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Microsoft word - pavliashvili-final.doc
Preferences for rural credit systems and their impact on the implementation of credit unions in Georgia
Despite newly implemented agricultural credit systems in Georgia designed to enhance
farmers’ access to financial means, the share of agricultural loans compared to all loans
remains low. This severely limits the availability of loans (Brown, Coles, Heron et al. 2000;
IFAD 2007; Kortenbusch & Cervoneascii 2003) suitable for Georgian farmers, thus impeding
amongst other factors agricultural development (Baramidze 2007; Kortenbusch &
Cervoneascii 2003; Swinnen 2002) in the country. To investigate this problem information is
required on the supply of credit schemes and barriers for the provision of credit to the rural
population, and on farmers’ preferences with regard to different rural credit systems.
Focussing on the demand side, the overall aim of this study is to assess farmers’ preferences
for different rural credit systems and to discuss the findings in light of the implementation of
credit unions or credit cooperatives that are seen as a viable solution for farmers’ credit
problems (IFAD 2007; Revishvili & Kinnucan 2004; Zeller 2003).
We conducted a household survey with smallholders (N=406) that is representative for the
Georgian region of Shida Kartli in early 2008. The household survey included stated
preference methods to elicit farmers’ preferences for different rural credit systems. A choice
between two general types of credit systems was followed by repeated choices among the
credit options that differed in several loan characteristics or attributes. The characteristics
were loan size, interest rate, collateral, maturity of instalments, commission, and loan
With regard to the general type of rural credit systems, preliminary study results show that
nine out of ten farmers prefer individual loans over group loans with joint liability. Overall
demand for rural credit in the research area appears to be high. In Shida Kartli, rural credits
are mainly provided by pawn shops, banks and non-profit NGOs. Credit unions play a
marginal role due to the following reasons. Firstly, one country-wide project funded by the
International Fund for Agricultural Development (IFAD) to implement credit unions between
1997 and 2005 had failed after a promising start due to management problems (IFAD 2007).
Secondly, many farmers seem to confound credit unions with the former Soviet kolkhozes,
although they clearly differ in their organisational structure and management. Credit unions
are voluntary associations that are governed by their members who are customers and owners
at the same time. One member has one vote. Credit unions are registered under a country’s
cooperative law (Zeller 2003). The former Soviet kolkhozes were organised differently.
Farmers were forced to carry out collective agriculture. They officially owned the means of
production, but not the soil. The government controlled the kolkhozes through a kolkhoz
management composed of communistic party members.
Despite a negative attitude towards cooperatives among Georgian farmers (Derflinger,
Ivaniychuk & Grossmann 2006; IFAD 2007), credit unions that employ the individual lending
scheme could be a viable alternative to loans with short term duration and high interest rates
offered by banks or NGOs. The advantage of credit unions lies in a member-based
governance structure which leads to a higher degree of independence of loans provided by
banks, NGOs and pawn shops. In addition to that, credit unions are reported to be the most
suitable financial institution to reach vulnerable groups (IFAD 2007; Zeller 2003).
The remaining sections of the paper are arranged as follows: 1) Literature review on different
aspects of rural credit systems in Georgia; 2) Economics, demographics, and microfinance in
Georgia; 3) The research region Shida Kartli; 4) Methodology and Survey Design; 5) Results
In this section we give an overview on different aspects of rural credit systems in Georgia,
covering the following aspects: (i) loan institutions and their outreach, (ii) access to loans, (iii)
loan uptake, (iv) lending systems, and (v) credit unions.
