized the economies and also
led to higher inflows of FDI. Economic growth resumed bringing Latin America to be part of
the emerging economies (Ciravegna, 2012). The increasing inflows of FDI provided a range
of new opportunities. Further economic growth was fueled, infrastructure development
supported and firms showed greater innovative capabilities (O’Neil, 2014).
The enhanced innovative performance of Latin America could be explained by the recent
development in offshoring activities. Over the past few years MNEs have shifted from not
only offshoring manufacturing activities but also knowledge to emerging economies (Couto et
al., 2008). There are several reasons for offshoring R&D to emerging economies: strategic
asset seeking (Dunning and Narula, 1995); gaining knowledge and internalizing technical
spillovers (Feinberg and Gupta, 2004); diversifying knowledge and using the gained
and leveraging both the growing talent pool and growing technical competence in emerging
economies (Li and Kozhikode, 2009). Nieto and Rodriguez (2011) found a positive effect of
offshoring R&D on the innovation performance of MNEs. Positive results will stimulate
MNEs to continue the offshoring process and investigate in possible other emerging
economies. Subsequently, emerging economy firms have begun to catch up and develop their
own innovative capabilities. According to Mathews (2006) a good catching up strategy
contains three crucial elements: 1) linking with MNEs to access key resources; 2) leveraging
existing resources to gain a foothold in the target industry; and 3) learning from the linkages
and leverage. Thus, MNEs are said to play an important role in the catching up of emerging
economies and as such in the development of innovations.
Emerging economy governments have been aware of the beneficial externalities that come
with inward FDI. They have started to create a more favorable climate for MNEs and
encouraged domestic firms to collaborate with those MNEs in order to develop innovative
capabilities (Kim, 1997; Li and Kozhikode 2008; 2009). Despite the large risks for MNEs to
spillover knowledge, there is also the possibility of gaining reversed spillover effects as
argued by Sartor and Beamish (2014). The authors state that MNEs from developed
economies and emerging economy firms can learn from each other. As the technological- and
demand uncertainty for an MNE investing in an emerging economy increases, the MNE will
be willing to loosen its organizational control and learn from the local firms. When more
tacit/process innovation type of knowledge is desired, MNEs are likely to rely on socially
oriented mechanisms to enhance their learning (Makhija and Ganesh, 1997). Consequently,
local firms can teach MNEs about the local technological environment (Govindarajan and
technological knowledge of MNEs. FDI is therefore said to act as a technology transfer
vehicle between developed and emerging economies (Borensztein et al., 1998).
All in all, the reversed spillover effect and positive results from (knowledge) offshoring could
ensure that MNEs will continue to invest in Latin America. These investments are assumed to
generate knowledge spillovers, which are in turn expected to improve the innovative
capabilities of Latin American economies. Hence, the following hypothesis is formulated:
Hypothesis 1. Inward FDI has a positive effect on the innovation performance of Latin
American economies
3.1.1 Inward FDI effect on product and process innovation
Initial innovations of emerging economy firms tend to be production process related rather
than product development related (Hobday, 1995). This could be attributed to the fact that
emerging economies primarily serve as original equipment manufacturers (OEMs) for MNEs
(Li and Kozhikode, 2009). These OEM arrangements allow emerging economy firms to take
an active part in the value-added activities but not so much in the product development
technologies (Hobday, 1995). However, more recent literature highlights the growing activity
of outsourcing knowledge to emerging economies (e.g. Couto et al., 2008), where the
emerging economy does not just serve as an OEM but as an R&D developer. Another
important development is the fact that Latin America has become an interesting destination
for outsourcing services (Manning et al., 2010). The Global Services Report (2017) shows
that several Latin American cities are listed among the Top 20 offshoring/outsourcing
destinations for business services. These developments could lead to more tacit,
As previously mentioned, the process of translating knowledge to business practices is
generally less complicated for product innovations since product innovations tend to consist
of more codified knowledge compared to process innovations, which require complex and
tacit knowledge (Nieto and Rodriguez, 2011). The most codified knowledge may be diffused by simply carefully observing a practice, by examining a firm’s end products or other
processes that do not require extensive interaction among employees from the two firms
(Spencer, 2008). Though, the greater the tacitness, complexity and specificity of an MNEs
knowledge resources, the more difficult it will be for local firms to imitate the innovations or
practices that require these knowledge resources (Reed and DeFillippi, 1990).
