Innovative Finance for Social Justice

Microfinance and risk management:

Impact evaluation of an integrated risk management
and microinsurance client training TYM, Vietnam
Microfinance for Decent Work
Working Paper No. 69
2015

Social Finance Programme &

Mannheim University
Copyright © International Labour Organization 2015
First published 2015

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Froelich, Markus; Kemper, Niels; Poppe, Robert; Breda, Valérie; Richter, Patricia

Microfinance and risk management: Impact evaluation of an integrated risk

management and microinsurance client training, TYM Vietnam;
International Labour Office, Social Finance Programme & Mannheim University.
Geneva: ILO, 2015

ISBN: 9789221305033 (print); 9789221305040 (web pdf)

International Labour Office Social Finance Programme.

microfinance / financial management / credit / risk management / bank / informal
employment / decent work / workers education / aid programme / role of ILO /
Cambodia
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ii
 Microfinance for Decent Work action research

Microfinance and risk management:

Impact evaluation of an integrated
risk management and
microinsurance client training,
TYM Vietnam

Final Report

Markus Froelich, Niels Kemper and Robert Poppe

Valerie Breda and Patricia Richter**


Authors from Chair of Econometrics, Department of Economics and Business Administration, University of
Mannheim, Germany. Responsible for sections 4, 5, 6 and appendix. Corresponding author: froelich@uni-
mannheim.de.
**
Authors from ILO Social Finance Programme. Responsible for sections 1, 2, 3 and 6. Corresponding
author: richter@ilo.org.
ii
Preface
Entrepreneurs in the informal economy, and the employees that work in those
businesses, are often exposed to difficult and dangerous working conditions. The tools
used to identify, prevent and rectify such conditions in the formal economy – including
social dialogue between employers and employees, labour inspection and other
applications of labour law – generally do not apply to the unregistered enterprises that
proliferate in many emerging economies. Consequently, alternative approaches are
required. But how can one reach these enterprises and influence their conditions?

Microfinance institutions (MFIs) are a potential conduit. In many emerging markets,

they have significant outreach, providing financial services to thousands of small and
micro enterprises. Since their primary relationship with these entrepreneurs often
involves an enterprise loan, they could theoretically use that leverage to encourage
improvements to conditions in the business.

Why would microfinance institutions be interested in doing that? Many MFIs have a
social agenda, or a double bottom line approach that strives to combine social and
commercial objectives. These organizations are often looking for new tools and
approaches that allow them to efficiently enhance their social impact, especially since
recent research has raised serious questions about the welfare benefits derived from
microfinance. It is also possible that such interventions enhance business objectives,
which would be of interest even to MFIs without a social agenda.

With this concept in mind, and with the generous support from the German Ministry of
Labour and Social Affairs, the International Labour Organization (ILO) launched an
action research programme to assess if MFIs could use their relationship with
entrepreneurs to target decent work deficits and improve the plight of workers in the
informal economy.

This Working Paper presents the results of an intervention of TYM, Vietnam and is part
of a series of impact reports that present the outcomes of this action research
programme. The primary target audiences are MFI managers who will hopefully be
inspired by their colleagues’ ingenuity, educated about the impact of innovative
approaches, and informed about the challenges of conducting action research (but not
scared off). Other microfinance actors, including networks and associations, investors
and funders, regulators and policymakers, academics and anyone interested in the
social performance of microfinance will also find this paper informative.

For the ILO’s constituents – employers’ and workers’ organizations and Ministries of
Labour – the findings of this research present them with a new instrument in their
policy toolkit to improve the circumstances of entrepreneurs and workers in the
informal economy.

Through this initiative, the ILO wishes to promote its “Decent Work Agenda” among
MFIs and also to demonstrate that MFIs can improve livelihoods of their clients through
more comprehensive approaches, often including the provision of both financial and
non-financial services.

For anyone interested in reading the other impact studies and the synthesis report,
click on the MF4DW button on the Social Finance website (www.ilo.org/socialfinance).

Craig Churchill
Chief, Social Finance Programme

i
Table of Contents
Preface ................................................................................................... i
Acknowledgements .................................................................................. iv
Executive summary .................................................................................. v
Abbreviations and acronyms ...................................................................... vi
1. Background: The ILO Microfinance for Decent Work action research ............... 1
2. The decent work innovation: An integrated client training on risk management
and microinsurance ............................................................................. 2
3. Intended outcomes .............................................................................. 4
4. Surveys, data and evaluation methodology ................................................ 6
4.1 Surveys and data........................................................................... 6
4.2 Evaluation methodology .................................................................. 7
4.3 Household characteristics at baseline ..................................................... 7
5. Evaluation Results ............................................................................... 9
5.1 Understanding of and satisfaction with the MAF ..................................... 9
5.2 Impact on financial attitude ............................................................10
5.3 Impact on risk management strategies ...............................................13
5.4 Impact on asset building ................................................................16
5.5 Impact on over-indebtedness/multiple borrowing .................................18
5.6 Impact on vulnerability ..................................................................20
6. Conclusion and recommendations ......................................................... 22
Appendix .............................................................................................. 24
A1: Evaluation methodology: Difference-in-difference estimation ..................... 24
A2: Evaluation methodology: Interpretation of difference-in-difference estimates 26
A3: Limitations to the evaluation of the training programme ............................ 27
A4: Tables ............................................................................................ 28
Social Finance Working Papers since 2000 ................................................... 48

List of Tables
Table 4.1.1: Sample sizes reached during each data collection .............................. 6
Table 4.3.1: Summary statistics of client households at baseline ............................ 8
Table 5.2.1: Impact of the training programme on debt- and precaution-related
financial attitudes ....................................................................10
Table 5.3.1: Impact of the client training on risk management and microinsurance
on risk management strategies .....................................................14
Table 5.4.1: Impact of the client training on asset building ..................................16
Table 5.5.1: Impact of the client training on over-indebtedness/multiple borrowing ...18
Table 5.6.1: Impact of the client training on vulnerability ...................................20
Table A2.1. Illustration of the difference-in-difference methodology ......................26
Table A4.1: Outcome summary statistics on asset building ...................................28
Table A4.2: Outcome summary statistics on multiple borrowing/ over-indebtedness ...30
Table A4.3: Outcome summary statistics on financial attitude (1) ..........................31
Table A4.3: Outcome summary statistics on financial attitude (2) ..........................32
Table A4.3: Outcome summary statistics on financial attitude (3) ..........................33

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Table A4.4: Outcome summary statistics on risk management ..............................34
Table A4.5: Outcome summary statistics on vulnerability ....................................35
Table A4.6: Outcome summary statistics on type of shocks/ unforeseen expenses (1) .36
Table A4.6: Outcome summary statistics on type of shocks/ unforeseen expenses (2) .37
Table A4.7: Outcome summary statistics on MAF (1) ..........................................38
Table A4.7: Outcome summary statistics on MAF (2) ..........................................39
Table A4.7: Outcome summary statistics on MAF (3) ..........................................40
Table A4.8: Impact on financial attitude (1) ....................................................41
Table A4.8: Impact on financial attitude (2) ....................................................42
Table A4.8: Impact on financial attitude (3) ....................................................43
Table A4.9: Impact on risk management .........................................................44
Table A4.10: Impact on asset building ............................................................45
Table A4.11: Impact on multiple borrowing/over-indebtedness .............................46
Table A4.12: Impact on vulnerability .............................................................47

List of Figures
Figure 1: Results chain of TYM’s client training on risk management and
microinsurance. ........................................................................ 4
Figure 5.2.1: Percentage of clients who agree that it is not necessary to analyse
expenses ................................................................................12
Figure 5.2.2: Percentage of clients who agree that it is impossible to save because
of expenses ............................................................................12
Figure 5.2.3: Percentage of clients who agree that loan is only last resort ...............13
Figure 5.3.1: Percentage of clients who run out of money before making income .......15
Figure 5.3.2: Percentage of clients having money left at the end of the month .........15
Figure 5.4.1: Percentage of clients with motorbike liability insurance .....................17
Figure 5.4.2: Percentage of clients with life insurance .......................................17
Figure 5.5.1: Percentage of clients with late payments .......................................19
Figure 5.5.2: Percentage of clients with difficulties repaying ...............................19
Figure 5.6.1: Percentage of clients who could cover unforeseen household expenses ..21
Figure 5.6.2: Percentage of clients who could cover unforeseen business expenses ....21

iii
Acknowledgements
We would like to thank Markus Froelich, Niels Kemper and Robert Poppe from the
University of Mannheim for their active collaboration in writing this working paper.

