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Financial literacy, role models, and micro-enterprise performance in the informal economy

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  • Stockholm School of Economics & NLA University College Hauge School of Management

Abstract and Figures

This article analyses how financial literacy and role models contribute to explaining the performance of micro-enterprises in the informal economy. Grounded in human capital reasoning and social learning theory, we argue that financial literacy and personal knowledge of role models lead to improved firm performance. We test our hypotheses on a unique dataset of 739 micro-enterprises in Ecuador. We find that financial literacy is an important predictor of financial performance but not growth, and the use of role models predicts return on assets but not other performance metrics. Our results have implications for future work on micro-enterprises and the nature of the human and social capital of their founders.
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FINANCIAL LITERACY, ROLE MODELS AND MICRO-ENTERPRISE
PERFORMANCE IN THE INFORMAL ECONOMY
Abstract
This study focuses on how financial literacy and role models help to explain the performance of
micro-enterprises in the informal economy. Grounded in human capital reasoning and social
learning theory, we argue that financial literacy and personally knowing role models lead to
improved firm performance. We test our hypotheses on a unique dataset of 739 micro-
enterprises in Ecuador. We find that financial literacy is an important predictor of financial
performance but not growth, and the use of role models predicts return on assets but not other
performance metrics. Our results have implications for future work on micro-enterprises and the
nature of the human and social capital of their founders.
Keywords
Financial literacy, informal economy, role models, micro-enterprise performance
Introduction
The extension of microcredit to help support micro-enterprises is no longer a small industry; its
growth rate is in the double digits (MicroRate, 2013). More than 200 million poor individuals
globally receive microfinance services, compared to 13 million in 1997 and microfinance has
become a very important source of entrepreneurial finance for the poor (Chakravarty and
Shahriar, 2015; Reed et al., 2014). Many of the firms that receive microfinance services operate
in the informal economy, out of view of government regulators and official statistics and lending
data. Indeed, in some countries, the majority of economic activity takes place in these ‘shadow’
micro-enterprises (Bruton et al., 2008; Webb et al., 2009; Williams and Nadin, 2012). For many
developing countries, such as Ecuador, Tanzania and India, employment in the informal
economy helps to support more than 80% of the population (ILO, 2013). Furthermore, the
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importance of such informal micro-enterprises is illustrated by the fact that such activity is seen
as the modus operandi of individuals seeking to exit poverty (Bruton et al., 2013).
Despite the importance of the informal economy for the entrepreneurial pursuits of
individuals and for employment, research into the actual performance of informal micro-
enterprises has remained relatively scant (Webb et al., 2009; Webb, Bruton, et al., 2013). This is
notable as these types of firms allow individuals to overcome situations of poverty by providing
basic provisions to the family and contribute to local communities (Khandker, 2005; Khavul et
al., 2009; Webb, Morris, et al., 2013). One difficulty that may explain this limited attention in
the literature relates to the challenges in finding systematic, reliable financial data about these
micro-enterprises, due to them operating in the gap between what is “legal” and what is “socially
legitimate,” though perhaps illegal (Ahlstrom and Bruton, 2010; Webb et al., 2009), with small
or inconsistent performance (Collins et al., 2009), and oftentimes lacking formal documentation
or governmental registration (Roy and Wheeler, 2006). However, recent developments in micro-
finance have provided the opportunity for scholars to empirically examine these firms as they
must register with the micro-finance institutions to receive any funding. One example is Khavul
et al. (2009) who gained access to informal family businesses through a non-profit microfinance
organization. However, studies that have addressed these issues have tended to be qualitative in
nature and smaller in scope, which is perhaps not surprising given the emerging stage of
research on the topic (Bruton et al., 2011; Khavul et al., 2009). As a result, greater inroads into
understanding micro-enterprise performance through the partnership with more formal
institutions can still be made.
In this paper, we explore issues related to the development of informal economy micro-
enterprises via microfinance institutions. More specifically, we extend research on
entrepreneurship in the informal economy to examine how a basic comprehension of key
financial concepts such as financial literacy (Bruhn and Zia, 2011; Lusardi and Mitchell, 2014),
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and the usage of entrepreneurial role models impact firm performance. Drawing upon human
capital theory (Becker, 1994) and social learning theory (Bandura and Walters, 1977), we
examine whether financial literacy, as a measure of a particularly useful and specific skillset
rather than a broader measure of human capital (such as levels of formal education), as well as
the proximal use of successful role models, affect micro-enterprise performance. We argue that
while financial literacy addresses an individual’s ability to internally assess the benefits and
costs of an entrepreneurial opportunity, role models help reduce the ambiguity in decision-
making (Minniti, 2005) and offer opportunities for vicarious and observational learning.
In doing so, we address the appropriateness of human capital measures in the informal
economy and micro-enterprise context. The majority of the entrepreneurship and new venture
performance literature has focused on entrepreneurs with higher levels of education (such as
Master’s or PhD levels), or possessing substantial previous industry and entrepreneurial
experience (often referred to as expertise). One recurring result is that greater levels of human
capital are important for venture performance (Unger et al., 2011). However, this same literature
has tended to overlook more context-specific and appropriate area of human capital, including
among base-of-the-pyramid micro-enterprises where the entrepreneurs’ goals are more in line
with escaping poverty rather than traditionally espoused entrepreneurial goals (Williams and
Nadin, 2010). For instance, in a context where formal education is oftentimes limited to between
three and nine years, understanding applicable skillsets and base level knowledge, such as
financial literacy, might be more relevant than completion of higher education to the subsequent
performance of those entrepreneurs. We treat the ability to assess an opportunity financially, i.e.,
the financial literacy of the individual doing the evaluating, as an important part of opportunity
evaluation (Wood and McKelvie, 2015). Fundamentally, if entrepreneurs in the informal
economy lack understanding of rudimentary financial concepts and tools, how can they
accurately evaluate an entrepreneurial opportunity such might lead to good – or even satisfactory
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– performance? Performance, in this case, acts as a means to potentially alleviate resource
deficiency and poverty (Adekunle, 2011).
Our study offers several contributions to the literature. First, we outline and empirically
test a model of entrepreneurial micro-enterprise performance in the informal economy. In doing
so, we overcome a singular view of performance (Adekunle, 2011; Murphy et al., 1996; Wood,
2006) by analyzing three forms of firm micro-enterprise performance profits, return on assets
(ROA), and sales growth. This is notable as scholars are only beginning to develop robust
empirical insights into micro-enterprises that operate outside of the purview of established
institutions since micro-enterprise performance data is relatively rare (Bruton et al., 2008; Webb
et al., 2009). To achieve this, we partner with a micro-finance institution (Banco-D-Miro) to
secure reliable and valid financial performance data. These data help provide more systematic
empirical insights about the performance of micro-firms overall, as well as some of the factors
that might improve that performance.
