HOUSEHOLD PARTICIPATION IN COMMUNITY FOREST ASSOCIATIONS: Evidence from Kakamega County in Kenya

Abstract

Forest management rules depend crucially on who attends the meetings where critical decisions on these rules are taken. In this study we assess the determinants of participation in Community Forest Association meetings. Primary data for our analysis was drawn from a survey of communities in Kakamega Forest, Kenya. First we investigate the determinants influencing decision making for households attending meetings. Second, the factors that determine whether households attend community meetings are investigated. The analysis shows that household’s ability to influence decisions and the levels of education are important determinants. Local elite and often wealthy households are found to attend and dominate the decision making processes.

JEL Code:

Key Words: Devolution; Decision making; Community forestry; Participation

1.0 Introduction

Forest decentralization programs have rapidly spread in developing countries in the last

twenty years (Agrawal, Chhatre and Hardin 2008). Support for the principle is derived

from grounds of economic efficiency, public accountability, community and individual

empowerment; as well as allocative efficiency (World Bank 2009, Coleman, 2011)).

These reforms are designed to recognize forest and land rights and the diversity of local

people eking a living from these forests.. The institutional arrangements for forest

management are thus shifting from central management by the state to management

involving local communities. Consequently, promulgating laws to recognize local

ownership over land and natural resources based on historical claims is taking place

(Agrawal, Chhatre and Hardin 2008). CBNRM (community based natural resource

management) has been considered a new initiative by many governments in response to

the inefficiency of top-down forest management of state forestry. Decentralization and

devolution of management of natural resources and forests is a particular focus of

national governments in developing countries (Springate-Baginski & Blaikie, 2007).

The nature of the decentralization or devolution approaches, however, differs from region

to region. The changes in approaches to natural resources management are part of the

wider democratization and decentralization policies. Part of the rationalization is based

on the view that unlike central government officials, locals are more familiar with their

environment and user needs and hence will be more easily accountable, (Agwaral and

Ribot, 1999).

The reform process in Kenya is still in its infancy. The Forest Act 2005, recognizes the

central role of forests in the livelihoods of the rural communities and proposes measures

to enhance community participation in forest conservation as follows:

· Encouraging sustainable use of forest resources by communities;

· Supporting the establishment of community forests through which communities

can be able to participate int eh conservation and management of forests;

· Protecting the traditional interests of local communities customarily resident

within and around forests.

Devolution is expected to increase local participation. In the Kenya, that is the focus of

our study devolution involved enabling public participation in forestry management by

the government that gave responsibility and some benefits in return for their

participation. Devolution as a strategy aims at involving people or communities in forest

management for achieving both development and conservation objectives. As a condition

for ceding power the government expects local communities to form community forest

associations (CFAs) to manage the resources. The CFAs are also expected to formulate

strategic plans for managing the forests. The Kenya Forest Service (KFS) seeks the

cooperation of local people living around the forest for forest regeneration and protection.

It is important to observe that the relationship between the KFS and local people has

historically been one of mistrust. The former forest department invited people to engage

in forest protection

Decentralization reforms in Kenya are still in their infancy. In light of the foregoing and

despite the prominent role those CFAs are expected to play in the devolution process, we

know relatively little about the factors that drive participation in these community forest

associations. The country is still struggling in the search for institutional arrangements

and structures that will deliver benefits to local communities and ensure sustainability.

Such information is needed to enhance their efficiency and effectiveness. The

government has taken it for granted that people will participate in CFAs ignoring

constraints to group formation.

We contribute to the literature on the determinants of household participation by

examining factors that explain various levels of participation in CFA institutions. In

particular we look at the levels of participation in meetings, membership in committees

and influence on decisions taken at these meetings.

There are many studies on the impacts of forest devolution in many countries (Colfer et

al., 2008; Jumbe & Angelsen, 2006; Edmunds &Wollenberg, 2003; Agrawal & Ostrom,

2001). Most of these have focused mainly on outcomes of devolution such as changes in

forest cover and condition, impact on household livelihoods. Who participates in

community forest associations and the motivation are missing in the current literature on

decentralization.

