HIAS-E-15

Changing saving and investment behavior:
the impact of financial literacy training andreminders on micro-businesses
Girum Abebe, Biruk Tekle
Micro and Sectoral Research Center, Ethiopian Development Research Institute (EDRI)

Yukichi Mano
Graduate School of Economics, Hitotsubashi University

December 08, 2015

Hitotsubashi Institute for Advanced Study, Hitotsubashi University
2-1, Naka, Kunitachi, Tokyo 186-8601, Japan
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http://hias.ad.hit-u.ac.jp/
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Changing saving and investment behavior: the impact of financial
literacy training and reminders on micro-businesses
Girum Abebe±, Biruk Tekle±, and Yukichi Mano§
December 08, 2015

Abstract
In developing countries, savings is an important financial tool, particularly for micro-business withlimited access to credit. However, micro-entrepreneurs often undersave, even when they havesome surplus and the desire to save may be because of a knowledge gap and behavioral biases. We
employed an experimental approach relaxing these savings constraints to explore the effects ofproviding financial literacy training and reminders to micro-entrepreneurs in Ethiopia. Whilefinancial literacy training alone seemed ineffective, the reminders significantly increased thesavings-to-sales ratio by 54.5%, the percentage of business proceeds reinvested back to businessby 91.0 %, and the percentage of savings goal achieved by 116%. Joint treatment significantly
increased the percentage of savings goal achieved by 66.5% and deposit in an ordinary bankaccount by 84%. Our results confirm earlier findings that savings can be limited by attention,
whereas how entrepreneurs manage savings depends on their levels of financial literacy [151words].

JEL Codes: D92, E21, L26
Key words: savings, reminders, financial training, entrepreneurs±

Micro and Sectoral Research Center, Ethiopian Development Research Institute (EDRI)§

Graduate School of Economics, Hitotsubashi University
1

I.

Introduction

Aid agencies and researchers have devoted much time and resources to study and help improvemicro-entrepreneurs’ access to credit, as, for example, witnessed by the explosive growth of microfinance institutions in developing countries. Some studies, however, show that the impact ofimproving credit access on micro-enterprise performance is not always clear cut (Akoten, Swada,
and Otsuka 2006; McPherson and Rous 2010; Karlan and Zinman 2011; Banerjee et al. 2013;
Angelucci 2015). Moreover, many micro-enterprises continue to find accessing credit on favorable
terms difficult. Hence, investments for their start-up and growth are often financed internally(Brealey and Meyers 2000; Carpenter and Petersen 2002; Guariglia, Xiaoxuan, and Song 2011;
Chen and Guariglia 2013). While credit can potentially help meet micro-entrepreneurs’ upfront
resource demand for fixed and working capital, it does little to promote internal financing or
savings on its own (Karlan and Zinman 2011). Complementing credit access, a myriad ofinterventions that promote internal financing of investment is increasingly recognized as animportant tool to mobilize limited resources by stimulating desirable savings and investment
behavior (e.g, Brune et al. 2011; Kast, Meir, and Pomeranz 2012; Karlan, Ratan, and Zinman 2014;
Goldberg 2014).
Promoting savings is important to enterprise development for several reasons. First, savings
could be one way of building adequate capital to overcome credit constraints and withstandtransitory business shocks that are commonly faced by micro- and small enterprises (e.g., Dupas
and Robinson 2013a).1 Second, savings instruments offer a safer option for storing wealth thankeeping money at home and can also be adopted as mechanisms to reduce the temptation ofutilizing cash at hand; particularly for those who have present-biased preferences. Third, many
poorly educated entrepreneurs operating small enterprises in developing countries have limitedaccess to any form of banking services, and thus the use of savings instruments, such as bankaccounts, represent the first opportunity they get to create a relationship with formal financial
institutions, which might pave the way for obtaining credit at future dates. Fourth, for micro- andSimilar positive impacts of savings instruments are documented at the household level. Kaboski and Townsend(2005), for example, find that the provision of savings services to micro-finance clients has significantly led to longterm asset growth in Thailand. Similarly, Dupas and Robinson (2013a) find that the provision of savings accounts has
enabled Kenyan villagers with accounts to withstand business shocks better without liquidating their assets comparedwith those without bank accounts.
12

small businesses, the cost of internal financing of investment through savings is often much lower
than the cost of accessing credit (Evans and Jovanovic 1989). Fifth, savings help in case of
emergencies.
The question that then arises is why do micro-entrepreneurs in developing countries
undersave. An intuitively appealing response is that, in an environment where people are generally
impoverished and entrepreneurship is subsistence, there will not be adequate surplus that can be
set aside for savings. There is, however, evidence from across numerous countries that even poor
households do have some surplus, express a desire to save, and utilize various informal channels
to save (e.g., Rutherford 2000; Banerjee and Duflo 2007; Collins et al. 2009). Alternatively, lowsaving rates may be the result of a knowledge gap and behavioral biases that diminish both thelikelihood and the amount of savings by micro-entrepreneurs (Karlan at al. 2014).
Low levels of financial literacy often lead to suboptimal choices and typically to high levelsof risk aversion in the allocation of resources due to overestimation of the business risk andinadequate capability in dealing with it. Micro-entrepreneurs may undersave because they do notunderstand the benefit of saving, good opportunities for investment, or how to use savings
instruments well. This tendency might have the combined effect of keeping micro-entrepreneurs
in a “low-knowledge trap” (Banerjee 1992; Cole, Sampson, and Zia 2011; Drexler, Fischer, andSchoar 2014). Psychological aspects that affect saving behavior, such as inattention, are also
important in influencing the saving and investment behavior of micro-entrepreneurs. Microentrepreneurs may initially plan to save regularly, but they often fail to keep it on ‘the top of theirmind,’ especially when they are busy dealing with unexpected expenditures such as funerals(Dercon et al. 2006), a relative’s or a friend’s request for borrowed funds (Platteau 2000; Ashraf2009), and yielding to drinking and gambling temptations (Laibson 1997; Gul and Pesendorfe
2001, 2004). Moreover, as a result of inattention or limited attention, micro- and small businessowners often find it cumbersome to regularly keep and check records, track payment and receipts,
as well as manage cash flows (Atkinson et al. 2010). Due to such cognitive tendencies,
entrepreneurs often undersave and, when they do save, they often rely on costly strategies tocommit themselves to save their proceeds, as in, for example, the use of ROSCAs (Rotating
Savings and Credit Associations) and “Susus” (deposit collectors) in Eastern and Western Africa,
respectively (Aryeetey and Udry 1997). Indeed, studies find that people can be induced to improvetheir saving behavior through short-term financial literacy training programs and hard and soft3

commitment-saving devices (Ashraf, Karlan, and Yin 2006; Atkinson et al. 2010; Dupas andRobinson 2013b; Karlan et al. 2014).
This study employs a novel experimental approach that relaxes savings constraints related
to knowledge gap and limited attention to explore the effects of providing financial literacy
training and reminders on saving behavior. The first intervention is based on a 4-hour-longfinancial literacy training to a randomly selected micro-entrepreneurs in Addis Ababa. The training
was offered by university lecturers at the School of Commerce, Addis Ababa University. The
lecturers have a rich experience in conducting similar training programs to small business owners
in Ethiopia. Another group of randomly selected entrepreneurs was treated with periodic
SMSreminders for about 3 months to encourage positive saving behavior. Fortnightly, these microentrepreneurs received SMS reminders containing a message about the importance of saving to“realize one’s dream”. A third group received both treatments, while the last group served ascontrol and got neither treatment.
Our work contributes to the existing literature on this issue in two important ways: (i) mostresearch studies often draw their sample from clients of banks or micro-finance institutions (e.g.,
Atkinson et al. 2010; Karlan et al. 2014); we expand the literature by employing data from arandomly selected sample of micro-entrepreneurs to examine the importance of financial literacy
and reminders in more general settings; (ii) to our knowledge, none of the previous studies compareindividual and joint effects of financial literacy training programs and SMS-reminders; ourexperimental design allows us to perform such comparisons.
We find that periodic SMS reminders significantly changed the saving behavior of
entrepreneurs. The entrepreneurs assigned to the reminder treatment were found to save a larger
proportion of their income, invest a greater percentage of their business proceeds and were more
likely to save amounts that reach or even surpass their self-set saving targets. These effects of the
SMS reminder are robust to model selection. Similarly, the entrepreneurs assigned to the joint
treatment increased the percentage of saving goal achieved. They also increased the deposit in an
ordinary bank account, which did not happen for entrepreneurs assigned to the SMS-reminder
treatment only. In contrast, entrepreneurs assigned to the financial literacy group experienced
limited changes in their saving behavior. This may be because there is limited supply of strongsaving instruments such as a commitment savings account, which would help them overcome theproblem of inattention, rather than an ordinary bank account, which may partially overcome
4temptation but may not be strong enough against demand from outside (Dupas and Robinson,
2013b). It also failed to meaningfully change business knowledge as evidenced by lack ofcorrelation with test scores on financial literacy questions.
The rest of the paper is organized as follows. The next section presents a brief review of theliterature with focus on financial literacy training and reminders. Section III lays out theexperimental design. Discussion on sampling and data is presented in section IV. The empiricalstrategy (econometric framework) and estimation results are discussed in section V. The final
section concludes the paper.

II.

Related literature

An important attribute of successful micro-entrepreneurs is their ability to save and reinvest
their proceeds with the aim of expanding their businesses. Poor entrepreneurs, however, often
seem to have limited access to safe and secure means of saving; they live in impoverishedhouseholds where it is often difficult to store money. Indeed, when presented with instruments ofsaving, takeup among poor households and micro-entrepreneurs has usually been very high(Goldberg 2014). To empirically investigate whether limited access to saving instruments affects
the ability to save, Dupas and Robinson (2013a), for example, conducted a field experiment byavailing access to non-interest-bearing savings accounts with withdrawal charges to womenmarket vendors and male bicycle taxi drivers in Kenya. They find that takeup of savings accounts
was about 87% and that women vendors in the treatment group frequently used the accounts,
increased their investments by 38–56 %, and increased their private daily expenditures by 37%
more than did the women in the control group. Similarly, Prina (2015) finds a comparable takeup
rate of 84% among a sample of randomly selected female respondents who were offered a simple
bank account free of charge in Nepal.
Access to savings products is not only associated with higher takeup, it also seems to havesignificant investment and welfare impacts. For example, the practice of using bank accounts
increased savings as well as education expenditures in Nepal (Prina 2015), improved household
resistance to sudden health shocks in Kenya (Dupas and Robinson 2013b), helped in consumption
smoothing in Chile (Kast et al. 2012), and increased farmers’ investment in fertilizers in Malawi(Brune et al. 2011). The lack of financial inclusion or limited use of financial services can thus
5

potentially cause significant welfare losses on poor unbanked people in developing countries,
thereby amplifying the importance of access and use of financial products. We examine two
possible mechanisms that can potentially stimulate financial inclusion and desirable financial
behavior among micro-entrepreneurs: financial literacy training and SMS reminders.

