Livestock Research for Rural Development 24 (2) 2012 Guide for preparation of papers LRRD Newsletter

Citation of this paper

Intra-household access to livestock information and financial services in Kenya

S Mburu, J Njuki and J Kariuki

International Livestock Research Institute (ILRI)
P.O Box Nairobi 00100, Kenya
skmburu@cgiar.org

Abstract

Access to timely and reliable information on livestock production and marketing is important in addressing the production and marketing aspects of the sector alongside access to financial services.  This study analyzes the intra-household disparities in access to information and financial services among rural households in selected districts in Kenya. Specifically, the study compares women’s access to information on livestock production and financial services with that of men.

Results show that informal channels such as farmer to farmer interactions were the key sources of information for livestock production and marketing. More men in male headed households received more training and were exposed to greater and varied topics than women. Men borrowed more from formal credit providers such as banks and co-operatives while women mainly borrowed from their community groups and neighbors. Analysis of determinants of savings by women revealed that women’s age and education positively and significantly increase their probability to save.

Key words: Credit, Markets, Male-headed, Probit, Women


Introduction

Information is an economic resource, and “information poverty” is increasingly being recognized as one of the prime causes of underdevelopment (Chowdury 2006; Romer 1993). Access to information is more likely to be limited for those who are already marginalized by their limited access to other resources, by their location in remote rural areas, or by their gender. The United Nations (UN) considers that after poverty and violence, the third major challenge facing women in developing countries is lack of access to information (Primo 2003).

Why is access to information so important? Households whose access to information is either limited, or very costly, may be unaware of other resources available to them, may fail to allocate their resources efficiently, may forego income-enhancing opportunities, or may bear unnecessarily high levels of risk. This would be the case if, for example, individuals are unaware of several forms of information, including the requirements for obtaining loans with favorable conditions, how to obtain land titles, existing markets for their products, available technologies that could increase their profits, and how to insure themselves against idiosyncratic shocks. In the specific context of financial markets, inadequate access to information can lead producers to choose a suboptimal loan, savings, or insurance strategy despite the options available to them, or to simply abstain from participating in formal financial markets (Stango and Zinman 2008).

Addressing the challenges faced by the livestock sector depends increasingly on an effective and efficient flow of information. This is crucial to addressing the production, economic, environmental, and health aspects, among others, of the sector. Whether on a small or a large scale, women and men producers and processors depend on information related to markets, consumer demands, and disease patterns to help them plan their enterprises. Women and men leverage social capital and collective action (such as women’s groups and neighbors) around livestock activities to strengthen their livelihoods and resilience against possible shocks (for example, market, environmental, and health).

While information is increasingly recognized as an important resource for development, there is little empirical evidence on the extent of information poverty in the rural areas of developing countries (Chowdury  2006). In particular, there is scanty sex disaggregated evidence documenting how women’s access to livestock information and financial services compares to men’s. This study analyzes the intra-household disparities in access to information and financial services among rural households in selected districts in Kenya. Specifically, the study compares women’s access to information on livestock production and financial services with that of men. Women’s information access matters for several reasons. If women’s access to information is more limited or costlier than that of men of similar backgrounds, women may either have less access to economic opportunities or have limited engagement in the optimal use of the resources they control. Rural financial services help households to increase their incomes and build the assets that allow them to mitigate risks, smoothen consumption, plan for the future, increase food consumption and invest in education and other welfare-related needs. The study identifies systematic differences between women and men’s access to information on livestock production and marketing, knowledge and access to financial services and the factors that determine why women save their money.

The role of financial services in promoting agricultural productivity

Promoting efficient, sustainable and widely accessible rural financial systems remains a major development challenge in most sub Saharan African countries. With about 73 percent of Africa’s population living in the rural areas and experiencing a high incidence of rural poverty, improved rural finance is crucial in achieving pro-poor growth and poverty reduction goals. The development of rural financial systems is, however, hampered by the high cost of delivering the services to few, and widely dispersed customers as well as in difficult financial terrain – characterized by high covariant risks, missing markets for risk management instruments and lack of suitable collateral (Onumah 2003).  Rural financial services refer to financial services extended to agricultural and non-agricultural activities in rural areas; these include money deposit/savings, loans, money transfer, safe deposit and insurance.  Demanders and beneficiaries of rural financial services are mainly households, producers, input stockists and suppliers, traders, agro processors and service providers (Kibaara and Mburu 2006).  