Many thanks also to Ms Duong Thi Ngoc Linh, Ms Nguyen Thi Ha, Ms Duong Thi Hai Yen,
Mr Nguyen Duy Truong and other TYM team members for their enthusiasm and
continuous support in implementing and testing the innovation and responding to our
questions.

iv
Executive summary
Tao Yeu May (TYM), a microfinance institution in Vietnam, participated in the ILO
Microfinance for Decent Work (MF4DW) action research from 2008-2012. As part of this
global experimental research, TYM introduced an integrated risk management and
microinsurance client training in two rural branches. The training aimed to address
challenges that clients faced in regard to the risk management strategies they use and
their levels of indebtedness. The impact of the training on clients’ financial attitudes,
risk management strategies, asset building, over-indebtedness and multiple borrowing,
and vulnerability, was measured employing a difference-in-difference methodology.
The econometric analysis was based on a balanced five-wave panel data set with target
and control groups.

The evaluation showed that TYM’s integrated risk management and microinsurance
client training had the strongest effect on the financial attitudes of clients, especially
on planning attitudes and on attitudes related to savings. The percentage of clients in
the target compared to the control group that agreed to be able to put money aside for
emergency expenses increased by a remarkable 22 per cent and the attitude towards
planning household budgets for longer than a year improved by 17 per cent. Impact on
client risk management behaviour was also strong by contributing to improving a
number of situations that clients face. For example, clients who had access to the
training less often ran out of money before making income than clients who did not
have access to the training (decrease of 13 per cent). Interestingly, the observed
change in financial attitudes regarding savings and planning already reflected in
changed financial behaviour related to the same as we saw a 17 per cent increase in
the ability to set aside money for emergencies as well as a 13 percent increase in
clients with longer planning horizons.

The analysis also showed some insignificant and some unexpected results for other
outcome variables, which may be due to some issues with the experimental design of
the research and the survey instrument. It is therefore possible that the innovation may
have had a stronger impact than actually measured.

v
Abbreviations and acronyms

CG Control group

DiD Difference-in-difference

ILO International Labour Organization

MAF Mutual Assistance Fund

MFI Microfinance institution

MFO Microfinance Opportunities

MF4DW Microfinance for Decent Work

TG Target group

ToT Training of Trainers

TYM Tao Yeu May

vi
1. Background: The ILO Microfinance for
Decent Work action research
The Microfinance for Decent Work (MF4DW) action research aimed at building
knowledge about the effects of innovations on microfinance clients’ livelihoods.
Launched by the ILO Social Finance Programme in 2008, the MF4DW action research
started by identifying specific work-related challenges among microfinance clients and
to address them, implemented tailor-made innovations with 16 microfinance
institutions (MFIs) worldwide. The MF4DW action research set out to apply an
experimental research design to measure the impact of these innovations overtime.
The MF4DW action research concluded in June 2012.

At the outset of the MF4DW action research, each participating MFI conducted a
diagnostic survey among 200 of its clients to determine their most pressing work-
related challenges. The analysis was guided by ILO’s vision of decent work for all and
its goal to promote opportunities for women and men to obtain decent and productive
work, in conditions of freedom, equity, security and human dignity. Within this
framework, the diagnostic determined child labour, working conditions,
formalisation, job creation and productive employment, risk management/over-
indebtedness, and women’s empowerment, as key challenges for microfinance clients
to obtain decent work.

Informed by the diagnostic results, each MFI developed an innovation to address the
work-related challenge that most affected its clients and started implementing the
innovations from 2009 onwards. The innovations included new or upgraded
 financial services (loan, savings, insurance, leasing),
 non-financial services (training, awareness campaign), or
 mechanisms for delivering services (organisational restructuring).

The MF4DW action research used an experimental research design meaning that one
group of clients received the innovation (target group) while another group of clients
did not (control group). Ideally, clients of each group were selected randomly. Before
the introduction of the innovations, all clients of the target and control groups were
interviewed to establish a baseline against which changes could be compared.
Depending on the implementation timeline, up to four follow-up surveys were
conducted once the innovation was launched. The last follow-up surveys were
completed in February 2012.

This report presents the final impact results of the innovation implemented by Tao Yeu
May (TYM) in Vietnam1. TYM is one of the largest MFIs in Vietnam and the first one to
have become officially licensed to establish and operate a small-scale finance
institution in the country in 20102. It has 17 branches and operates in 10 provinces in
the North and Centre of the country. As of December 2012, it served 78,818 women
with a staff of 3663. TYM provides a range of financial services such as group and
individual loans, savings products, mutual assistance fund and training, mostly in rural
areas of Vietnam. TYM conducted the MF4DW action research in two provinces: Hanoi
province and Nam Dinh province. The TYM branches in these two provinces were
selected as they tend to have comparable characteristics. They are both in rural areas
and were created in 1999, their clients are engaged in similar economic activities, the
average loan amount, the drop out and repayment rates are rather close. Me Linh 7
(Hanoi province) provided the target branch (where the innovation was introduced)
while Y Yen 8 (Nam Dinh province) provided the control branch.

1
In May 2013, TYM officially was renamed as Tinh Thuong One member Limited Liability Microfinance
Institution. This report refers to the name used during the research period which is TYM.
2
As of 31/12/2012, only 2 MFIs were licensed in Vietnam, i.e. TYM and M7 microfinance institution.
3
Source: http://mixmarket.org/mfi/tym/report (accessed 17 October 2014).

1
2. The decent work innovation: An integrated
client training on risk management and
microinsurance
The initial diagnostic that TYM conducted in 2008 identified risk management as one of
the most pressing challenges for TYM clients:

 27 per cent of respondents stated that they had been confronted with large
unforeseen expenses, mainly due to illness/accident, death, or natural disaster in
the past year.
 68.5 per cent of respondents covered the large unforeseen expenses by
withdrawing savings, 55.6 per cent by taking a loan, 18.5 per cent by working
extra, and 15.5 per cent by using microinsurance. Only 2 per cent covered large
unforeseen expenses in the last year by using insurance.
 While 100 per cent of the respondents are members of TYM’s Mutual Assistance
Fund (a compulsory microinsurance programme), only 91 per cent acknowledged
being a member.
 61 per cent of the respondents stated taking loans from other sources (mostly from
banks) and among them 6.5 per cent said they used the loan to pay back another
loan.

These diagnostic findings showed that client understanding of risk management and the
role of different financial products, in particular TYM’s Mutual Assistance Fund (MAF),
in managing risks is still low. As a result, the client strategies to cope with risk are not
optimal and unforeseen shocks can have negative impact on their livelihoods. In an
earlier attempt to improve the situations of its clients, TYM introduced the Mutual
Assistance Fund in 1996 to provide a credit life insurance product as well as health and
death benefits to its clients (including spouse/children). However, given the very small
compulsory contributions, the limited benefits and low awareness among TYM clients,
the product was not appropriate to cover health and death related expenses of clients
and thus mitigate the financial pressure. In an effort to better address the needs of its
clients and offer meaningful benefits, TYM upgraded the MAF in early 2009. In parallel,
TYM started to work on setting up a separate legal entity dedicated to microinsurance
to offer more and better insurance products to its clients. The new entity was expected
to be registered under Government Decree 18 in 2013 when all legal and financial
requirements were to be met.

To support the introduction of the upgraded MAF product, and to address the still
limited awareness among TYM clients about the use of the MAF and other risk
management strategies, TYM introduced an integrated client training on risk
management and microinsurance. The curriculum and training material was developed
by TYM, in particular by the MAF team in collaboration with the TYM training
department. TYM built on its internal training capacity and adapted the Microfinance
Opportunities (MFO) curriculum on microinsurance and savings on which TYM staff had
been capacitated during a Training of Trainers (ToT) course organised by MFO in
Vietnam in 2008. In addition, a local ILO expert on microinsurance reviewed the
materials. The training aimed to equip clients with skills and knowledge on risk
management so that they can make informed and sound financial decisions about
spending, saving or borrowing, especially for emergency purposes, and using insurance.
The curriculum covered five topics:
1) Introduction to risk management
2) Savings
3) Concepts of insurance

2
4) Insurance terms and types of common insurance
5) Use of the Mutual Assistance Fund

The material included a trainer’s manual and visual aids (posters and brochures) to
facilitate the transfer of knowledge to the clients.
The client training on risk management and microinsurance was implemented in three
steps:

First, TYM at central level trained 16 of its provincial staff (ToT on 19-22 November
2009). The ToT covered all five topics of the curriculum and introduced the training
materials and adult learning methods to the participants. The participants included one
area manager, two branch managers, 11 loan officers and two area accountants. Among
the 16 trained staff, TYM selected 12 to deliver the client training in the target branch
(Me Linh 7). The training was first pilot tested on 26-27 December 2009 for 30 clients.
Contents and methodology were refined taking into account clients’ and trainers’
feedback.