Financial Literacy
To the extent that lack of knowledge about the benefits of saving deters entrepreneurs fromusing vital financial products, higher takeup can be promoted with financial education (Xu and
Xia 2012; Atkinson and Messy 2013). More often than not, the vast majority of entrepreneurs indeveloping countries appear to have limited financial knowledge and hence their financial
decision-making capacity is poor (Karlan and Morduch 2010; Cole et al. 2011; Xu and Xia 2012).2
Consequently, even when access to savings instruments is available, lack of knowledge about
financial concepts and how banks operate can prevent entrepreneurs from saving and reinvesting
their business proceeds. The observations that micro-entrepreneurs in many developing countries
do not keep proper accounts of their transactions, do not know how to prepare budget and financial
plans, and do not understand the importance of separating the business from the household are
expressions of low levels of financial education (Bruhn, Karlan, and Schoar 2010; Abebe andSonobe 2012; Mano et al. 2012; Mano et al. 2014).
Financial literacy involves all forms of skills and knowledge that aid in the proper utilizationof one’s financial resources. It includes basic skills in numeracy; ability to calculate simple payoffs
from investments; knowledge in budgeting, planning, and cash flow management using limited
financial resources; as well as following heuristics-based financial decision-making rules such as
separating business expenses from household expenses. Without understanding the importance ofsaving and earmarking a certain proportion of business proceeds to savings, micro-enterprises will
not be able to accumulate an adequate level of capital and expand in size. Such types of skills arealso crucial to efficient enterprise management. For example, preparing annual financial plans andAccording to the 2011 Global Findex survey, for example, a quarter of the poorest 40 % of households in SubSaharan Africa do not have bank accounts (Demirguc-Kunt et al. 2015).
2

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statements will help expose the business’ weakness and strength as well as identify areas andproducts where returns are high so as to deploy more funds toward more profitable areas.
While business knowledge is long recognized to be essential in operating enterprises
efficiently, especially for young entrepreneurs who have little experience running businesses,
financial education is gaining in importance only recently (Karlan and Valdivia 2011; Cole et al.
2011; Drexler et al. 2014). Formal education systems in many developing countries, for example,
do not teach financial skills beyond simple arithmetic in mathematics and accounting courses.
Short-term financial literacy training programs are thus increasingly considered as tools for
improving the financial knowledge of entrepreneurs in many countries (Karlan et al. 2014).
However, the effectiveness of such forms of intervention in stimulating better financial decisionmaking—and hence business outcomes—remains a debated research topic. Relatedly, empiricalevidence on the impact of financial literacy on improving financial knowledge and thus changing
financial decisions appears to be highly mixed.
Drexler et al. (2014), for example, find a simple “rule-of-thumb” financial education
program that teaches micro-entrepreneurs rudimentary bookkeeping practices to be more effective
than a training program that teaches standard accounting practices in the Dominican Republic.
Compared with the standard accounting training program, the “rule-of-thumb” financial education
program increased business revenue, improved record keeping, and increased the likelihood thatparticipating micro-entrepreneurs keep business expenses separate from personal expenses.
Similarly, Bruhn and Zia (2011) find that financial training led to the adoption of new production
processes, higher investment, and larger profitability in Bosnia and Herzegovina.
A much more nuanced effect of financial education is reported by Bernheim, Garrett, andMaki’s (2001) study of the impact of state-mandated financial education on saving for high school
students in the U.S.; they report that financial education led to a paltry 1.5 percent increment insaving rate. This finding was, however, countered as spurious with poor identification assumptions
by Cole and Shastry (2008). Augmenting the above study with large census data and controllingfor state fixed effects, the non-parametric estimation of the treatment indicated that the intervention
may not have had a meaningful impact on saving behavior.
Other studies report even less robust findings. Carpena et al.’s (2011) and Field,
Jayachandran, and Pande’s (2010) experiments on financial education and literacy program inIndia, for example, did not yield significant improvements in knowledge and business outcomes,
7respectively. Similarly, Cole et al. (2011) find the impact of financial literacy education on saving
behavior to be trivial in Indonesia, particularly compared with the effect of monetary incentive to
use financial services.
These results suggest that the impact of financial literacy on saving is highly mixed andhence, drawing inference on the effectiveness (or lack thereof) of financial education from thesestudies to other settings might be difficult. Some of the results, for example, may uniquely reflect
the nature of the studies’ sample where researchers often work with young clients of a bank, whose
demographical makeup, such as level of education, is vastly different from poor households andentrepreneurs in other developing countries.
In short, the vast majority of interventions that aim at improving the use of financial products
or access to financial services mainly try to attend to the low use of financial instruments andimprove attitudes toward financial institutions. Although there is almost a universal consensus on
the low state of financial literacy in developing countries (e.g., Cole et al. 2011; Xu and Zia 2012),
the empirical question as to how to improve financial literacy and secure its attendant benefits
largely remains unanswered. Many of the financial literacy interventions to date, for example, do
not appear to greatly expand the business knowledge and practices of micro-entrepreneurs(Carpena et al. 2011; Karlan et al. 2014). Further, there are numerous types of financial literacy
programs ranging from a one-hour on-site consultation to several months of classroom-based
training programs, rendering interpretation and comparison of results difficult. What are the best
ways to teach financial education and how best to do that and which components of financial
literacy programs generate the highest impact with the lowest cost are some of the unresolved
questions that make the existing research on this topic incomplete.
This study, which examines the impact of providing financial literacy training on businessknowledge and saving behavior of micro-entrepreneurs in general settings, is therefore a usefuladdition to the existing literature to enhance our understanding of what works and what does notin the context of developing countries.

Text reminders

8

The impact of reminders and their potential for effecting desirable behavioral changes have long
been studied in relation to the takeup of health care services. Krishna et al. (2009), for example,
extensively reviewed 25 studies in 13 countries to study how text messages and cellphones areused in health care services. The review suggests that using text messages from once a week tofive times a day helped meet multiple outcomes of care, including preventing smoking, taking
medicine, and minimizing the number of failed doctor’s appointments. In a similar study,
Zolfaghari et al. (2012) administered short messages and telephone followups to 77 type-2 diabetes
patients in Iran to explore effective ways of guiding patients to adhere to diabetes therapy. A
randomly selected group of patients received telephone calls for 3 consecutive months, twice aweek in the first month and once a week for the remaining 2 months, while patients in the SMS
group received about six messages every week for 3 months. Results from the study indicate thatboth the telephone and text reminder interventions have improved adherence to diabetic treatment.
By sending standard automated texts to randomly assigned 1,187 obstetrics patients at a
community-based clinic in New York City, Stockwell et al. (2012) tested if reminders could
increase influenza vaccination. After 5 weeks of continued texts on influenza vaccination and two
reminders alerting the patients to doctor‘s appointments, the treatment group experienced a 30%
higher rate of vaccination compared with the control group.
Reminders have also been found to be useful in encouraging takeup of financial products
and services. Reminders, for example, were found to encourage loan repayment by clients of a
microfinance institution in Uganda with the same order of magnitude as a 25% reduction inmonthly interest rate (Cadena and Schoar 2011).
Need we be reminded to change our expenditure and saving behavior as well? We
hypothesize that reminders can generate desirable saving behavior for the same reason that they
appear to encourage healthy lifestyle and higher takeup of health services and better loan
repayment. Micro-entrepreneurs can benefit from reminders as the cognitive load required toregularly keep alert of overconsumption or undersaving is not trivial.
Micro-entrepreneurs, for example, sometimes tend to be inattentive to a wide array of key
business expenditure that needs to be made in future dates (Duflo Kremer and Robinson 2011).
Reminders can bring such expenses to “the top of the mind,” improving entrepreneurs’ cash

9

management (Mullainathan and Shafir 2013; Karlan et al. 2014). More precisely, reminders enableadjustment of decisions over time by altering the likelihood of remembering a decision madeearlier, thereby creating a salient relationship between current choices and future expenditure plans(Karlan et al. 2014). Karlan et al. (2014) formulated a theoretical model that shows that inattentive
individuals would likely undersave and that reminders can be effective instruments to enhancesaving. The example in Box 1 summarizes the main message of the model in less abstract andmore illustrative manner.
BOX 1. Example of inattention bias (inspired by Karlan et al. 2014)
Suppose an entrepreneur, who is retailing ready-made garment products, is planning to also start
making clothes in 6 months’ time. To finance her new line of business, she plans to save enoughamount from her business proceeds that would enable her to buy her first sewing machine in thesame period. Assuming a concave utility function, the entrepreneur would ideally pay for the
sewing machine by smoothing the expenditure over her lifetime, including some amount ofsaving over the next 6 months. If the entrepreneur is inattentive, however, she may forget her
investment plan and choose to continue with the same pattern of consumption she had before
her investment plan was hatched. At the end of the 6 months thus, she will not have saved enoughamount to buy the machine. She will thus be confronted with two options, scrapping theinvestment plan altogether or financing the investment disproportionately through debt. Giving
up on the investment plan would waste a rare opportunity microenterprise owners get to growand expand their business so it is not desirable. The second option is also problematic because
small businesses are heavily credit-constrained and, even if they have access to credit, the costof borrowing is often prohibitively high, seriously denting the returns from the new investment.
If the entrepreneur is periodically reminded about her investment plan and the attendant benefits
from the investment, however, she would likely improve her attention, balancing the current
consumption decisions with the need for saving to be able to buy the sewing machine in 6
months’ time. Thus, reminders have the potential to improve an entrepreneur’s current behavior
by overcoming attention failure that could possibly preclude the entrepreneur from making
lumpy high-return investment in the future.

There are, however, very few empirical studies that examine the impact of reminders on
saving behavior. Karlan et al. (2014) is one of these studies that provided targeted messages or
letters to a random list of bank clients in Bolivia, Peru, and the Philippines to test whether
reminders encourage savings. They find that reminders increased the likelihood of achieving the10

saving goal and total amount saved by 3% and 6%, respectively. Moreover, when comparing
reminders that attach a particular saving plan to those that did not have a saving plan, reminders
were twice more effective when saving plans were mentioned. Similarly, Atkinson et al. (2010)
combined an offer of commitment saving devices with reminders to a group of account holders in
Guatemala. They find that reminders encouraged the use of accounts and enabled account holders
to reach their saving targets on time compared with those who did not get reminders.
Both of these studies drew their sample from commitment saving account holders and theirresults may therefore not be generalized to those not exposed to such types of saving devices.
Moreover, the effect of reminders on saving and investment behavior of micro- and small businessowners is less studied. An important exception is McConnell’s (2012) messaging experiment thatwas designed to encourage market vendors in Ghana to save. In contrast to Karlan et al. (2014)
and Atkinson et al. (2010), the study finds no evidence that reminders significantly increase theuse of formal saving instruments or saving amounts. The question on the effectiveness ofreminders in encouraging better saving and investment decisions is thus far from settled.

III.

Experimental Design

We collaborated with instructors at Addis Ababa University, School of Commerce, who offered
the financial literacy training arm of the treatment. The School of Commerce is a renowned
institution for producing young professionals in the fields of business and management and foroffering business consultancy services to large firms in the financial and insurance industry in
Ethiopia. Further to their strong academic background in financial planning and management, theinstructors that offered the training had taken advanced courses in entrepreneurship and businessincubation. They had also previously offered training on entrepreneurship, bookkeeping, andrelated business management skills to small business owners.
To the extent that the entrepreneur’s level of financial literacy is strongly correlated withfinancial behavior, we presume that there is a large scope for improving both financial knowledge
and practices through classroom-based training. However, consistent with Drexler et al.’s (2014)
finding, we decided that the training will have to be very simple and compatible with theentrepreneur’s skill levels and reasonably short in duration. Moreover, our baseline survey showedthat our sample of entrepreneurs do not have strong educational background with 8.7 average years11

of schooling and only about 15% of them having gone to vocational schools or colleges after highschool (more on sample characteristics and sampling shortly).
The main objective of the financial literacy training was to induce micro-entrepreneurs tosteadily shift their business proceeds from spending on non-essential items toward saving andinvestment. Accordingly, the training was designed to incorporate the following key elements: (a)teach participants the importance of planning, saving, and budgeting; (b) teach entrepreneurs tocarefully weigh their options in using various forms of saving instruments to make more informed
and better financial decisions; (c) encourage entrepreneurs to set achievable goals and regularly
save some amount of money from their business proceeds to reach those goals; and (d) teachentrepreneurs how to keep records of income and expenses separately and prepare a budget
regularly. A brief outline of the training material is presented in Appendix 1.
The instructors prepared a financial literacy training module, taking into consideration thebaseline information that majority of the prospective trainees would mostly have a high schoollevel of education. The module was then translated into Amharic and distributed to training
participants upon arrival. To maximize takeup, the training was offered over the weekends(Saturdays and Sundays) between May and June, 2014.3 Several brainstorming questions that elicit
entrepreneur’s active contribution and that gauge their level of understanding of financial concepts
and products were included in the training module. The brainstorming questions were particularly
useful for instructors to make minor adjustments in the training material to make the training
content compatible with the skills of the participants. Each entrepreneur was invited to a sessionthat lasted for about 4 hours. We invited 50 randomly selected entrepreneurs to each of the two
training sessions by phone roughly 2 weeks before the actual date of training. To remind theentrepreneurs, our research assistant made scripted follow-up calls 2 days before the actual day of
training. Takeup, however, was low, at 42%. Appendix 4 analyzes the determinants of take-up or
attendance in training. Aside from the significant effects of the reminder and joint treatment, wefind that businesses that were older, larger in size in terms of capital stock, time-consistent, andrun by females were less likely to attend the financial literacy training. Larger firms were likely tohave higher opportunity cost, whereas time-inconsistent entrepreneurs, if sufficiently sophisticated,