Thus, product innovation type of knowledge is more easily accessible compared to process
innovation type of knowledge, as it is less tacit and more easily codified. This brings about
the following hypothesis:
Hypothesis 1a. The positive effect of inward FDI on innovation performance is stronger for
product innovations over process innovations
3.2 Moderating effect of formal competition intensity
Firms in emerging markets typically face competitive threats from three groups: formal
domestic firms, foreign MNEs and informal firms (Iriyama et al., 2016). Formal firms are
likely to recognize other formal firms as closer competitors than informal firms, which are
perceived as more distant rivals. When formal competition is low, greater portions of formal firms’ attention capacity can be allocated to informal firms. On the contrary, when formal
informal firms, high levels of formal competition are proposed to increase the formal firms’
incentives to innovate.
Moreover, formal competition intensity is suggested to foster the positive relationship
between inward FDI and innovation for several reasons. First of all, FDI inflows bring
increased formal competition. The exposure to larger formal competition may force local
firms to be more productive and to enhance their innovation performance (Kokko, 1996).
Multiple studies have already acknowledged competition as enhancer of FDI spillovers (e.g. Sjöholm, 1999; Blomström et al., 1994; Kokko, 1996). One possible explanation is given by
Blomström and Sjöholm (1999). They argue thatMNEs possess a wide range of technologies
of which they can choose from when investing abroad. This technology transfer is adapted to
the competitive situation in the host economy. If MNEs face stronger competition in the local
market, they will be forced to use more advanced technology in order to assure their market
share (Wang and Blomström, 1992). Likewise, the increased competition as a consequence of
foreign entry forces domestic firms to become more efficient and innovative as well. Thus,
spillovers can be expected to increase with competition in the local market (Crespo and
Fontoura, 2007).
Second, when competition is intense, firms need to engage in risk-taking and proactive
activities (Cui et al., 2005). Due to the highly globalized market firms experience nowadays,
firms are becoming more dependent upon externalities outside of its own. It has become
almost impossible for an individual firm to produce all relevant knowledge itself. Let alone to
translate this knowledge into innovative products or production processes. Firms are
dependent upon external complementary knowledge and know-how (Cimoli, 2002). Hence,
multiple (spillover) externalities. As an increase in inward FDI is suggested to bring in more
of such knowledge externalities and competitive intense markets forces MNEs to bring in
more advanced technologies, competition intensity is proposed to aggravate the effect of
inward FDI on innovation performance.
Conjointly, Bester and Petrakis (1993) proposed that a competitor in a situation of intense
competition will favor product innovations over process innovations. This can be clarified by
the fact that a competitive intensive market forces firms to innovate on a continuous and fast
pace. Product innovations require less complicated knowledge and are therefore in general
more easily converted into practice than process innovations. Thus, competitive pressures are
proposed to increase a firms’ preference to improve and invent products over processes.
In conjunction with above findings, competition intensity is suggested to strengthen the
positive effect of inward FDI on innovation performance. Henceforth, the following
hypothesis is formulated:
Hypothesis 2. The positive effect of inward FDI on innovation performance is stronger when
the competition intensity in Latin American economies is higher
3.3 Moderating effect of informal competition
McCann and Bahl (2017) define informal firms as firms that produce and sell legal products
and services but remain unregistered, allowing them to avoid legal requirements such as taxes
and regulations. The informal sector often targets low-income consumers who cannot afford
effectuates the unemployed from the formal sector but rather as a sector whose products
overlap and compete with those from the formal sector, despite the quality gap (Banerji and
Jain, 2007). Formal firms might thus be forced to compete directly against informal firms for
the same resources, possibly leading to an inefficient allocation of resources in the economy
and hence an efficiency loss (Mendi and Mudida, 2017). As mentioned earlier, formal
competition is considered to be positively affecting the relationship between inward FDI and
innovation. Competition between formal and informal firms on the other hand, is not
necessarily productive (González and Lamanna, 2007). Informal competition can be
damaging to the overall economic performance, as the cost advantage informal firms enjoy is
the outcome of neglecting business regulations.