Second, we extend theoretical discussions of human capital and the “ability” in
evaluating opportunities into the tangential realm of financial literacy. Consequently, we expand
the literature on human capital (in regards to financial literacy) and social learning theory (in
regards to role models) to reflect a more appropriate context. From a theoretical point of view,
our treatment of financial literacy as a form of human capital is more in line with the skills
approach (Davidsson, 2004; Ucbasaran et al., 2008; Unger et al., 2011), and one that is notably
relevant for micro-entrepreneurs facing poverty; we argue that financial literacy is a more
germane indicator of human capital given the context of informal economy micro-enterprises, at
least as compared to traditional measures such as years of formal education. In comparison with
relative concepts such as self-efficacy (Chen et al., 1998), financial literacy measures actual
skills and abilities as opposed to self-perceived skills and abilities. Specifically, the financial
literacy measures involve physically completing a task rather than the self-perceived ability to
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solve a task. This is important as there has been limited work done related to skills and abilities
of micro-entrepreneurs in the informal economy (Drexler et al., 2014; Field et al., 2010). To that
end, we are able to help address gaps in the financial literacy literature (Lusardi and Mitchell,
2014) about the extent to which it helps alleviate poverty, as well as extend the human capital
literature to a relatively novel domain where traditional measures are not most germane.
Relatedly, our examination of proximal role models as a source of social learning and
social capital follows Aldrich and Zimmer's (1986) view that “entrepreneurship is a social role,
embedded in a social context” (p.20). Our theoretical and empirical contribution lies in our
treatment of proximal (i.e. personally known) role models, as opposed to distal (i.e. generally but
not personally known) role models as it offers greater specificity in the importance of role
models (Bosma et al., 2012). This takes into better consideration discussion the generally
overlooked part of social communities for micro-enterprises (Khavul et al., 2009), but also
extends the role model literature from their impact on entrepreneurial intentions (e.g. Krueger et
al., 2000) to that of micro-enterprise performance (Bosma et al., 2012). The combined effect of
these contributions is that we are able to better understand how informal economy micro-
enterprises are able to alleviate conditions of poverty.
Theory and hypothesis development
The capabilities of micro-enterprises are nearly synonymous with those of the entrepreneur, as the
vast majority of these firms are centered around one individual. To achieve a baseline level of
performance, which for the most part is sufficient to help alleviate poverty, it is important for
these businesses to offer goods or services that are somewhat unique or meet unsatisfied customer
demand. For many firms in the formal economy, there is a larger focus on the role of resources
and formal human capital of the entrepreneur as a predictor of firm performance (Unger et al.,
2011)."
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Human capital is often enhanced through education or experience, but when lacking skills
or facing uncertainty about decisions, entrepreneurs may also learn from role models (Bandura
and Walters, 1977; Minniti, 2005). In many developing countries, individuals leave school after
five years, as the perceived marginal benefit of more schooling does not outweigh the perceived
incremental cost. Unger et al. (2011) argue that education and experience are only indirect
measures of human capital, instead showing that the direct outcome of human capital
investments, such as skills and knowledge, provides a better link to performance. In other words,
what you learn is more important than how many years of education you have. Hanushek and
Woessmann (2008) argue that:
“there is strong evidence that the cognitive skills of the populationrather than mere
school attainmentare powerfully related to individual earnings, to the distribution
of income, and to economic growth.(p.607)
Past studies on the impact of human capital on micro-enterprise performance often apply
measures such as the entrepreneur’s formal education and previous work experience. However,
research shows that the outcome of education and work experience – such as skills and
knowledge – are better predictors of firm performance than simply education (Unger et al.,
2011). We argue that, in the context of informal micro-enterprises, the applicability of formal
human capital measures may be less germane. For instance, Honig (1998) finds that Jamaican
micro-entrepreneurs’ education had a negative relationship with performance and no clear
linkage between formal education level and the income levels of individuals. Further, he finds
that those with only primary education earned more money than those who had junior secondary
education. This suggests a negative relationship between education and performance, possibly as
a result of experience being more important than education in certain conditions or contexts.
However, Honig (1998) also found that those with vocational training earned more, suggesting
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again that the skills acquired in those educational situations are critical for firm performance.
Moreover, Berge, Bjorvatn, and Tungodden (2014) find a positive impact among Tanzanian
male entrepreneurs when learning business skills. These trainings may also reflect levels of
social interaction with others. Finally, van der Sluis et al. (2005) find that one year extra of
entrepreneurship education in the developing world leads to an increase in enterprise income by
5.5%. "
In developing countries, the opportunity to achieve a high level of formal education may
not be possible; and if it were, it might not be relevant to running a micro-enterprise. Practically
speaking, many people leave school early, leading to undeveloped basic skills. There are many
reasons for leaving school early, including the cost of schooling (or the indirect costs such as
food, uniforms, travel, etc.), the cost of extra tutoring or the opportunity cost of not being able to
provide extra income to one’s family (Ardiente and Guiking, 2015). However, we argue that a
rudimentary understanding of basic finance is still expected to help entrepreneurs make
decisions via mental accounting. In other words, there may be benefits from alternate measures
of human capital than formal education. In the space between the discovery phase and the
exploitation phase of the entrepreneurial process (Shane and Venkataraman, 2000), an
entrepreneur´s inner ability to evaluate the perceived opportunity demands a certain level of
financial literacy that, even in developed markets, is not universal (Lusardi and Mitchell, 2011d).
Financial literacy is generally described as important to human economic decision-making
(Lusardi and Mitchell, 2014). This is particularly important in an informal economy with
frequently high interest rates and high inflation, oftentimes calculated as above 30% for inflation
adjusted interest rates (Mersland and Strøm, 2012)
Prior research on financial literacy is linked to intended pension planning or saving
behavior. This line of research shows a meaningful impact on pension and saving behavior,
whereby a causal relation is said to begin with knowledge (of finance) and ends with a behavior
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(a decision, in this case). Assessing an opportunity requires the ability to make numerical
calculations (Lusardi, 2012). In a qualitative study, Bruton et al. (2011) find that an important
characteristic of borrowers in better-performing businesses is their “awareness of interest rates
and the time value of money” (p. 727), suggesting that financial literacy is vital to firm
performance. However, there is no consensus around the general utility of financial literacy. For
example, in India, research on micro-enterprises indicates that the cognitive ability of micro-
entrepreneurs is low and that rather than thinking about interest rates, they think about how much
they owe on a weekly or monthly basis (Tiwari et al., 2008). The theory of mental accounting
(Thaler, 1985) suggests that individuals make decisions based on a higher expected value based
on the perceived benefit (concave curve) versus the perceived loss (convex curve). This implies
that an individual must be able to assess an opportunity based on how much cash it will bring in
relative to the investments needed. This qualitative approach seems to suggest that those who are
more financially literate would indeed perform better.