(i) Loan institutions and their outreach
The Georgian government did not take broad measures to implement credit systems via state
owned banks due to the high degree of market liberalisation after independence in 1991. The
only state owned bank serving the rural credit market was the Agro-Business Bank of Georgia
(ABG) that was established in 2000 by the Georgian government in cooperation with the
European Commission (Kortenbusch & Cervoneascii 2003 p. 75). Despite of the high credit
demand in rural areas, ABG’s success on the rural credit market was very limited due to
problems in its corporate governance (Kortenbusch & Cervoneascii 2003). In 2003, a strategy
for privatisation and take-over of ABG by institutional investors was prepared (Kortenbusch
& Cervoneascii 2003). The bank was eventually sold to a private shareholder in the summer
The United Georgian Bank (UGB), VTB Bank since 2006, is one of the few Georgian
commercial banks that recently got involved in agricultural lending. As competition between
the increasing numbers of banks in Georgia rises, UGB decided to extend into the rural
financial market with special credit offers for farmers. A study by Derflinger et al. (2006)
describes the experiences of UGB with agricultural lending. Contrary to the widespread
assumption that agricultural micro-lending cannot be profitable due to higher risks and costs
as compared to urban micro-lending, UGB experienced the opposite. After only two years the
bank considered agricultural micro-lending to be successful, less risky and more profitable
than urban micro-loans (Derflinger, Ivaniychuk & Grossmann 2006). This was attributed to
the following reasons (Derflinger, Ivaniychuk & Grossmann 2006 p. 5):
(1) average loan sizes are smaller, which reduces the loan risk; (2) farmers prefer ‘express’
loans even though they have to pay higher interest rates and upfront fees (commission); (3)
farmers have fewer financing choices, therefore they are more loyal to the bank and readily
offer information about themselves and others in the community; (4) loan officers
productivity is very high due to the so-called cluster approach and because most farmers in a
particular location are engaged in the same kind of agricultural activities enabling loan
officers to partly standardise the loan appraisal.
Contrary to other countries such as Bangladesh (Yunus 2008) and Cameroon (Sika & Strasser
2000) agricultural micro-lending via the group-loan approach was not possible in Georgia.
According to Derflinger et al. (2006 p. 9), there are hardly any farmer organisations in
Georgia, and credit unions had failed for the reasons mentioned above (IFAD 2007).
Therefore, UGB had to employ the individual lending scheme that is very expensive in rural
areas because the loan officers haveto travel to each individual farmer. The cluster approach
simplifies the procedure through the selection of villages with good agricultural potential. The
village head was informed beforehand about the loan scheme, and discussions with all
relevant groups in the village followed.Without the cluster approach UGB would never have
been that successful in agricultural micro-lending (Derflinger, Ivaniychuk & Grossmann
2006). Alternatively to the cluster approach the bank sends out its credit-mobile (Derflinger,
Ivaniychuk & Grossmann 2006 p. 10), a re-equipped mini-bus designed to carry out first
interviews on farmer markets with future loan clients. The credit-mobileturned out to be a
very useful tool with regard to agricultural micro-lending. Overall delinquency rate of
agricultural loans is very low, and growth rates of 100% (Derflinger, Ivaniychuk &
Until recently, the rural population in Georgia had little or no access to microfinance services
(Hirche & Kortenbusch 2005; Kortenbusch & Cervoneascii 2003; Pytkowska & Gelenidze
2005), which is as well reflected in the low share of formal credit supply (1.2%) granted to the
agricultural sector (National Bank of Georgia 2006 p. 46 ff). Correspondingly, two of the
biggest banks in Georgia, ProCredit Bank and United Georgian Bank (VTB Bank since 2006)
show low shares with respect to agricultural lending. ProCredit Bank disburses 7-9% (KfW
2004 p. 2 f) of all credits to the agricultural sector, and United Georgian Bank (UGB)
disburses 4.1% (Derflinger, Ivaniychuk & Grossmann 2006 p. 6). As mentioned above, UGB
aims to increase its share due to the successful new agricultural lending scheme. This positive
development is supported by Revishvili & Kinnucan (2004), but they remark that despite the
beneficial impact of agricultural lending smallholders are almost not served. To improve
access to loans for Georgian smallholders with limited collateral, Revishvili & Kinnucan
(2004) state that it is crucial to promote the implementation of credit unions in villages that
focus on enhancing the living conditions and on improving farm activities.