Second, from January to June 2010, TYM target branch staff delivered 59 two half-day
training courses to the 1’567 clients of the branch. The two half-day training course
covered the whole curriculum, i.e. the five topics mentioned above. The training
courses were organized during weekends and holidays to accommodate TYM staff
schedule.

Third, as of July 2010, once all target branch clients had received the two half-day
training, the branch staff delivered briefing sessions at the end of weekly and monthly
client meetings to refresh the clients’ knowledge on the five training topics and
reinforce client skills. After the regular client meeting activities were completed (such
as collecting loan repayments and savings), the branch staff reiterated the key
messages of one training topic using participatory methods and visual aids. Each
briefing session lasted from 15 to 20 minutes.

In September 2010, TYM organised a consultative meeting in Hanoi to take stock of the
action research including the progress of the risk management and microinsurance
training, achievements and challenges, and planning for the following months. Around
25 TYM staff from central level and from the two participating branches (Me Lynh 7 and
Y Yen) attended the consultative meeting. As an outcome, the training curriculum was
slightly modified to better reflect client needs. In particular, the fourth topic
“Insurance terms and types of common insurance” was replaced by “The civil
responsibility of motor vehicle owners”. The change was based on the fact that most
clients do have motorbike insurance (it is compulsory); however, they do not have a
clear understanding of what it covers and how it shall be used. In addition, it was
decided to organize a refresher ToT for the trainers at branch level and to revise some
of the training aids (posters) to make them better fit with the local context.

A refresher ToT was therefore organized fourteen months after the launch of the risk
management and microinsurance training, on 18-20 March 2011. The objectives were to
share and discuss lessons learnt from the client training, strengthen branch staff’s
knowledge on risk management and enhance their training skills. Fifteen participants,
including the eight Me Lyn branch officers who delivered the training sessions as well as
the TYM training department and the MAF team at central level, attended the refresher
training.

3
3. Intended outcomes
TYM’s client training on risk management and microinsurance intends to generate social
and economic impact on client households through stimulating change in financial
attitude and behaviour towards risks amongst TYM clients. Aware of good risk
management practices and of their own practices, clients are expected to change first
their attitude toward taking and coping with risk. Based on such a change in attitude,
and equipped with knowledge and skills for better risk management, clients are
expected to improve their financial behaviour. As a result, it is expected that clients
adopt informed and effective risk management strategies and build assets, which
contribute to reducing their risk of over-indebtedness and multiple borrowing and
decreases their vulnerability. Figure 1 presents the results chain of the client training
on risk management and microinsurance.

Figure 2: Results chain of TYM’s client training on risk management and microinsurance.

This report analyses the impact of the client training on risk management and
microinsurance:

1. A change in financial attitude towards taking and coping with risk (see section
5.2 for results)
Financial attitude shows a client’s opinions and judgements about money issues
and the use of financial services including insurance. Opinions and judgements
change over time and thus they are key determinants of one’s behaviour. It is
therefore expected that the client training on risk management and
microinsurance will instil financial attitudes that support informed financial
behaviour toward taking and coping with risk.

4
 2. An improvement in client's risk management strategies (see section 5.3 for
results)
It is expected that financially informed clients will be able to better assess the
risks in their daily lives (health shocks, disasters, business failure, and over-
indebtedness) and take effective steps to eliminate or reduce them. For
example, it is expected that clients use financial planning to take decisions
about business and household spending, that they consider their needs and
capacity to repay as well as the risk of default before taking a loan, that they
spend wisely to be able to save for emergencies and build their assets, and that
they use a mix of financial services including the TYM Mutual Assistance Fund
and other insurance products to protect themselves against risk.

3. The building of assets (see section 5.4 for results)

It is expected that financially informed clients will be in a better position to
build and maintain their financial assets (savings, life insurance).

4. A reduction in over-indebtedness (see section 5.5 for results)

As a result of 1 to 3, it is expected that financially informed clients will be able
to better balance the number of active loans and corresponding amounts of
money owed to formal and informal financial service providers. As a
consequence, they should be able to minimize their repayment difficulties,
late repayments and defaults.

5. A reduction in clients’ vulnerability (see section 5.6 for results)

Likewise, it is expected that financially informed clients will be in a better
position to meet their monthly expenses (including loan repayments) no matter
if they are planned or unexpected and reduce income variability. It is hoped
that the clients’ need to sell assets in times of hardship will be reduced.

This report analyses the causal relationships between the innovation and the intended
outcomes in (1) to (5) without imposing ad-hoc relationships within the outcomes. As
the impact of the training on risk management and microinsurance cannot be measured
with a single indicator, sets of indicators will be used for each of the intended
outcomes in the empirical analysis below.

5
4. Surveys, data and evaluation
methodology
4.1 Surveys and data
The sample consists of clients from two selected branches with Me Linh in Hanoi
province presenting the target branch and Y Yen in Nam Dinh province presenting the
control branch. In both branches, clients were randomly selected to participate in the
survey. Consequently, the sample is representative of all TYM clients in target and
control branches.

The survey instrument, i.e. the client questionnaire, contained questions covering
socio-demographic information on the client household; household income; household
expenditures; money management; business and activity registration; savings,
insurance and money transfer services; use of and satisfaction with the MAF; loan and
indebtedness information; unforeseen expenses; and situational questions assessing
financial attitude and behaviour.

Five surveys were implemented to collect client data in the two selected branches. The
baseline survey was conducted from November to December 2009, the four follow-up
surveys sequenced in 6-months intervals. The last data collection was completed in
December 2011. Given the 6-months data collection intervals, data for target and
control groups originated approximately at the same time of the year and hence
seasonal factors play only a minor role in the empirical analysis.

Taking into account historical client dropout rates in both target and control branches,
minimum sample sizes requirements were set before the data collection. Accordingly,
1’000 clients were included in the baseline survey (500 clients in the target and 500
clients in the control branches). Table 4.1.1 shows the sample size actually reached
during each data collection. It shows that attrition between the waves has been low.
The large majority of clients could be followed over time.

Table 4.1.1: Sample sizes reached during each data collection

Target branch Control branch Total
499 499 998
Baseline survey
500 498 998
1st Follow-up survey
499 495 994
2nd Follow up survey
499 486 985
496 481 977
3rdFollow-up survey 499 499 998

4thFollow-up survey 500 498 998

Data quality
While the collected data is very rich, there are also some concerns with the data at
hand. As a result, it cannot be excluded that the innovation actually had a stronger
impact than we are able to measure. The concerns mainly relate to the experimental
design and the survey instrument.

Given that there is only one target branch and one control branch, it is quite difficult
to disentangle the impact of the innovation from other factors that may have affected

6
the intended outcomes (see appendix A3 for two examples). To be more specific: It is
quite possible that a positive effect occurred as a consequence of the innovation, but
that it was overlaid by some unobserved factor in the control branch. One solution
would be to increase the number of target and control branches to average out this
unobserved factors. Ideally, the assignment to target and control branches takes place
through a randomized control trial, which offers the most credible approach to
measuring the impact of such an innovation.

The survey instrument also raises some concerns, in particular with respect to content
validity. For example, does the measurement of a concept, such as financial attitude,
really capture the concept in all its dimensions? In psychology, attitude is defined as a
positive or negative evaluation of people, objects, events, activities, ideas etc. This
implies that a questionnaire, which attempts to elicit financial attitude, needs to check
positive and negative messages to understand the full effect of financial education. In
the case of TYM, the questionnaire asks with respect to savings:

 When things are going well, I try to put money aside to see me through difficult
times.

In addition to this negative reference event, it should also ask for the positive
reference event like “When things are going well, I try to put money aside for happy
future events” which the questionnaire omitted. Furthermore, if such questions were
included, they could either be asked to the same individual or randomized so that the
former question is asked to half of the clients while the latter question is asked to the
other half of the clients to get an average effect for all clients.4

4.2 Evaluation methodology

This evaluation employs a difference-in-difference (DiD) methodology to evaluate the
impact of the financial education programme. In a nutshell, it compares changes in the
target group before and after the implementation of the innovation to changes in the
control group before and after the implementation. Given that the innovation works
and that the experimental design is clean, one should see a change in outcomes in the
target group (because there is an innovation) but no change in the control group
(because there is no innovation). 5 The difference between the changes in the two
groups is then the effect of the innovation on a particular outcome.