Eswaran and Kotwal (1990) argue that having access to credit may reduce household vulnerability to negative shocks by increasing their ability to smooth consumption during difficult times, and that availability of credit also allows households to undertake riskier investments as it will enable them to better deal with the consequences of poorly performing investments.  In addition, Deaton (1992) argues that by reducing the financial risks faced by households in this way, access to financial services may decrease the proportion of low-risk, low-return assets held by households for precautionary purposes and enable them to invest in potentially higher risk but higher return assets, with overall long-term income enhancing impacts.

Ghosh et al (1999) argue that credit is essential in allowing capital investments among producers (such as farmers) who are not able to save, as well as giving households the ability to obtain money in an emergency (Ghosh et al 1999). The availability of credit also increases risk taking with the adoption of new technologies or productivity enhancing investments for poorer households or producers, hence contributing to increases in production and income.  Galor and Zeira (1993) find that access to household credit can have a positive impact on growth through its impact on human capital accumulation, and that this is affected by the initial distribution of wealth; richer families are better able to invest in human capital accumulation leading to increased growth. De Gregorio (1996) also argues that in the context of education, access to credit promotes human capital accumulation, as credit constraints will force students to work, which will reduce the time available for study. Dehejia and Gatti (2002) also find that access to risk-reducing financial services increases investment in schooling.

The level of savings is also an important determinant of overall household welfare.  In their study on the effects of bank expansion into rural India, Burgess and Pande (2005) found an overall reduction in rural poverty, which was also linked to an increase in savings mobilization. The study also found that the increased number of bank branches allowed households to accumulate more capital and have access to longer term investment loans than previously possible. Bank branch openings thus helped increase total per capita output, especially for small scale manufacturing and services.

Rural women’s access to information and financial services

Women and men have different access to markets, infrastructures, and related services. For the most part, women producers face greater constraints than men in accessing different points along agricultural commodity value chains, as well as the related technologies, infrastructures, and information about livestock markets. A study undertaken by the International Food Policy Research Institute (IFPRI) in Ethiopia showed that an increase of 10 kilometers in the distance from the rural village to the closest market town reduces the likelihood of sales of livestock and livestock products and decreases the likelihood that women engage in, and sell processed foods (Dercon and Hoddinott 2005). Women who lack financial capital also have a more difficult time accessing privatized veterinary and extension services that are often essential in helping producers meet market standards. One example of how this could happen comes from a study in Orissa, India (IFAD 2004) where although dairy cooperatives were established in the wives’ names, a committee of men actually managed the group. Along with traditional veterinary and extension services, women’s networks and groups have been proven to be useful “organizational” pathways for passing information on livestock to women. A study on Heifer Project International’s efforts to disseminate improved goat breeds through a village group process in Tanzania showed that social capital influenced people’s ability to access a goat. Their ability to access and manage information was also crucial (De Haan 2001).

In spite of the growing recognition of information and knowledge as critical determinants of economic performance, access to timely, relevant, and affordable information in the rural communities of developing countries remains very limited. The reasons have much to do with lacking, poorly developed, or poorly maintained infrastructure;  rural dwellers’ significantly lower income levels; and the lack of information content that is targeted to local needs (Munyua 2000). For women within these rural communities, these constraints are compounded by socially-constructed gender roles and relationships that further hinder women’s ability, relative to men, to access information. These gender specific norms limit women’s access to information by constraining their access to education, their mobility, and their interaction with members of the opposite sex. They also limit women’s ability to make use of the information that is available to them (Primo 2003).