Initially, our plan was to offer the training during weekdays, but it was impossible because many participants admitted
that they would not be able to come.
3

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were more highly appreciative of financial literacy and instruments to help control theirintertemporal choice. The women’s lack of participation could be explained by several factors
including tradition practices that negatively influence female entrepreneurship, the subsistence
nature of most of the female-operated businesses and the limited growth ambitions exhibited bysuch businesses (examples from other countries include McKenzie and Weber 2009; Field et al.
2010; Sonobe and Otsuka 2014, page 195). While we have not recorded times of arrival anddeparture, only a very few left early but some came late. We gave the participants 50 birr (2.5
USD) for lunch and transport allowance.
The second treatment, regular sending of text message reminders to entrepreneurs, closely
mimicked the design of Karlan et al. (2014). Before reminders were sent out, all respondents inthis treatment group were called by our research assistant and were informed that they would
receive regular text messages reminding them to save every 2 weeks for 3 months. Except for a
few respondents, whose phones were switched off and were in locations that did not receive
sufficiently strong network signals, all entrepreneurs expressed their willingness to receive the text
message regularly. 4 Moreover, upon receipt of these messages, many entrepreneurs called our
research assistant to thank him for reminding them to save.
Except in the case of network failure and problems with an individual’s mobile phone, thereminder messages were sent to all entrepreneurs in the treatment group as per scheduled dates.
When messages were not sometimes delivered, they were resent on the second and third days.5
The reminder treatment was implemented from June to the last week of August in 2014. The third
treatment combined financial literacy with reminders for another randomly selected group of
entrepreneurs.

Following Karlan et al. (2014), messages were designed in two ways: with gain and loss framing. The gain framing
message was “Do not forget to save: if you continuously save, you can realize your dream” and the loss framing
message was “Do not forget to save: if you do not continuously save, you cannot realize your dream”. Although we
randomly assigned the gain and loss framing to the reminder treatment group, because of limited power, we cannot
separate the effect of framing.
4

Only 1% and 3.6% of entrepreneurs assigned to the reminder and joint treatment groups, respectively, failed toreceive the SMS messages because they were either unreachable due to network problems or their phones were
switched off.
5

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IV.

Sampling and Data

To see the validity of our hypotheses regarding saving constraints, we analyzed our own survey
data on micro-entrepreneurs in Ethiopia. Our sample was drawn from a national survey of microand small businesses carried out by the Ministry of Urban Development, Housing and Construction(MoUDC) in 2012 in 13 large cities in Ethiopia. Enumeration areas (EA) in these cities wererandomly selected and a comprehensive list of micro- and small businesses operating in these areas
was prepared.6 From each EA, 12 firms were randomly selected and data on more than 3,000
micro- and small businesses were generated from the 13 cities (see MoUDC 2013).
Firms, our unit of analysis, were sampled from Addis Ababa in the MoUDC 2012 survey.
However, the survey instrument did not contain sufficient information that could serve our purpose.
Thus, in 2013, we decided to conduct our own survey using the entire sample of firms from Addis
Ababa. We developed a survey instrument that would enable us to collect a rich set of information
including, but not limited to, firm attributes and individual demographic characteristics and timeand risk preferences. More importantly, our questionnaire contained a battery of indicators on
saving and investment practices of entrepreneurs.
Subsequently, baseline data were collected from 515 micro- and small enterprises involved
in different sectors in December 2013.7 The four major subsectors where the sampled enterprises
were operating are manufacturing, construction, services and retail business, and urban agriculture.
A preponderance of the enterprises were in services and retail business (57%), followed by the
manufacturing subsector (30%). About 12% of the firms were engaged in construction and only
four firms were operating urban agriculture. Due to the unique nature of the business and the small
sample size, we decided to exclude the four firms in urban agriculture from our analysis throughout
this study. We thus have 511 sample micro-enterprises in the baseline.8

6

The Central Statistical Agency (CSA) of Ethiopia defines enumeration area as “a unit of land delineated for the
purpose of enumerating population and housing units without omission and duplication.” EAs are geographicallydelineated to consist of 150-200 housing units in urban areas.
7
There were more than 600 firms in the 2012 survey. In 2013, some of the firms, particularly those who werecooperative-based were found to have stopped operation and disbanded. We managed to contact 515 of those thatsurvived in 2013.
8

We further excluded three outliers from the sample.

14

In April 2014, to examine whether relaxing the saving constraints affects the likelihood andamount of saving, we randomly assigned, using STATA command runiform, these sample
entrepreneurs to one of three treatment groups or to a control group. Our sample was thus
composed of enterprises that received (1) a financial literacy training, (2) SMS messaging thatencouraged saving, (3) both financial literacy training and SMS messaging, or (4) neither of thetwo (the control group). The interventions then took place from May to June 2014. We conducted
the end-line survey in 1 year’s time after the baseline in December 2014. We managed to interview
426 firms but found that the other 82 have exited from the market. Appendix 5 analyzes thedeterminants of attrition from the sample. Importantly, we found that none of the treatment statusescorrelated with state of exit.9 We mainly analyzed these 426 firms below.
To test the quality of randomization, Table 1 presents the baseline mean values of several
individual and business characteristics of entrepreneurs assigned to the three treatment groups andthe control group. For each variable and for each treatment type, equality of the means of thevariables between each treatment group and the control is conducted.
Table 1 reveals a number of interesting characteristics of the sample. First, across thetreatment groups as well as in the control, about two-thirds of the businesses were operated bymale entrepreneurs in their mid-30s. There was a statistically significant difference in gender
between entrepreneurs assigned to the SMS-reminder treatment and the control group; nearly 73%
of entrepreneurs assigned to the SMS-reminder treatment were males compared with 59% in thecontrol. Second, most of the sample enterprises were self-initiated businesses (81%), which were
founded and run by entrepreneurs with prior work and training experience. The sample enterprises
have been operating for about 7.3 years and run by entrepreneurs who had attended about 9 yearsof schooling and worked on average for about 7 years prior to their current enterprise. Similarly,
a sizable number of entrepreneurs had prior experience in the formal sector ranging from 24% in
the joint treatment sample to 35% in the control sample. In terms of participation in training, savefor the SMS-reminder group, nearly a quarter of the entrepreneurs had taken management training
and more than 30% had attended production skills training.
Third, the survey also measured preference parameters, financial literacy, and cognitive
skills, which may have important relationships with saving behavior (Ashraf et al. 2006; Dupas

9

To address possible attrition bias, we will control for all explanatory variables used here in the following analysis.

15and Robinson 2013a). Looking at time preference, Table 1 indicates that majority of entrepreneurs
were impatient. We elicited time preference using both subjective evaluation of own-time
preference and through a hypothetical time-preference game. Regarding the former, entrepreneurs
were asked to judge their level of patience on a scale of 0 (very impatient) to 10 (very patient).
The subjective evaluation average ranged from 3.2 in the control group to 3.7 in the reminder
treatment group, suggesting that overall level of patience (3.4 out of 10) is not high. In addition to,
self-perception of patience, we elicited the entrepreneurs’ time preference from respondents’choices in the following two hypothetical games: (i) receiving 1000 birr tomorrow or receiving
1100 birr in 1 month and (ii) receiving 1000 birr in 1 month or receiving 1100 birr in 2 months.
Consistent with the subjective evaluation, the majority of entrepreneurs exhibited impatience. For
example, the largest proportion of entrepreneurs whom we label as “somewhat patient” wasassociated with the joint treatment category (about 20.5% of them in this category).10 This result
is strikingly similar to the time preference behavior of rural Kenyans studied by Dupas andRobinson (2013a).
As expected, about 91% of the sample respondents were time-consistent, meaning that they
do not switch their current preference in the future as long as they are confronted with the same
set of options.11 Table 1 also shows that entrepreneurs assigned to the financial training and joint
treatments were slightly more present-biased than the control group. 12 Such entrepreneurs arecharacterized by a higher discount rate in the short run than in the long run. Only 2.4% ofentrepreneurs who were assigned to the financial literacy training exhibited more patience in the
future than in the present in contrast to about 7 % in the control.

“Somewhat patient” individuals preferred 1100 birr a month later over 1000 birr tomorrow (Dupas and Robinson2013).
10“Time-consistent” respondents are either: (1) those who choose both “1000 birr tomorrow” in game (i) and “1000birr in 1 month” in game (ii) or (2) those who choose both “1100 birr in 1 month” in game (i) and “1100 birr in 2
months” in game (ii).
11“Present-biased” respondents are those who choose “1000 birr tomorrow” in game (i) and “1100 birr in 2 months”
in game (ii), or, in other words, those entrepreneurs who are impatient now and patient later. In game (i), we
intentionally proposed the reward for tomorrow rather than today. This is called the "front-end delay" method,which corrects biased choice toward current rewards because entrepreneurs may lack confidence in receiving
rewards in the future due to low credibility and high transaction costs associated with future payment (see Harrison
Lau and Williams 2002; Bauer Chytilová and Morduch 2012).
1216

Fourth, measures of risk preference calculated based on the decision of entrepreneurs to playa hypothetical lottery game (risk taker), choose the safe bet (risk averse) or be indifferent between
playing the game and the safe bet (risk neutral) seem to be balanced across the treatment andcontrol groups.13 Yet, more than two-thirds of the entrepreneurs were found to be risk averse. Fifth,
the treatment and control group entrepreneurs scored comparable values when tested for financial
literacy14 and ability to recall digits correctly.15 The average respondent correctly answered morethan half of the financial literacy questions, scoring 2.4 out of 4.0 points. In the digit span score
test, the average respondent correctly remembered 2.9 out of 8 digit numbers. Sixth, thedistribution of the subsectors was balanced across the treatment and control groups.
In short, Table 1 shows that the treatment and control groups were well-balanced overall.
Although there were small differences in a few variables, we will control for them in the regression
analysis below to minimize bias and increase the precision of the estimates.
Table 2 presents the baseline values of saving, expenditure, and business performanceindicators.16 Except for the amount of saving for housing at the Commercial Bank of Ethiopia(CBE), the baseline values of saving-related variables were balanced well (see Appendix 2 for

Respondents were offered a choice between (1) receiving 2000 birr for sure or (2) playing a game that pays 4000
birr with a probability of 0.5 and zero birr with a probability of 0.5 in a hypothetical lottery game.
13

Following Cole et al. (2011) and Xu and Zia (2012), financial literacy score was constructed by adding thenumber of correct answers that a respondent provided for four basic financial literacy questions.
14

Digit-span score tests cognition by presenting cards labeled with different digit numbers to respondents for 10
seconds and asking the respondent to recall the digits in the exact same order as displayed earlier after the card istaken away from him. Aside from being part of a basic individual characteristic, digit-span measures innate ability toremember important events such as intertemporal saving decisions. The exercise starts recalling eight numbers intotal, from a four-digit number and increasing in difficulty with the final card containing 11-digit number.
15