Appendix A1 discusses the evaluation methodology in detail. In addition, appendix A2

illustrates the DiD methodology with an example and section 4.1 plus appendix A3
describe the limitations of the research design.

4.3 Household characteristics at baseline

For a better credibility of the empirical analysis, the target and control groups must be
as similar as possible before the implementation of the innovation. The sample of the
baseline survey consisted of 998 clients (499 in target branch and 499 in control
branch); all of them were female clients. Table 4.3.1 shows some descriptive statistics
on clients and client households at baseline.

4
Given that the order of the questions may influence the response it may make sense not to ask both
questions to the same individual. In general, research in decision theory shows that individuals treat
gains and losses differently. In particular, individuals tend to strongly prefer avoiding losses to acquiring
gains.
5
To be more precise: There may be changes in target and control branch. However, if they are unrelated
to the innovation these changes must be the same for both groups (common trend assumption).

7
Table 4.3.1: Summary statistics of client households at baseline

Legend: TG - Target Group, CG - Control Group.

In the target branch, all clients were female, 42.1 years of age on average and their
households had 5 members. 10 per cent of client households had been affected by
unforeseen expenses in the past year. 4 per cent had a monthly household income of
lower than 1 million Vietnamese Dong (VND), 23 per cent between 1 and 2 million VND,
49 per cent between 2 and 5 million VND, and 24 per cent of more than 5 million VND.
In terms of loans, clients owed on average 4.7 million VND to others while the size of
the last TYM loan was 9.1 million VND. Most clients took their first TYM loan in 2004.

In the control branch, all clients were female, 44.9 years of age on average and their
households had, on average, 4.5 household members. 52 per cent of client households
had been affected by unforeseen expenses in the past year. 13 per cent had a monthly
household income of lower than 1 million Vietnamese Dong (VND), 29 per cent between
1 and 2 million VND, 46 per cent between 2 and 5 million VND, and 12 per cent of more
than 5 million VND. In terms of loans, clients owed on average 8.9 million VND to others
while the size of the last TYM loan was 5.6 million VND. Most clients took their first
loan in 2004.

The comparison between the characteristics of target group and control group clients
shows that the clients in both branches significantly differ along virtually all
dimensions. Clients in the target group are richer, were clearly less often confronted
with unforeseen expenses, and higher in debt with TYM awhile clearly lower in debt
elsewhere.

The reason for this discrepancy, in addition to the inclusion of too few branches in the
survey, may lie in the choice of hardly comparable target and control branches.
Although both branches are located in the economically vibrant and successful red river
delta, the target branch is located in Me Linh district and therefore very close to the
greater Hanoi area which presumably fairs on a higher welfare level than Y Yen in Nam
Dinh province.

We conclude that target and control groups differ along some important dimensions
before the introduction of the innovation. Therefore, differences in outcomes may
partially be the consequence of different initial conditions between target and control
branches, which existed prior to the innovation.

8
5. Evaluation Results
This chapter summarises the analytical results from the application of the difference-
in-difference methodology and illustrates them through representative graphs.

5.1 Understanding of and satisfaction with the MAF

The survey questionnaire asked clients about their knowledge of and satisfaction with
the Mutual Assistance Fund (MAF). Detailed analytical results are shown in table A4.7
in appendix A4. Below, we first present the summary results regarding client
understanding of the terms of the MAF and second, the results regarding their
satisfaction with the MAF.

Client understanding of the MAF

The MAF is mandatory and hence covers all TYM clients. However, are clients aware of
that coverage? The survey found that nearly 100 per cent of clients in both target and
control branches know about the MAF coverage across all waves.

Asking about which services are covered by the MAF, we find a similar response. Nearly
100 per cent of clients are aware that costs related to hospitalization and deaths of
family members are covered. Findings between target and control groups hardly differ.
Control questions that asked clients whether household and business assets and vehicle
damage are covered yield less than 2.5 per cent yes, and therefore wrong, answers.

We conclude that clients understand the terms of the MAF well in both target and
control groups. This equally applies to all waves.

Client satisfaction with the MAF

Satisfaction with the risks covered by the MAF is high: 87 per cent of the target group
clients answered that they were “very satisfied” or “satisfied” at baseline. This
percentage increased to 97 per cent in the first follow-up survey and remained close to
100 per cent through the end of the research period. In the control group, satisfaction
was high from the very beginning: 98 per cent of clients were satisfied at baseline.
Satisfaction remained close to 100 per cent for all subsequent waves.

Satisfaction with the persons covered by the MAF evolved similar: 87 per cent of the
target group clients answered that they were “very satisfied” or “satisfied” at baseline.
This percentage increased to 99 per cent in the first follow-up survey. It remained close
to 100 per cent through the end of the research period with the exception of the third
follow-up survey when it dropped to 95 per cent but went up to 98 per cent in the final
wave. In the control group, satisfaction was high from the very beginning: 98 per cent
were satisfied at the baseline. For all following waves satisfaction remained close to
100 per cent with the exception of the last follow-up survey where it dropped to 96 per
cent.

Clients also seemed satisfied with the premium that they paid for being covered by the
MAF. In both target and control groups more than 96 per cent were satisfied for all
follow-up waves. Nearly the same satisfaction rates apply out for the premium
collection method, the explanation of the product and the customer service.

The satisfaction with the amount of reimbursement fluctuated more strongly. For the
target group it varied between 74 and 93 per cent and for the control group between
87 and 100 per cent.

We conclude that overall client satisfaction with the MAF is very high in both target and
control groups. This finding equally applies to all waves.

9
5.2 Impact on financial attitude

Financial attitude measures a client’s state of mind on money issues and the use of
financial services. As such, financial attitude reflects a client’s opinions and
judgements and can change over time. The action research investigated financial
attitudes in two broad categories: debt-related and precaution-related.6 Clients were
asked to which extent they agreed or disagreed with given statements covering these
two categories.7 The results of 19 variables are shown in table 5.2.1. The symbol “+”
indicates a significant increase in the number of clients in the target group agreeing
with certain financial attitudes as compared to the control group after the introduction
of the innovation, the symbol “o” indicates an insignificant change and the symbol “-“
indicates a significant decrease in the number of clients in the target group agreeing
with certain financial attitudes as compared to the control group. Looking at the
impact, six of the outcome variables show a significant increase, five an insignificant
change and eight a significant decrease.

In addition to showing the actual impact results, table 5.2.1 also compares them to
intended results in column 1 to see whether the observed effects are going in the
expected direction. Here we see that the majority of variables, all together 13, follow
the expected trend while only one goes against expectations. The remaining five
variables did neither follow nor oppose the expected trend.

Table 5.2.1: Impact of the training programme on debt- and precaution-related

financial attitudes
Impact
Intent Actual
Debt-related attitudes / opinions
+ o When things are going well, I try to put money aside to see me through
difficult times.
- - When your income is low, it is not necessary to keep detailed track of
your monthly income and expenses.
- o It is not necessary to analyze which expenses are the most important
for the family because, anyway, there is not enough money to pay for
everything.
+ + I try to plan my household budget for a period longer than a year.
- - I cannot keep an emergency reserve because my income is so low that
there is never any money left.
+ + I am able to put aside enough money for emergency expenses to make
their impact less severe.
- - There is no need to worry in advance and budget for emergencies.
+ + It is worth saving even if your income is low.
- - It does not make sense to save since you do not know what tomorrow
will bring.

Pre-caution related attitudes / opinions

+ + I try to save these days, even if these are just small amounts.
+ + Even small savings can improve your stability and security in the
future.
- - It is impossible to save because there are always expenses coming up
that force you to use your savings.
- - I don’t need insurance because nothing is happening.
- - Insurance is expensive.
- - I don’t need insurance to solve own problems.

6
Based on Matul, Michal (2010): “Financial Behaviours and Vulnerability to Poverty in Transition Context”.
7
To simplify the econometric analysis theses variables were aggregated in binary variables if clients
answer “I definitely agree” and “I rather agree” and zero if they answer “I rather disagree” and “I
definitely disagree”.

10
 Impact
Intent Actual
+ o Insurance companies are reliable.
- + We can achieve our goals more quickly with borrowed money.
+ o We consider a loan only as a last resort.
- o Insurance benefit is not much.