Secondly, the ability of an entrepreneur to engage in planning is positively related to
performance (Baum et al., 2001; Frese et al., 2007), and in this process, financial literacy is a
prerequisite for successful financial planning (Lusardi, 2012). An entrepreneur must be able to
weigh the expected return from making an investment in one category against the expected return
from making the same investment in another category, where the risk/return characteristics
should be the basis for the evaluation (Fama and MacBeth, 1973). Thus, in this study, we argue
that the degree to which understanding the basic financial concepts of compound interest rates,
inflation and risk diversification affect the performance of micro-entrepreneurs in the informal
economy. We therefore hypothesize:
Hypothesis 1: Among micro-enterprises in the informal economy, there is a positive
association between an entrepreneur´s financial literacy and their micro-enterprise’s
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financial performance as measured by a) profitability, b) return on assets, and c) sales
growth.
Entrepreneurship as a process involves relationships with others where the social context
matters. Entrepreneurs are at some point “affected by relations with socializing agents who
motivated them” (Aldrich and Zimmer, 1986). Entrepreneurs are seldom autonomous decision-
makers, but rather are individuals acting in a social environment whereby they are influenced by
the behavior and advice of others (Sarasvathy, 2009). This social environment is notably
important in decision-making situations that involve uncertainty, including the probability of
failure. In an informal economy, the consequences of failure are not subject to a judicial system.
Consequently, failure may haunt an individual on a personal level for the rest of his or her life
including persistent poverty. Although the range of possible outcomes is known to the
entrepreneur, and although he or she may be able to do simple numeric exercises, such as the
financial literacy ones we employ in this study, he or she may still face ambiguity about which
decision to take (March and Olsen, 1976) and needed behaviors to move towards success. The
future road map is puzzling or more likely mysterious, with much missing information that has to
be gathered and assessed through trial and error (Nye, 1994; Sarasvathy, 2009) especially if the
entrepreneur also lacks formal training or background where they may have learned tools to
address this ambiguity. Therefore, absent a key decision-making resource internally, the
entrepreneur may need to look to a role model for advice, influence and connections (Bruton et
al., 2010). We argue that this is even more important in an informal economy, where human
capital is less developed, where financial literacy is relatively poor, where many entrepreneurs are
likely faced with much ambiguity, and where negative outcomes can be particularly detrimental.
Social learning theory, in the context of entrepreneurship, proposes that learning can take
place by observing the behaviors of role models (Bandura and Walters, 1977). Social learning
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suggests that entrepreneurs replicate the behavior if it is viewed as socially effective, thereby
attempting to match appropriate successful models (Bandura et al., 1963). Similar to an
institutional framework like Cooperative Thrift and Credit Societies (CTCSs) the presence of
role models creates an enabling external environment for entrepreneurship (Adekunle, 2011).
Research on role models has shown that individuals tend to make decisions on the basis of social
cues (Aldrich 1999, cited in Minniti 2005). This implies, for example, that decisions to expand a
business, enter a new business, or make other changes can be made through the indirect
influence of others. As argued by social learning theory, entrepreneurs learn from observing
others. In this sense, role models act as a form of social capital (Newman et al., 2014) and where
they may provide concrete advice. The mere presence of successful peers generally offers
inspiration or support (Bandura and Walters, 1977) or legitimizes entrepreneurial pursuits
(Davidsson and Wiklund, 1997). This helps to reduce ambiguity in a decision (Minniti, 2005) as
well as offer guidance for future actions (Bosma et al., 2012). In sum, for micro-entrepreneurs,
social learning via role models is vital as it helps to circumvent any lack of previous experience
or formal training. It also allows micro-entrepreneurs to observe, discuss, and learn about and
opportunity and business related issues. "
The majority of work on role models and entrepreneurship has focused on the effect of
role models on the development of entrepreneurial intentions (Bosma et al., 2012; Krueger et al.,
2000). In other words, the main gist of the literature is towards the effects of social learning on
the desire to enter into entrepreneurship. We argue that role models continue to be influential
even after the entrepreneurial intention stage. Entrepreneurs use role models, or social linkages,
as a source of information, to learn, and lacking specific skills may cause them to turn to the role
model for advice or even to be inspired to follow the role model. Of importance is that there may
be some diversity in role models, including distal role models with which the entrepreneur has no
direct familiarity and much more proximal role models where there is the opportunity for social
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interaction (Bosma et al., 2012). Our focus is on the usage and personal familiarity with the role
models, rather than distal (e.g. generally well known but not personally known) role models. In
line with social learning theory (Bandura and Walters, 1977), micro-entrepreneurs are more
attracted to and will learn from role models who are more similar in nature. This helps with
identifying with the role model and thereby engage in more imitative or modeling behavior
(Bosma et al., 2012; Gibson et al., 2004), including when facing similar situations or challenges.
It is through the involvement and engagement with the role model that the micro-entrepreneur is
able to learn.
Consequently, role models contribute to on-going social learning (Bandura and Walters,
1977). While there is limited research on the impact of role models on the micro-enterprise
performance, there is some research that suggest that social learning even broadly defined
has an impact of entrepreneurial performance in the informal economy. One example of this is
the study by Honig (1998), who found that semiweekly church attendance and marital status
positively influenced the performance of the business, not through a divine impact but through a
return on the social capital. Khavul et al. (2009) illustrate the importance of both family ties and
local community ties to the establishment and growth of businesses via achieving support.
We argue that with established linkages motivated by role models, micro-entrepreneurs
can be better guided in their opportunity seeking and evaluating behavior (Aldrich and Zimmer,
1986) as well as their on-going entrepreneurial efforts after the firm has been started (Cooper et
al., 1994). The social environment “contributes to reducing the ambiguity associated with
entrepreneurial decisions” (Minniti, 2005, p. 5). In the micro-enterprise context observational
learning or vicarious learning (Bandura, 2004; Bandura et al., 1963) from other successful
individuals impacts performance positively by making micro-entrepreneurs aware of the potential
pitfalls and understand potential solutions to issues as they arise (Cooper et al., 1994). Further,
Newman et al. (2014) propose that relational social capital impacts positively on existing venture
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growth. As such, we argue that it is important to have role models as part of one’s network as
they may lower the ambiguity in decision-making but also provide extra experience and know-
how for guiding decisions and behavior that will positively affect firm performance.