In this study, we investigate two issues: First, we examine the level of transaction costs

households faced in participating in community forestry, and to gauge their effects on

community forestry initiatives. One of the reasons for lack of people’s participation is

that poor households have a high opportunity cost of participation as the time spent on

participation could be used as labour for cash and off farm income. Indeed high

transaction costs may also discourage the participation of poorer segments of forest

communities in the decision making of forest protection communities, thereby allowing

the richer segments to adopt rules biased towards their own interests.

Secondly, we determine the distribution of community forestry transaction costs across

households with diverse socio-economic characteristics and gauge their effects on

households participating in community forestry initiatives.

The rest of the paper is organized as follows: In the next section we review the history of

decentralized forest reforms in Kenya. In section 3 we draw from the existing literature

and derive the conceptual framework. Section 4 examines the data and provides summary

statistics of the variables used. In section 5, we report our empirical results and discuss

these findings and in section 6 we conclude and draw policy recommendations.

2. Forest Decentralization trends and current status in Kakamega

Kakamega forest covering 17838 ha in size is a tropical moist forest, rich in biodiversity

and surrounded by densely populated areas. Most of the population is heavily dependent

on the forest for their livelihoods and other cultural practices. The Forest Department

(now Kenya Forest Service) and the Kenya Wildlife Service (KWS) are the key

authorities mandated to manage the forest. Even though Kenya’s history of centralized

governance regime only changed in 2005, Kakamega forest has been the focus of

community collaborative management since the mid 1990s.

Prior to decentralization, forest conservation and management in Kenya was guided by

the forest policy of 1957, which was revised in 1968, and then again in 1994. The main

legislation is the Forest Act Cap 385 of 1962 that was revised in 1982 and 1992. The act

was drafted in support of the 1957 policy and covered a broad range of activities from

gazettement to degazettement of forests and nature reserves, licensing of use, prohibitions

and imposition of penalties. The Forest department managed the forests without

consultation outside the relevant government ministry. Conflicts increased in the late

1980s between communities who needed fuelwood from neighbouring forests, and the

forest department (Ongugo and Njuguna 2004). Subsidiary regulations cover the rights

of adjacent communities to utilize specified resources in specific ways.

Under control of the Forest Department (FD), several management programmes existed.

These included the ‘Shamba System’ in which farmers were allowed to cultivate on clear

cut land in return for tending saplings planted by the department. This system was

dropped in the 1980s due to widespread abuse of the programme by local farmers. A tea

belt was planted at the edges of the forest to act as buffer against further forest

destruction. The first attempt aimed at community inclusion under a pilot program was

made in 1990 and 1992 supported by the Kenya Indigenous Forest Conservation Project

of the Overseas Development Association (ODA). Under the plan, Kakamega Forest was

divided into four zones: protected zone, rehabilitation zone, subsistence zone and

plantation zone.

Under the new law the community is expected to be institutionalized in form of

Community Forest Associations (CFAs) registered under the Societies’ Act. This way the

community can be able to apply to KFS for management of a forest which will be done

with the help of a management plan and an agreement signed by all concerned parties.

The community is thus potentially a significant beneficiary under the new act especially

for extractive purposes.

The New Forest Act of 2005 saw the formation of the Kenya Forest Service (KFS), a

semi autonomous government agency with representation from various government

ministries. Under the Act, the KFS is expected to devolve powers to the private sector

and to forest conservation committees and community forest associations (CFAs).

Community participation is achieved primarily through CFAs, and integrated

management of forests are central principles motivating the new policy (Ongugo, et al.,

2007).

There is still controversy over the concept of forest devolution in Kenya. In reality,

communities have just been assigned the responsibility of guarding forests and in turn

they get some opportunity to harvest non timber forest products. This type of

management is actually not devolution because communities do not have control over the

forestry land.

3. Conceptual Framework of household participation

We postulate that household decisions on participation in CFA meetings depend on the

expected present and future values from the devolution. In particular a household’s

decision to attend a CFA meeting depends on the expected net present value of such

participation. This in turn depends on two factors: first are the expected returns on

participating in the meeting and second, the costs of participation which can be viewed in

terms of the opportunity cost of attendance.