In addition to comparing actual results to intended effects in table 5.2.1, it is

interesting to explore the detailed analytical results which are presented in table A4.8
in appendix A4. It presents the percentage changes for the target group relative to the
control group. The strongest findings – meaning that there is a significantly higher
change in agreement for clients in the target group as compared to clients in the
control group after the introduction of the innovation – exist for the following
statements:
 I am able to put aside enough money for emergency expenses to make their impact
less severe (22 per cent),
 I try to plan my household budget for a period longer than a year (17 per cent),
 It is worth saving even if your income is low (10 per cent),
 I try to save these days, even if these are just small amounts (10 per cent), and
 Even small savings can improve your stability and security in the future (5 per
cent).

Further, we find a 9 per cent increase in agreement with the statement We can achieve
our goals more quickly with borrowed money in the target relative to the control
group. Given that fewer clients in the target group took a loan to repay another loan
we interpret this as a positive outcome.

We find additional strong results – this time meaning that clients in the target group
disagree significantly more often as compared to the control group – for the following
statements:
 It does not make sense to save since you do not know what tomorrow will bring (17
per cent),
 I cannot keep an emergency reserve because my income is so low that there is
never any money left (by 17 per cent),
 There is no need to worry in advance and budget for emergencies (16 per cent),
 When your income is low, it is not necessary to keep detailed track of your
monthly income and expenses (15 per cent), and
 It is not necessary to analyze which expenses are the most important for the
family because, anyway, there is not enough money to pay for everything (4 per
cent).

As an illustration, figure 5.2.1 shows the development of the variable It is not

necessary to analyse expenses. We see that the percentage of clients in the target
group who agree the statement fluctuates across the waves with two strong decreases
between baseline and the first follow-up survey as well as between the second and
third follow-up survey. In contrast, it only slightly decreases for the control group. The
net effect is a clear decrease in the target group as compared to the control group.

11
Figure 5.2.1: Percentage of clients who agree that it is not necessary to analyse expenses

Legend: target group o, control group 

Another illustration of an overall decrease is shown in figure 5.2.2 for the variable It is
impossible to save because of expenses. The percentage of clients in the control group
who agree with the statement remains fairly stable at low levels. In contrast, it
decreases, increases and decreases for the target group. Because of the steep decrease
between baseline and first follow-up, the net effect measures a decrease in the target
group as compared to the control group.

Figure 5.2.2: Percentage of clients who agree that it is impossible to save because of expenses

Legend: target group o, control group 

Figure 5.2.3 shows an example of a net effect that measures no change in the target
group as compared to the control group. While the percentage of clients who share the
opinion that a Loan is only last resort has been lower in the target group than in the
control group from the very beginning, we do not observe a clear shift in this trend for
the target group. It also remains fairly stable for the control group. Hence, the net
effect does not change.

12
Figure 5.2.3: Percentage of clients who agree that loan is only last resort

Legend: target group o, control group 

Lastly, fewer clients in the target group think that There is no need to worry in
advance and budget for emergencies after the introduction of the innovation. This
result may seem counterintuitive. One possible explanation is that clients in the target
group are wealthier and therefore better able to self-insure as compared to clients in
the control group. This might also explain why fewer clients in the target group think
that Insurance benefit is not much.

Overall, most outcome variables suggest that the training on risk management and
microinsurance had a very strong, and desired, impact on TYM clients’ financial
attitude.

5.3 Impact on risk management strategies

While chapter 5.2 showed how the financial attitude of clients changed over time, the
following chapter presents the impact of the risk management and microinsurance
training on the financial behaviour and the risk management strategies that clients
engage in. This outcome category was tested with a set of situational questions on
actual behaviour as well as on variation in income sources of clients. These included,
for example, questions regarding clients’ planning horizons or how unforeseen expenses
are covered with a special focus on the Mutual Assistance Fund (MAF).

The results of 9 risk management variables are shown in Table 4.1 5.3.1 in column 2
and compared to intended impact in column 1. Similar to sub-section 5.2, the symbol
“+” indicates a significant increase in the number of clients in the target group
agreeing with certain financial behaviour as compared to the control group after the
introduction of the innovation, the symbol “o” indicates an insignificant change and the
symbol “-“ indicates a significant decrease in the number of clients in the target group
agreeing with certain financial behaviour as compared to the control group. Detailed
analytical results for the impact of the innovation on risk management strategies can
be found in Table A.4.9 in appendix A4.

13
Table 5.3.1: Impact of the client training on risk management and microinsurance on
risk management strategies

Impact
Intent Actual
+ + We have planning horizon of more than a month (household).
+ o We have planning horizon of more than a month (business).
- - We run out of money before making income.
- o We do not have enough money left to meet fixed monthly payments.
- + Major seasonal expenses have a negative impact on our living standard
in the month when they occur because we do not budget for them in
advance.
+ + We set aside money for future emergencies.
+ - At the end of the month, we have some money left that can be put
into savings or spent on extra purchases.
- - We give in to the temptation and buy things, which we later regret.
- - When we run out of money, we borrow or buy on credit and pay debts
a later.

In summary, we find that five variables follow the expected trend while two show
counterintuitive results. Further, two variables neither follow the expected trend nor
do they counter it.

Looking more closely, we see that in the target group as compared to the control group
clients significantly less often agree with the following situations: We run out of money
before making income, We give in to the temptation and buy things which we later
regret and when we run out of money, we borrow or buy on credit and pay debts later
after the introduction of the innovation. Furthermore, clients in the target group more
often agree with the following statements: We have planning horizon of more than a
month (household) and We set aside money for future emergencies. While the
innovation was expected to create these impacts, the increase in the ability to set
aside money for emergencies is the most remarkable result with a plus of 17 per cent
followed by a 13 percent increase in clients with longer planning horizons as well as a
13 per cent decrease in clients running out of money before making income.

While the former outcomes were intended, we also find counterintuitive results as
clients in the target group less often state that At the end of the month, we have some
money left that can be put into savings or spent on extra purchases (decrease of 13 per
cent) after the introduction of the innovation. We also find more target group clients
agreeing with the statement Major seasonal expenses have a negative impact on our
living standard in the month when they occur because we do not budget for them in
advance (plus 13 per cent), although we do not know whether this has to be
interpreted as higher awareness among target group clients that seasonal expenses
constrain the budget (due to the training) or that target group clients did manage to
cyclically balance their budget with respect to seasonal expenses (despite the training).

The training did not have any impact on the following two variables: We have planning
horizon of more than a month (business) and We do not have enough money left to
meet fixed monthly payments.

The below two figures graphically illustrate some of the findings. Figure 5.3.1 shows
the percentage of clients agreeing with the statement that We run out of money before
making income. We see a clear decrease for the target group between baseline and
first follow-up survey. Thereafter, the percentage remains at a low level. The control
group shows a very slight downward trend, which, however, does not show any clear
shift around the introduction of the innovation. This is expected as the control group
did not receive the training. Comparing target and control groups we thus find a
significant decrease of 13 per cent. The innovation had a strong impact on this
variable.

14
Figure 5.3.1: Percentage of clients who run out of money before making income

Legend: target group o, control group 

Figure 5.3.2 shows the development of the variable We have money left at the end of
the month. For the target group, we observe an increase between baseline and first
follow-up survey which is followed by a slight decrease and another increase. In the
control group, we find a strong increase between baseline and first and second follow-
up surveys, while the variable remains stable thereafter. Comparing target and control
groups we thus find a decrease of about 13 per cent which is an unintended and
counterintuitive result.

Figure 5.3.2: Percentage of clients having money left at the end of the month

Legend: target group o, control group 

In summary, most of the risk management related outcome variables show that the TYM
client training on risk management and microinsurance had a positive impact on client
risk management strategies.

15
5.4 Impact on asset building
The action research covered client behaviour related to building and maintaining of
assets mainly through financial assets (e.g. life insurance). Table 5.4.1 gives an
overview of results on asset building and compares actual to intended effects. Similar
to the sub-sections before, the symbol “+” indicates a significant increase in the
number of clients in the target group that built assets as compared to the control group
after the introduction of the innovation, the symbol “o” indicates an insignificant
change and the symbol “-“ indicates a significant decrease in the number of clients in
the target group as compared to the control group that built assets. In principle, the
intended effect for all asset variables was an increase (with the exception of not having
insurance).