Generally, the rural loan uptake rate developed positively in the last years in several Georgian
regions, and is reflected in the increasing share of farmers with credit experience starting with
16.2% in 2003 (Kortenbusch & Cervoneascii 2003 p. 57), and rising to 30% in 2008 (author’s
survey results). One third of the farmers in Shida Kartli who took up a loan obtained it from
banks. This relatively high share in loans for the rural population shows that banks like
ProCredit Bank, and VTB Bank increased their loan offer for farmers, but the majority of
these loans are not special agricultural loans, and they are not adjusted to farmers’ needs
(personal communication 2008). The new involvement of formal financial institutions in the
rural credit sector is contrary to many developing countries such as Cameroon, where 90% of
the rural population depend on informal credit sources (Sika & Strasser 2000 p. 316). In
addition to loans from the formal credit sector, Georgian smallholders take up loans from the
informal sector consisting primarily of pawn shops. These are called ‘Lombardi’ in
accordance with the type of loan they disburse. The number of pawn shops has increased
strongly in the past couple of years, and they serve the urban as well as the rural poorer
population, especially women. Borrowers predominantly put their jewellery or domestic
appliances as collateral. Moneylenders which dominate the informal loan sector in other
countries (see Dufhues 2007 for Vietnam) are not very common in Georgia.
Armendáriz de Aghion & Morduch (2000) examined whether individual loans or group loans
(with joint liability) are preferred in Eastern Europe. They state that, contrary to many other
countries where group loans with joint liability prevail, individual lending is the dominant
lending type in Eastern Europe. In some cases, individual lending systems contain features of
group lending systems like regular repayment schedules, which serve to sort out undisciplined
borrowers. Armendáriz de Aghion & Morduch (2000) argue that individual lending in Eastern
Europe could be installed without demanding collateral from the clients if mechanisms like
direct monitoring, regular repayment schedules and the use of non-refinancing threats were
implemented. These new features could help to target low-income clients. Individual
‘express’ loans without collateral are already disbursed in Shida Kartli by ProCredit Bank,
VTB Bank and FINCA (NGO). ProCredit Bank aims to win over new clients with this loan
In the Georgian city of Batumi, Vigenina & Kritikos (2004) investigated the incentive
mechanism of individual micro-lending contracts offered by a bank, and compared its key
factors with those of joint-liability loan contracts offered by a NGO. Vigenina & Kritikos
(2004) point out that borrowers chose the individual lending approach if they were able to
pledge the collateral and planned to start a business with a dynamic development perspective,
and had a demand for relatively high or increasing loan sizes. Borrowers with business plans
that had a rather static development perspective and those who needed relatively low loan
sizes preferred the group liability approach. Surprisingly, a number of wealthier borrowers
deliberately chose the group liability approach despite their ability to pledge collateral, and
although the interest rate of the individual lender was lower. These borrowers were willing to
provide peer support within the group as a kind of insurance against repayment problems.
(Vigenina & Kritikos 2004). The authors conclude that ‘[…] a combination of both
approaches is necessary if it is aimed to reach all creditworthy borrowers irrespective of their
initial wealth status and their ability to provide collateral and irrespective of the expected
dynamics of the client’s business (Vigenina & Kritikos 2004 p. 175)’.
The following part addresses the development of credit unions (CU) and their dissemination
in Georgia. The credit cooperative concept was developed in Germany in the 1840s and 1850s
by Friedrich Wilhelm Raiffeisen and Hermann Schulze von Delitzsch (Zeller 2003 p. 19). The
idea behind cooperatives was to help the rural population become independent from
moneylenders and to increase their welfare through a financial institution owned and
controlled by its members (Zeller 2003). One important feature of credit unions is the
reinvestment of profits or their distribution amongst members. Credit unions are for-profit
organisations with a democratic governance structure that take into account the concerns of
weaker members. This is expressed through the one-member, one-vote rule (Zeller 2003).
Today the German Raiffeisen cooperatives provide inputs to farmers. In addition, they
became wide spread financial institutions (Raiffeisenbanken) having bank status in Germany.
Notwithstanding their advantages due to the member-based governance structure, CUs do not
prevail in Georgia. This is reflected in the low share of CUs; that is, 1.6 percent of all
financial institutions (Kortenbusch & Cervoneascii 2003 p. 16).
2. Economics, demographics, and microfinance in Georgia
Georgia became independent from the former Soviet Union in 1991. After independence the
economic system changed from a communistic economy to a market economy. The country
became a presidential republic with the adoption of the new constitution in 1995. One of the
biggest problems Georgia faces is internal ethnic conflicts that threaten territorial integrity.
