Recurrent access to farm credit positively impacts farmers evidence from an impact study in Benin

Abstract

Low access to financial services is known as a major constraint to development in the agricultural sector of both farms and small entrepreneurs within their value chains. This insufficient access is partly due to the lack of knowledge of the real uses and impacts of such credit upon its borrowers. Farm credit, for example, is expected to have a high rate of default payment due to the high risk of farm activities. Some authors even expect it to have negative effects on some of the farmers and drive them into indebtment. On the other hand, in view of the low access rates many projects, programmes and policies recently try to enhance and support financial services to farmers. Such support with taxpayers' money which is in competition with other uses of scarce financial resources is based on the assumptions that positive development and economic outcomes and impacts are achieved. In this regard, demonstrating impacts of agricultural finance is an important component of aid effectiveness, including best aid allocation and good practices. This contribution intends to present results of an impact assessment of agricultural credit in Benin. The paper is constructed in 4 parts. A literature review discusses how uncertain and contradictory impacts of credit on welfare may be. The controversy concerning such impacts is partly related to methodological issues which are briefly presented prior to the methods adopted for this study. Major results of the study are then exposed and they are discussed in conclusion.

Full text

Recurrent access to farm credit positively impacts farmers
evidence from an impact study in Benin
Floquet A1, Sagbo S2, and Brüntrup M3
1 Corresponding author, Laboratoire d’Analyse des Dynamiques Sociales et de Développement,
Université d’Abomey-Calavi, Abomey-Calavi, Benin, Contact : anneb.floquet@gmail.com
2 Department of Agricultural Economics, University of Kentucky, Lexington, Kentucky, United States
3 Research Programme Transformation of Economic and Social Systems, German Development
Institute / Deutsches Institut für Entwicklungspolitik (DIE), Bonn, Germany
Low access to financial services is known as a major constraint to development in the agricultural
sector of both farms and small entrepreneurs within their value chains. This insufficient access is
partly due to the lack of knowledge of the real uses and impacts of such credit upon its borrowers.
Farm credit, for example, is expected to have a high rate of default payment due to the high risk of
farm activities. Some authors even expect it to have negative effects on some of the farmers and
drive them into indebtment. On the other hand, in view of the low access rates many projects,
programmes and policies recently try to enhance and support financial services to farmers. Such
support with taxpayers’ money which is in competition with other uses of scarce financial resources
is based on the assumptions that positive development and economic outcomes and impacts are
achieved. In this regard, demonstrating impacts of agricultural finance is an important component of
aid effectiveness, including best aid allocation and good practices.
This contribution intends to present results of an impact assessment of agricultural credit in Benin.
The paper is constructed in 4 parts. A literature review discusses how uncertain and contradictory
impacts of credit on welfare may be. The controversy concerning such impacts is partly related to
methodological issues which are briefly presented prior to the methods adopted for this study.
Major results of the study are then exposed and they are discussed in conclusion.
1. Controversial impacts of microfinance at large and of agricultural credit in particular
Microfinance is expected to improve investment capacities of smallholders and therefore revenues
as well as diversification et risk reduction of their income generating activities. This should lead to
assets accumulation. Credit may directly or indirectly smooth consumption, reduce vulnerability to
life crisis, and improve beneficiaries’ social status, especially those marginalized. All these effects
may also yield positive spillovers beyond the sole beneficiaries.
After much hope had been put on how improved access of the poor to microfinance services would
reduce poverty, several authors questioned the ability of the poorest to benefit from credit. Several
reviews conducted since the nineties have questioned the materiality of such outcomes: there is no
evidence of consistent effects of microfinance on the multidimensional outcomes affecting welfare
(Armendariz and Morduch, 2005). Cull and Morduch (2018) in a more recent review conclude that
microfinance has no transformative potential per se and that its impacts are highly diverse
depending on the context. Banerjee et al. (2015) comparing results from 6 randomized evaluations of
microcredit in diverse settings also conclude about a lack of evidence of transformative power and
even reveal negative effects on the average borrowers (p.3). The authors attribute such poor
performances to the heterogeneity of goals among microfinance institutions, the diversity of
contexts and opportunities as well as to the very different types of social and economic categories