Consequently, we hypothesize:
Hypothesis 2: Among micro-enterprises in the informal economy, there is a positive
association between the usage of role models and the micro-enterprise’s financial
performance, as measured by a) profitability, b) return on assets, and c) sales growth.
Method
Sample
We draw upon a unique sample of micro-enterprises in Ecuador, a country with widespread
informality covering more than 80% of the working population (Canelas, 2014; World Bank,
2012). Ecuador therefore offers a valid context to understand micro-enterprises in the informal
economy. Moreover, the focus on micro-enterprises is important as these types of firms provide
jobs and income to more than one-third of all households in Ecuador. By collaborating with the
leading microfinance institution in Ecuador1, Banco D-Miro, we were able to acquire detailed
financial data collected as part of their credit analyses, including data from a national credit
bureau. The credit officers spend considerable time assessing and evaluating businesses, both its
assets, its income and costs, including multiple on-site visits, to make sure the risk of default
remains low. In other words, we have a full picture of the financial position of the clients,
including debt with other financial institutions, as well as their credit analysts’ best assessments
of the value of assets, such as machines, cars, inventories, or buildings, of the individual
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1 According to a global ranking by Microfinance Investment Exchange (Martínez, 2014).
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entrepreneurs involved. We also conducted an additional 20 minute telephone survey, reaching
750 micro-entrepreneurs in order to gather further information regarding their financial literacy
and usage of role models. By combining methods - a telephone survey about the entrepreneur as
well as the data acquired from Banco D-Miro -- we are able to gather rich information about both
the entrepreneur and the micro-enterprises. Employing a telephone, as opposed to a written
survey, also allowed us to circumvent potential concerns in regards to literacy. Further, given our
focus on firm financial performance, we have excluded the value of family assets, and focused
only on the micro-enterprises’. After limiting the number of firms to only those with fewer than
10 people helping the founder, the full sample was 739 firms. These are truly micro-enterprises,
where the average number of employees working with the firm is slightly above one. The total
assets are worth roughly US$ 16,000 - with many possessing almost no assets, with an average
debt US$ 2,600 and an average annual sales of approximately US$ 26,000. These descriptive
statistics provide support that the firms in our sample are indeed micro-enterprises (Ayyagari et
al., 2007). Further, 60% of the micro-enterprises in the sample are women. The age of the
founders ranges from 19 to 68 with an average of 42 years old. On average, these micro-
entrepreneurs have completed 1.6 levels of education, which implies that most have only a basic
level of education (6 years). Although the mean number of years of experience in running a
business among our respondents is quite high (almost 12 years), this is slightly skewed by the
number (almost 5%) of entrepreneurs with greater than 30 years of experience. In contrast,
approximately one third of the sample had less than five years of experience. See Table 1 for
more details.
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INSERT TABLE 1 ABOUT HERE
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Measures
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Dependent variable. Our dependent variable is micro-enterprise performance. The literature
suggests a multidimensional approach to measuring performance (Combs et al., 2005), separating
performance into financial and operational measures. The rich dataset allows us to measure
performance across three core dimensions, representing different aspects of micro-enterprise
performance, in line with Bosma et al. (2004). Because these micro-enterprises are typically
very small, our first measure of performance is the annual profit. Profit relates to the amount of
money the entrepreneur has left at the end of the day. In this context, profit entails positive cash
flow to the entrepreneur, allowing them to pay for daily and routine expenses, including food,
clothes, or potentially housing. In other words, the notion of profit has a direct impact on the
daily discretionary spending of the micro-entrepreneur and helps support their life-needs. As a
secondary measure, we measure the return on assets (ROA) of the firm. This performance
measure relates directly to the assets employed as part of the micro-enterprise. While this
performance measure may seem at odds with the micro-enterprise context, ROA illustrates
efficiency. Given that the level of assets owned is generally very low, we are able to take into
account the potential variations that come with any potential investments into fixed assets (such
as physical retail locations or inventory) rather than service businesses without assets. We
measure ROA as net income divided by total assets. In line with other research (e.g., Hvide and
Møen 2010), we winsorized the assets at the 5% level and replaced asset values below US$
3,200 with US$ 3,200 – the 5% winsorization cut-off level in our sample. Moreover, in most of
these businesses, the entrepreneur does not take a salary any firm financial profit is extracted
to pay for personal expenses of the founder. As such, the opportunity cost of labor accordingly
needs to be deducted (Shane and Venkataraman, 2000). By comparing the wages of workers in
the formal sector versus those in the informal sector, it is estimated that the informal wage is
91% of the actual minimum wage in Ecuador during the period 2010-2012 (Canelas, 2014), or
$289. This avoids overestimating the return on asset of the micro-enterprise.
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Third, we use a longitudinal measure of micro-enterprise performance sales growth.
Given that all credit assessments are not done every year, we use a variable where we compare
the average sales in 2014 and 2015 with the average sales during the period 2009-2013. This
method allows us to circumvent issues related to missing data resulting from the informal nature
of the firms and their financial assessment. Growth as a measure of performance is important
such that we may understand whether or not the micro-entrepreneur is willing and able to grow.
Sales growth is the most common performance measure in new venture performance (McKelvie
and Wiklund, 2010). We take the log transformation of the raw sales growth variables in order to
ensure normalcy.
Independent variables. We use two independent variables in our study, reflecting
Hypotheses 1 and 2. First, we examine financial literacy. Building upon a previously tested
concept (Lusardi and Mitchell, 2011a), we asked three questions to test the entrepreneurs’
understanding of financial concepts: 1) we capture the ability to perform simple calculations
(numeracy) and the understanding of the idea of compound interest; 2) we tap into understanding
of the concept of inflation; and 3) we examine the concept of risk and diversification. In our test,
the third question is modified from the original questions (Lusardi and Mitchell, 2011a, 2011c) to
be relevant to the informal economy. In the original question, the concept of “stock” or “mutual
fund” was used, i.e., share investment. We changed this to “opportunity” instead, making it
synonymous with the word used when taking a loan and using the money for a hopefully value-
enhancing opportunity. The survey, which included questions for the test, was conducted using a
professional call center at Banco D-Miro that was supervised by a team of three researchers and a
manager during the entire process. Using telephone interviews also overcomes any potential
issues with illiteracy. By first pre-testing the questions on a sample of 60 individuals, we obtained
sufficient variability in the responses and were able to validate that our modified question number
fulfilled the same criteria of being simple, relevant, brief and differentiable among individuals.