Table 5.4.1: Impact of the client training on asset building

Impact
Intent Actual
+ o Life insurance
+ o Mandatory social insurance
+ o Voluntary social insurance
+ + Motorbike liability insurance
+ o Unemployment insurance
+ o Health insurance
+ o HH property insurance
+ o Business assets insurance
+ o Car insurance
- o No insurance

The detailed analytic results of all variables are shown in table A4.10 in appendix A4.
An interesting result with respect to asset building is the clients’ use of motorbike
liability insurance: we observe a significant increase for the target group as compared
to the control group after the introduction of the innovation by 5 per cent. The client
training, in particular the topic related to “The civil responsibility of motor vehicle
owners”, had a strong impact.

All other variables show no significant difference in changes, this includes Life
insurance, Mandatory social insurance, Voluntary social insurance, Unemployment
insurance, Health insurance, Household property insurance, Business assets insurance,
Car insurance and No insurance.

As an illustration, figure 5.4.1 shows the development of clients with Motorbike

liability insurance. In the target group, we see a steep decrease in coverage between
baseline and first follow-up survey which is followed by a steep increase before it
remains on a close-to-baseline level of about 20 per cent up to the end. In the control
group, the coverage steadily decreased from 20 per cent at baseline to less than 10 per
cent in the final survey. Thus, comparing differences in target and control group we
find a significant increase in coverage with motorbike liability insurance of 5 per cent.

16
Figure 5.4.1: Percentage of clients with motorbike liability insurance

Legend: target group o, control group 

While results for other variables were not significant in statistical terms, some trends
are nonetheless interesting. Figure 5.4.2 shows the percentage of clients that were
covered by Life insurance. Compared to the baseline survey, we see a steep increase in
coverage for the target group between baseline and second follow-up survey which was
followed by a slight decline. For the control group, which started at higher levels than
the target group, coverage decreased from roughly 6 per cent in the baseline to roughly
4 per cent in the last survey. Thus, comparing the difference in changes between target
and control groups we find an increase in life insurance coverage; however, it is not
significant in statistical terms.

Figure 5.4.2: Percentage of clients with life insurance

Legend: target group o, control group 

17
5.5 Impact on over-indebtedness/multiple borrowing
Financially informed clients are expected to reduce the number of their active loans
and corresponding amounts of money owed to formal and informal financial service
providers as a result of the innovation. They should also be able to minimize their
repayment difficulties, late repayments and defaults. Table 5.5.1 gives an overview of
the results of six variables related to over-indebtedness and multiple borrowing
following the same structure as before: the table presents actual impact results
(column 2) and compares to intended effects (column 1). The symbol “+” indicates a
significant increase in the number of clients in the target group showing a certain
indebtedness-related financial behaviour as compared to the control group after the
introduction of the innovation, the symbol “o” indicates an insignificant change and the
symbol “-“ indicates a significant decrease. In principle, the intended effect for all
indebtedness-related variables was a decrease.

Table 5.5.1: Impact of the client training on over-indebtedness/multiple borrowing

Impact
Intent Actual
- o Did you borrow from informal sources?8
- o Did you borrow from other formal sources?
- - Have you taken a loan to repay another loan?
- o Did you have any difficulties repaying your TYM loans in the last year?
- o Do you expect difficulties in repaying loans to TYM or another
financier in the next 6 months?
- o Late payment

In general, the training does not seem to have a very strong impact on the repayment
behaviour of clients. However, the main reason for this is that the repayment
performance of clients in both target and control groups was already excellent. Table
5.5.1 above shows little impact on almost all key indicators with respect to over-
indebtedness and multiple borrowing. Table A.4.11 in appendix A4 shows the detailed
analytic results of all indebtedness-related variables presenting the percentage changes
for the target relative to the control group. The training only had one significant result:
the percentage of clients that have Taken a loan to repay another loan clearly
decreased over the survey period in the target group. Compared to the control group,
we estimate that it decreased by roughly 12 per cent for the target group after the
introduction of the innovation which is a very strong result.

We could not find any impact for the other outcome variables: Did you borrow from
informal sources, Did you borrow from other formal sources, Did you have any
difficulties repaying your TYM loans in the last year, Do you expect difficulties in
repaying loans to TYM or another financier in the next 6 months and Late repayment.

As in earlier results chapters, we also add some graphical illustrations of the effects
observed. Figure 5.5.1 shows the percentage of clients with late payments. We see
that late payments are a rare exception for both target and control groups. In the
target group, late payments were reported for less than 0.5 per cent of clients for the
whole survey period. In the control group, we observe a peak in the second follow-up
survey where late payments reached 1.5 per cent while they remained below 0.5 per
cent otherwise. Comparing target and control group, we cannot make out a clear
trend. Neither are the results significant.

8
By informal we typically refer to loans coming from individuals and formal from institutions.

18
Figure 5.5.1: Percentage of clients with late payments

Legend: target group o, control group 

The second example shows the development of the percentage of clients that have
difficulties repaying, see figure 5.5.2. Very similar to figure 5.5.1, the percentage of
clients is very low: 3 per cent in the control group and roughly 1.5 per cent of the
clients in the target group had some repayment difficulties at baseline. Thereafter, less
than 1 per cent of clients in both target and control groups had repayment difficulties.

Figure 5.5.2: Percentage of clients with difficulties repaying

Legend: target group o, control group 

In summary, we see a strong impact of the training on reducing the number of clients
who take a loan for paying back other loans. We find little impact on other variables
which can be explained by the already excellent repayment performance in both target
and control groups.

19
5.6 Impact on vulnerability

The action research measured vulnerability by the clients’ capacity to cover their
monthly expenses (planned or unexpected), by income variability and the clients’ need
to sell assets in times of hardship. Table 5.6.1 gives an overview of the results of seven
vulnerability variables following the same structure as before: the table presents actual
impact results (column 2) and compares to intended effects (column 1). The symbol
“+” indicates a significant increase in the number of clients in the target group showing
a certain vulnerability-related financial behaviour as compared to the control group
after the introduction of the innovation, the symbol “o” indicates an insignificant
change and the symbol “-“ indicates a significant decrease in the number of clients in
the target group showing a certain vulnerability-related financial behaviour as
compared to the control group. Detailed analytic results of all variables are presented
in table A4.12 in appendix A4.

Table 5.6.1: Impact of the client training on vulnerability

Impact
Intent Actual
+ + Did household income cover all household expenses in the last 12
months?
+ o To what extent could client cover unforeseen household expenses in
the last 12 months?
+ o To what extent could client cover unforeseen business expenses in the
last 12 months?
+ o Used savings to cover unforeseen expenses
- - Sold assets to cover unforeseen expenses
+ o Used microinsurance to cover unforeseen expenses
- o Sacrificed household expenses to cover unforeseen expenses

Comparing the results in the target and control groups, we find that two variables
develop in the intended direction while five show neither positive nor negative change.
None of the variables shows unintended results.

The percentage of clients who positively responded to the question Did household
income cover all household expenses in the last 12 months increased significantly by
3.3 per cent in the target group as compared to the control group after the
introduction of the innovation. In addition, we find that significantly fewer households,
approximately 10 per cent, sold assets to cover unforeseen expenses. These results
show that the innovation created the intended impact.

For the remaining five variables, results are not significant and hence we cannot report
any impact of the training on them.

To end this subchapter, we graphically illustrate the observed effects for the
percentage of clients that could cover unforeseen household or business expenses.
Figure 5.6.1 shows that both target and control groups started at different
percentages at baseline for the question Did household cover unforeseen expenses in
the last 12 months but closed at the same level at the end of the research. The target
group increased from below 70 per cent to a little more than 80 per cent in the second
follow-up survey, and then dropped slightly before increasing to 90 percent. The
control group started at roughly 80 per cent which remained fairly constant through the
second follow-up survey after which it increased to more than 90 per cent and slightly
dropped again in the last survey. However, comparing target and control group results
we find no significant impact.

20
Figure 5.6.1: Percentage of clients who could cover unforeseen household expenses

Legend: target group o, control group 

Figure 5.6.2 shows a very strong fluctuation in the percentage of clients who could
cover unforeseen business expenses in the treatment group. It decreases from more
than 60 to less than 20 per cent, before it increases to almost 100 per cent. The
percentage in the control group fluctuates between less than 80 and almost 100 per
cent. The net effect, however, is insignificant.

Figure 5.6.2: Percentage of clients who could cover unforeseen business expenses

Legend: target group o, control group 

In summary, we find intended impact of the client training on two vulnerability

variables:(Did household income cover all household expenses in the last 12 months,
Sold assets to cover unforeseen expenses. For the other five vulnerability variables we
find no impact.