targeted. Further recent studies also reflect these contrasted impacts: Agbola et al. (2017) could
attribute welfare improvement in the Philippines to credit while Nghiem et al. (2012) in Vietnam
could not, not even among those having taken credit over several years. Van Rooyen et al. (2012)
specifically reviewed the evidence of the impact of microfinance in Sub-Saharan Africa. Out of 15
reliable studies they also concluded that effects were mixed and different among targets.
Credit in agriculture
At first credit to agricultural households was offered for production. In the 1990s it was recognized
that rural households were also in need of further financial services for consumption smoothing and
insurance and that different pathways could lead to food security improvement (Zeller et al., 1997).
Microfinance institutions began to offer credit for consumption and crisis management purposes and
farm production credit became in short supply, as observed in the case of Benin, while off-farm
activities with a quick turnover were preferred.
Farm productive credit does not yield systematically positive outcomes. A review from Clark et al.
(2015) revealed that credit for inputs did not improve crop incomes, an outcome attributed to a lack
of flexibility in repayment schedules and uses. Diagne and Zeller (2001) in Malawi also found out that
borrowers were not better off than non-borrowers due to lower net crop incomes after repayment
of the principals and the interests; one reason was that loans were in kind, provided costly fertilizers
for hybrid maize and encouraged this risky crop where farmers would have cultivated less risky
tubers and legumes or higher value tobacco crops. Credit only had positive impacts in the more
conducive environments.
In regions where credit supply is abundant, the analysis needs to consider credit constraints and
measure outcomes for credit constrained compared to not-constrained producers. Moreover, credit
impacts depend on the availability of other major factors affecting agricultural growth. Credit may
well affect technology adoption provided such innovative technologies exist and are accessible to
farmers. When such innovation does not exist and farm activities are not profitable, unexpected
results may occur as in Zambia, where farmers used credit to reduce the off-farm activities they used
to conduct in bad times and ate more regularly rather than improve their cash incomes (Clark et al.,
op.cit.). Complex further chains of outcomes were also observed. Credit did finance storage for later
sales at a higher price, but spillovers levelled its effect when too many farmers sold at a later period.
The uncertainty of the outcomes combined with the very low access to formal farm credit in Africa is
inducing a renewed interest in detailed impact studies not only concerned by bringing a proof of
impact but also by displaying the mechanisms of how impacts are produced considering contextual
factors and a more detailed analysis of the financial services provided and of their adequation and
complementarity. Evidence based theories of change are needed and the chain to impact should be
tested.
Impacts on gender issues and women empowerment
It is often claimed that access to credit empowers women. Indeed, credit in many cases helps women
in managing their household expenditures by providing own sources of incomes but both reviews
conducted by Duvendack et al. (2014) and Vaessen et al. (2014) focused on female beneficiaries’
control over household spending could neither find a significant effect of credit on women control
from experimental nor from quasi-experimental studies. It has been assumed that an improved
income would positively influence power relations within the household and the community and
improve women social status. Some authors strongly question this assumption. A higher efficiency
within a given inequitable system of norms cannot be considered as an indicator of empowerment