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The questions were translated into Spanish by the research team in close collaboration with the
head of the call center, were as follows:
1. Suppose you had $100 in a savings account and the interest rate was 2% per year. After 5
years, how much do you think you would have in the account if you left the money to
grow: more than $102, exactly $102, less than $102?
2. Imagine that the interest rate on your savings account was 1% per year and that inflation
was 2% per year. After 1 year, would you be able to buy more than, exactly the same as,
or less than today with the money in this account?
3. Do you think that the following statement is true or false? Investing everything in one
opportunity usually provides a more certain economic reward than investing smaller
amounts in many different opportunities.2
Our second independent variable is role models. Many previous studies equate exposure to
entrepreneurs to having “role models” (BarNir et al., 2011; Bosma et al., 2012; Franco et al.,
2010; Liñán and Chen, 2009; Van Auken et al., 2006) without considering whether or not the
role models were seen to be successful or if the entrepreneur had a relationship with them (i.e.
distal or proximal role models). In line with social learning theory, and in particular that of role
identification and modeling, we focus on the personal knowledge and usage of entrepreneurial
roles models. As a consequence, and to circumvent issues related to distal role models, we
developed four novel items that reflect both exposure to and usage of role models. On a scale
from 1 through 5, interviewees were asked to indicate their level of agreement with the
following four statements:
1. I am personally familiar with successful entrepreneurs.
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2 In studies of developed countries, the question read: “Do you think that the following statement is true or false?
Buying a single company stock usually provides a safer return than a stock mutual fund.(Lusardi and Mitchell,
2014)
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2. In my network of friends and colleagues, there are successful entrepreneurs.
3. I regard some of the entrepreneurs I know as role models.
4. Some entrepreneurs I know have been a source of influence for me.
We offered respondents the response scale on a scale of “strongly disagree”, “disagree”,
“neither disagree nor agree”, “somewhat agree” and “fully agree”, rather than the numerical
statements of a 5-point scale. We elected to do this as the numerical statements resulted in poor
variability in our pilot study. Through this modification we saw improved variance in the
responses. The results of these four questions were averaged to obtain a single measure of role
model, with a Cronbach’s alpha of .832.
Control variables. Because firm performance can be affected by numerous other factors,
we control for both micro-enterprise specific measures and entrepreneur specific measures. At the
micro-enterprise level, we control for financial leverage (debt / equity), size (assets), industry,
number of employees and degree of urban location. The informal economy is often dominated by
certain industries, and for industry specifications, we created dummy variables using the standard
industrial classifications relevant to the informal economy (United Nations, 2008), such as
wholesale, construction, repair shops, restaurants, etc. For degree of urban location, we used data
from national statistics in Ecuador (INEC, 2011) combined with the location of the particular
micro-enterprise in our study. This gave us a degree (e.g., a percentage) of urbaneness in the
specific location. At the entrepreneur level, we control for gender, age, level of education and
previous loan experience, measured as the number of previous loans taken. For level of education
we employ a categorical measure with three levels, where each is approximately 6 years apart
(basic, upper secondary and post upper secondary), thus assuming equidistance.
Results
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Although not traditional for reporting hypothesis testing, we nevertheless thought it was
important to provide a general overview of entrepreneurs in terms of their financial literacy. As
seen in Table 2, only 2.6% of the individuals answered all three questions correctly. On the other
hand, only 5.5% answered none of the questions correctly. The interest question was answered
correctly by 45.3% of respondents, the inflation question, by 37.8%; and the risk question, by
29.2%. The interest rate question therefore appears to have been the easiest, followed by the
inflation question and, finally, by the risk question. In Table 2, we provide a comparison of the
financial literacy test results to other national populations. We discuss these comparisons in
greater depth in the Discussion section.
---------------
INSERT TABLE 2 ABOUT HERE
---------------
Table 3 reveals a statistically significant correlation between two of the three dependent
variables (Profits and ROA, r=0.40, p< 0.01). This is not surprising given their measurement
overlaps, although with some differences (i.e. cash in hand versus efficiency). Surprisingly, sales
growth is negatively as opposed to positively - correlated with our other performance measures.
This unexpected finding nevertheless highlights the importance of using multiple measures of
firm performance in studies as they can provide a fuller picture of performance. The other
correlations among key variables are relatively low (i.e. under 0.30), with only a few of notable
statistical significance, with the exception of Size and Profit. As a result, we do not view
multicollinearity as a significant concern for our data. This is supported by the fact that the VIFs
are under 1.3, which is well below the recommended cut-off of 10 (Hair et al., 2010).
---------------
INSERT TABLE 3 ABOUT HERE
---------------
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We now turn our attention to testing our two main hypotheses. In the regression analysis,
shown in Table 4, we find significant statistically significant relations between financial literacy
and profits (Model 1; coeff. 0.084, p < 0.01) and financial literacy and ROA (Model 2; coeff.
0.092, p < 0.01). Our findings thus support Hypotheses 1a and 1b. However, we do not find a
statistically significant relationship with sales growth, Hypothesis 1c (Model 3; coeff. -.088, n.s.).
Other new venture research highlights a generally positive relationship between sales and
profitability, although this literature does acknowledge the potential risks of growth (Delmar et
al., 2013). Further, that research is focused on formal economy new ventures (of various sizes).
Nevertheless, our findings do not support Hypothesis 1c. For Hypothesis 2, we find that role
models are significantly and positively related to ROA (Model 2, coeff. 0.090, p < 0.01),
supporting Hypothesis 2b. However, we do not find any statistically significant impact of role
models on profits (Model 1, coeff. 0.047, n.s.) or sales growth (Model 3, coeff. 0.079, n.s.).
Consequently, we do not find support for Hypotheses 2a and 2c.
Among the controls, we find that loan experience, age (younger), gender (being a male),
leverage, size (larger), number of employees and location (rural) all have a statistically significant
relationship with profits (Model 1). We also find that previous loan experience, leverage, size
(smaller) and location (rural) are all statistically significant related to ROA (Model 2). Lastly,
loan experience and size (smaller) are related to sales growth (Model 3).