Informal competition is found to have a negative effect on both product and process
innovations (Mendi and Costamagna, 2017). Informal firms may affect formal firms’
innovation decisions in a number of ways. First, the informal sector generally disruptsformal firms’ innovation practices when formal and informal firms compete for similar customers
and resources (McGahan, 2012). As a consequence, input resources such as high skilled
human capital can become more scarce to formal firms. The informal sector generally offers
readily available jobs that require low skills, distorting the process of skills accumulation by
formal firms (Mendi and Costamagna, 2017). Second, informal firms have a large impact on
the competition in product markets. By their very nature, informal firms face lower entry
costs than formal firms since they are not being taxed (Djankov et al., 2002; McKenzie and
Sakho, 2010). Due to the low entry barrier, informality can quickly raise the number of competitors for a firm’s product (Mendi and Costamagna, 2017). The increasing informal
competition will lead to lower prices for the customer, as informal firms will compete on
Mudida, 2017). This event can pressurize formal firms to cut costs as well, making it
unattractive to be spending on R&D practices. Third, informal firms cause competitive
pressure on product quality, as they typically produce lower-quality versions of the products
produced by formal firms (Banerji and Jain, 2007). In emerging economies like Latin
America the incomes of consumers are generally low hence consumers might be unable to
afford the higher-quality product and opt for the lower-quality one.
All in all, there are many arguments prompting that informal firms form a great obstacle to formal firms’ performances and innovation capabilities (Mendi and Costamagna, 2017).
Based on these disruptive characteristics of informal firms, the third hypothesis is formulated
as follows:
Hypothesis 3. The positive effect of inward FDI on innovation performance is weakened by
the size of the informal economy in Latin American countries
3.4 Moderating effect of imitation tolerance
According to Cerqueti et al. (2016) imitation is an inverse measure of IPR protection. As IPR
refers to the legal protection provided for innovative firms, it indicates the extent to which a
firm is able to protect and capture the economic value of its innovations (Kafouros, 2012).
The adverse would thus be a condition where the firm is not able to protect its innovations
and where imitation is stimulated. Whereas IPR protection has previously been regarded to as
an essential for attracting inward FDI. More authors have started recognizing the drawbacks
of strong IPR protection and the benefits of imitation (e.g. Sohn, 2008; Bessen and Maskin,
incentive to innovate than before, despite its lowering rents, as it finds itself in a
neck-and-neck competition with a technologically equal rival and will remain so until it innovates again
(Aghion et al., 2001).
Imitation is said to be beneficial for the entire society as it alleviates the damage caused by
monopolies and thus increases consumers’ surplus (Cerqueti et al., 2016). Fershtman and
Markovich (2010) argue that a weak patent protection regime will eventually lead to higher
value for firms as opposed to a strong patent protection regime. According to Kafouros et al.
(2012), MNEs can profit more easily in economies where IPR protection is less effective
since knowledge spillovers tend to be higher in these economies. Imitation is also argued to
be one of the most evident spillover channels (Crespo and Fontoura, 2007). Introducing a new
technology may be too expensive and risky for local firms to undertake hence a technology
that has already been used successfully by an MNE is more encouraging for local firms to
adopt. Imitation engenders more external discoveries and leads to reversal knowledge
spillovers, in which the MNE and the local firm can learn from each other. Pisano (2006)
states that other mechanisms such as technological complexity, careful assignment of
responsibilities and possession of complementary co-specialized resources that are
unavailable to other firms, generates more effective protection of innovations.
All in all, economies where imitation is more readily practiced are proposed to provide an
attractive environment for MNEs. Knowledge spillovers are more easily realized, enhancing
the conditions for new innovation developments. A tolerant policy towards imitation is
therefore expected to have a positive moderating role on hypothesis 1, forming the fourth and
Hypothesis 4. The positive effect of inward FDI on innovation performance is strengthened
when an economy has a high imitation tolerance
4. Methodology
4.1 Sample and data collection
The underlying population of this study is the totality of emerging economies as these
economies have proven to develop quickly (Brenes et al., 2016). The final empirical setting
choice is Latin America based on three main reasons. First of all, several countries in Latin
America have been regarded as new engines of economic growth and have shown to possess
innovative and entrepreneurial capabilities (Lederman et al. 2013). Secondly, data provided
by UNCTAD 2017 illustrates a growing interest in Latin America; from 2010 to 2016 the
inward FDI increased from respectively 70.869 stocks to 138.766. Lastly, relatively little
research has been done in this area despite the growing potentials and almost doubling
amount of inward FDI. Most studies concerning the effect of inward FDI on the innovation
performance of emerging economies focus on larger emerging economies such as China and
India (e.g Lew and Liu, 2016; Feinberg and Majumdar, 2001)
Based on a similar looking study of Godinez and Liu (2015) a country-level unit of analysis is
used. Data is obtained for 22 Latin American countries for the year 2010. Unfortunately,
multiple challenges when conducting research in Latin America have been acknowledged.