and it may even reinforce such norms. More decision power in some domains of life, here economic
initiatives, may not affect power of decision in other domains (Bali Swain and Wallentin, 2017).
Credit to women farmers is also often offered in association with other services such as training and
organization, which also affect measured outcomes. Here again a theory of change or competing
theories should be developed based on evidence and tested.
2. Methodological issues
As we were interested in how multidimensional impacts are obtained, the general framework of the
impact assessment developed for the present study on agricultural credit in Benin is theory based
(White, 2009). It builds on a theory of change developed during an exploratory survey and on the use
of mixed methods, both qualitative (perceptions and explanations) and quantitative (distances
between groups to test possible causal relationships).
Credit impact measurement is difficult for various reasons. One of the major ones is the construction
of a good counterfactual. Obviously, non-borrowers cannot be compared without precaution with
borrowers, as there are good reasons to assume that most of the non-borrowers structurally differ
from the borrowers. In many cases, they would not even apply for a credit, which they expect to put
them at risk. If matching procedures are implemented, the sample of heterogenous non-borrowers
will have to be very large. Even with such a large sample, statistical matching will be incomplete,
since some non-measurable variables are considered during the applicants’ selection procedures,
such as a local evaluation of their morality and trustworthiness; such variables influencing the
propensity of selection cannot be included in the matching. This has led to a plea in favor of
experimental designs (RCTs), for example by delaying the beginning of a credit program in parts of
the areas which can become the control of the others (cluster randomization) or by halving the group
of beneficiaries in two sub groups, one being denied the treatment. In the case of FECECAM in Benin,
which is a cooperative union, such a design would not be acceptable. How could a board explain that
some of the association members who fulfill the conditions of savings, collaterals and profitability of
the activities requiring the loan, won’t receive it because of an experimental design? This would
provoke immediate exit out of the association of both members and their savings.
For this reason, this study relies on an alternative design known as “pipeline”. In a pipeline design,
groups enter a program at different stages, so that some benefit from long-term, others from short-
term outcomes; some may even have been newly selected without having access to the program yet.
The design is an alternative to a fully randomized assignment, provided selection criteria remained
more or less the same over the years. Copestake et al. (2001) compared 3 cohorts of borrowers with
2, 1 and 0 loans, the most recently accepted in the program “not yet treated” being used as a
control. Incomes and investments were improved after a second loan, as displayed in a multiple
regression. In other studies, it was not possible to find potential clients already selected and waiting
for a first loan as loan are very quickly allocated. The control group was then composed of recent
versus early borrowers (White, 2010). This was also the case in this study.
As both groups of early and late entrants might still have different characteristics, participants from
both groups were matched according to their propensity of being a borrower. Effects are then
calculated for pairs of new vs. old borrowers and average treatment effect on the treated (ATET) as
well as average treatment effect (ATE) tested for significance.
Some researchers still assess pipeline designs, even combined with PSM, to be “vulnerable to
unobservables”. They also fear that dismissing too many cases which cannot be matched in both