---------------
INSERT TABLE 4 ABOUT HERE
---------------
Discussion
The goal of our paper was to assess the impact of financial literacy and role models on informal
economy micro-enterprise performance. As part of achieving that, we provide novel contributions
to research, methods and practice. First, our findings contribute to the theoretical and empirical
research on financial literacy (Lusardi and Mitchell, 2014), but extended to the context of
20
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informal economy micro-enterprises, many of whom are in conditions of poverty. Our results
reveal a pattern of positive results for the effects of financial literacy on micro-enterprise
performance, specifically ROA and profits. We find that an emphasis on basic financial literacy
skills matters (Cole et al., 2009; Webb, Morris, et al., 2013). This suggests that the ability to
understand basic financial concepts adds significant value to the micro-enterprises and their
owners. Further, these numeracy skills and abilities, rather than formal education and previous
experience as seen most obviously when comparing the impact of financial literacy with that of
education in Table 4 - act as a more context-appropriate view of human capital given its
predictive power. As such, financial literacy seems to provide a clearer path forward to escaping
poverty, or at least covering subsistence expenses. To that end, our findings highlight the need for
more detailed treatment of a context-specific type of human capital that may be viewed at the
“left tail” as compared to firms in the formal economy. Generally speaking, our finding is in line
with Bruhn and Zia's (2013) results on female-run businesses in Bosnia and Herzegovina, as well
as others such as improved marketing skills, which some research indicates have a positive effect
on micro-enterprise growth (Webb, Morris, et al. 2013). However, our findings are in contrast to
the long line of studies that capture human capital through measures such as higher education and
previous entrepreneurial experience (Bosma et al., 2004; Unger et al., 2011). We view our results
on micro-enterprises as important inasmuch as these performance measures have a direct impact
on the day-to-day lives and discretionary spending of the entrepreneurs, allowing them to address
daily living needs in the face of poverty. As such, they may stand in stark contrast to new venture
goals portrayed elsewhere in the literature that reflect growth aspirations and profit maximization.
In addition, our findings offer new contributions to the role model literature. We see that
those micro-entrepreneurs who know successful entrepreneurs as role models (i.e. as proximal
role models) also make better investment decisions and achieve a higher ROA. This is a similar
effect to that of financial literacy. However, for role models, we did not see any impact on profits
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or sales growth. The positive impact on ROA adds further evidence that the existence of role
models may reduce the ambiguity in decision-making (Minniti, 2005) and possibly enhance
returns through higher or improved risk-taking. More importantly, it lends support of social
learning theory, as individuals who learn by observing and interact with other successful
entrepreneurs achieve a higher ROA in their businesses. The results also point (albeit marginally)
towards a relationship between role models and profits. These findings lend partial support to
proposition that social capital will positively impact venture performance (Newman et al., 2014).
We nevertheless are hesitant to draw that as a conclusion. Our results may represent a more
complex impact of role models than previously argued, or simply by the fact that it is difficult to
grow informal businesses due to other factors, such as high competitiveness and being
economically isolated. The use of role models within entrepreneurship has tended to be in relation
to intentions for new venture creation, rather than financial performance (Bosma et al., 2012).
Our results nonetheless illustrate that increasing the opportunity for vicarious or observational
learning of other successful entrepreneurs, perhaps with the support of microfinance institutions
and among their clients to take place, might affect performance positively.
Further, as part of a methodological contribution, we were able to work with a local
partner firm to gain access to micro-enterprises. While not the first to adopt a partnership
approach (e.g. Khavul et al., 2009), we were able to acquire systematic financial performance
data via the partnership. When combined with a telephone survey of individual, our entire dataset
allowed us to capture a fuller set of information on micro-enterprises than previously reported in
the literature. Specifically, working with a microfinance firm helped to partly address calls by
Godfrey (2011) and (Webb, Bruton, et al., 2013) for increased research on legitimate forms of
micro-enterprises transitioning to the formal economy. Our results also highlight the importance
of using different performance measures as it might provide an explanation for the relatively
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inconsistent results found in the literature (e.g. Bruhn and Zia, 2011; Cole et al., 2009; Delmar et
al., 2013; Webb, Morris, et al., 2013).
Moreover, our control variables show several interesting findings, which may have
implications for future research. Our measure of loan experience, number of previous loans taken
with this microfinance institution, is significantly and positively related to a higher ROA, higher
profits and higher sales growth. This is important as multiple loan opportunities may signal that
the entrepreneur further develops their financial literacy capabilities (despite the non-statistically
significant correlation) or at least understands the loan process. Contrary to the meta-analysis by
Unger et al. (2011), we do not observe any direct causal effect of formal human capital
investments, such as education level and experience (apart from a significant and negative
relationship between age and profits), implying that younger micro-entrepreneurs earn higher
profits. Honig (1998) even found a negative relationship between level of education and success.
Our findings therefore illustrate that financial literacy is a better predictor of micro-enterprise
performance outcomes than broader measures of human capital investments, such as education,
reinforcing the message that future researchers should focus more effort on measuring skills,
rather than level of education. Our measure of size shows that with increased size, ROA and sales
growth diminish, but profits increase. This seems consistent as it is easier to achieve a higher
ROA and grow sales at higher rates when the business is very small. In our study, firm size shows
an association with profits, implying the existence of positive economies of scale. The urban
location measure shows that firms located in more rural areas tend to have higher returns and
profits than firms in urban locations. Sales growth was not impacted by location however, which
might be due to a selection preference by the local credit officer who might prefer to spend time
on larger and more profitable rural businesses rather than on less profitable ones due to the time it
takes to reach the rural entrepreneur.
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From a practitioner perspective, our findings offer a number of contributions. Our
findings emphasize that even small improvements in financial literacy among poor micro-
entrepreneurs can have major impact on their performance. Muhammad Yunus once equated
those in poverty to bonsai trees, suggesting that if a bonsai tree does not grow there is nothing
wrong in the seed -- “only the soil-base that is too inadequate” (Yunus, 2006). In our study, the
poor soil-base is perhaps exemplified through poor financial literacy and lacking formal
education. More broadly, it may imply the promise of microfinance to unleash the capacity of
informal economy entrepreneurs may still be valid, if the soil-base can be improved. This is
relevant to entrepreneurship scholarship in the way that good businesses opportunities require
both enterprising individuals and a conducive context (Shane and Venkataraman, 2000), and this
is equally true among adverse conditions where context-specific human capital may trump
traditional measures. Nonetheless, we also acknowledge some of the potential negatives that
might come from microfinance, not the least the consequences of financially illiteracy. One
specific negative example is from Andra Pradesh in India, where rural women were caught in a
negative spiral, having to take on more debt to pay off previous debt. The result of the escalating
financial difficulties was a large number of suicides among the women.