In the 2014 survey round, we have also inquired about entrepreneurs’ access to credit. Our data showed that 50%
of our sample enterprises have never borrowed money from any sources, including family and friends, and only twoenterprises (0.45%) had borrowed from banks and about 16% had borrowed from MFIs. Given that about 37.7% of
the enterprises said they have formally applied for a business loan, the proportion of entrepreneurs who got loans was
small. Entrepreneurs who never applied for a loan were also asked why they did not apply. About 49% stated that they
do not need a loan. Yet 19% and 8% of them mentioned lack of collateral and high interest rate, respectively, to be
key reasons for not lodging loan applications with formal financial institutions. Moreover, when asked how much they
can borrow in case of emergency in 2 weeks’ time, 30% of the entrepreneurs claimed that they cannot borrow any
amount from any sources. About 17% said they can get more than 20,000 birr (about 1000 USD) in emergency loanin 2 weeks. All these taken together give credence to the assertion that many micro-enterprises are credit-constrained
in developing countries.
16

17

detailed description of the variables listed in this paper). 17 For example, saving size was notstatistically different between the treatment and control groups; actual average saving size perentrepreneur was about 510 birr; and the average amount that entrepreneurs would like to save was
832 birr. Baseline income level, measured by self-reported gross profit earned in November 2013,
was also balanced across the treatment and control groups. This was the dominant source of income
and averaged 1985 birr in the past 30 days, which was only slightly less than the average monthly
GDP per capita in PPP, 2215 birr.18 We also found that more than 80% of the entrepreneurs haveordinary bank accounts and that the average amount of deposit in the past 30 days was from 128
birr to 382 birr. As to informal saving, about 29% of the entrepreneurs are members of Iqub
(ROSCA). Furthermore, more than half of the entrepreneurs also have special housing savings
account at the CBE. Those who save regularly would get a better chance of winning the housing
raffle, whereas people who fail to save would be kicked out of the program. The deposit cannot be
withdrawn. Because of these unique features, we treated this CBE housing saving independently.
The cost of saving is another important predictor of saving. Because our sample
entrepreneurs are operating their business in Addis Ababa, the capital city of Ethiopia, it is not
surprising that they have good access to bank offices. Making a deposit takes only half an hour
and their perceived forgone earnings ranged from 7 to 12 birr in 2013.
In spite of the easy access to financial instruments, sample entrepreneurs may not be fully
sophisticated in terms of accounting activities. Drexler et al. (2014) stress that separating businessand personal accounts enables entrepreneurs to recognize the profitability of their business andalso serves as a commitment device not to misuse working capital. More than 50% of their sample
micro-entrepreneurs in the Dominican Republic separated the accounts, whereas our sample
entrepreneurs did not, consistent with their modest participation in management training in thepast (Table 1). Table 2 presents that they invested 7–13% of their household expenditure back to

The housing savings account is part of the government-run housing development project. It bears an interest rate of
5%, which is equal to the saving rate of personal savings account. Participants are obliged to save a fixed amount andnot allowed to make withdrawals once they started saving. If one withdraws his/her saving from the housing savings
account, she/he is effectively expelled from the housing scheme and would also be ineligible to register for otherhousing programs in the future. So this is a strictly limited-purpose commitment saving device with harsh penalties
for non-compliance.
17

Ethiopia’s average annual GDP per capita PPP is USD1329 in 2013 and USD1425 in 2014, according to the world
development indicators (http://data.worldbank.org/data-catalog/world-development-indicators).
18

18

business, while 60% was spent on food and house rent. Entrepreneurs assigned to the financial
training treatment group spent a slightly lower proportion of their business proceeds on food andhouse rent and more on household durables than did the control group entrepreneurs. Furthermore,
37% of the sample entrepreneurs kept records on business transactions, which fell between 25%
in Ghana (Mano et al. 2012) and 63% in Kenya (Mano et al. 2014). While only 28% of theentrepreneurs also kept records on defective products, most entrepreneurs inspected productquality before marketing.
Treatment and control group entrepreneurs did not differ in terms of business practices andperformance measures as indicated in the last rows of Table 2. In December 2013, average sales
revenue was 10,100 birr; the value added 4,000 birr; and gross profit 2,000 birr.19 While capitalstock was 26,400 birr on average, capacity utilization rate was 42%. The average sample
entrepreneur also employed three workers to operate their business.
In sum, we cannot reject the null hypothesis of equality of the means of saving, income,expenditure, business practices, and performance indicators for each of the treatment groups withthe control group.
Table 3 presents the post-treatment values for saving, expenditure, and businessperformance, by treatment status, in December 2014. The average amount of savings was
significantly higher for the SMS reminder treatment. Moreover, this average saved amount has
increased by 115% and 33% since December 2013 for entrepreneurs treated with SMS-reminderand financial training, respectively, while it increased by only 28% among the control group. Table
3 also shows that SMS-reminder was associated with saving a greater proportion of income, moredesire to save larger amounts, higher likelihood of achieving saving goal, and larger amount ofsaving for housing at CBE. The joint treatment has substantially increased the amount of money
entrepreneurs deposited in the banks, while having no effect on the other saving variables. In
contrast, the financial training treatment did not have any impact on saving practices. This may be
because those who attended the training were engaged in smaller businesses, which did not offer
much room for changing their saving behavior.

Value added is sales revenue minus material cost and utility (electricity and water) cost, whereas gross profit isvalue added minus labor cost.
19

19

A striking finding is also that the entrepreneurs assigned to the financial literacy treatment
arm tended to use Iqub (ROSCA) compared with both the control group and the entrepreneurs
treated with SMS reminders and joint interventions. Iqub membership remained at about 20.5%,
whereas the control group gained membership from 28% to 34%. Given that ROSCAs are costly
saving strategies, this correlation is quite intuitive. Still, Iqub can serve as a commitment saving
device.
Table 3 also shows that the SMS-reminder treatment has increased the proportion ofbusiness proceeds that was invested back to the business to 35%, compared with 27 % in thecontrol group. The higher investment on the business appears to be the result of spending cuts onfood and house rent. Entrepreneurs assigned to the SMS-reminder treatment spent 41% of theirbusiness proceeds on food and house rent, which is significantly less than the amount spent byentrepreneurs who are assigned to either of the other treatment groups or the control. This suggeststhat SMS-reminders encouraged consumption smoothing and a more frugal way of living withoutcompromising essential expenditures such as health, education, clothing, and footwear. Also,
given that income levels did not vary by treatment status,20 the higher saving amount observed
among entrepreneurs assigned to the SMS-reminder treatment suggests that micro- and small
businesses suffer from cash management problems because of limited attention. By contrast, thejoint treatment increased deposits in ordinary bank accounts and increased the percentage of saving
goal achieved. To measure the treatment effects more precisely, we would employ regression
analysis and control for relevant characteristics below.

V.

Empirical Strategy and Discussion of Results
As the entrepreneurs were similar in each baseline characteristic across treatment status(Tables 1 and 2), the probit regression of treatment status on baseline characteristics also suggeststhat the random assignment of treatment status was successful (Appendix 3). Moreover, Table 3
shows that the SMS reminder group had significantly greater savings, higher percentage of saving
goal achieved, and larger reinvestment, and that the joint treatment group had significantly higher
percentage of saving goal achieved and larger amount deposited in a bank in the post-treatment

In fact, average income in the control group was higher than the income levels in any of the treatment arms,
although differences were not statistically significant.
20

20

period. To measure the effects of the financial literacy training, the SMS reminder messages andthe joint treatment more precisely, we would run regressions, controlling for other potential
determinants of saving.
More specifically, following McKenzie (2012), we ran an analysis of covariance(ANCOVA) regression, regressing the saving outcome on its lag as well as the treatment status
dummies and other controls. We used the ANCOVA regression because there are important gains
in power over the differences-in-differences (DID) regression, which used to be a major analytical
tool for randomized controlled trials (DID regression results are also largely similar and areavailable upon request).21 The ANCOVA regression can be expressed as follows:S

where S=𝛼+𝛽 𝑍 + 𝜃S

+𝑋 𝛾+𝜀denotes the saving outcomes of individual i after receiving the treatment, 𝑍 is thedummy variable for the randomized treatment k, which refers to (1) financial literacy training, (2)SMS reminder, (3) joint treatment, with (4) the control group as the default status. While subscript
B denotes the data point before receiving the treatment, X denotes the vector of the other controls.
We would estimate the regression parameters 𝛼, 𝛽 , 𝜃, and 𝛾, and 𝜀 is the error term. We are
primarily interested in the value of 𝛽 , which measures the intention to treat effect (ITT), that is,
the average increment in the saving outcome of each treatment group in excess of the saving
outcome of the control group.
Replacing the random assignment dummy 𝑍 with the actual takeup dummy 𝐷 , which is
to be instrumented by 𝑍 , we can estimate the local average treatment effect (LATE). Because therandom assignment dummy 𝑍 is independent of the entrepreneur’s characteristics, it satisfies theexogeneity assumption of the instrumental variable approach. Moreover, the random assignment
dummy 𝑍 is strongly correlated with the takeup dummy 𝐷 , which is the other premise of a valid
instrumental variable. The SMS reminder was sent exclusively to the entrepreneurs assigned to the
SMS reminder and the joint treatment groups. The attendance rate in the financial literacy training
was 42% among the financial training group and 41% among the joint treatment group, but no

According to McKenzie (2012), the ratio of the DID variance to the ANCOVA is 2/[1+ρ], where ρ is the
autocorrelation coefficient. For example, when ρ = 0, we need twice the sample size when using DID to get thesame power as that obtained in ANCOVA.
21

21other attendees (See Appendix 4 for the strong correlation between attendance and assignment totraining). Furthermore, all the treatments were received by the intended entrepreneurs only, andthere were no always-takers, who would receive treatments regardless of their treatment
assignment. This implies that our estimated LATE is equivalent to the average treatment effect on
the actually treated entrepreneurs (ATT) (see Theorem 4.4.2 of Angrist and Pischke 2009).
Table 4 presents the estimated coefficients of the treatment dummies in the ANCOVA
regressions—ITT estimates in the upper panel and LATE estimates in the lower panel.22 We also
report the alternative OLS estimates, which do not control for the lagged outcomes, in Appendices
6 and 7, and the results are essentially the same. We can see from Table 4 that the financial literacy
training did not significantly change the entrepreneur’s saving behavior. This result suggests thatknowledge or financial literacy alone may not be the only reason entrepreneurs tend to undersave.
But it is important to note that the training emphasized rudimentary financial knowledge andtechniques. The financial literacy score in Table 1, which measures the entrepreneur’sunderstanding of basic concepts in finance, seems to suggest that the entrepreneurs already knew
much about them. In fact, the financial literacy score was not significantly different between thefinancial training group and the control group after the training.
By contrast, the SMS reminder significantly increased the savings-to-sales ratio by 54.5%(0.12 standard deviation unit), the percentage of business proceeds reinvested back to business by
91.0% (0.51 standard deviation unit), and the percentage of saving goal achieved by 116% (0.45
standard deviation unit).23 Entrepreneurs assigned to the SMS-reminder also experienced a 137%
increment in their total savings (0.40 standard deviation unit) and 115 % higher deposit amounts
in ordinary bank account (0.16 standard deviation unit). In principle, the SMS reminder wasreceived by all the entrepreneurs assigned to the SMS reminder treatment. This is why ITT
The coefficients of the other explanatory variables are omitted to save space but are available upon request. More
importantly, to check whether the attrition of a few sample entrepreneurs could have caused any serious bias in thetreatment estimates, we ran the probit of sample attrition. The estimation results reported in Appendix 5 suggest thattreatment status is not correlated with attrition. Although few other explanatory variables are correlated with attrition,
they are controlled in the ANCOVA regression to alleviate potential bias. We thus conclude that the attrition bias is
not a serious concern.
22

23Standard deviation units are calculated by taking the ratio between the regression coefficients and the standard
deviations in the baseline for the subgroup. For example, as indicated in Table 4, the coefficient on the SMS
reminder dummy in column 3 is 0.06 and the baseline standard deviation for savings-to-sales ratio is 0.49. SMS
reminder treatment is thus associated with 0.12 standard deviation higher savings-to-sales ratio.