groups, variability may be affected. A sensitivity analysis of the PSM results should be conducted at
least (Duvendack et al., 2011). In our case, we included the drop-outs among the borrowers having
obtained a credit and left (due to non-repayment or difficulties in repayment). We compared both
groups of early and late borrowers to assess that they were originating from the same population. In
the end we discussed whether the causal linkages were plausible regarding the agricultural economic
theory.
This contribution intends to present the results of an impact study of agricultural loans provided by
FECECAM (Faîtière des Caisses Locales de Crédit Agricole Mutuel) in Benin. FECECAM is an old
national federation of mutual credit cooperatives called CLCAM (Caisse Locale de Credit Agricol
Mutuel). The organization is the largest MFI in the country. It has the highest geographical coverage
with its 136 service points. The network includes more than 1.5 million account holders and nearly
400,000 borrowers in 2017.
Despite the initial objectives of the federation to serve farmers, agricultural loans were nearly
abandoned and now hardly constitute 20% of the total amount disbursed (77,000 borrowers in
2017). Yet, agricultural loans are being developed again, in parallel to the general trend towards the
promotion of agriculture worldwide and in developing countries. FECECAM offers a fairly large range
of credit types, duration and reimbursement modalities to meet the diverse needs in rural areas, but
flexible annual loans are predominant. Noteworthy are farm loans successively taken for each main
cropping and post-harvest activities. It allows for smaller amounts of credit, and in case of crop
failure, producers won’t have to take a loan for the harvest. According to FECECAM statistics, default
rates are lower among farmers compared to urban traders.
Literature study and an exploratory phase allowed the team to iteratively design a theory of the
changes induced by agricultural credit over time and identify a range of outcomes. Farm activity
returns, total farm income, asset base, farm labor demand, food security and nutrition, and gender
status (for female borrowers) are the main indicators which will be discussed here.
Sampling relied on a regional stratification based on agroecological and socioeconomic criteria. Being
limited by financial means, the study focusses on three of the seven contrasted country “Pôles de
Développement Agricole” (with a population of 48,000 individual agricultural borrowers and 3,000
groups between 2012 and 2017). In each of these three selected strata, ten service points (clusters)
were selected with a probability proportional to their population size, and an equal number of 26 old
and new borrowers was sampled in each cluster (epsem sampling procedure). Borrowers who had
left the system were also included and traced. The sample size was estimated to obtain adequate
significance levels for impact on net farm income, considering the variability observed for this
variable in a former survey. 780 credit borrowers were surveyed, yielding 750 complete and
acceptable data sets. In the end, the principle of epsem sampling having been somehow violated in
practice due to missing borrowers and missing data, each case was assigned a weight and weighted
calculations out of sampling values performed for those variables, which were important to
characterize the population of FECECAM agricultural borrowers. The survey was conducted in
October 2017 using ODK collect software on smartphones and data were analyzed using STATA
(Sagbo et al., 2018).
FECECAM credit borrowers are more often men than women (32,3% female borrowers) and are in
most cases farm-household heads (92% of the men and 19% of the women). No discrimination
according to ethnicity or autochthony could be observed. Borrowers in their majority did not attend
school and do not speak French, which is the official language but many of them also have learnt a
craft as an apprentice or acquired skills during work migrations. Agricultural extension support is very

poor (16% of female and 29% of male borrowers benefited from extension services over the
preceding year). Also, credit monitoring by the bank after loan obtention is not very intensive, except
for the few women in group-lending who are monitored by facilitators. However, borrowers have a
long experience in the domain of activities they request loans for (19 years on average).
It was expected that credit impacts would depend on the region. In the Northern region, land
availability is higher but so is remoteness. Average cultivated areas are respectively 11.1 ha; 7.3 ha
and 3.6 ha in the northern, central and southern regions. Agricultural production brings most of the
borrowers’ income (82%) in the North, is complemented by trade in the central region and by
processing and trade in the southern region (64% and 57% of the income from primary production
activities). Maize, cotton and soy are the main income sources in the North; maize, soy, cotton, and
cashew in the Central region. Different high-value crops can be found in the South (chili pepper or
tomato-based, pineapple-based, oil palm-based farming systems, etc.), combined with a large range
of food processing, trade and non-farm activities.
In Benin, cotton producers obtain their inputs on credit, which is automatically paid back to input
providers when cotton is being paid by ginners. Therefore, cotton farmers request loans for
associated labor costs and for other products or activities. Maize is the main crop requesting credit
followed by cotton, soy, and cashew as well as trade. 23% of the borrowers partly use their credit to
finance further activities beyond those mentioned in their loan request.
3. Results
Producers, who already had access to credit in 2015 or before, obtain a yearly crop income in 2017
by 49% higher than their peers first coming to access in 2016 or 2017. Impacts are particularly high
for male farmers and in the northern and central regions (Table 1). Credit there is used to increase
the farm size, to use more inputs (especially in the cotton zone where they are easily accessible on
the “black market” from farmers selling those received on credit via the cotton system) or to hire
more labor (especially in the central region). Women tend to reduce their farming activities. Our first
hypothesis on the impact of agricultural credit on agricultural income is verified, but under
conditions of land and inputs or labor accessibility. Income per workday is significantly higher but
expenditure (input) efficiency in agriculture does not increase, i.e. there is no adoption of productive
innovation.
Additional agricultural incomes are used to develop other activities. The income structure changes
between late and early borrowers with a much higher share of non-farm activities. Women and
borrowers in the South especially tend to develop food processing and trade activities. Eventually,
total farm-household incomes of older borrowers are 127% higher than those of the more recent
ones. Total income differences between matched early and late borrowers attributable to credit
(ATE) are 2 million FCFA (US$ 3,660); would the recent borrowers have had an earlier access to loans,
average total incomes would now be 1.5 million FCFA higher. The general trend to develop non-farm
activities when getting more prosperous is generally observed in most rural areas and in Benin in
particular, reflecting the poor economic performances in agriculture. It is more visible among women
than among men.
In our theory of change, we were expecting even more visible effects on asset accumulation than on
incomes, which are in the short run notoriously affected by sets of unpredictable factors. Elder
borrowers have indeed increased their assets, both productive and domestic (household durable
goods) by 200% compared to more recent borrowers. They do invest in better housing,
transportation, cattle and access to land. Here again male early borrowers can attribute an asset
increase of 850,000 FCFA to this earliness, while women do not enjoy any higher asset accumulation,