Further related to practitioner contributions, we argue that our sample of micro-
entrepreneurs, all of whom were approved for credit by a microfinance institution based on their
past performance (i.e., is not forward looking), illustrates that those with higher financial literacy
also possess the ability to better evaluate an opportunity. To that end, they appear to make better
investment decisions. This highlights the importance of developing studies of entrepreneurs with
generally low financial literacy skills and poor levels of education. To note is that our results, in
terms of the levels of financial literacy (see Table 2), are for the most part comparable to those of
other developing countries, such as Romania (Beckmann, 2013). A more striking difference is the
number of individuals who answered “do not know” (47.3%), including 11.4% who answered
24
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that way for all questions. The number of “do not know” answers is higher than reported in
studies conducted in different countries (Lusardi and Mitchell, 2014). However, the number of
individuals answering none of the questions correctly was relatively low (5.5%). The results to
the interest rate question were similar to studies in Romania and Italy, the responses to the
inflation question were similar to those in Romania, and the risk question was more correctly
answered compared to Romania (Beckmann, 2013; Fornero and Monticone, 2011). Combined,
we conclude that the levels of financial literacy that we observed in our sample (but not the full
population) of Ecuadorian micro-entrepreneurs are relatively similar to other developing
countries in the world. Other OECD countries generally score much higher than the informal
economy, thus also confirming the link with improved financial literacy as a measure of a human
capital skill and general economic development. However, we are hesitant to extrapolate our
findings to other populations of informal economy micro-firms.
Limitations and future research
As with all studies, this study is not without limitations. First, the study focuses on the
informal economy of Ecuador, where it is not possible nor is it our aspiration - to generalize the
findings to the informal economy globally. Indeed the unique nature of Ecuador offers a
particular area for where we could begin to examine micro-enterprise performance; it is not our
goal to generalize outside of this context. Second, the sample of selected micro-entrepreneurs is
not fully at the bottom-of-the-pyramid (London and Hart, 2004). Rather, the micro-enterprises are
concerned with stable cash-flow generating businesses that are able to receive financing. Indeed,
the micro-enterprises received a micro-loan from Banco D-Miro and where the average sales of
the firms was approximately US$ 26,000 per year. Although we do capture micro-enterprises that
do not repay their loans, we acknowledge that our sample does not capture the most extreme
poverty that many micro-entrepreneurs in developing countries face.
25
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Third, we rely on self-reported financial information based on the specialized information
provided by our partner Banco D-Miro and the survey we conducted. Due to data limitations of
informal economy firms, we acknowledge the rudimentary measures for our sales growth
variable, where we, due to the specialized nature of the data, are not able to acquire year-by-year
firm data. However, we hope that this limitation is somewhat minimized by the rarity of the data
involved. To that end, we recognize the caveat that we rely on one microfinance institute for data.
Research has shown that microfinance institutions may have various goals, and these will impact
their lending preferences and performance (Shahriar et al., 2016). Fourth, although one strength
of this study is the multi-faceted nature of the performance variables, we do not capture the full
set of potential performance outcomes. There may be other psychological or social goals for the
micro-enterprises (Newman et al., 2014), rather than purely financial. For instance, the goal
behind the firm may simply be to have some income to the household in the absence of other
employment options or to address poverty. This may provide a reasoning for our lack of findings
for sales growth. Addressing further, non-financial goals would be an important next step for
research to examine. Fifth, we also acknowledge that there may be other human capital-related
factors which also may be at play here apart from financial literacy. For instance, micro-
entrepreneurs may lack other fundamental skills, such as writing and reading, although they
possess financial literacy. These same micro-entrepreneurs may also draw upon their previous
work experience or familial relations in furthering their business. Although we focus on two
important variables financial literacy and use of role models we acknowledge that other
human capital and social learning factors may also be important in understanding micro-firm
performance.
Finally, some of our non-results offer opportunities for future research. For instance, we
find that financial literacy is not related to sales growth. There may be a number of explanations
for this lack of findings. First, growing the business may not be a primary goal for these
26
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entrepreneurs (Christensen, 2006). If the goal is to achieve a satisfactory income to live on, then
growth may not be a desirable outcome for informal economy micro-enterprises (Jensen, 2001).
Growth implies adding new work tasks and taking on new responsibilities (Wiklund et al., 2003).
Growth may also lead to being required to formalize the business as well, which may have
implications for the “informal economy” status of the firm. Further, growth can be difficult to
manage and can often lead to more problems and concerns than benefits. Given the findings in
the research where microfinance clients complain about being an entrepreneur is difficult and
they therefore remain satisfied (Magill and Meyer, 2005), the non-finding of financial literacy
affecting growth is perhaps not all that surprising. Second, in line with Magill and Meyer (2005),
growth may lead to increased competition. Adding capacity and leveraging firms in such an
environment therefore may potentially make the competitive landscape even tougher, where
competing firms may take notice of the success of the micro-enterprise and attempt to duplicate
business models or practices. (Webb, Morris, et al., 2013) found that financial literacy had a
negative relationship with growth. Those authors attributed that finding to that those
entrepreneurs who had financial literacy also had a higher awareness of the risks involved in
growth. Entrepreneurs subsequently eschewed growth. Our non-finding (compared to Webb et
al.’s (2013) negative relationship) may suggest that other factors such as the intense competitive
nature of the informal economy may be a cause the lack of growth. Lastly, Ecuadorian micro-
enterprises sell mostly to other individuals, and not to other larger companies or institutions, as in
other countries. This may further constrain their growth potential (Magill and Meyer, 2005).
Deeper understanding of the goals and considerations of micro-entrepreneurs may begin to
address some of the non-findings in our study.
Conclusions
Our findings offer an important foray into the role of context specific human capital and social
learning theory on micro-enterprise performance. By examining the importance of financial
27
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literacy, as a measure of human capital skill, and the existence of successful role models, as part
of social learning, we see that these have a stronger impact on performance compared to more
traditional metrics, such as formal education and previous experience. To this end, we are better
able to examine a context specific aspect of human capital, which we argue is more relevant than
traditional treatments of human capital. In this way, we investigate the fundamental skills
involved in potentially evaluating an opportunity, albeit for a micro-enterprise. This has important
implications for future theorizing about the role of human capital in micro-enterprises in the
informal economy. Further, it also provides a clear signal to policymakers about increasing the
financial literacy of entrepreneurs can further their micro-enterprises. Our findings point to that
entrepreneurship research may more effectively employ measures of human capital that reflect
the needs and specific skills for the task at hand, rather than simply the number of years spent in
school (Hanushek and Woessmann, 2008). Consequently, our study bridges previous research on
financial literacy in the developed world (Lusardi and Mitchell, 2014) with the informal
economy of a developing country, while also suggesting that working to increase the prevalence,
visibility and access to potential entrepreneurial role models can help the performance of the
micro-enterprises. Therefore, mentorship programs linking experienced and successful
entrepreneurs with micro-entrepreneurs may be a complementary strategy in poverty alleviation
programs. The informal economy is undoubtedly important for the well-being of many
developing countries. With the World Bank and other nonprofit organizations actively promoting
financial literacy to help economic development, it is vital to understand and measure its impact
on the target groups, such as micro-enterprises. Our study provides some further insight into how
more simplistic areas of basic training can increase the performance of the micro-enterprises that
make up the informal economy, and thereby improving the lives of the entrepreneurs. The
promise of microfinance to unleash the energy and creativity in poor individuals is still an
important vision, but much needed work on the soil-base is needed. There is no doubt that further
28
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investments in to financial literacy and the provision of role models will further help to transform
developing societies into strong soil-bases.