22

estimates are close to LATE (and also ATT) estimates. As expected from the nature of thetreatment, the SMS reminder did not affect the financial literacy score nor did it affect whether theentrepreneur saves or not. In fact, none of our treatments induced entrepreneurs who did not save
before to newly start saving.
Joint treatment significantly increased financial literacy score by 0.28 point on average (ITT)and by 0.60 point for those entrepreneurs who actually received the financial training as well as
SMS reminders (LATE and also ATT). Joint treatment also significantly increased the percentage
of saving goal achieved by 66.5% on average (ITT) and by 148.2% for those entrepreneurs who
actually received both training and reminders (LATE and also ATT). Joint treatment alsosignificantly increased the deposit in the ordinary bank account by 139% (0.64 standard deviationunit) and by more than 633% (1.39 standard deviation unit) for those entrepreneurs who actually
got both treatments.
There was no significant difference among the treatment and control groups regardingwhether the entrepreneur has a housing savings account at the CBE and its deposit amount. We
observed this result probably because this account is not as convenient as a usual saving
commitment account in the sense that the money deposited in this housing account cannot bediverted for other purposes. Moreover, because CBE obliges the participants to save a fixedamount, there is not much room for the account holders’ behavior to change.24
We have come to understand that saving behavior is driven by limited attention, which canbe altered by SMS reminders. Furthermore, the entrepreneurs who attended the financial literacy
training learned the basic financial management. Beyond the fact that the SMS reminder and thejoint treatment influenced the saving outcome, we wish to know whether our treatment had any
effect on Iqub membership and business practices, particularly those closely related with financial
management. For this purpose, we ran the ANCOVA regression on Iqub membership and businesspractices. More specifically, we estimated the treatment effects on whether the entrepreneur (1) isa member of Iqub, 2) keeps records of business transactions, (3) keeps records of defective
products, or (4) inspects quality of products. Table 5 presents the estimation result, and it suggests

Interestingly, however, a specification that trims the bottom 1 percentile and the top 99 percentile of the
distribution of saving for housing purposes shows that reminders increase housing savings amount by as much as
25%.
24

23

that our treatment did not significantly affect the adoption of selected business practices. Yet,column 1 of Table 5 indicates that the financial literacy treatment led to a significant decline in
Iqub membership (the results remain the same across different specifications as indicated inAppendix 8). ROSCAs such as Iqub are often ideal saving instruments for people with low levelsof financial literacy and time-inconsistent preference. As indicated in Appendix 9, entrepreneurs
who have time-inconsistent preference are also more likely to belong to Iqub.

24

VI.

Conclusions
In developing countries, micro-entrepreneurs tend to have insufficient credit access, eventhough they are increasingly expected to play important roles in production and employment.
Alternatively, they could internally retain their earnings and make them available for future
projects. It is unfortunate, however, that they often fail to save sufficiently. This study explores
the reason behind this failure and attempts to find out how we can help micro-entrepreneurs tointernally finance and expand their business. In particular, we hypothesized that microentrepreneurs do not recognize the importance of internally accumulating financial resources andthey also lack the necessary financial skills. Another possibility is that, even if they initially havethe intention of saving, it is difficult to keep it up over the course of their business operation, where
they repeatedly encounter unexpected temptations and pressures of expenditure, including
relatives’ urgent request for borrowing.
To empirically test the validity of these hypotheses, we conducted randomized controlled
trials with 426 sample micro-entrepreneurs operating in Addis Ababa, Ethiopia. Specifically, we
randomly assigned the sample entrepreneurs to four groups: (1) the financial literacy treatment;(2) the SMS reminder treatment; (3) the joint treatment; and (4) the control. Using the ANCOVA
regression method, we find that the SMS reminder significantly increased the savings-to-sales ratio
by 54.5% (0.12 standard deviation unit), the percentage of business proceeds reinvested back tobusiness by 91.0% (0.51 standard deviation unit), savings amount by 137% (0.40 standard
deviation unit), deposits in ordinary bank accounts by 115% (0.16 standard deviation unit), andthe percentage of saving goal achieved by 116% (0.45 standard deviation unit). Moreover, joint
treatment significantly increased the financial literacy score by 0.27 points on average (ITT) andby 0.60 points for those entrepreneurs who actually received the financial training as well as SMS
reminders (ATT). Joint treatment also significantly increased the percentage of saving goal
achieved by 66.5% on average (ITT) and by 148.2% for those entrepreneurs who actually received
both financial training and SMS reminders (ATT). It also had a significant effect on deposit in theordinary bank account, increasing it by 139%.
We find that the entrepreneurs who received only the financial literacy training did not
significantly increase saving. While the entrepreneurs who received only the SMS reminders
increased their savings by reducing daily expenditure on food and house rent, those entrepreneurs
who received both financial literacy training and SMS reminders increased their savings by making
25

use of bank accounts. In short, the amount of savings is crucially driven by attention, which canbe altered with SMS reminders, whereas how they manage savings depends on the financial
literacy of the entrepreneur, which may be improved by financial literacy training. Sending SMS
reminders is not costly, but we find it effective. This is good news for future development policies.
Future research projects would help us learn more about the optimal content and intensity offinancial literacy training.

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Table 1. Baseline characteristics of entrepreneurs and their business andbalancing test (December, 2013)
Variable
Financial
Training
Demographics and experience% maleAgeYears of schoolingYears of working experience% with working experience in formal sector% with management training% with production training
Years of operation% enterprise is self-initiated% with parents in private business
Number of siblings in a similar businessTime preference (% of entrepreneurs)1
Perceived patience score (0 very impatient,
10 very patient)
Somewhat patientTime-consistent
Present-biased
More impatient in future than in present
Discount rate between today and in 3 months’
time (%)
Risk preference 2
Risk taker (%)
Risk neutral (%)
Risk averse (%)
Financial literacy and cognitive skills3
Financial literacy score (max=4)
Digit span recall score (max=8)
Subsectors (% of enterprises)
Manufacturing

Treatment Status
SMS
Joint
Reminder Treatment

Control

All

69.9
37.2
8.55
7.5
28.9
26.5
42.2
8.1
75.9
31.3
0.3

72.6**
36.8
8.23
6.6
29.8
17.9
31.0
7.7
81.0
16.7
0.19

60.2
36.4
8.98
5.9
24.1
27.7
34.9
7.3
80.7
30.1
0.22

58.5
36.8
8.7
7.0
34.7
25.0
30.7
6.8
84.1
25.0
0.19

63.9
36.8
8.64
6.8
30.5
24.4
33.8
7.3
81.2
25.6
0.22

3.3

3.7

3.5

3.2

3.4

12.1
92.8
4.8
2.4
230

7.1
89.3
3.6
7.1
202

20.5
89.2
4.8
6.0
241

10.8
92.1
1.1
6.8
224

12.2
91.1
3.1
5.9
224

31.3
2.4
66.3

32.5
2.4
65.1

19.3
4.8
75.9

26.3
5.1
68.6

27.1
4.0
68.9

2.7
2.9

2.3
2.9

2.3
3.2

2.4
2.8

2.4
2.9

28.9

33.3

38.6

30.1

32.2

31

Construction
10.8
13.1
8.4
4.6
8.2
Retail and service
60.2
53.6
53.0
65.3
59.6
83
84
83
176
426
Number of observations
Notes: Except for the digit span exercise, the mean values for all the variables are from the baseline data collected
in December 2013. * p < 0.10 and ** p < 0.05 in mean test with the control group.
1
The measures of time preference are generated from respondent’s choices in the following two games: i) receiving
1000 birr tomorrow or receiving 1100 birr in 1 month and ii) receiving 1000 birr in 1 month or receiving 1100 birrin 2 months. “Somewhat patient” individuals prefer 1100 birr a month later from 1000 birr tomorrow (Dupas andRobinson, 2013). “Time-consistent” respondents are either those who choose “1000 birr tomorrow” in game (i) and“1000 birr in 1 month” in game (ii), or those who choose “1100 birr in 1 month” in game (i) and “1100 birr in 2
months” in game (ii). In contrast,“time-inconsistent” respondents are either those who choose “1000 birr tomorrow”
in game (i) and “1100 birr in 2 months” in game (ii), or those who choose “1100 birr in 1 month” in game (i) and“1000 birr in 1 month” in game (ii). “Present-biased” respondents are those who choose “1000 birr tomorrow” ingame (i) and “1100 birr in 2 months” in game (ii). This behavior may be explained by higher discount rate in the
short run than in the long run. Respondents are “More patient in the future than in the present” if they have higher
discount rates in the future than in the present; they choose “1100 birr in 1 month” in game (i) and “1000 birr in 1
month” in game (ii). “Discount rate between today and in 3 months’ time” indicates how much the respondents
would like to receive in 3 months’ time to be indifferent with receiving 1000 birr today, it is calculated in percent
form using

× 100 (%) where 𝑇 denotes the amount in 3 months’ time proposed by the respondent.

2

Risk preference is captured as follows. Respondents were offered a choice between receiving 2000 birr for sure orplaying a game that pays 4000 birr with a probability of 0.5 and zero birr with a probability of 0.5 in a hypotheticallottery game. The variables “risk taker,” “risk averse,” and “risk neutral” are dummies that assume the value 1 if the
respondent chooses the lottery game, the sure bet, or is indifferent between the two options, respectively.
3
Following Cole et al. (2011) and Xu and Zia (2012), financial literacy score is constructed by adding the number ofcorrect answers a respondent provided to four basic financial literacy questions. The questions are:
Q1) Suppose you borrow 1000 birr from a money lender at an interest rate of 2 percent per month, with no repayment
for 3 months. After 3 months, do you owe (Options are 1. Less than 1020 birr 2. Exactly 1020 birr 3. Greater than
1020 birr 4. Don’t know)
Q2) Do you think you can open a bank account with an amount as low as 50 birr? (Options are 1. Yes
2. No
3. Don’t know)
Q3, Suppose you need to borrow 500 birr. Two persons offer you a loan. The first loan requires you to pay back 600
birr in 1 month. The second loan requires you to pay back 500 birr plus 15% interest rate in 1 month’s time. Whichloan would you prefer? (Options are 1. The first loan 2. The second loan 3. Both are equal)
Q4. If you have 1000 birr in a savings account earning 1% interest per annum, and prices for goods and services rise
at 2% over a 1-year period, with the money in your account you can buy. (Options are 1. More goods and services in
1 year’s time compared with today 2. Less goods and services in 1 year’s time compared with today; 3.The sameamount of goods and services in 1 year’s time compared with today)
Digit-span score tests cognition by presenting cards labeled with different digit numbers to respondents for 10 seconds
and asking the respondent to recall the digits in the exact same order as displayed earlier after the card is taken awayfrom him. The exercise starts recalling from a four-digit number and increases in difficulty with the final card
containing an 11-digit number.