The Ossetian and Abkhazian minorities declared independence of their autonomous regions
without internal acknowledgement or acknowledgement by the international community
(Kortenbusch & Cervoneascii 2003). Regarding employment, only 11.2% (DS 2008b p. 24)
of the working-age population receives regular salaries. This situation is forcing a large part
of the population into subsistence farming or into informal economic activities limiting the
amount of taxes raised. In addition, Georgia suffers severely from corruption. In 2003,
Georgia ranked 124th out of 133 surveyed countries on an index developed by Transparency
International (Kortenbusch & Cervoneascii 2003 p. 20). Since then the corruption rate
dropped considerably. In 2007, Georgia was ranked on place 79 out of 179 countries (TI
2007). According to official statistics (DS 2008a p. 44), 55.3% of the working age population
works in the agricultural sector. The average farm size is 0.9 ha (Lerman, Kistev, Kriss et al.
2003 p. 15; SDS 2005 p. 55). The share of rural population increased considerably from
47.8% in 2004 (DS 2005a p. 8) to 57% in 2005 (DS 2005b table 9.1). This increase was
ascribed to the ongoing long-term unemployment, which pushed people into subsistence
farming (see Lerman, Kistev, Kriss et al. 2003). Kegel (2003) states that the Georgian
government is not able to provide food security, thus further increasing the tendency towards
subsistence farming to ensure food security in rural areas.
Demographically, Georgia is characterised by emigration of young, working-age people and
by a low reproduction rate. More than two children per family are traditionally not common.
Furthermore, rural areas show a high proportion of pensioners (Kegel 2003). Emigration, low
reproduction rate and a relatively high share of pensioners led to a constant decrease in
population, which is reflected in the following figures. In 1996, the total population was 4.7
million and decreased to 4.4 million in 2007 (DS 2008b p. 77).
In this section we describe the development of microfinance and its current situation in
Georgia. The first microfinance activities started in Georgia between 1996 and 2000
(Kortenbusch & Cervoneascii 2003 p. 15). They were introduced by non-banking
microfinance institutions that were established by international humanitarian and economic
aid organisations. These microfinance institutions provided loans to the poor population that
was not served by commercial banks. After the year 2000, the banking sector showed interest
in microfinance products based on the success of the Microfinance Bank of Georgia (MBG),
ProCredit Bank since 2003 which became one of the largest banks (Kortenbusch &
Cervoneascii 2003). Four microfinance systems can be distinguished: 1) NGOs delivering
microcredit; 2) Specialised microfinance banks; 3) Downscaling programmes in commercial
banks; 4) Membership-based financial institutions, such as credit unions (CU) (Kortenbusch
& Cervoneascii 2003 p. 68). The following table shows the microcredit supply in Georgia by
NGOs, credit unions (CUs) and the banking sector:
Institution Outstanding loan portfolio as of September 30, 2003 USD Percent
Total 30,500,000 100.0 Table 1, source: Kortenbusch & Cervoneascii 2003 p. 16
The agricultural sector contributed 11.2% (DS 2008a p. 141) to the gross domestic product in
2007. Despite its importance for over the half of the Georgian Population, agriculture has not
been in the focus of financial institutions until recently. It is severely undersupplied with
credits especially in the primary production (crops, livestock). In Shida Kartli, the credit
situation improved since then. At the time of the survey (2007-2008), several banks and
NGOs were offering loans to the rural population. However, these loans are often not adapted
to farmer’s needs, because the majority of loans is characterised by short loan durations and
Shida Kartli is one out of 10 regions (including the breakaway regions Abkhazia and South
Ossetia) in Georgia, and lies in the middle-eastern part of the country. It is subdivided into
four districts (raioni). The region’s capital is Gori, a city of 49.500 inhabitants (DS 2008a p.
36, data from census 2002) lies in 70 km distance from Georgia’s capital, Tbilisi. Main
ethnicities in Shida Kartli are Georgians, Ossetians, Azeri, Azerbaijani, Armenian, Russian,
Greeks and Jews. 74% (SDS 2005 p. 33) of rural households use land for agricultural
purposes of which they own 98% (SDS 2005 p. 36). They obtained their plots from the
government after distribution of the state owned land in the 1990s. Apples, grapes, wheat, and
maize are the main crops in Shida Kartli. Out of these crops, farmers produce mainly wine
and flour of which flour is marketed. With respect to livestock, rural households own very
small numbers of cattle, pigs, sheep, and horses, of which they produce smoked meat, sour
milk and cheese (SDS 2005) for home consumption and for the market. Concerning the type
of agriculture, 84% (Heron, Lee & Winter 2001 p. 46) of all Georgian farmers depend on
subsistence farming and consume 73% (Heron, Lee & Winter 2001 p. 46) of the agricultural
products by themselves. Overall educational level is high. Survey results show that in Shida
Kartli 28% of smallholder farmers enjoyed university education, 28% have a specialised
technical secondary education, and 42% have a general secondary education (author’s survey
results). The high level of education in rural areas may be explained by the former Soviet
Union’s education system, which reached out even to remote settlements.