when having earlier credit access. Women have a very low ability to accumulate assets out of their
incomes, which also affects credit impact on this dimension.
Table: Difference in outcomes between early and late borrowers and estimation of effects would all
have been early borrowers
ATET
Difference
ATE
Difference
Crop income (FCFA)
131 300
0,000 hs
56 600
0,011 sig
- Women
-341 000
0,000 hs
-315 200
0,000 hs
- Men
753 400
0,000 hs
745 500
0,000 hs
- North
124 400
0,000 hs
268 900
0,000 hs
-Central area
412 700
0,000 hs
501 300
0,000 hs
- South
- 2 605 700
0,000 hs
- 2 894 800
0,000 hs
Cultivated area (ha)
1,59
0,000 hs
1,39
0,000 hs
- women
-6,93
0,000 hs
-4,68
0,000 hs
- men
3,26
0,000 hs
1,97
0,000 hs
- North
-2,11
0,000 hs
-0,76
0,000 hs
-Central area
2,74
0,000 hs
1,65
0,000 hs
- South
0,76
0,000 hs
0,18
0,320 ns
Total income (FCFA)
2 036 700
0,00 hs
1 520 500
0,011 sig
- Women
2 843 100
0,000 hs
2 171 400
0,000 hs
- Men
1 917 300
0,000 hs
1 627 200
0,000 hs
- North
750 200
0,000 hs
1 108 400
0,000 hs
-Central area
2 857 700
0,000 hs
3 116 000
0,000 hs
- South
-1 998 500
0,000 hs
-1 115 000
0,000 hs
Assets (FCFA)
720 800
0,000 hs
934 500
0,000 sig
- Women
-55 970
0,000 hs
-72 700
0,555 ns
- Men
856 400
0,000 hs
957 000
0,000 hs
- North
660 200
0,000 hs
585 300
0,000 hs
-Central area
2 808 200
0,000 hs
1 758 200
0,000 hs
- South
202 900
0,453 ns
0,282 400
0,223 ns
Additional wage labor (% borrowers)
5,9
0,000 hs
4,5
0,000 sig
- Women
8,2
0,000 hs
3,0
0,000 hs
- Men
7,2
0,000 hs
4,2
0,000 hs
- North
-8,8
0,000 hs
-9,7
0,000 hs
-Central area
1,8
0,02 sig
4,5
0,000 hs
- South
3,5
0,000 hs
2,5
0,000 hs
Additional family labor (% borrowers)
3,2
0,000 hs
-2,6
0,555 ns
- Women
11,2
0,000 hs
3,1
0,000 hs
- Men
-4,0
0,000 hs
-6,4
0,223 ns
- North
-10,6
0,000 hs
-7,1
0,000 hs
-Central area
0,0
0,982 ns
5,9
0,000 hs
- South
-7,2
0,000 hs
-3,5
0,025 hs
A much-discussed impact in the theory of change was the effect of credit on employment. Depending
on the type of activities developed due to credit, labor demand may increase or decrease. In the
analysis, differences between earlier and late borrowers are significant but low. Women tend to