Returns to participation

Returns on participation are of two types: expected present and future forest value, and

wage income by engaging in forest activities such as singling and plantations etc. People

attend meetings in order to acquire information about harvesting, set rules for grazing etc.

Poor households are more likely to depend on forests for their daily lives and are known

to collect forest products for their livelihoods. Dependency on the forests for daily

livelihood is an important factor for a household to participate in the CFA. Households’

ability to influence decisions is likely to depend on the household’s bargaining power and

membership in other village activities. Bargaining power is likely to depend on the

relative strength of the household’s characteristics such as education, wealth, land size

holding, age and gender. The benefits of participating not only depend on the value of

influencing a decision but also whether the household’s interests would be represented by

others.

Costs of participation

The opportunity cost of participation will very likely differ across households and is

largely influenced by employment opportunities in agricultural activities and the

availability of off farm activities. When the opportunity costs of a household increase due

to the availability of both agricultural and non agricultural non forest activities, the

household is less inclined to participate in CFA meetings. Wealthier households with

more land, education and livestock may not participate in the meetings unless they have a

specific interest in forests. The probability of being engaged in off farm income activities

depends on the skills acquired through education.

Model

Household decisions on participation in CFA activities depend on the expected present

and future values from the devolution. A household j will participate in CFA meetings if

the expected utility from attending CFA meetingsajEU is greater than the expected utility

from not attending meetingsnajEU . i.e. if

naj

aj EUEU > . (1)

The expected utility from the attendance of meetings ajEU is determined by the

household’s ability to influence decisions in the meetings ( jI ) and other household

characteristics ( jX ), as well as community characteristics (G ) and other external factors

such as the forest management regime (FS):

( , , , )aj j jEU f I X G FS= (2)

The households’ ability to influence decisions depends on whether the household is a

member of the management committee ( jE ) as well as on the other socio economic

characteristics, for instance the gender, wealth status, education, age of the household

head) and other factors such as whether the overall forest management regime is by the

church or the local council. Membership in the local CFA committee itself will also

depend on household characteristics, community factors and others. Consequently, we

can specify the following equations:

( , , , )j j jI g E X G FS= (3)

( , , )j jE k X G FS= (4)

The expected utility from not attending CFA meetings is the basically the households’

opportunity cost. This is also depends on household, community and other external

factors:

( , ).naj jEU k X G FS= (5)

Thus the probability that a household participates in a CFA meeting can be written as:

{ { }Pr { } ( , , , ) ( , ) 0a naj j j j job EU EU prob f I X G FS k X G FS> = - > (6)

Econometric Specification

There are two levels of household participation in the CFA meetings that are used for

estimation. First, is (EFFECT) a dummy variable which takes a value of 1 if the

household contributed to the discussions at the meeting or 0 otherwise. Since both of

these dependent variables are binary, we assume the following Probit specification:

Second, we have attendance of meetings (ATTEND), which a dummy variable which

takes a value of 1 if a household attended meetings in the past month and 0 otherwise.

1 2 3 4Pr( 1) ( )jEFFECT F X G FSb b b b= = + + + (8a)

Similarly, the EFFECT equation can be specified as another Probit as follows:

1 2 3 4 5ˆPr( 1) ( )jATTEND F P X G FSa a a a a= = + + + + (8b)

Where P̂ are the predicted values from the estimation of equation (8a) on effect.

In the first stage we estimate the determinants of household’s ability to influence

decisions using household and individual characteristics and FS interaction. Thus, in the

second stage we estimate the determinants of household’s attendance of meetings,

assumed to be dependent on household characteristics, community characteristics, as well

as the Forest Service-community interaction. We hypothesize that a household’s

expected influence decisions in the meetings is one of the key factors that determine

household attendance of meetings. Our formulation allows us to make a distinction

between effects of household, community and external characteristics ( 3 4 5, ,a a a ) on

participation in meetings and the indirect effects of these variables ( 2 3 4, ,b b b ).