32

Table 2. Baseline values for saving, expenditure, and business performanceindicators and balancing test (December 2013)
Variable
Financial
Training

Treatment Status
SMS
Joint
ReminderTreatment

ControlAll

Savings
Total amount saved in the last 30 days (birr)
457
749
328
503
509
Amount entrepreneur would like to save per month given
744
961
933
744
832
his income (birr)% of saving goal achieved
49.6
65.1
79.9
49.6
58.6
Savings-to-sales ratio
0.07
0.15
0.15
0.09
0.11
% with a bank account
81.9
84.5
84.3
80.7
82.4
Amount deposited in a bank in the last 30 days (birr)
141
382
186
128
192
% who are Iqub (ROSCA) members
20.5
32.1
34.9
28.4
28.9
% with special housing savings account at CBE 1
56.6
52.3
55.4
63.1
58.2
Amount of savings for housing at CBE (birr)
565
808*
620
511
462
IncomeProfit from business in the last 30 days (birr)
2116
2286
1905
1816
1985
Cost of saving
Minutes spent in making deposits in the nearest bank
27.4
30.1
30.4
27.9
28.8
Distance to the nearest bank to make deposit (in km)
0.98
1.49
1.34
0.89
1.11
Transport cost to make deposits (in birr)
0.63
3.99
0.81
0.61
1.32
Forgone business income when commuting to make
5.92
8.18
11.5
8.18
9.55
deposits (in birr) 2
Expenditure in the last 3 months (%)
Invested back to business
13.2
7.3
8.4
9.8
9.7
Food and house rent
55.2
60.3
60.4
61.0
59.6
Clothing and footwear
3.6
4.2
4.7
4.6
4.4
Health and education
7.4
6.8
7.0
7.3
7.1
Household durables
1.3
1.2
1.0
1.0
1.0
Consumption of alcohol and entertainment
3.3
3.5
2.2
3.5
3.2
Other expenditures
2.8
3.3
2.9
3.6
3.3
Business practice
Keeps records of business transactions
37.8
41.7
34.9
33.9
36.4
Keeps records of defective products
31.3
27.4
26.8
33.1
30.4
Inspects quality of products before marketing them
98.8
90.5
92.8
95.4
94.6
Business performance (103birr)
Sales in November 2013
8.1
10.1
15.7
8.5
10.1
Value added in November 2013
4.0
4.6
4.4
3.6
4.0
Gross profit in November 2013
2.1
2.3
1.9
1.8
2.0
Capital stock as of November 2013
31.2
27.8
20.3
26.2
26.4
Capacity utilization rate in November 2013 (%)
43.4
43.3
43.1
41.1
42.4
Number of employees as of November 2013
3.31
3.46
3.10
3.00
3.17
83
84
83
176
426
Number of observations
Notes. * p < 0.10, ** p < 0.05 and *** p < 0.01 in mean test with the control group.
1.Saving for housing at CBE is almost a sort of forced savings where people would be kicked out of the program for
failing to save, and those who save quickly and constantly get a better chance of winning the housing raffle.
Because of this difference in nature from the rest of saving, we have decided to treat them separately.

33

2. Forgone business income when commuting to make deposits (in birr) is measured by asking the respondent how
much money they lose in earned income when they go to the nearest bank to make deposits.
3. Variability of sales is measured by taking the difference between sales in peak month and sales in slack month.

Table 3. Impact on business knowledge, financial decision, business practice, and businessperformance (2014)
Variable
Financial
Training

Treatment Status
SMS
Joint
ReminderTreatment

ControlAll

Savings
Amount saved in the last 30 days (birr)
645
1586*
1071
700
937
Amount entrepreneur would like to save per month
1436
1419
2154*
1241
1206
given his income (birr)a% of saving goal achieved
44.7
96.7***
81.2**
45.8
62.5
Savings-to-sales ratio
0.07
0.11***
0.09***
0.06
0.08% with a bank account
85.5
86.9
84.3
86.9
86.2
Amount deposited in a bank in the last 30 days (birr)
373
628
815**
319
487
% who are Iqub (ROSCA) members
20.7**
31.0
28.9
33.9
29.6
% with special housing savings account at CBE
50.6
52.4
52.4
58.6
54.6
Amount of savings for housing at CBE (birr)
521
519
635*
556
457
IncomeProfit from business in the last 30 days (birr)
3838
4741
4827
5043
4706
Cost of saving
Minutes spent in making deposits in the nearest bank
20.6
22.9
21.3
21.5
21.5
Distance to the nearest bank to make deposit (in km)
0.95
0.95
0.84
0.77
0.86
Transport cost to make deposits (in birr)
0.70
1.32
0.66
0.48
0.73
Forgone business income when commuting to make
22.8
18.1
25.4
16.8
19.9
deposits (in birr) 1
Expenditure in the last 3 months (%)
Invested back to business
25.6
34.5*
25.1
27.3
27.9
Food and house rent
49.1
40.7**
50.5
47.5
47.1
Clothing and footwear
8.1
7.5
6.9
7.3
7.4
Health and education
8.6
8.7
10.9
10.1
8.9
Household durables
1.6***
0.7
0.9
0.7
0.9
Consumption of alcohol and entertainment
2.4
2.5
1.9
2.7
2.5
Other expenditures
5.5
5.5
3.8
4.2
4.6
Business practice
Keep records of business transactions
44.6
44.1
45.8
51.1
47.4
Keep records on defective products
25.3
27.4
27.7
23.3
25.4
Inspect quality of products before marketing them
79.5
73.8
85.5
76.7
78.4
Business performance (103birr)
Sales in November 2014
29.7
21.6
16.9
18.5
21.0
Value added in November 2014
6.4
7.4
6.9
7.4
7.1
Gross profit in November 2014
5.0
6.0
5.4
6.0
5.7
Capital stock as of November 2014
29.2
33.0
26.7
36.0
32.2
Capacity utilization rate in November 2014 (%)
46.2
50.7
52.0
51.6
50.4
Number of employees as of November 2014
1.77
1.77
1.65
1.39
1.59
Number of observations
83
84
82
174
426
Notes. aWe control for three outliers that reported the value of saving goals to be more than 2500 %. * p < 0.10, **p < 0.05 and *** p < 0.01 in mean test with the control group.

34

35

-0.07(0.12)
0.00(0.12)
0.28**(0.12)(1)Financial
literacy
score

420

0.02
(0.07)
0.07(0.07)
0.06(0.07)(2)

Savingdummy(Yes=1)

0.03(0.04)
0.06***(0.02)
0.08**

422

0.01(0.02)
0.06***(0.02)
0.04*(0.02)(3)(6.47)

1.56(7.30)
5.62*(2.93)
-5.20

422

0.67
(2.98)
5.67*(2.97)-2.38(2.96)% businessproceeds
investedback tobusiness(4)

420(1,026.78)

90.48(1,142.75)
968.18**(457.85)
1,014.78

420

32.36
(468.07)955.94**(469.26)454.01(469.21)(5)419(49.94)27.85(56.18)75.31***(22.60)110.33**

419

10.70
(22.93)74.21***(23.04)49.51**(22.87)(6)422(0.13)-0.04(0.14)
0.03(0.06)
-0.06

422

-0.02
(0.06)
0.05(0.06)-0.03(0.06)(7)

With a bankaccount

422

261.96(575.93)386.86*(231.34)
1,178.61**(510.08)

422

99.63
(236.29)372.55(236.98)530.54**(235.72)(8)

Depositedamount in
the last 30
days

422

(0.11)-0.06(0.13)
0.01(0.05)
-0.00

422

-0.02
(0.05)
0.01(0.05)-0.00(0.05)

Has a
housingsavings
account at
CBE
(9)

422

(130.37)-61.11(145.07)79.10(58.86)47.56

422-25.19(60.37)78.26(60.25)22.31(60.03)(10)% of saving
goal achieved

422

0.06
(0.16)
0.07(0.06)
0.13(0.04)

422

Savings-tosales ratio-0.17(0.29)
0.01(0.12)
0.60**(0.14)

422

Saved
amount for
housing at
CBE(0.25)

420

Saved amountin the last 30
days

422

Table 4. Estimated effects of getting financial literary treatment, reminder treatment, and both treatments in 2015 (ITT and LATE)VARIABLEANCOVAestimates (ITT)
Financial training
SMS reminder
Joint treatment
Number of
Observations

ANCOVA IV
estimates (LATE)
Financial training
SMS reminder
Joint treatment

Number ofobservations

Notes. Standard errors are in parentheses. * p < 0.10, ** p < 0.05 and *** p < 0.01.

36

Is a member of
Iqub (Yes=1)(2)

ITT
Keeps recordsof business
transactions

0.00(0.05)
0.01(0.05)
0.02(0.05)
420

Keeps
records ofdefective
products(3)

0.02(0.05)-0.05(0.05)
0.06(0.05)
421(4)

Inspects
quality of
products-0.25*(0.14)
0.00(0.06)-0.13(0.13)
421(1)

Is a member of
Iqub (Yes=1)-0.26(0.17)-0.08(0.07)-0.09(0.14)
419

(2)

0.02
(0.13)
0.02(0.05)
0.05(0.11)
420

Keeps
records ofdefective
products(3)

0.05(0.13)-0.06(0.05)
0.14(0.12)
421(4)

Inspects
quality of
products(1)-0.10(0.07)-0.09(0.07)-0.04(0.07)
419

LATE
Keeps recordsof business
transaction-0.10*(0.06)
0.00(0.06)-0.05(0.06)
421

Table 5. OLS and IV estimates of the effects of getting financial literary, reminder, and both treatments on ROSCA membership andbusiness practice indicators
VARIABLE

Financial training
SMS reminder
Joint treatment
Number of observations

Notes. Standard errors are in parentheses. * p < 0.10, ** p < 0.05 and *** p < 0.01.

37

Appendix 1: Brief outline of the financial literacy training
Outline1. Financial Planning, Budgeting, and Savingsx

Learn how to plan with respect to business proceeds by first taking stock of
their expenditures and then critically exploring ways to reduce expenses andsave the differencex

Learn the importance of discussing budgets with family/spouse on a monthly
basis

x

Lessons on how to prioritize expenditure and ways of cutting back on nonessential expensesx

Prepare and follow a budget in line with expensesx

Know the advantages of properly recording business transactions, such as
revenue, expenses, credits and loans.

2. Saving strategies¾ Examine various saving options looking at the risk/reward trade-offs. Amongothers, saving options include saving money under a mattress, ROSCA, bank,microfinance, and with relatives and friends¾ Banksx

Types of accountsxMinimum balance to open a savings accountx

Account operating mechanisms (There are, for example, two types of operating
mechanisms: individual or jointly; the latter involves “AND” or “AND/OR”
types)

x

Benefits from using formal bank accountsx

Required documents

3. Goal setting and planningx

Learn about the need to set specific, achievable, and realistic goals and work

towards them. There should be a deadline for each goal. At the end of the training,
we will ask each participant to come up with such goals for the next 3 months.
x

Lessons on how to live within their means and not spend excessively

38

Appendix 2: Description of variables used in the analysis
Variable
Male

Description

Age

Percentage of firms owned by male entrepreneurs or whose lead person
are males in case of cooperatively owned firms
Age of the owner or the lead person

Years of schoolingHighest completed years of schooling achieved by the owner/lead person

Years of working experience% with working experience in formal sector

Total years of experience of the owner/lead person
Percentage of the owner/lead person in the sample who had worked in theformal sector
Percentage of firms which took formal training on management andfinancial skills
Percentage of firms involved in technical/skill-based training
Number of years the enterprise was actively engaged in business
Percentage of firms established by the owner’s initiative as opposed tothose initially established by the state
Percentage of firms whose owner’s mother or father was a business owner
Total number of brothers or sisters of the owner of the enterprise who are
involved in a similar business before the owner started businessRespondent’s own rating of his/her level of patience on a scale from 0=very impatient to 10=very patient
A respondent who preferred 1100 birr a month later from 1000 birr
tomorrow
Respondents who showed a similar pattern of behavior when asked tochoose between a guaranteed income of 1000 or 1100 of income sometime
later
Respondents who preferred guaranteed income of lesser amount in thenear future than wait for more income at a later time
Respondents who have higher discount rate in the future than in thepresent
Amount of money a respondent will be willing to receive in 3 months’
time to be indifferent to receiving a 1000 birr today.
A respondent who chose to play a hypothetical lottery game when an offerthat pays 2000 birr for sure or playing a game that pays 4000 birr withequal probability of winning or losing was madeA respondent who was indifferent between accepting the sure payment of2000 birr or playing the lottery in a hypothetical lottery game when anoffer that pays 2000 birr for sure or playing a game that pays 4000 birr
with equal probability of winning or losing was madeA respondent who chose to accept the sure amount of 2000 birr in ahypothetical lottery game when an offer that pays 2000 birr for sure orplaying a game that pays 4000 birr with equal probability of winning or
losing was madeThree questions were asked the respondents to check how financiallyliterate they are. The questions are about interest calculation, minimumbank deposit requirement, and knowledge of inflation. Finally,
respondents were rated out of a maximum of four points.
Measures the cognition ability of the respondent where the respondent isallowed to look at a number written on a card for 10 seconds only andasked to remember what was written on the card.