Rural women’s mobility is often more restricted than men’s, which has consequences on their ability to engage in formal financial activities. In some cases women may also be unable to get away from their domestic responsibilities, or may be unable to afford the costs of travel—even when men in households of the same socioeconomic level can afford travel (Primo 2003). In any case, women’s ability to acquire information will be constrained if, in order to access information, they are required to visit institutions that have inconvenient business hours or are located far from the areas women tend to frequent. Because the options and constraints that women face in developing economies differ from those of men, their saving behavior may also differ. One of the most important purposes of saving in developing economies is for consumption smoothing purposes (Deaton 1990). There may be gender differences in responsiveness to this motive. Men who, by their position in the labor market, are more likely to be beneficiaries of social insurance policies may have less need to fall back on savings for consumption smoothing purposes (World Bank  2002). Financial market conditions also interact with gender norms in influencing an individual’s saving behavior. The extent to which financial institutions provide both women and men access to and control over individual accounts without the spouse’s permission is likely to have a differential impact on men and women’s savings rate. For example, Bangladeshi women are constrained from saving in large sums and in cash since this is likely to attract the attention of male household members who can then take control of those savings. In these circumstances, women are more likely to save only in small quantities (Goetz and Gupta 1996). Women’s access to and control over income can affect saving behavior in other ways. Papanek and Schwede (1988) in a Jakarta study show that women are more likely to participate in arisan, informal saving groups, if they are employed. Further, increases in women’s earnings raise the household’s income and can lead to an increase in saving once basic necessities are met. Equally important, higher relative income improves women’s ability to influence the amount of saving out of household income since their fallback position and thus bargaining power improves. 


Methodology

Data was collected from four districts in Kenya – Kiambu, Kajiado, Tharaka and Meru which were purposively selected, based on three criteria; presence of multiple livestock species, type of production system and access to markets. Since there was no pre-existing sampling frame in any of the study sub-locations, a comprehensive list of all households was compiled with local officials, elders and administrators. The list was then separated into two, those that owned livestock and those that did not. A sample of households from the list of livestock owners was drawn using a table of random numbers.

To analyze gender disparity in access to livestock information within male-headed households, household data from surveys administered to a sample of 181 male-headed rural households was used. A questionnaire with two separate modules; one administered to heads of households and the second one administered to the female spouses in male-headed households was administered. 

Data was analyzed both at household level and compared across men and women within households for different variables of interest including access to livestock information and financial services. Exploratory analysis of the data carried out used descriptive and analytical procedures in SPSS and STATA. The exploratory analysis revealed patterns on access to livestock information and financial services by men and women. Further analysis was carried out using the Probit model to identify the factors that influenced whether women saved their money. The Probit model was based on a dummy dependent variable (1 = women in the household saved money and 0= they did not save) and a number explanatory variables. 

The Probit model took the following form:

                      

Where;

Pr denotes the probability of women saving or not saving (1 or 0)

X is a vector of regressors on the spouse’s and household characteristics.

 is the Cumulative Distribution Function  (CDF) of the standard normal distribution.

β are parameters typically estimated by maximum likelihood. 


Results

Household characteristics

Of the 243 households interviewed, 181 (74.5percent) were male-headed and 62 (25.5 percent) female-headed.  Male heads of households were more educated than female heads. The level of education is often used as an indicator of economic development, whereby households with more educated heads are more likely to be wealthier than households with less educated heads (Morrison and Jutting   2005). The average age of heads of households was 54 years with female heads of households being older (58 years) than male heads of households (52 years).

Table 1: Household head characteristics for the sampled households

Characteristic

 

Male-headed

Female-headed

Overall

Age

 (in years)

52

58

54

Household size

(numbers)

6

5

6

Education

No formal and illiterate

5

25.8

10.3

 

No formal but literate

5

11.3

6.6

 

Primary

45.9

46.8

46.1

 

Secondary

31.5

14.5

27.2

 

College

9.4

1.6

7.4

 

University

3.3

0

2.5

For the purpose of this study, only the male-headed households were considered to capture the intra-household differences between men and women’s access to livestock information and financial services. Data from the 181 male-headed households was used in four districts. Kiambu district had the highest number of male-headed households interviewed (85) while Kajiado, Meru and Tharaka districts had an equal number households (32). Proportionately male-headed households represented 69.1 percent, 76.2 percent, 82.1 percent and 82.1 percent of all households in Kiambu, Kajiado, Meru and Tharaka Districts respectively.