reduce the involvement of family labor (including their own) by switching to non-farm activities.
Small increases in wage labor are being estimated in the South and decreases in the North, where
mechanization and herbicides are accessible and overcompensate the extension of cultivated area
attributed to early credit.
Table 2: Difference in outcomes between early and late borrowers and estimation of effects would all
have been early borrowers
ATET
Difference
ATE
Difference
Food insecurity Anxiety index
- North
-0,4685
0,000 hs
-0,5227
0,000 hs
-Central area
-0,1041
0,019 sig
-0,1887
0,000 hs
- South
0,0433
0,808 ns
-0,0439
0,777 ns
Diet diversity score
1,333
0,000 hs
1,554
0,000 sig
- Women
3,412
0,000 hs
1,840
0,000 hs
- Men
1,543
0,009 hs
1,895
0,000 hs
- North
-2,046
0,000 hs
-0,608
0,005 hs
-Central area
-0,777
0,019 sig
-0,984
0,000 hs
- South
3,355
0,000 hs
2,862
0,000 hs
Women autonomy (WEIA)
0,176
0,000 hs
0,132
0,000 hs
More than half of the borrowers’ households suffer from a hunger gap in the year, and two thirds of
them in the North (Table 2). This and the high prevalence of chronic malnutrition among children
under 5 in the country makes the issue of credit impacts on food security very relevant. Borrowers
perceive a positive effect of credit on their food security, also confirmed by the slightly lower anxiety
among early borrowers than among their later peers, and standard measures of food security (Food
Insecurity Experience Scale, FIES) and dietary quality (Food Consumption Score) are slightly but
significantly better for early borrowers, and particularly for women borrowers.
The influence of credit on women situation was also analyzed by surveying their perceptions as well
as by using a Women’s Empowerment in Agriculture (WEIA) index. Women ability to make decisions
and take actions is considerably lower in the North than in the South. A large majority of female
borrowers assesses credit impacts on their own social status as positive, but it doesn’t change this
regional trend. The effect of early credit on the WEIA score is moderate but significant. Social
changes in norms are slow and economic changes limited for women who have structurally limited
access to production factors, land especially.
In all, FECECAM’s recurrent agricultural credit had a positive impact on borrowers’ situations. It could
be higher, would all producers have improved access to extension, innovations and inputs. Credit
should also be further adjusted to the activities developed according to gender and regions. Food
processing and trade activities deserve specific recognition.
4. Discussion and recommendations
With its longstanding experience, FECECAM is cautious in not taking risks with the savings of their
membership beyond those risks already assessed in agriculture. Loans are granted after applicants
have been proofed by their local peers. Outcomes on the activities benefiting from credit are
positive, but even more are the effects on the borrower’s income. In contrast to many of the studies

mentioned in the literature review, significant differences could be estimated on all the outcome
dimensions and they were also in line with the borrowers’ perceptions. Results also match with the
knowledge on the circumstances in the three different areas and on gender related differences and
are therefore credible. The type of microfinance institution should be taken into account when
assessing impacts of agricultural credit. FECECAM differs from those types of projects delivering
credit according to administrative criteria for example.
Credit is mainly allocated to a crop, but its outcomes go well beyond this sole activity and helps
increase other farm and on farm activities. The lack of transformative power displayed in many other
impact studies cannot be deplored here. Nevertheless, during the period considered (2012-17),
agricultural extension as well as applied research were weak and therefore access to innovations
concerning the cropping practices but also new activities through formal channels was low. This
explains why most of the credit was supplied for the cultivation of the well-known maize and cotton
crops with a low focus on other links in the value chains such as storage, processing or packaging,
which are often those adding more value. Very recently, processing units and exporters developed
contractual arrangements with pineapple producer groups, which secured these groups’ access to
credit. Higher impacts would have been expected with a better access to innovation and extension
services.
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