% with management training% with production training
Years of operation% enterprise is self-initiated% with parents in private business
Number of siblings in a similar business
Perceived patience score (0 very impatient,
10 very patient)
Somewhat patientTime-consistent
Present-biased
More impatient in the future than in present
Discount rate between today and in 3
months’ time (%)
Risk taker (%)
Risk neutral (%)

Risk averse (%)

Financial literacy score (max=4)

Digit span recall score (max=8)39

Manufacturing
Construction
Retail and service
Total amount saved in the last 30 days (birr)
Amount entrepreneur would like to save permonth given his income (birr)% of saving goal achieved
Savings-to-sales ratio% with a bank accountAmount deposited in a bank in the last 30
days (birr)% with special housing savings account at
CBE
Amount of savings for housing at CBE (birr)

Percentage of firms engaged in the manufacturing sector
Percentage of firms engaged in the construction sector
Percentage of firms engaged in the retail and services sector
Total amount of money saved, including cash at home and on hand
Largest possible amount of savings the owner would like to save per
month
Percentage of money the owner actually saved, given the amount he would
like to save
The ratio of savings amount to sales revenue.
Ratio of firms that have opened an ordinary savings accountTotal amount of money the firm managed to deposit in the 30 days before
the interview
Percent of firms that have opened a mortgage account at CBE to qualify
for the state-run housing project
Total amount of money deposited at the CBE special housing account

Profit from business in the last 30 days (birr)

Total amount of money the firm earned during the month of October

Minutes spent in making deposits in thenearest bank
Distance to the nearest bank to make deposit(in km)Transport cost to make deposits (in birr)

Total time taken to make deposits to the nearest bank

Forgone business income when commuting
to make deposits (in birr)
Invested back to business
Food and house rent
Clothing and footwear
Health and education
Household durables
Consumption of alcohol and entertainment
Keeps records of business transactions
Keeps records of defective products
Inspects quality of products before marketingthem

Distance in kilometers of the nearest bank the firm could make deposits at
Total amount of money spent on transportation by the firm to makedeposits at the bankMoney that is lost in earned income by the firm when making deposits atthe nearest bank
Percentage of proceeds from business in the last 3 months that is invested
back to the business
Percentage of business proceeds of the last 3 months which is spent onfood and house rent
Percentage of last 3 months’ business proceeds spent on clothing and footwear
Percentage of last 3 months’ business proceeds spent on education, healthand medical expenses
Percentage of business proceeds of the last 3 months spent on purchase ofhousehold durables
Percentage share of business proceeds of the last 3 months spent on
consumption of alcoholic beverages, khat and/or tobacco
Frequency of keeping records of business transactions by the business firm
Firms that keep records of the defective products
Firms that answered “yes” to the question “Do you inspect quality of
products before selling them?”

40Appendix 3: Evidence of randomization (probit; marginal effects)
VARIABLE
Entrepreneur is male (Yes=1)
Entrepreneur’s age
Years of schoolingYears of prior experienceHas working experience in formal sector(Yes=1)
Had taken training in production skills as ofDecember 2013(Yes=1)
Had taken training in management skills as ofDecember 2013 (Yes=1)
Year of operation
Enterprise is own initiative (Yes=1)
Parents in private business (Yes=1)
Has siblings in similar business before the startof own business (Yes=1)

Financial
Training(1)

SMS
Reminder(2)

Joint
Treatment(3)

Financial
Training(4)

SMS
Reminder(5)

Joint
Treatment(6)

0.04(0.04)-0.00(0.00)
0.00(0.00)
0.00(0.00)-0.04

0.06(0.04)-0.00(0.00)-0.00(0.00)
0.00(0.00)
0.00-0.02(0.04)
0.00(0.00)
0.00(0.00)-0.00(0.00)-0.05

0.05(0.04)-0.00(0.00)-0.00(0.01)
0.00(0.00)-0.03

0.04(0.04)-0.00(0.00)-0.00(0.01)-0.00(0.00)
0.01-0.03(0.05)
0.00(0.00)
0.00(0.01)-0.00(0.00)-0.06(0.04)
0.06(0.04)-0.01(0.04)
0.01(0.04)
0.09(0.05)-0.05(0.04)
0.03(0.05)-0.02(0.04)
0.00(0.05)
0.00(0.06)-0.05(0.05)
0.01(0.05)-0.00(0.05)
0.00(0.00)-0.03(0.05)
0.05(0.04)
0.02(0.00)
0.00(0.00)
0.01(0.05)-0.04(0.04)-0.02(0.00)-0.00(0.00)-0.01(0.05)
0.03(0.04)
0.01(0.06)
0.00(0.00)-0.04(0.06)
0.06(0.05)
0.02(0.01)
0.00(0.00)
0.06(0.06)-0.07(0.04)-0.00(0.01)-0.00(0.00)-0.00(0.06)
0.03(0.05)-0.01(0.03)(0.03)(0.03)(0.03)
0.00(0.03)-0.01(0.03)
0.00(0.01)-0.01(0.07)
0.14(0.14)
0.09(0.10)
0.04*(0.02)-0.01(0.02)-0.03(0.04)
0.02(0.10)
422(0.01)
0.03(0.07)
0.17(0.14)
0.10(0.10)-0.01(0.02)-0.01(0.02)
0.02(0.05)
0.24*(0.14)
422(0.01)
0.06(0.07)-0.09(0.09)-0.01(0.10)-0.03(0.02)
0.03**(0.02)
0.08*(0.05)-0.01(0.09)
422

Discount rate between today and in 3 months’
time (%)
Time inconsistent (Yes=1)
Risk taker (Yes=1)
Risk averse (Yes=1)
Financial literacy score (max=4)
Digit span recall score (max=8)
Manufacturing sector (Yes=1)
Construction sector (Yes=1)
Number of observations

508

508

508

Notes. Standard errors are in parentheses. * p < 0.10, ** p < 0.05 and *** p < 0.01.

41

42

(1)
0.40***(0.03)
0.00(0.03)-0.01(0.03)
0.03(0.02)-0.00(0.00)
0.01**(0.00)
0.00(0.00)-0.03(0.02)
0.06*(0.03)-0.00(0.03)-0.00*(0.00)
0.01(0.03)
0.02(0.03)
0.01(0.02)(2)
0.40***(0.03)
0.00(0.03)-0.01(0.03)
0.03(0.02)-0.00(0.00)
0.01*(0.00)
0.00(0.00)-0.02(0.03)
0.06**(0.03)-0.01(0.03)-0.00*(0.00)
0.01(0.03)
0.02(0.03)
0.01(0.02)
0.03(0.04)-0.02(0.06)
0.02(3)
0.40***(0.03)-0.00(0.03)-0.02(0.03)
0.01(0.03)-0.00(0.00)
0.01*(0.00)
0.00(0.00)-0.02(0.03)
0.05(0.03)-0.00(0.03)-0.00*(0.00)
0.03(0.04)
0.02(0.03)
0.02(0.02)
0.03(0.04)-0.00(0.06)
0.03

(4)
-0.00
(0.03)-0.00(0.03)
0.46***(0.03)
0.03(0.02)
0.00(0.00)-0.00(0.00)
0.00(0.00)-0.04(0.03)-0.03(0.03)-0.01(0.03)-0.00*(0.00)-0.07**(0.03)
0.02(0.03)
0.00(0.02)(5)-0.01(0.03)-0.01(0.03)
0.46***(0.03)
0.03(0.02)
0.00(0.00)-0.00(0.00)
0.00(0.00)-0.03(0.03)-0.02(0.03)-0.02(0.03)-0.00*(0.00)-0.08**(0.03)
0.02(0.03)
0.00(0.02)
0.08**(0.04)
0.05(0.06)
0.07

(6)
-0.01
(0.03)-0.01(0.03)
0.45***(0.03)
0.03(0.03)
0.00(0.00)-0.00(0.00)-0.00(0.00)-0.04(0.03)-0.01(0.03)-0.03(0.03)-0.00*(0.00)-0.09**(0.04)
0.02(0.03)-0.00(0.02)
0.09**(0.04)
0.05(0.06)
0.07

Appendix 4: Estimated linear probability model of attendance rate in the financial literacy training
VARIABLE
Attendance rate in the
Attendance rate in the financial
financial literacy training
literacy training when assigned
when assigned to theto the joint treatment regime
financial literacy training
regimeFinancial training
SMS reminder
Joint treatment

Entrepreneur is male (Yes=1)
Entrepreneur’s age
Years of schoolingYears of prior experienceHas a working experience in formal
sector (Yes=1)
Had taken training in production skills asof December 2013(Yes=1)
Had taken training in management skills
as of December 2013 (Yes=1)
Year of operation
Enterprise is own initiative (Yes=1)
Parents in private business (Yes=1)
Has siblings in similar business before
the start of own business (Yes=1)
Time inconsistent (Yes=1)
Risk taker (Yes=1)
Risk averse (Yes=1)43(9)0.39***(0.04)-0.01(0.04)
0.44***(0.04)
0.05(0.04)
0.00(0.00)
0.00(0.00)
0.00(0.00)-0.06(0.04)
0.04(0.05)-0.03(0.05)-0.01***(0.00)-0.06(0.05)
0.04(0.04)
0.02(0.02)
0.11**(0.05)
0.04(0.08)
0.10

Attendance rate in the financial
literacy training when assigned
to either treatment regime(7)
0.40***(0.04)-0.00(0.04)
0.45***(0.04)
0.06*(0.03)
0.00(0.00)
0.01(0.00)
0.00(0.00)-0.07*(0.04)
0.03(0.04)-0.01(0.05)-0.01***(0.00)-0.06(0.05)
0.04(0.04)
0.01(0.02)(8)
0.39***(0.04)-0.01(0.04)
0.44***(0.04)
0.06*(0.03)
0.00(0.00)
0.00(0.00)
0.00(0.00)-0.06*(0.04)
0.04(0.04)-0.03(0.05)-0.01***(0.00)-0.07(0.05)
0.04(0.04)
0.01(0.02)
0.11**(0.05)
0.03(0.08)
0.09

Financial literacy score (max=4)
Ln capital stock
Manufacturing sector (Yes=1)
Construction sector (Yes=1)
Constant
Number of observations

0.15*(0.08)
417-0.02***(0.01)

0.14(0.09)
415(0.06)
0.01(0.01)-0.02***(0.01)(0.06)
0.01(0.01)-0.02***(0.01)
0.00(0.02)
0.08(0.05)
0.10(0.10)
415

Notes. Standard errors in parentheses. * p < 0.10, ** p < 0.05 and *** p < 0.01.

44

0.03
(0.08)
417

0.00(0.01)-0.04(0.10)
415(0.06)
0.00(0.01)
0.00(0.01)(0.06)
0.00(0.01)
0.00(0.01)
0.02(0.02)-0.03(0.05)-0.02(0.10)
415

0.17(0.11)
417-0.02*(0.01)

0.10(0.13)
415(0.08)
0.01(0.01)-0.02*(0.01)(0.08)
0.01(0.01)-0.02*(0.01)
0.02(0.03)
0.05(0.08)
0.08(0.14)
415

Appendix 5: Estimated probit model of attrition
VARIABLE
Financial training
SMS reminder
Joint treatment
Entrepreneur is male (Yes=1)
Entrepreneur’s age
Years of schoolingYears of prior experienceHas a working experience in formal sector(Yes=1)

Dependent variable is Exit, which is equal to 1 for enterprises thatare not observed in 2014 and to 0 otherwise.
(1)
(2)
(3)
(4)
-0.01
-0.00
-0.01
-0.02
(0.04)(0.04)(0.04)(0.04)
-0.01
-0.01
-0.02
-0.02
(0.04)(0.04)(0.04)(0.04)
0.00
0.01
0.01
0.01
(0.04)(0.04)(0.04)(0.04)
0.08***
0.08***
0.04(0.03)(0.03)(0.03)
0.00
0.00
0.00
(0.00)(0.00)(0.00)
-0.00
0.00
-0.00
(0.00)(0.00)(0.00)
-0.00
-0.00
-0.00
(0.00)(0.00)(0.00)
0.09**
0.08**
0.09**

Had taken training in production skills as ofDecember 2013(Yes=1)
Had taken training in management skills as ofDecember 2013 (Yes=1)
Year of operation
Enterprise is own initiative (Yes=1)
Parents in private business (Yes=1)
Has siblings in similar business before the start ofown business (Yes=1)(0.04)-0.08**(0.04)-0.08**(0.04)-0.13***(0.04)
0.00(0.04)
0.00(0.03)
0.00(0.00)-0.01**(0.00)-0.14**(0.06)
0.00(0.04)-0.05(0.00)-0.01**(0.00)-0.14**(0.06)
0.00(0.04)-0.05(0.00)-0.01*(0.00)
0.03(0.05)
0.01(0.04)-0.03(0.03)(0.03)
0.01(0.05)
0.17(0.13)
0.11(0.08)-0.00(0.02)

508

504(0.03)
0.00(0.05)
0.28*(0.15)
0.16**(0.07)
0.00(0.02)-0.05(0.03)
0.50***(0.12)
504

Time inconsistent (Yes=1)
Risk taker (Yes=1)
Risk averse (Yes=1)
Financial literacy score (max=4)
Manufacturing sector (Yes=1)
Construction sector (Yes=1)
Number of observations
508
Notes. Standard errors in parentheses * p<0.1, , ** p<0.05, *** p<0.01.