Sources of information on livestock production and marketing

The most common source of information on livestock production and marketing was other farmers (ranging from 32 - 67.2 percent). Women used this farmer to farmer information exchange more than the men. This was followed by Co-operatives / group / associations. Specifically, production and marketing information for cattle was mainly exchanged informally between farmers for both men and women. Information from government sources was quite low for both men and women and in some few cases the farmers accessed information during open days. These findings concur with (Brockhaus 1996) study which indicated that only 15 percent of women in Southern Jordan were found to have access to state extension services. A higher proportion of women obtained marketing information from other farmers compared to production information.

Table 2: Main sources of information for cattle production and marketing for men and women

Livestock

Gender

Other farmers

Cooperative / Group/Association

Extension services

Radio

NGOs convening

Govt. Institutes

Open days

Cattle marketing

Women

58.4

15.2

0

7.2

3.2

6.4

1.6

Men

50.4

14.8

6.7

5.9

5.2

3

1.5

Cattle production

Women

37.6

22.1

0

11.4

10.7

8.1

3.4

Men

32.2

16.9

0

14.1

6.2

5.1

4.5

Similarly, the main source of information for sheep/goats (shoats) production and marketing was from other farmers for both men and women. There were no distinct differences in information sources between men and women.

Table 3: Main sources of information for shoats production and marketing for men and women

Livestock

Gender

Other farmers

Cooperative / Group/Association

Extension services

Radio

NGOs convening

Govt. Institutes

Shoat marketing information

Women

64.9

16.5

0

8.2

2.1

4.1

Men

53.3

18.5

3.3

5.4

3.3

4.3

Shoat production  information

Women

57.4

14.9

0

10.9

7.9

5.0

Men

51

12.2

1

10.2

4.1

5.1

For chicken production, the results also indicate that farmers obtained most of the production and marketing information from the other farmers. The second most important source of information on chicken production and marketing was the radio. This is contrary to information on cattle, sheep and goat production, where the second most common source of information, after other farmers was from members in groups and co-operatives.

Table 4: Main sources of information for chicken production and marketing for men and women

Livestock

Gender

Other farmers

Cooperative / Group/Association

Radio

NGOs convening

Govt. Institutes

Chicken marketing

Women

67.2

10.4

9.7

2.2

3

Men

63.4

9.8

5.7

1.6

3.3

Chicken production

Women

51.6

10.3

18.1

4.5

3.9

Men

46.9

7.6

12.4

5.5

4.8

Training on livestock production and marketing

About 41.4 percent of men and 36.7 percent of women reported to have received training on livestock production and marketing in the last 5 years. Men in male headed households received more training and were exposed to a greater variety of training topics and venues than women. Women, on the other hand, had access to a larger variety of extension agents than the men, and were trained mainly in general livestock management, while men were trained in multiple technical subjects such as livestock health, breeding and marketing. In looking at extension services and information access, studies have shown that it is difficult to disentangle the effects of gender and income levels. In Zambia, extension reaches only 25% of farmers, and it fails to reach the poorest farmers (Alwang and Siegel 1994). To the extent that these are women, the authors concluded that extension was not reaching female farmers.  Hirschmann and Vaughan (1983) observe that the bias of extension was against poor households, not against women in particular. They found that those farmers who had enough land to grow maize in pure stands had adequate labor and capital, and use inputs were the most likely to receive assistance from extension agents. Because women are underrepresented in this group, they were often less likely to obtain assistance.

Some efforts to reach women through extension services have been successful. In Zimbabwe, emphasis has been placed on having extension work with groups, and indeed, women there constitute the majority membership in such groups (Muchena 1994). These groups provide extension services and also make it easier for the women to gain access to credit. Yet, women’s participation is still constrained by a variety of practices, including the expectation that a woman’s husband must approve any legal transaction in which she is involved. Utilization of information may depend on education and literacy levels. Lack of education and higher levels of illiteracy among women farmers may be an additional constraint to women receiving adequate information (Baser 1988).