29
"
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34#
#
Table 1. Sample descriptive statistics
Variable
Mean
Std.
Deviation
Females
60%
51%
Age
42
11
Completed school level (1-4)
1.7
0.7
Number of previous loans
3.1
2.5
Number of years running own business
12
9
Total assets (in US$)
16,552
14,784
Total liabilities (in US$)
2,607
4,878
Net sales (in US$)
26,640
22,222
Net result (in US$)
6,366
6,029
Return on Assets (ROA)
45%
38%
Sales/Assets
2.5
7.0
Profit margin
10%
14%
35#
#
Table 2. Measured financial literacy in the informal economy of Ecuador, compared with
previous research on the US, Italy and Romania.
Informal
Ecuador
US
Italy
Romania
45.3%
64.9%
40.0%
41.3%
4.5%
11.3%
25.0%
11.5%
2.5%
9.2%
6.8%
8.2%
47.3%
13.5%
28.2%
34.4%
0.4%
1.0%
n/a
4.6%
14.7%
11.2%
6.2%
11.5%
8.6%
9.0%
3.8%
11.4%
37.8%
64.3%
59.3%
31.8%
38.8%
14.2%
30.7%
40.4%
0.1%
1.4%
n/a
4.9%
29.2%
51.8%
52.2%
13.5%
48.3%
13.3%
14.2%
14.7%
22.1%
33.7%
33.6%
63.5%
0.4%
1.2%
n/a
8.3%
41.5%
46.2%
31.5%
20.5%
2.6%
30.2%
24.9%
3.8%
5.5%
12.3%
26.4%
40.1%
60.9%
42.4%
44.9%
75.5%
11.4%
4.7%
19.9%
29.8%
2013
2009
2007
2011
755
1488
3992
1030
Source: The US data are as reported in Lusardi and Mitchell (2011d), Italian data are from
Fornero and Monticone (2011), and Romanian, from (Beckmann, 2013).
36#
#
Table 3. Descriptive statistics and bivariate correlations
Mean
Std.
Dev.
1
2
3
4
5
6
7
8
9
10
11
12
13
1
ROA
0.45
0.38
2
Profit
6366
6029
.396
**
!!
!!
!!
!!
!!
!!
!!
!!
!!
!!
3
Sales growth
0.31
0.47
-.088
-.321
**
!!
!!
!!
!!
!!
!!
!!
!!
4
Financial literacy
1.1
1.0
.086
*
.131
**
-.081
!!
!!
!!
!!
!!
!!
!!
!!
5
Role models
4.0
0.8
.102
**
.077
*
-.001
.158
**
!!
!!
!!
!!
!!
!!
6
Loan experience
3.1
2.5
.044
.265
**
.148*
-.008
-.004
!!
!!
!!
!!
!!
!!
7
Age
0.0
11.0
-.150
**
.069
-.067
-.031
-.008
.214
**
!!
!!
!!
!!
8
Age2
121.4
134.9
-.048
-.114
**
.006
-.096
**
-.021
-.040
.119
**
!!
!!
!!
9
Education level
1.7
0.6
-.011
.001
-.042
.092
*
.047
-.074
*
-.111
**
.029
!!
!!
!!
10
Gender
0.4
0.5
.040
.122
**
-.069
-.002
.054
-.081
*
-.005
-.080
*
.049
!!
!!
11
Leverage
0.3
1.4
.151
**
.158
**
-.038
-.004
-.051
.037
-.009
-.061
.052
.038
!!
12
Size (sales)
113.5
8.5
-.317
**
.572
**
-.278
*
*
.063
.011
.214
**
.307
**
-.067
.025
.078
*
.034
13
Nr of employees
1.4
1.3
.052
.167
**
-.068
.036
.056
.030
-.002
-.080*
.005
.168
**
.028
.117
**
14
Urban location
0.9
0.2
-.141
**
-.064
.047
.007
-.074
*
.960
**
.039
-.033
.035
-.051
-.019
.088
*
.001
Notes: ** Correlation is significant at the 0.01 level (2-tailed); * Correlation is significant at the 0.05 level (2-tailed).
37#
#
Table 4. OLS regression relating financial literacy and role models with micro-enterprise
performance
Model 1
Model 2
Model 3
Profit
ROA
Sales
Growth
H1: Financial literacy
.084
**
.092
**
-.088
(2.902
)
(2.650
)
-(1.280
)
H2: Role models
.047
.090
**
.079
(1.619
)
(2.618
)
(1.108
)
Controls
Loan experience
.175
***
.133
***
.198
**
(5.767
)
(3.659
)
(2.753
)
Age
-.134
***
-.064
*
-.023
-(4.319
)
-(1.726
)
-(0.318
)
Age2
-.030
-.029
-.031
-(1.021
)
-(0.845
)
-(0.454
)
Level of education
-.028
-.014
-.056
-(0.975
)
-(0.394
)
-(0.836
)
Gender (male = 1)
.071
*
.065
*
.043
(2.314
)
(1.784
)
(0.582
)
Leverage (debt / equity)
.124
***
.158
***
.001
(4.364
)
(4.654
)
(0.018
)
Size ln
.560
***
-.329
***
-.297
***
(17.943
)
-(8.847
)
-(4.117
)
Nr of employees
.080
**
.067
*
-.005
(2.729
)
(1.929
)
-(0.067
)
Urban location (%)
-.112
***
-.108
**
-.088
-(3.881
)
-(3.120
)
-(1.280
)
n
739
739
217
F statistic
27.334
***
8.659
***
2.177
**
R2
.434
.196
.174
Adjusted R2
.418
.173
.094
ΔR2
.010
***
.019
**
.010
Notes: Standardized beta displayed, with standard errors within parentheses. Profits are winsorized at the 5% level.
Industry controls are included but not reported. ΔR2 is over and above control variables. One-tailed tests.
Significant at the 5% level; ∗∗ significant at the 1% level; ∗∗∗ significant at the .1% level
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