45%business
proceeds
investedback tobusiness(4)-54.29(451.54)886.24**(449.72)
371.51(453.41)(5)

6.24(22.66)67.11***(22.62)50.58**(22.47)-2.23(22.40)59.14***(22.40)42.84*(22.40)(6)-0.02(0.06)
0.06(0.06)-0.01(0.06)
426-0.02(0.06)
0.06(0.06)
0.00(0.06)-0.07(0.07)
0.03(0.07)-0.01(0.07)(7)

With a bankaccount

96.33(236.35)
389.52(236.58)
529.12**(235.79)426

93.11(233.93)
340.19(232.55)
522.68**(232.11)53.98(230.19)309.51(229.25)495.36**(230.19)(8)

Depositedamount in
the last 30
days

-0.08
(0.06)-0.07(0.06)-0.05(0.06)
423-0.08(0.06)-0.06(0.06)-0.03(0.06)-0.08(0.07)-0.06(0.07)-0.06(0.07)(9)Has ahousingsavings
account at
CBE

11.37
(63.85)92.85(63.91)
32.24(63.70)422

20.31(64.49)97.13(64.11)
43.00(63.99)6.58(65.25)70.06(64.98)25.87(65.25)

(10)

Saved
amount for
housing at
CBE% of saving
goal
achieved(3)-1.70(3.14)
7.14**(3.18)-2.26(3.18)

16.66(461.51)901.19*(459.12)439.57(459.77)

10.72(22.90)74.35***(23.02)49.88**(22.84)423

Savingsto-sales
ratio

(2)
0.01
(0.02)
0.05**(0.02)
0.03*(0.02)-0.25(3.17)
7.84**(3.17)-1.92(3.15)

15.68(468.31)989.16**(469.00)
427.97(469.21)424

Savingdummy(Yes=1)(1)-0.03(0.17)
0.07(0.17)
0.20(0.17)

0.01(0.02)
0.05***(0.02)
0.04*(0.02)

0.18(3.09)
6.61**(3.12)-1.98(3.09)
422

Financial
literacy
score

-0.02
(0.13)
0.03(0.13)
0.30**(0.13)

0.02(0.17)
0.17(0.17)
0.19(0.18)

0.01(0.02)
0.06***(0.02)
0.04*(0.02)
422

Saved
amount in
the last 30
days

-0.05
(0.12)-0.01(0.12)
0.29**(0.12)

0.01
(0.2)
0.2
(0.2)
0.2
(0.2)
424

Appendix 6: Estimated effects of getting financial literary, reminder, and both treatments in 2015 (ITT)VARIABLE

OLS without baseline controls
Financial training
SMS reminder
Joint treatment
OLS with baseline controls forentrepreneurial characteristics andbusiness sector
Financial training
SMS reminder
Joint treatment
OLS with baseline controls forentrepreneurial characteristics, sector
and risk and time preferences
Financial raining
SMS reminder
Joint treatment-0.07(0.12)
0.00(0.12)
0.27**(0.12)
426

Notes. Standard errors are in parentheses. * p < 0.10, ** p < 0.05 and *** p < 0.01.

Number of observations46

-0.04(0.31)
0.03(0.13)
0.65**(0.28)(1)Financial
literacy score

0.01(0.16)
0.07(0.06)
0.17(0.15)-0.03(0.16)
0.03(0.07)
0.17(0.15)(2)

Savingdummy(Yes=1)0.03(0.05)
0.06***(0.02)
0.08*(0.04)

0.03(0.05)
0.05***(0.02)
0.08*(0.04)

0.02(0.05)
0.05**(0.02)
0.07*(0.04)

(3)

420

0.04
(7.73)
6.32**(3.05)-4.33(6.62)-0.78(8.00)
7.74**(3.13)-4.20(6.78)-4.12(7.63)
7.14**(3.19)-4.83(6.82)% businessproceeds
investedback tobusiness
(4)

424

50.53
(1,143.84)
998.8**(457.77)958.74(1,030.83)

48.58(1,133.3)
907.43**(450.85)
987.42(1,015.07)-132.5(1,093.9)
823.34(997.2)886.2**(446.28)

(5)

Saved
amount in
the last 30
days

423

27.88
(56.19)75.39***(22.60)110.78**(49.74)16.20(55.88)67.8***(22.33)112.0**(49.11)-5.45(54.61)59.1***(22.37)93.58*(48.86)(6)% of saving
goal
achieved

426

-0.06
(0.15)
0.04(0.06)-0.03(0.13)-0.05(0.15)
0.05(0.06)
0.00(0.13)-0.16(0.16)
0.03(0.07)-0.02(0.14)(7)

With a bankaccount

426

254.71(576.61)401.7*(230.88)
1,175.6**(510.83)240.56(573.71)347.74(228.33)
1,159.7**(504.78)131.77(557.22)
1,082.0**(498.56)309.51(227.33)(8)

Depositedamount in
the last 30
days

423

-0.20
(0.16)-0.06(0.06)-0.11(0.14)-0.19(0.16)-0.05(0.06)-0.08(0.14)-0.20(0.16)-0.06(0.07)-0.14(0.15)

Has a
housingsavings
account at
CBE
(9)

422

29.33
(156.32)
93.58(62.59)72.09(138.49)

51.48(158.92)
97.75(63.25)95.92(139.82)

16.06(158.67)56.50(141.97)70.06(64.73)(10)

Savings-tosales ratio-0.13(0.29)-0.00(0.12)
0.65**(0.26)

0.04(0.16)
0.08(0.06)
0.16(0.15)

422

Saved
amount for
housing at
CBE

-0.17
(0.29)
0.01(0.12)
0.60**(0.25)

424

Appendix 7: IV estimates of the effects of getting financial literary, reminder, and both treatments (LATE)VARIABLE

OLS without baseline controls
Financial training
SMS reminder
Joint treatment

OLS with baseline controls forentrepreneurial characteristics andbusiness sector
Financial training
SMS reminder
Joint treatment

OLS with baseline controls forentrepreneurial characteristics, sector andrisk and time preferences
Financial training
SMS reminder
Joint treatment

426

Notes. Standard errors are in parentheses. * p < 0.10, ** p < 0.05 and *** p < 0.01.

Number of observations

Appendix 8: OLS and IV estimates of the effects of getting financial literary, reminder, and both treatments on business practiceindicators
47

VARIABLE

OLS without baseline controls
Financial training
SMS reminder
Joint treatment
OLS with baseline controls forentrepreneurial characteristics
Financial training
SMS reminder
Joint treatment
OLS with baseline controls forentrepreneurial characteristics and risk
and time preferences
Financial training
SMS reminder
Joint treatment
Number of observations

0.02(0.06)
0.04(0.06)
0.04(0.06)

0.02(0.05)-0.05(0.05)
0.07(0.05)

0.03(0.05)-0.03(0.05)
0.09(0.05)(4)

Inspects
quality of
products-0.31**(0.15)-0.10(0.13)
0.01(0.06)
425-0.29*(0.15)-0.08(0.13)
0.01(0.06)-0.31**(0.15)-0.10(0.13)-0.03(0.06)(5)

Is a memberof Iqub(Yes=1)-0.23(0.17)-0.07(0.07)-0.10(0.15)
426-0.19(0.17)-0.06(0.07)
-0.10
-0.19

-0.16
(0.16)-0.07(0.07)-0.12(0.15)(6)

0.02(0.13)
0.02(0.05)
0.04(0.11)
426

0.00(0.13)
0.02(0.05)
0.03
0.00

0.05
(0.14)
0.04(0.06)
0.10(0.13)(7)

0.07(0.13)-0.06(0.05)
0.15(0.12)
426

0.05(0.13)-0.06(0.05)
0.16
0.05

0.07
(0.13)-0.03(0.05)
0.19(0.12)(8)

Inspects qualityof products-0.07(0.07)-0.07(0.07)-0.05(0.07)-0.00(0.05)
0.01(0.05)
0.01(0.05)

0.02(0.05)-0.05(0.05)
0.07(0.05)
426

LATE
Keeps records Keeps recordsof businessof defective
transaction
products-0.12**(0.05)-0.02(0.06)-0.04(0.06)-0.08(0.07)-0.07(0.07)-0.04(0.07)

0.00(0.05)
0.01(0.05)
0.02(0.05)
426

ITT
Keeps
Keeps records
records ofof defective
business
products
transactions(2)(3)-0.11*(0.06)
0.02(0.06)-0.03(0.06)-0.09(0.07)-0.08(0.07)-0.04(0.07)
426

Is amember of
Iqub(Yes=1)(1)-0.11**(0.06)
0.02(0.06)-0.03(0.06)
425

Notes. Standard errors are in parentheses. * p < 0.10, ** p < 0.05 and *** p < 0.01.

48

Appendix 9: OLS and IV estimates of the effects of getting financial literary, reminder, and both
treatments on Iqub membership
VARIABLE
Financial training
SMS reminder
Joint treatment
Was an Iqub member in 2013 (Yes=1)
Entrepreneur is male (Yes=1)
Entrepreneur’s age
Years of schoolingYears of prior experienceHas a working experience in formal sector (Yes=1)
Had taken training in production skills as of December 2013(Yes=1)
Had taken training in management skills as of December 2013 (Yes=1)
Year of operation
Enterprise is own initiative (Yes=1)
Parents in private business (Yes=1)
Has siblings in similar business before the start of own business (Yes=1)
Discount rate between today and in 3 months’ time (%)

Time inconsistent (Yes=1)
Risk taker (Yes=1)
Risk averse (Yes=1)
Financial literacy score (max=4)
Digit span recall score (max=8)
Manufacturing sector (Yes=1)
Construction sector (Yes=1)
Constant
Observations
R-squared49

ITT
Is a member of
Iqub (Yes=1)-0.10*(0.06)
0.00(0.06)-0.05(0.06)
0.26***(0.05)-0.06(0.05)-0.00*(0.00)-0.00(0.01)
0.01**(0.00)-0.02(0.05)
0.14**(0.06)
0.00(0.07)-0.00(0.01)-0.03(0.06)
0.05(0.05)-0.04(0.03)
0.01(0.01)
0.20***(0.08)
0.03(0.12)
0.07(0.11)
0.01(0.02)-0.02(0.02)
0.01(0.05)-0.31***(0.10)
0.36**(0.17)
421
0.168

LATE
Is a member of
Iqub (Yes=1)-0.25*(0.14)
0.00(0.06)-0.13(0.13)
0.27***(0.05)-0.06(0.05)-0.00*(0.00)-0.00(0.01)
0.01**(0.00)-0.03(0.05)
0.15**(0.06)-0.00(0.06)
-0.00
(0.0)
-0.02
(0.06)
0.06(0.05)-0.04(0.03)
0.00(0.01)
0.21***(0.07)
0.03(0.11)
0.09(0.11)
0.01(0.02)-0.01(0.02)
0.01(0.05)-0.30***(0.10)
0.33*(0.17)
421
0.160