There is a lack of research networks for data collection and problems regarding data gathering
generalizations derived from data gathered in developed countries are not necessarily
applicable to emerging economies (Burgess and Steenkamp, 2006). For validity reasons the
quality of the research could have been improved by creating a longitudinal panel dataset that
includes multiple years. However, the majority of the data is dependent upon the availability
of the World Bank Enterprise Survey data. As this survey is not conducted on a yearly basis
and the only fully complete year for all 22 Latin American countries is the survey conducted
in 2010, only one year can be analyzed correctly. A similar method was practiced by Mendi
and Costamagna (2017); their research uses the 2006 World Bank Enterprise Survey and is
hence solely focused on one year (2006) as well.
The quantitative analysis is thus performed by use of secondary data and, consistent with
many previous studies, mainly gathered from the World Bank Enterprise Surveys (e.g. Meyer
and Sinani, 2009; Gorodnichenko et al., 2014; Kayalvizhi and Thenmozhi, 2017). The World
Bank Enterprise Surveys database consists of firm survey responses of over 19,000 firms in
47 developing countries. The survey employs standardized survey instruments and a uniform
sampling methodology to minimize measurement error and to yield data that are comparable
across economies (González and Lamanna, 2007). Mostly developing countries are
administered (Mendi and Costamagna, 2017). However, not only data from the World Bank
has been used. To prevent triangulation of data and to assure data credibility, four other
sources have been consulted: WIPO, UNCTAD, the World Economic Forum’s Global
4.2 Estimation Methodology
Hypotheses 1, 2, 3 and 4 are being analyzed by use of a Generalized Linear Model (GLM).
The dependent variable for these hypotheses is the number of patent applications. Thus, the
outcome variable contains data in the form of counts and is not normally distributed. Using an
Ordinary Least Squares (OLS) regression is considered a problematic strategy for analyzing
count data for two main reasons. First of all, an OLS regression is likely to produce
non-sensical, negative predicted values for the expected count. Secondly, the validity of an OLS
regression depends on variance assumptions that are unlikely to be met in count data
(Gardner, Mulvey and Shaw, 1995). There are alternative regression models based on
non-linear models for the expected counts that respect the characteristic of a non-negative
variable. The most practical one is considered to be the Poisson regression (Gardner, Mulvey
and Shaw, 1995), which requires the dependent variable to follow a Poission distribution and
the mean and variance of this variable to be close. However, the goodness-of-fit test rejects
the Poisson distribution assumption of our dependent variable. The one-sample
Kolmogorov-Smirnov is highly significant (p<0.01) indicating overdispersion. The mean of the total patent
applications is 127.18 while the variance is 66504.0129. As such, a Poisson regression would
not be appropriate. To correct for overdispersion the negative binomial regression is
recommended by multiple sources (e.g. Gardner et al., 1995; Allison and Waterman, 2002).
The negative binomial model was originally practiced by Greenwood and Yule (1920) to
represent accident proneness. The estimation is particularly useful in accounting for the
overdispersion issue as it rationalizes overdispersion. In comparison to Poisson distribution,
the negative binomial assumes that accidents of the dependent variable are Poisson
distributed, but the values of the variable do not have the same mean rate (Land, McCall and
coefficients for large numbers of dummy variables (Allison and Waterman, 2002). Since this
study does not contain a large sample size and no large numbers of dummy variables, no
problems regarding the estimate coefficients are foreseen.