To analyse the rural credit demand in Shida Kartli, a questionnaire was designed. One section
contains a choice exercise to quantify respondents’ relative preferences for certain credit
characteristics. This will allow the calculation of the influence of credit characteristics on the
probability to take up a certain loan. The choice exercise was designed as a stated choice
experiment (e.g., Louviere, Hensher & Swait 2001), which was developed in transport and
marketing and found increasing popularity for the purpose of environmental valuation in
recent years (e.g. Bateman, Carson, Day et al. 2002; Pearce & Özdemiroglu 2002). Conjoint
analysis, a related technique, has been applied by Dufhues (2007) in Vietnam to assess the
factors that impede or support access of rural households in Northern Vietnam to the formal
Prior to the choice task, we asked respondents whether they would prefer to take up a group
loan with joint liability or a loan with individual liability. Following the choice between two
loan types each respondent received four different choice cards depending on whether they
preferred group to individual loans. The choice cards for both loan types show the same
attributes: 1) loan amount, 2) monthly interest rate, 3) collateral, 4) instalment periods, 5)
commission, and 6) loan duration. These attributes were chosen because they describe the
most relevant loan characteristics that a farmer would face in real loan uptake situations at a
financial institution. The use of a hypothetical choice situation allows for an ex-ante
assessment of demand for products that are not yet available on the market or are not yet
available to a target population of consumers. With regard to our choice experiment two
attributes, interest rate and commission, reflect the expected cost of the credit. Each attribute
has four levels except for collateral, which shows only two levels in both loan types. The
variation of attributes or characteristics (levels) was based on information on real loan
characteristics of loans granted by a Georgian NGO and a Georgian bank. The following table
summarises information on attributes and on attribute levels for both of loans with joint
liability and loans with individual liability.
Table 2 Attributes and levels of two loan types
Source: Table created by author. 1 US$ = 1.40 Lari (21 July 2008, National Bank of Georgia).
The experimental design, an orthogonal design, was created in SPSS. For this purpose each
attribute level was given a code number from 1 to 4, and a block variable with four levels was
used to create four option blocks with the aim of generating 32 choice cards. As the choice
cards have to show two choice possibilities A and B, a second set of 32 cards had to be
established. To do this the attribute codes were firstly recoded in SPSS with the Mix & Match
method into different code numbers, and then orthocodes (Hensher, Rose & Greene 2005 p.
132) were generated for all 64 alternatives. The experimental design allows for the estimation
of all attribute main effects and is based on percentage values for the attributes interests and
commission, which represent the credit cost. To make the choice cards more comprehensible
for respondents, percentages were transformed into monetary terms (Georgian Lari) that
appeared on the choice cards used in the interviews. The results of the choice experiment may
be useful for institutions to tailor rural credits and other financial products to the demand of
Following the choice task respondents received several supporting questions on the choice
experiment. The questions involved a subjective assessment of certainty regarding choices,
and an importance rating of credit attributes. These questions help us to better understand how
people made their choices, how they perceived the choice task and to assess the reliability and
In another section of the questionnaire, we asked about general credit demand and past credit
experience. These questions provide useful information on the level of credit demand in the
research region, and how past credit experience and demand are related. Because Kortenbusch
& Cervoneascii analysed credit uptake for, amongst others, the region of Shida Kartli in 2003,
The final section comprises questions with respect to socio-economic and household
characteristics. These should give a general, representative impression on the researched
population in Shida Kartli and serve to analyse their possible influence on credit demand,
choice of credit system and preference of loan attributes.