4.0 DATA AND DESCRPTIVE ANALYSIS

The data for this study was collected from communities around Kakamega forest. The

choice of Kakamega forest is justified on the following ground. Devolution of powers to

community has been relatively long having been started in the early 1990s, compared to

other regions in Kenya. In spite of the early start anecdotal evidence suggests that

Kakamega still lags in the formation of CFAs. Based on that evidence Kakamega is

selected for an in-depth study in order to investigate factors likely to influence

participation in community forest management.

A random sample of 318 households was interviewed using a detailed semi-structured

questionnaire. We have collected detailed information on household participation in CFA

meetings where crucial decisions are discussed and final resolutions made. Some of the

issues included forest protection, decisions on use of community labour on forest work

etc., formulation of rules for forest access and use. The issues on which the resolutions

were made were confirmed by minutes of the meetings taken.

Following Agarwal (2001), household participation in the meetings was classified into

four categories: (a) nominal (b) passive (c) active and (d) interactive. Nominal

participation implies that the participant was present when a decision was made. Passive

indicates that the member merely attended and was informed about the decisions but did

not speak up in the meetings. Active participation means a participant expressed an

opinion in the meetings whether or not the opinion was sought. Interactive participation

indicates that the participants felt that she influenced the resolutions taken at the

meetings. Table 1 presents the responses of the households on their levels of participation

in their meetings.

Table 1: Household Levels of Participation in CFA Meetings

Participation Level

Forest meetings in the last 3 months

Attended Meetings

256

(81%) Expressed Opinion

129

(41%)

Influenced Opinion 57 (18%) Source: Field data

About 256 households (81%) had attended the meetings in the last three months on forest

management. Among the households that attended the meetings about 41 percent

expressed an opinion in the meetings regarding forest management. A small proportion,

however, 18 percent reported having made contribution that influenced the resolutions

passed.

We focus on two levels of participation for our regression analysis: passive (attendance

of meetings) and interactive (having effect). From the survey a set of variables was

selected for inclusion in the econometric model. These variables are drawn from theory

and the literature. The variables used in the analysis are summarized in Table 2, which

defines the explanatory variables incorporated in the econometric analysis.

On the farm characteristics, the average farm size in Kakamega is 2.2 acres. The average

distance to the nearest forest edge is 1.5 km. With regards to institutional attributes, 73

percent of households belong to social groups while 52 percent participate in community

forest management through CFAs.

Table 2: Definitions for Summary Statistics for the Explanatory Variables

Variable Definition Mean Std. Deviation Min Max

Effect Dummy variable=1 if household 0.73 0.35

0 1

feels that it influenced decision

in recent CFA meeting ,=0

Otherwise

Years of Years of Schooling of household Head 9 3.9

1 16

Education

Membership

Membership in CFA (1 if yes, 0 otherwise)

0.52 0.50

0 1

Land Size Size of land owned 2.2 0.5

0.2 32

in Acres.

Sex of head Dummy variable=1 if household 0.63 0.24

0 1 Household head is a male, =0 otherwise

Age Household head’s age 48 3.4

24 81

(Years)

Value of Assets Total value of HH assets 22026 61038

5040 234,000 Female ratio Female-Male ratio (Nr. of

household female members 0.56 0.43

0 1

divided by males.

Road

Dummy variable=1 if village linked to motorable 0.23 0.43

0 1

road

Distance to Distance to nearest Nearest mkt market

3.6 3.8

0.02 16

Labour Units of labour

2.15 0.76

0.01 6.8

in household

Predicted

Predicted probability of influence in recent CFA

Effect meetings

Social groups Membership in social groups 0.73 0.44

0 1

The household characteristics show that the average age of the household heads is 48

years, with the average number of schooling years being 9. The low education level of

the household head explains the inability to secure more remunerative employment

opportunities elsewhere, thereby resorting to farming activities. Education increases

household’s off-farm employment opportunities. Furthermore, highly educated members

of the household tend to look for greener pastures in off-farm activities. This is because

of the traditional nature of farming activities within the region which many people view

as not competitively rewarding compared to non-farming activities. The average

household size measured in this survey is 5 members. Of the households interviewed 73

percent were male headed.