21
6. Conclusion and recommendations
This report presented findings from an evaluation of an integrated client training on
risk management and microinsurance that the MFI TYM introduced in Vietnam. The
training put a special emphasis on the Mutual Assistance Fund (MAF) that TYM offers to
its clients. The evaluation employed a difference-in-difference methodology to
estimate the effects of the training on client livelihood outcomes including a change in
financial attitude and behaviour, building and maintaining of assets, vulnerability, and
over-indebtedness and multiple borrowing of clients.

Overall, the research showed that the client training did produce some of the intended
results.

First, data clearly demonstrated that clients understood very well the terms of the MAF
and that they were also quite satisfied with the product. This applied to all waves.

Second, the evaluation found that the training had very strong impact on financial
attitude especially on planning and on attitudes related to savings. The percentage of
clients in the target compared to the control group that agreed being able to put
money aside for emergency expenses increased by a remarkable 22 per cent and the
attitude towards planning household budgets for longer than a year improved by 17 per
cent.

Third, the training also had impact on client risk management behaviour by
contributing to improving a number of situations that clients face. For example, clients
who had access to the training less often ran out of money before making income than
clients who did not have access to the training (decrease of 13 per cent). Interestingly,
the observed change in financial attitude regarding savings and planning already also
reflected in changed financial behaviour as we saw a 17 per cent increase in the ability
to set aside money for emergencies as well as a 13 percent increase in clients with
longer planning horizons.

Fourth, the training seems to have had limited impact on asset building and multiple
borrowing/ over-indebtedness. The reason, however, is that repayment rates in target
and control groups had been high from the very beginning and left little room for
improvement.

Lastly, with respect to vulnerability outcomes we found positive impact as the ability
of households to cover their expenses increased and as fewer clients sold assets to
cover unforeseen expenses. However, we did not find an effect for the other
vulnerability outcome variables.

In summary, the evaluation showed strong impact of the integrated risk management
and microinsurance training on financial attitude and risk management, some impact
on vulnerability and little impact on multiple borrowing/ over-indebtedness and asset
building. The analysis also showed some insignificant and some unexpected results
which may be due to some issues with the experimental design of the research and the
survey instrument. It is therefore possible that the innovation may have had a stronger
impact than actually measured and reported in this document.

Based on the overall research process and conclusions, the ILO would like to make the
following recommendations to TYM regarding the future of the integrated risk
management training and the Mutual Assistance Fund:

1) Continue to implement the integrated client training on risk management and

microinsurance at defined moments during interactions with clients and roll out the
training to other branches;

22
2) Continue to track progress on the client level as part of TYM’s social performance
agenda;
3) Monitor the quality of training delivery and regularly strengthen the risk
management knowledge and training skills of TYM staff;
4) Strengthen the capacity of TYM staff to efficiently manage the Mutual Assistance
Fund; and
5) Share tools, methodologies, and findings from the action research through national
and international MFI networks to encourage efforts in improving clients’ risk
management and to promote the concept of Decent Work.

23
Appendix

A1: Evaluation methodology: Difference-in-

difference estimation

An experimental approach to empirical research was chosen for evaluating the impact
of the MF4DW innovations. In regard to TYM’s risk management training, one challenge
to this experimental approach is that the innovation was not randomized at the
individual level within TYM branches or across a large number of TYM branches, but
held fixed in one branch only (target branch). A greater number of branches would
have been ideal for such research. However, given resources, capacities and time
constraints, the MF4DW action research and TYM opted for the introduction of the
innovation in one branch. However, the sample size for target and control branches is
large enough and representative for all TYM clients in these branches.

The question of interest is whether a client exposed to the innovation has outcomes
different from that of a comparable client in the control group. For the quantitative
evaluation of the training programme (the innovation), a difference-in-difference
methodology is employed. The difference-in-difference approach yields causal effects
of the training programme on the intended outcomes when two assumptions are met:
First, there must not be contamination of the control group by the target group. Given
the geographic distance between the two selected branches (roughly 150 kilometres),
this assumption does not appear to be problematic. Second, outcomes in both branches
must follow a common trend. Given that we have little information how factors at the
branch level may affect outcomes (local changes in economic policy or other economic
conditions or extreme weather conditions respectively affecting one branch but not the
other etc.) it is not straightforward to believe that the model generally yields causal
relationships.

The fact that the innovation varies only at the branch level circumvents unobserved
heterogeneity at the individual level. The fixed innovation for clients in the target
branch allows us to employ a difference-in-difference estimator similar to Card and
Krueger.9

We define the dependent variable 𝑌𝑖𝑗𝑡 to include different outcomes of interest related
to customer 𝑖 in branch 𝑗 = 1,2 at time 𝑡 = 0,1,2. The innovation is introduced in 𝑡 = 1
in the target branch and remains active in all subsequent periods of time. Prior to 𝑡 = 1
no innovation is in place.

We attempt to estimate the counterfactual outcomes after the introduction of the

innovation. There are two branches. Clients in branch 𝑗 = 1 (Me Linh (ML)) are exposed
to the innovation, while clients in branch 𝑗 = 2 (Y Yen(YY)) are not. We specify the
following linear model to OLS estimate the innovation effect on certain outcomes:

𝑌𝑖𝑗𝑡 = 𝛼𝑗 + 𝜆𝑡 + 𝛾𝑀𝐿𝑖 + 𝛽𝑀𝐿𝑖 ∗ 𝐴𝐹𝑇𝐸𝑅𝑡>0 + 𝑢𝑖𝑗𝑡 (1)

The first term is branch-specific and fixed over time, the second term is vector of time
dummies common across branches and varying over time. The variable 𝑀𝐿𝑖 is a binary
indicator equal to one for the target branch and zero for the control branch. The
coefficient 𝛽 on the interaction between the branch dummy, 𝑀𝐿𝑖 , and 𝐴𝐹𝑇𝐸𝑅𝑡>0 gives
the average difference-in-difference effect where 𝐴𝐹𝑇𝐸𝑅𝑡>0 is a binary indicator equal

9
Card, D. and A. Krueger (1994) "Minimum Wages and Employment: A Case Study of the Fast-Food Industry
in New Jersey and Pennsylvania," American Economic Review, 84(4), 772-93.

24
to one for all time periods during which the innovation was in place. This imposes the
restriction that the innovation has the same effect in every period of time.

For 𝑡 = 1, the sample analog of above regression formulation of the difference-in-

differences estimator yields double differences in sample means, that is the difference
in outcomes across the branches and time periods: 𝐷𝐷 = (𝑌11 − 𝑌10 ) − (𝑌01 − 𝑌00 ).
We modify the basic specification in equation (1) in a number of ways to check the
stability of our estimated coefficients. Our biggest concern is the possibility of omitted
variables at the branch and wave level.
We estimate the equation in (1) under four specifications for each outcome. First, we
estimate the basic model without further controls and common support. Second, we
include controls (see Table 4.3.1 for a list of controls) but no common support. Third,
we include controls and restrict sample to common support. And, fourth, we include
additional branch-time dummies to the latter specification. With respect to inference
we present results with clustered standard.

25
A2: Evaluation methodology: Interpretation
of difference-in-difference estimates
It is necessary to clarify how the impact of the innovation on intended outcomes has to
be interpreted. Comparing target and control branches, we compare clients who were
trained in risk management and microinsurance to those who were not. If we see a
difference in outcomes comparing the two branches, then the change in clients’
financial attitude and behaviour results from an exposure to the training programme.

We illustrate the difference-in-difference approach with a simple example. The

exposure to the innovation is determined by being a client in the target branch after
the introduction of the innovation. Table A.2.1 below is a two-by-two table for target
and control branch for wave 2 and the baseline. Column (1) and (2) respectively display
the mean of an outcome variable (in this case difficulties of loan repayment by clients,
but it could be any other outcome variable) for the innovation and control branch for,
respectively, row (A) and row (B), the second wave of the survey and the baseline.

Table A2.1. Illustration of the difference-in-difference methodology

Note: Illustration of the difference-in-difference approach using repayment difficulties. The figures
presented are sample means for target branch (1) and control branch (2) for respectively wave 2 (A) and
baseline (B) for the outcome variable clients with repayment difficulties (figures can be interpreted as
percentage values). Single differences can be calculated as (1) - (2) for either (A) or (B) and (A) - (B) for
either (1) or (2). The difference-in-difference is either (A) - (B) for (1) minus (A) - (B) for (2) or (1) - (2) for
(A) minus (1) - (2) for (B).