We used SPSS, LIMDEP and Latent Class Gold Choice for the data analysis. SPSS was used
to analyse the socio-economic data, and LIMDEP and Latent Class Gold Choice to analyse
We employed a three-stage random sampling approach. First, two districts out of four in
Shida Kartli were randomly chosen. A complete list of villages and population figures of the
two districts was then used to randomly choose 16 villages for the survey of 406 rural
households having agricultural areas of approximately 1 ha. The population figure of each of
the 16 villages was weighted in percent with respect to the total number of interviews (406).
The number of interviews to conduct in each village was calculated based on each percentage.
Households were randomly chosen within the villages using a random walk procedure with
intervals between target households determined by total number of inhabitants/number of
interviews in a village. The first number of a banknote number on a randomly drawn Lari
Regarding loan uptake, one-third of respondents took up a loan (30%) and over two-thirds of
them did not have any credit experience (70%). Out of those without credit experience, one-
third stated that they did not need a loan (33%). Despite this, the implementation of a rural
credit system was rated to be very important or important by a great majority of farmers
(77%). Over half of the respondents said that they would very or pretty likely (55%) take up a
loan that would be tailored to their needs. These findings show that overall credit demand is
One central research question concerned the kind of rural credit system farmers prefer in the
region of Shida Kartli. In our sample farmers strongly preferred loans with individual liability
(87%) to loans with group liability (8%) (see Aghion & Morduch 2000; Vigenina & Kritikos
2004), and a small group did not want any rural credit system (5%). As only a small part of
respondents chose loans with joint liability, we did not analyse this further. The single main
reason for the choice of individual loans was distrust amongst villagers. This outcome
corresponds to the findings of Baramidze (2007), who states that farmers do not trust each
other and are not familiar with the advantages of cooperative institutions.
Another question concerned actual past and stated future loan investment of respondents –
both with and without credit experience. Based on our survey, smallholders in Shida Kartli
firstly prefer to invest loans into agriculture and secondly into their houses, followed by
consumption purposes. With respect to agriculture, they would use loans for buying farm
machinery, fertiliser and pesticides; land, good seed material, forage for cattle; and to invest
into bee-keeping. A third important field of investment is trade and transportation. Many
farmers chose a twofold investment strategy: agriculture and a second income source. This
indicates that agriculture alone is not perceived to be sufficient to generate income due to the
small plots and the lack of (export) markets. To invest into two different income generating
domains could be a viable step towards the development of the rural areas in Shida Kartli. As
described above, credit unions are not widespread in Georgia. According to Baramidze (2007
p. 1), the following five aspects are barriers to the development of cooperatives in rural areas
of Georgia: 1) peasants and small-scale farmers are unfamiliar with the benefits of
cooperation; 2) farmers are not well informed about the principles of community resource
management; 3) there is no concrete plan for the development of small farm cooperative
markets in rural communities; 4) villagers distrust each other too much to cooperate; 5) a lack
of financing exists for agricultural development.
Analysis of the choice experiments (CE) with Latent Class Gold Choice Analysis (see
Reunanen & Suikkanen 1999) shows that overall respondents prefer, as expected, lower
interest rates, lower commissions and longer loan durations. The preferred instalment is two
months. With respect to collateral, respondents favour real estates to secure their loans.
Regarding loan size, the surveyed population prefers the minimum loan of 8000 Lari that was
denoted on the choice cards. Interestingly, only few respondents chose the option ‘none of
these’ (none of both loans shown on the choice card), indicating that they received greater
utility from one of the offered loan options than remaining without a loan.
Latent class analysis offers a more differentiated picture of preferences with respect to loan
conditions. Model results suggest that respondents could be grouped into four classes that
differ in the preferences regarding the characteristics of individual loans. The four classes
with different preference structures are described in detail below:
Class 1 (size = 47% of those respondents that preferred individual loans): small loans, relatively low aversion against higher interest rates
Members of class 1 prefer lower interest rates, but this effect is far less influential on choices
than in segments 3 and 4. Loan durations of 30 months (maximum length indicated on the
choice cards) yield the highest utility and didn’t have as much influence on choices as in
groups 3 and 4. The most preferred loan size lies between 8000 and 16000 Lari. Furthermore,
members of class 1 favour putting high values (real estate) as collateral so as to obtain a
suitable loan in return. We have no firm explanation for this. However, farmers could not be
well endowed with moveable assets, or moveable assets could be perceived as a liquid reserve
that can easily be turned into cash in case of emergency. Similar to class 2, members of class
1 use loans mainly for investments in agriculture.