Discussion on Transaction costs

Questions on transaction costs focused on time household members spent participating in

various community forestry activities (attending village forestry meetings, monitoring

others’ forest resource use and management practices, and attending conflict resolution

meetings). Data was also collected on the amount of time household members spent in

collecting, processing and transporting a unit of forest products from Community Forests

(CFs) to house, rural hourly wages in agriculture, the costs and economic life of farm

implements, etc.

Based on the data, estimates of resource appropriation costs, transaction costs and value

of benefits households derived from community forests were computed. Using costs and

benefits thus computed, net benefits from community forestry were calculated for

households with different socio-economic characteristics and an evaluation made on their

effects on community forestry initiatives in the study area. Open-ended discussions with

groups of forest users, CFA and KFS officials provided additional information (i.e. forest

users’ patterns of resource extraction and management, village level decision-making

processes for community forestry, the nature of transaction costs faced in community

forestry and institutional and legal constraints). `

Households averaged 5 persons, with the majority of respondents claiming to have been

born in the areas where they resided, or being long-standing migrants in them. Almost all

respondents were heads of households with a mean age of 48 (males) and 36 (females),

with close to half belonging to ethnic groups that were indigenous to the study areas. The

majority of respondents also had basic (primary) and secondary education.

Household Asset Ownership

Majority of households had at their disposal land holdings above 2 acres, with those with

less, accessing land through land rental and lease markets, or as squatters. Customary

tenure was the dominant land tenure system. On average, household wealth held in

livestock, farm implements and other household use/consumer-oriented assets amounted

to (US$ 53.41), (US $30) and (US $147) respectively.

The main sources of income for most members of the community revolves around formal

employment and remittances, agricultural and livestock production, forest based activities

and some small scale informal business activities. Fuel wood, grazing, poles and thatch

grasses are prioritized over other products such as medicinal plants, charcoal, ropes, and

honey were found to be important products for the communities. Forest products were

sold in nearby urban areas of Kisumu and Kakamega

Households’ Farm and Non-farm activities

All households diversified their productive activities by engaging in both farm (crop

cultivation and livestock rearing) and non-farm (trading/shop keeping, craftwork, brick-

making, the dispensing of herbal medicines, brewing, sales of agricultural and non-

agricultural labour within and outside the community) activities.

Firewood and water were the key forest products households procured from community

forests, although medicinal/herbal plants, edible plants and livestock feeds were the other

important forest products. Households’ needs for timber were hardly met from

community forests, with the harvesting of this product facing severe quantity and

maturity restrictions, or outright bans.

Economic Importance of Community Forests to Households

Households visited community forests more often to extract water and firewood

resources. Land-constrained households were more likely to visit community forests to

procure food and firewood products and to encroach on the forests by engaging in

charcoal burning and crop cultivation. On the other hand, households rich in farm

implements benefited more from community forests as they could more effectively

extract threshold levels of forestry resources, face less resource extraction times, and visit

the forest more frequently.

Money Values of Community Forest Products to Households

Households on average extracted (US$ 0.42) and (US$ 1.32) worth of water and

firewood a week based on local prices. These values did not greatly differ among

households with different socio-economic characteristics. Especially for firewood, these

low values suggested that households faced few economic incentives (of a monetary

kind) to not use their community forest resources sustainably.

Resource Appropriation Costs

On average households expended approximately (US$ 0.31) in cost of tools weekly to

extract forest resources. Overall, poor (rich) households faced lower (higher) tools

appropriation costs as they held few (more) productive assets or tools. Also, a strong

relation existed between a household’s wealth position and resource appropriation costs,

which suggested that while the harvesting of key forest resources (i.e. water and

firewood) may have required the use of simple tools, resource collecting, processing and

transportation was time-intensive for some economically marginal households.

Rule Design and Households’ Members’ Participation in Community Forestry

Respondents in their majorities considered oversight functions in forests as the

responsibility of the CFA, even as they understood community forestry rules to emanate

from cooperative and participatory community governance institutions, such as

Management Council (MCs). The majority of respondents were also satisfied with the

way rules were designed, with complaints revolving around the domination of

deliberations by local leaders/elites and forestry officials, and discriminative practices

against women and disabled persons.