For instance, column (1) and row (A) state that 12 per cent of the clients in the target
branch had repayment difficulties in wave 2. Column (1) and row (B) state that 15 per
cent of the clients in the target branch had repayment difficulties in the baseline.
Taking the difference (A) - (B) for column (1), we obtain -3 per cent. This is the single
difference for clients with repayment difficulties in the target branch before and after
the modification of the innovation. Consequently, the percentage of clients with
repayment difficulties decreased over the survey period. Making the same exercise for
the control branch we find that the percentage of clients with repayment difficulties
stayed the same over the survey period. The single difference is 0 per cent.
The difference-in-differences are now calculated as the difference between the single
differences, that is -3 per cent minus 0 per cent. The difference-in-difference is thus -3
per cent. Clients in the target branch see a reduction of 3 per cent in repayment
difficulties as compared to clients in the control branch after the introduction of the
innovation.
The idea behind this approach can be understood in an experimental context. While we
should see an effect of the innovation in the target branch by looking at the difference
before and after, we should not see such an effect in the control branch. The
difference-in-difference should hence be driven by the first difference (before and
after in the target branch) and not the second difference (before and after in the
control branch).

26
A3: Limitations to the evaluation of the
training programme
Although we received some qualitative reports on factors that may have affected
outcomes at the branch level, the picture is not fully complete. In particular, more
quantitative data on these factors would allow for a better analysis. Consequently,
results presented in appendix A4 may not generally present causal relationships. Just
to give some examples of such factors:

 A drop in food prices (e.g. for rice) around the target branch but not the control
branch increases the clients’ capacity at the former to make all necessary
household expenses. If we see a difference in clients’ capacity to make all
necessary expenses this might be the result of changing food prices - and not the
modification of the innovation.
 The local economy around the target branch may have grown at a faster rate than
the one around the control branch. Then differences in business profits made are
the consequence of the more favourable economic development around the target
branch and not due to the modification in the innovation.

27
A4: Tables
Table A4.1: Outcome summary statistics on asset building

28
Legend: TB - target group, CB - control group.

29
Table A4.2: Outcome summary statistics on multiple borrowing/ over-indebtedness

Legend: TB - target group, CB - control group.

30
Table A4.3: Outcome summary statistics on financial attitude (1)

Continued on next page...

31
Table A4.3: Outcome summary statistics on financial attitude (2)

Continued on next page...

32
Table A4.3: Outcome summary statistics on financial attitude (3)

Legend: IB - target group, CB - control group.

33
Table A4.4: Outcome summary statistics on risk management

Legend: IB - target group, CB - control group.

34
Table A4.5: Outcome summary statistics on vulnerability

Legend: TB - target group, CB - control group.

35
Table A4.6: Outcome summary statistics on type of shocks/ unforeseen expenses (1)

Continued on next page...

36
Table A4.6: Outcome summary statistics on type of shocks/ unforeseen expenses (2)

Legend: TG - target group, CG - control group.

37
Table A4.7: Outcome summary statistics on MAF (1)

38
Table A4.7: Outcome summary statistics on MAF (2)

Continued on next page...

39
Table A4.7: Outcome summary statistics on MAF (3)

Legend: TG - target group, CG - control group.

40
Table A4.8: Impact on financial attitude (1)

Continued on next page...

41
Table A4.8: Impact on financial attitude (2)

Continued on next page...

42
Table A4.8: Impact on financial attitude (3)

Legend: IB - target group, CB - control group.

Notes: Table contains difference-in-difference estimates for β from the equation (1) in appendix A1.
Depended variables are clients’ outcomes and client’s household outcomes related to financial attitude.
Specification (1) includes no controls and common support, (2) controls but no common support, (3) both
controls and common support and (4) controls, common support and branch-time dummies. A p-value smaller
or equal to 0.1 denotes significance at least at the 10 per cent level.

43
Table A4.9: Impact on risk management

Notes: Table contains difference-in-difference estimates for β from the equation (1) in appendix A1.
Depended variables are clients’ outcomes and client’s household outcomes related to risk management.
Specification (1) includes no controls and common support, (2) controls but no common support, (3) both
controls and common support and (4) controls, common support and branch-time dummies. A p-value smaller
or equal to 0.1 denotes significance at least at the 10 per cent level.

44
Table A4.10: Impact on asset building

Notes: Table contains difference-in-difference estimates for β from the equation (1) in appendix A1.
Depended variables are clients’ outcomes and client’s household outcomes related to asset building.
Specification (1) includes no controls and common support, (2) controls but no common support, (3) both
controls and common support and (4) controls, common support and branch-time dummies. A p-value smaller
or equal to 0.1 denotes significance at least at the 10 per cent level.

45
Table A4.11: Impact on multiple borrowing/over-indebtedness

Notes: Table contains difference-in-difference estimates for β from the equation (1) in appendix A1.
Depended variables are clients’ outcomes and client’s household outcomes related to multiple
borrowing/over-indebtedness. Specification (1) includes no controls and common support, (2) controls but no
common support, (3) both controls and common support and (4) controls, common support and branch-time
dummies. A p-value smaller or equal to 0.1 denotes significance at least at the 10 per cent level.

46
Table A4.12: Impact on vulnerability

Notes: Table contains difference-in-difference estimates for β from the equation (1) in appendix A1.
Depended variables are clients’ outcomes and client’s household outcomes related to vulnerability.
Specification (1) includes no controls and common support, (2) controls but no common support, (3) both
controls and common support and (4) controls, common support and branch-time dummies. A p-value smaller
or equal to 0.1 denotes significance at least at the 10 per cent level.

47
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funeral Insurance in South Africa

No. 23 2000 L. Mayoux Micro-finance and the empowerment of women: a

review of key issues

No. 24 2000 SFP Institutional Assessment for NGOs and self-help

Organisations Managing Guarantee schemes

No. 25 2000 A. McDonagh Microfinance Strategies for HIV/AIDS mitigation and

prevention In Sub-Saharan Africa

No. 26 2001 B. Balkenhol & Collateral, collateral law and collateral substitutes
H. Schütte

No. 27 2002 D. M. Gross Financial Intermediation: a contributing factor to

economic growth and employment

No. 28 2002 L. Deelen & Equipment finance for small contractors in public
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No. 29 2002 M. Aliber, A. Ido Micro-insurance in Burkina Faso

No. 30 2002 E.S. Soriano, E.A A field study of microinsurance in the Philippines
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No. 38 2003 T. Siddiqui Migrant worker remittances and microfinance in

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48
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No. 41 2006 C. Kreuz Microlending in Germany

No. 42 2006 D. Cassimon Linking debt relief to microfinance: an issues paper

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No. 43 2006 G. Gloukoviezoff Surendettement des particuliers en France: Quels

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No. 45 2007 Alberto Didoni The impact of liberalisation policies on access to

microfinance: the case of Peru

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No. 47 2007 Cédric Ludwig Trade unions and financial inclusion : the case of
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No. 48 2007 J. Roth, R. Rusconi The poor and voluntary long term contractual
N. Shand savings: lessons from South Africa

No. 49 2007 J. Breyer Financial arrangements in Informal apprenticeships:

determinants and effects – findings from urban
Ghana
No. 50 2007 Kirsten Schüttler The contribution of migrant organisations to
income-generating activities in their countries of
origin
No. 51 2007 Cédric Ludwig Trade unions and financial inclusion: the case of
South Africa

No. 52 2008 Nicolas Gachet Formalisation through microfinance: an empirical

study in Egypt

No. 53 2011 Jonas Blume Microfinance and Child Labour

Julika Breyer

No. 54 2011 Renata Serra Walking on a tightrope: Balancing MF financial

Fabrizio Botti sustainability and poverty orientation in Mali

No. 55 2011 Shoko Ikezaki Rokin Bank: the story of workers’ organizations that
successfully promote financial inclusion

No. 56 2012 Richard C. Koven Strategies for unions to provide benefits and
financial services to workers: experiences in the US

No. 57 2014 SFP & Microfinance and job creation: a social

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49
 No. 58 2014 M. Frölich Microinsurance and child Labour: an impact
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H. Midkiff, V.Breda innovation

No. 59 2014 SFP & Microinsurance and Formalisation of Enterprises in

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University
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Robin Gravesteijn impact assessment of a start-up loan programme,
IMON International, Tajikistan

No. 61 2014 Doubell Labour unions and financial inclusion in South

Chamberlain Africa – How labour unions facilitate the provision
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(Edi.Input)

50