The number of patent applicants is not the only dependent variable to be tested as the interest
of this study also lies in the difference between product- and process innovations. The binary
logistic regression is the estimated efficient measure for testing this hypothesis (1a) as the
dependent variable is a dichotomous variable that takes value 0 for product innovations and 1
for process innovations. Similar to OLS, the independent variables can either be continuous or
categorical. The logistic regression model makes no distributional assumptions. Only the
assumptions of linearity and additivity need to be verified in addition to the usual assumptions
about independence of observations and inclusion of important control variables (Harrell,
2015). Unlike OLS whose goal is to predict a score on some outcome measure, the goal of
logistic regression is to assess the likelihood of falling into one of the outcome categories
based on a set of independent variables (Maroof, 2012).
4.3 Variables and measures
4.3.1 Dependent variable
Innovation performance Latin America. Following a myriad of previous studies (e.g. Garcia
et al., 2013; Funk, 2014; MacGarvie, 2006; Aghion et al., 2015; Guler and Nerkar, 2012;
Lahiri, 2010), innovation performance is measured by the use of number of patent
applications. Patents are unique and proposed to visualize the method of technology transfer
(e.g. Henderson et al., 1998). The measure of patent filings provides a fairly good, although
researches have operationalized patent citations as an indicator of knowledge spillovers (e.g.
Jaffe et al., 1993; Branstetter, 2006; Salomon and Shaver, 2005). In accordance with the
research ofWoo et al. (2015),this study draws on the patent data from the World Intellectual
Property Organization (WIPO). The WIPO distinguishes patent applications between
domestic and foreign applicants. Hence, the WIPO data is considered to be a good proxy of
the actual patent filings done by Latin American firms and cannot be biased by influences of
(large) foreign firms.
Product- and process innovations. Consistent with the 2011 paper of Nieto and Rodriguez,
the innovation performance outcome is further divided into product and process innovations.
This division provides a more accurate and detailed image of the innovation performance of
Latin America than the number of patent applications solely, as the patent counts capture both
product and process innovations (Fu et al., 2011). Hence, using product and/or process
innovations alongside patent application counts provides a valuable complement (Salomon
and Shaver, 2005; Garcia et al., 2013). The World Bank Enterprise Survey data provides two
proxies for distinguishing between product and process innovations; one being the amount of
firms that introduced a new product or service and the other being the amount of firms that
introduced a process innovation. As this study is performed on a country-level unit of
analysis, the totality of firms introducing a product- and/or process innovation has been
computed. This results in a total percentage of firms per country introducing a product
innovation and a total percentage of firms per country introducing a process innovation.
Thereafter, one variable has been created in order for the dependent variable to be appropriate
for binary logistic regression. This variable, labeled as Type of Innovation, is dichotomous
process innovations in that country and value 1 if the percentage of process innovations over
products innovations is higher.
4.3.2 Independent and moderating variables
Inward FDI Latin America. Consistent with related studies such as those of Trevino et al.
(2008) and Castellacci and Natera (2016), the inward FDI is operationalized by the amount of
inflows in US dollar (adjusted for inflation). This data is subtracted from the United Nations
Conference on Trade And Development (UNCTAD). The Kolomogorov-Smirnov test was
run in order to check the normality of variables. The results were significant for the
independent variable (p<0.05), implying that the distribution of the sample is significantly
different from a normal distribution (Field, 2009). Inward FDI is non-normal and positively
skewed. To correct for positive skewness a log transformation was performed (Field, 2009).
Formal competition intensity. This variable is constructed using the World Economic Forum’s
Global Competitiveness Index. The index ranks countries according to 12 pillars of
competitiveness (Schwab, 2010) and has been widely used by scholars studying competition
intensity (e.g. La Porta and Shleifer, 2008). The 12 pillars of competitiveness are: institutions,
infrastructure, macroeconomic environment, innovation, health and primary education,
business sophistication, higher education and training, market size, goods market efficiency,
technological readiness, financial market development and lastly labor market efficiency
(Schwab, 2010). The index ranges from 1 to 7, where 1 indicates a country with very low
levels of global competitiveness and 7 a country with very high levels of global
competitiveness. For reference, the index of 2010-2011 ranged from 2.73 (Chad) to 5.63
(Switzerland). Within Latin America, Chile achieved the highest score with a ranking of 4.69
Informal competition. In order to operationalize the moderating effect of informal
competition, data from the World Bank Enterprise Survey is used (Mendi and Costamagna,
2017). This survey captures the amount of firms competing against unregistered or informal
firms. More specifically, the survey measures the amount of perceived competitive pressure
from informal producers; formal firms are requested to rank on a 0 to 4 scale how much of an obstacle the informal sector competitors are to the firm’s operations (Mendi and Costamagna,
2017; McCann and Bahl, 2017). This paper captures the amount of firms competing against
unregistered or informal firms. The total percentage of firms dealing with informality is
computed per country and used as a representation of the size of the informal competition of
that country.