The majority of respondents claimed that they and/or members of their households

actively participated in community forestry activities. For those reporting non-

participation, corruption and illegal practices in forests (sanctioned by forestry officials

and politicians) such as timber felling, charcoal burning, crop cultivation and the

earmarking of degraded forests for CFA- all dampened their enthusiasm for community

forestry. Also, disproportionately more high income households participated in the

different community forestry activities, while disproportionately more poor households

were likely to commit less time to community forestry activities.

Transaction and Resource Appropriation Costs and Household Wealth

For those households that had members who actually participated in community forestry

activities, almost 90 per cent faced weekly transaction costs in community forestry, not

exceeding (US$ 1.36). Richer households faced higher transaction costs in community

forestry compared to middle wealth and poor households as richer households had

members who spent more time in community forestry. On the other hand, poor

households faced higher appropriation costs because of their lower asset bases (especially

productive tools), whose use values were quickly amortized over time.

Value of Benefits Households Accrue from Community Forests.

Richer households benefited more from the extraction of the key resources (water and

firewood) from community forests compared to their middle income and poor

counterparts. The possession of threshold levels of tools and the greater frequency with

which richer households extracted community forest products explained why richer

households benefited more from community forests.

Transaction Costs as a share of Appropriation Costs and Total Benefits

Transaction costs as a share of total resource appropriation costs were higher for rich and

middle income households than for poor households by a factor of three implying that

when transaction costs in community forestry were evaluated as a share of the costs of

forests resources extraction, wealthier households share a heavier burden of these costs

than their poorer counterparts. On the other hand, transaction costs as a share of total

value of benefits revealed no discernable patterns across different households. This

implied that when transaction costs in community forestry are factored into the benefits

households derived from their community forests, all households obtained the same

benefits–given the costs incurred in community forestry.

Household Net Benefits from Community Forestry

Overall, all households suffered zero or negative net benefits from community forestry

initiatives in the study area. The implication is that when transaction costs of community

forestry are evaluated in terms of their benefits to households, an incentive existed for

households to engage in greater resource appropriations than in those activities that

ensured sustainable resource use (i.e. those activities that underpin CFA).

5.0 Empirical Results and Discussion

Influence/Effect Decisions Equation

Table 4 presents the regression results on the determinants of influencing decisions in

CFA in the last three months equation (8a). The results are generally consistent with our

theoretical expectations. The model prediction is satisfactory with 82% of the cases

predicted correctly. More educated households are more likely to influence decisions in

CFA meetings. The estimated coefficient for education is positive and statistically

significant at the 1% level. The more educated members of a household head the more

they will influence the decisions. A plausible explanation is that educated household

heads can acquire information much easier compared to less educated ones. In addition,

they are better able to express themselves effectively in meetings.

Table 4: Determinants of influencing decisions in CFA meetings

Variable Coeff Robust t-value P-Value Std. Err Education 1.01 0.29 3.482 0.001 Sex

0.67 0.69 0.971 0.332

Female-Male Ratio 0.33 0.14 2.357 0.019 Age HH head 0.84 0.45 1.866 0.072 Wealth

1.52 0.35 4.343 0.001

Land Size 0.02 0.13 0.154 0.898 Constant

-6.78 1.98 -3.424 0.001

Nr. of Observations 318 Wald Chi 2(6)

46.92

Log pseudo-likelihood -193.21 Cases correctly predicted 82.32

The Female-Male ratio variable is also positive is positive and significant at the 5% level,

which is indicative of the role of female members in the likelihood of influencing CFA

decisions. A possible explanation is that women are closely associated with forests

especially in the collection of firewood and other non timber forest products (NTFPs)

relative to their male counterparts. They are most likely to petition household heads to

effect decisions that suit their interests.

The aspect of gender in CFA is well debated in the literature. The positive sign of the

SEX variable indicates that male headed households are more likely to influence

decisions in the meetings. This is not unexpected in a traditional and patriarchal society

as is the case in Western Kenya.

The AGE of the household head is positive and significant, implying that the older

members are likely to influence decisions more than younger persons. Plausibly, the older

persons have more information on the forest than younger persons.