Table 5: Percentage of men and women who received trainings on agricultural practices

Training

Women

Men

Livestock management

70.5

65.2

Livestock health

9.8

15.9

Livestock breeding

4.5

9.1

Processing

9.8

0.8

Marketing

0

6.1

Crop production

3.6

1.5

Terracing

0

0.8

Bee keeping

0.9

0.8

Total

100

100

Only men were trained in marketing. More women than men were trained in general livestock management, processing of products and crop production. Conversely, more men than women were trained in livestock health and livestock breeding, the more technical subjects on livestock. Studies have shown that compared to women, men have easier access to technology and training, mainly due to their strong position as head of the household and greater access to off-farm mobility ( FAO  2000). In most countries, research and planning activities in the livestock sector, such as breeding, handling, feeding and health care, are largely dominated by men. Official livestock services are often controlled by men and extension personnel are primarily men who are not accustomed or trained to teach technical subjects to women. In order to increase the benefits from training, services should be oriented towards those household members which execute these tasks. For example, in societies where sick animals are mainly treated by women, they have knowledge of the symptoms and cures for animal diseases. But with no access to training, progress in best practices and appropriate herding to reduce diseases is difficult. Therefore, where extension services are dominated by men and where women have little access to training due to socio-culturally-defined gender roles, men need to be persuaded to see the relevance and the benefit of training women. Only through a carefully planned gender approach can livestock production goals and successful training of women and men be achieved (FAO 2000).

Trainings for both men and women were mostly held within the village but outside their homes. Very few men and women were trained in their homes. Increasing access to training by women will require holding training in venues that do not constrain women. The variation in number of men and women trained from home could be because most extension officers are men and are more comfortable talking to men (Shicai and Jie 2009). Gendered disparities in access to training could be overcome if gender roles, relations and ideologies were studied before and during interventions so that the polarized attitudes and values of men and women are addressed in a way that more women could get involved (Kristjanson et al 2010).

Access to financial services

About 33 percent of households had obtained cash credit in the five years prior to the survey. For both men and women, groups were the main source of credit. More women received credit from groups and neighbours than men. Men borrowed more from formal credit providers, such as banks and co-operative societies, than women. Although more women (31.5 percent) than men (28.7 percent) had received credit, on average, men obtained over 3 times as much credit (Ksh 60,064 equivalent to USD 784.74) as women (Ksh 14,289 equivalent to USD 186.69).

Table 6: Percentage of men and women accessing credit from different sources

Source of credit

Women

Men

Group

52.6

42.6

Bank

22.8

24.6

Microfinance

10.5

14.8

Co-operative society

1.8

9.8

Neighbour / friend

10.5

4.9

Government  corporation

1.8

1.6

The finding that more women than men in male-headed households obtained credit from groups and neighbours, whereas more men than women obtained credit from financial service providers supports  (Bhatt  1995) observation that men tend to benefit more than women from formal organizations. In this case, men are able to borrow large amounts of money from formal financial service providers. The fact that women are also resource (Galab and Rao 2003; Shicai and Jie 2009) and rights (Moser 2006) poorer than men explains the gender gap in access to formal financial services which often require collateral. This gap could be overcome if women were provided financial services that are flexible and have consideration for women’s constrained access to collateral.   Women have developed their small credit/loan systems in most developing countries.  Credit funds and revolving savings of women's groups are common where the members of the group save a certain amount of money which is then granted to one of the women as a loan. Normally no interest is paid, and the social control guarantees that loans are repaid. Other credit systems consist of loans of animals or even milk for processing. Generally, these systems only function at the village level, often between neighbours, where social control can be assured (FAO 2000).

Men used most of their credit on purchase of assets whereas women spent it on school fees. About 19 percent of both men and women used credit obtained to purchase livestock. Considerably more women (15.8 percent) spent credit on food purchases than men (1.6 percent). More than twice the number of women than men borrowed money for construction.

Table 7: Different uses of credit by men and women in male headed households

Use of credit

Women

Men

Crop production

7

4.9

Livestock purchase

19.3

19.7

Asset purchase

14

41

School Fees

24.6

19.7

Medical Bills

1.8

0

Purchase of food

15.8

1.6

Business

10.5

9.8

Construction

3.5

1.6

Farm inputs

1.8

1.6

Group activities

1.8

0

Gender differences in savings

Over 50 percent of both male and female headed households saved money. More men (63.2 percent) than women (47 percent) saved money through formal banks. More women than men invested in saving groups and livestock, both of which represent the informal savings mechanisms.  These findings confirm the study by  (Ellis  et al 2010) that found that in Kenya men are much more likely to use formal financial services than women (32 percent of men, compared with 19 percent of women), and women are more likely to use semi-formal services than men (63 percent of women compared with 58 percent of men).