Imitation tolerance. Cerqueti et al. (2016) state that imitation is an inverse measure of IPR
protection. The country specific Intellectual Property Index (IPI) developed by Park (2008) is
mainly used to obtain the IPR measurement (e.g. Klein, 2018; Kafouros et al., 2012; Zhao,
2006). However, this index is not given for the year 2010. Another reliable option that has
been used by previous studies is the Property Rights score of the Index of Economic Freedom
(IEF) dataset. This index scales from 10 to 100 and combines various aspects of the degree to
which private property is protected in a given country, intellectual property rights are
respected, and citizens are protected against extralegal seizure of property (Autio and Acs,
2010). In accordance with the paper of Kafourus et al. (2012), this study measures IPR
ineffectiveness rather than IPR effectiveness. Thus, the measures need to be recoded by
4.3.3 Control variables
As there are other factors that could affect the innovation performance of Latin America,
control variables are included. Previous research has acknowledged the influence of R&D
expenditures on innovation productivity (e.g. Cohen and Levin, 1989), hence this factor is
controlled for. The Enterprise Survey of the World Bank captures the amount of firms that
spend on R&D. These amounts have been computed into a percentage value per country,
leading to the total percentage of firms that spend on R&D per Latin American economy.
Secondly, it is essential to account for disparities in economic development across Latin
American economies hence real GDP per capita is controlled for. The real GDP per capita
also controls for being a proxy for the attractiveness of foreign investors (Klein, 2018). The
GDP per capita variable is log transformed in order to correct for the positive skewness of the
variable (Field, 2013).
Lastly, in order to account for differing country size, the log of each country’s population is
included as a proxy for the size of the economy (Klein, 2018). The GDP per capita and total
country population data is collected from the World Bank’s World Development Indicators.
5. Findings
The countries that received the highest amount of inward FDI are the Bahamas and Barbados,
of which the inward FDI per capita in 2010 was respectively 3180.45 and 1596.54. One might
expect these high inflows to be surprising for such small countries, though, these economies
are known as tax havens (Hines and Rice, 1994). Consequently, the main objective of MNEs
investing in the Bahamas and Barbados is likely to be the pursuit of tax minimization rather
than taking an active role in the economy. As this might bias our results, the Bahamas and
Barbados have been excluded. Besides the two large tax havens, the country that received the
highest amount of FDI in 2010 is Chile (1012.44). The lowest ratio of FDI inflows is found
for Suriname, as its value is highly negative (-478.06). The most patents were filed in Mexico,
not in Chile. Though, Chile is the third runner-up after Mexico (951) and Argentina (552)
with 328 patent applications in 2010. The least amount of patents was applied for in Honduras
The mean, standard deviation and correlation matrix for each variable are presented in table 2.
A positive correlation between patent applications and inward FDI is shown, though this
correlation is not significant. The most concerning correlations close to or above the threshold
of 0,8 are between imitation tolerance and inward FDI (-.773**), imitation tolerance and
formal competition (-.822**), formal competition and inward FDI (.812**) and total country
population and patent application (.886**). The latter correlation is justified since the total
country population is a control variable and hence expected to (highly) correlate to the
dependent variable (Pallant, 2010). To diagnose any multicollinearity issues, the VIF scores
and collinearity tolerances have been computed. In order for the assumption to be met, the
VIF should be well below 10 with tolerance levels above 0.2 (Field, 2009). As the VIF of all
variables ranges from 1.307 to 4.132 and the tolerances all exceed 0.2 ranging from 0.242 to
0.765, multicollinearity between the variables is rejected. The majority of the correlations
between the explanatory variables have small correlation values. Moreover, data is gathered
from six different sources and none of the highly correlated variables are obtained from a
similar source. As such, multicollinearity is not expected to be a serious hassle for the