Class 2 (size = 23 %): long loan duration, relatively low aversion against higher interest rates
Similar to class 1, members of class 2 accept higher interest rates (or, in other words, have
lower aversion against higher rates) than segments 3 and 4. Additionally, members of class 2
are willing to pay a commission of 1.5 % of the loan size in order to take up a loan.
Concerning instalments, members of class 2 prefer a period of two months. Furthermore, loan
duration is the main important factor for this group. The preference for long loan durations as
revealed by this group can be traced back to several reasons. One reason lies in past Soviet
times. In particular, older respondents were used to agricultural loans with repayment periods
up to 10 years. The other reason is that the research region is well-known for its apple
production. There is a time lag of a couple of years between planting the trees and harvesting
Class 3 (size = 20 %): lower interest rates, movable assets
Like class 4, class 3 model results show a strong negative effect to an increase in interest
rates. Furthermore, respondents of both groups did not have a positive attitude towards loans.
This may be rooted in previous bad experience: many respondents in class 3 stated that they
were denied a loan when they applied for one previously. Similar to class 4, members of class
3 use loans predominantly for the renovation of houses, which shows that their housing
conditions are on a very low level. With regard to collateral, members of class 3 rely on
movable assets. The preferred instalment is 0.5 months.
Class 4 (size = 10 %): bigger loans
Members of class 4 have the strongest preference for low interest rates. With regard to
collateral, class 4 relies on real estate. The preferred instalment is 2.5 months. In contrast to
all other groups, this segment has a positive preference for a loan size of 24000 Lari. This
means that members of class 4 are willing to take up the biggest loans compared to all groups.
Big loan sizes indicate that farmers are in need of large amounts of money to realise planned
investments – possibly because they almost start from nothing.
The Georgian agricultural sector is currently not able to realise its potential due to manifold
reasons. Farmers depend on subsistence agriculture and do not dispose over sufficient
monetary income. Our empirical study supports these facts revealing that the population in
Shida Kartli predominantly prefers small loan sizes (8000 Lari) and long loan durations.
Small loans indicate the low value of respondents’ assets to secure a loan: small plots, houses
in very bad conditions, and the absence of high value movable assets. Long loan durations are
a sign of respondents’ very low monetary income, which impedes faster loan repayment. With
regard to collateral, half of the sampled population prefers to put real estate as collateral – the
higher value type of two collateral types displayed on the choice cards. Willingness to secure
a loan with the highest collateral available may be a sign of high credit demand and of low
value of the other possible collateral types. Two-thirds of respondents would like to invest in
agricultural production, whereas one-third prefers investments into the renovation of their
houses. High preference of investments in agriculture shows that this sector is in immediate
To improve the agricultural development in Georgia, rural credit, savings and insurance
systems, farm machinery, inputs like fertiliser and pesticides, seed material, agricultural
extension, veterinary services, new marketing chains, and new markets to address the problem
of the Russian trade embargo are needed. In this paper we focus on rural credit systems and
the possibilities of implementation of credit unions (CU) in the central-eastern region Shida
Kartli. The survey results clearly show that farmers prefer the individual lending system and
that they distrust others. Due to the lack of trust and other reasons, they are reluctant to any
cooperative system. Nevertheless CU and input cooperatives could be a possible solution
(Zeller 2003) because farmers as owners and customers of the CU manage their financial
institution. In addition, input cooperatives could provide farmers with more inexpensive
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Authors: Dr. Klaus Glenk Macaulay Institute and Associated Companies Macaulay Drive Craigiebuckler Aberdeen, AB15 8QH United Kingdom E-mail: [email protected]
Johanna Pavliashvili, M.Sc.* Georg-August Universität Göttingen Department of Agricultural Economics and Rural Development Platz der Göttinger Sieben 5 37073 Göttingen Germany E-mail: [email protected] Dr. Adriano Profeta Technische Universität München Lehrstuhl für VWL und Ressourcenökonomik Alte Akademie 14 85350 Freising Germany E-Mail: [email protected] *Corresponding author
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