Table 8: Percentage of men and women saving money in Kenya

Where save

Women

Men

Bank account

47

63.2

Savings group

33

24.2

Kept in compound

6

7.4

Investment in livestock

14

5.3

Total

100

100

Probity Analysis: Factors that determine whether women save their money

To identify the factors that determine whether women save or do not save, a binary probit analysis was carried out (see table 9). The dependent variable was a binary form (1= women have a way of saving, 0=women do not save).

Table 9: Factors that determine whether women save their money

women save (1=yes, 0=no)

Coefficient

z

P>z

Age of spouse

0.02

2.26

0.024

primary education(1=yes)

0.625

2.05

0.04

Above primary (1=yes)

0.917

2.48

0.013

Belong to group (1=yes)

-0.024

-0.5

0.617

Other assets

-0.008

-1.53

0.126

TLU livestock (women)

0.02

0.09

0.925

dist1=Kajiado

1.019

2.7

0.007

dist3=Meru

-0.388

-1.31

0.191

dist4=Tharaka

-0.312

-0.91

0.365

Constant

-1.362

-2.2

0.028

Number of observations

172

 

 

LR chi2(9)

37.03

 

 

Prob > chi2

0.0001

 

 

Pseudo R2

0.56

 

 

Log likelihood = -99.960

 

 

Older women were more likely to save money than younger women.  An age increase of one per cent increased the probability that women would save by 0.02 percent. Older women may have more decision making authority at household level or may have more sources of income that enables them to save.  Similar findings were reported by Kalyanwala et al (2006) study in India that looked at saving patterns among adolescent and young women.  Results showed that in general, older, urban and better-educated young females displayed greater control and awareness of their own accounts than younger women participants. The older women were more likely to be familiar with banking procedures, to have family support for controlling their accounts and to have specific goals for which they proposed to use their savings. As suggested by Browning (2000), the fact that women live longer than men could explain women’s higher propensity to save for old age. The study found that the need to save for retirement is also corroborated by the positive and diminishing effect of age on the probability of saving. The estimated marginal effect of age implied that a 50-year-old individual is 9 percent more likely to save than a 40-year old.

Education was also an important determinant of savings. The more educated women were, the higher the probability to save. Education empowers women to secure jobs or engage in high income generating activities enabling them to save their money. The results show that women with primary or above primary level education were more likely to save compared to women with no education.  Increased literacy skills can give women confidence and knowledge of how to engage with formal financial institutions. Browning (2000) found that an extra year of schooling increases the probability of saving by 0.4 percent and women from households in the highest income quartile are 3 percent more likely to save. The study further showed that education affects savings performance by influencing the level of income and the options for asset accumulation available to the individual.

The women in Kajiado were more likely to save money compared to women in Kiambu while probability for women in Meru and Tharaka to save compared to Kiambu was lower although not significant. These patterns may be related to access to urban centers with both Kiambu and Kajiado being more urbanized with higher densities of banking services compared to Meru and Tharaka. Rosenzweig (2001) shows that the proximity of formal financial institutions increases financial savings and crowds out informal arrangements. Geographic distance to the nearest bank, or the density of branches relative to the population, can provide a first crude indication of geographic access or lack of physical barriers to access to financial services (Beck et al 2011).

Livestock and other assets owned by the women from the sample were found to be insignificant in determining whether women have a way of saving either through formal or informal mechanisms.  This was surprising because ownership of assets has often been associated with women’s empowerment.  Asset ownership influences the “fallback” position of each spouse in negotiations over key household and family decisions and hence the exit options available to each (Quisumbing and Hallman 2006). In Colombia, Friedemann-Sanchez (2006) found that women use property and social assets to negotiate for the right to work, control their own income, move freely, and live without spousal violence. Women’s asset ownership may increase the anthropometric status of children (Duflo 2000), the incidence of prenatal care and children’s schooling (Doss 2006b); it may also reduce domestic violence (Srinivasan and Bedi 2007). Because of these social welfare effects, it is important to have individual level information on assets in order to find ways to assist women’s acquisition of and control over key assets.


Conclusions


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Received 12 January 2012; Accepted 27 January 2012; Published 7 February 2012

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