The variable on Value of Assets shows a positive effect that is highly significant,

implying that wealthier households are more likely to dominate and influence decisions

in CFAs. This finding is corroborated with recent literature on devolution of natural

resources, which argues that local elite capture more benefits than the poor, (Platteau and

Gaspart, 2003). Similarly, land size of holding showed a positive effect but is

insignificant.

Determinants of Attendance

The regression results from the meeting attendance equation are presented in Table 5.

The level of education of the household head is negative and significant. This suggests

that more educated persons are not likely to attend CFA meetings. This finding is

consistent with the notion that their opportunity cost of time is higher than that of less

educated persons. This finding may be counterintuitive given that earlier we found that

education is important in influencing decisions at CFA meetings. We conjecture that less

educated households are more likely to rely on forests and tend to have less off farm

earning opportunities.

Land Size has a negative and significant effect on the attendance of meetings, indicating

that land poor households are more likely to attend meetings. This is consistent with the

expectation that households with less land are more dependent on the forest. It may be the

case that land poor households show more interest in attending meetings in order to lobby

for land through the “Shamba System” now known as Plantation Establishment and

Livelihood Improvement System (PELIS)1.

Table 5: Determinants of attendance in CFA meetings

Variable Coeff Robust t-Value P-Value Std. Err Education -0.51 0.44 -1.15 0.363 Sex

-0.72 0.51 -1.41 0.156

Female-Male Ratio -0.35 0.17 -2.05 0.004 Age HH head -1.37 0.52 -2.63 0.005 Wealth

-2.20 0.71 -3.09 0.001

Road

-0.21 0.36 -0.58 0.554 Distance to market 0.15 0.04 3.75 0.001 Predicted probability 7.64 2.94 2.60 0.003 Land Size

-0.23 0.14 -1.64 0.101

Constant

8.44 2.39 3.53 0.000 Nr. of Observations 318 Wald Chi 2(9)

48.11

Prob>chi2

0.000 Log pseudo-likelihood -256.015 Cases correctly predicted 81.44%

The predicted probability of influencing decisions is positive and has a highly significant

effect on meeting attendance. This supports the notion that households that are more

likely to influence decisions are also more likely to attend the meetings.

An interesting result is that of gender participation. The variable SEX of the household

head is negatively related with the attendance of meetings. This is an indication that more

1 PELIS involves non-residential cultivation activities in forest areas earmarked for forest establishment. Communities are allowed to plant crops for three years, in 0.5 acre plots that are allocated through Community Forest Associations (CFAs).

females attend CFA meetings than men, ceteris paribus. This is consistent with the idea

that women are more dependent on the forest and thus have higher benefits from

attending CFA meetings. The results also show that younger people have higher

likelihood to attend meetings than the older people. The coefficient on age is negative

and highly significant. Plausibly, younger people are interested in either gaining

employment or have higher awareness about the environment. Similar findings have been

reported in Nepal, (Maskey et al., 2003).

Distance to market has a positive effect on meeting attendance, which indicates that

households in communities located far away from the local market are more likely to

participate in the meetings. This finding may be explained by the lower opportunity costs

to these households and also the likelihood that they are more dependent on forest

resources.

6.0 Conclusions and Policy Implications

In this study we analyzed, the determinants of household participation in community

forest associations, in Kakamega District of Western Kenya. Unlike other studies we

made a clear distinction between different levels of participation. In particular, we

introduced active decision making at these meetings. In the first stage we analyzed the

relative importance of the determinants of having influence at these meetings. In the

second stage, we estimated the determinants of attendance of meetings.

As discussed in the conceptual framework, household participation in the decision

making process of CFA is influenced by household characteristics, community

characteristics and external factors. Our results point that wealthier and educated

households in the community are more likely to influence the decisions taken. Older

persons are also likely to influence decisions at these CFA meetings.

In the second step we estimated the determinants of attendance of meetings. The ability

of a household to influence decision making is a crucial determinant of the household’s

decision whether or not to attend a meeting. In that regard, our findings that poorer and

less educated households are discouraged from attending because of their low ability to

affect the decision making process. This is to some extent discouraging, given the stake

that these households hold in the forest and their fewer options elsewhere. Wealth has a

significant effect on meeting attendance, indicating that ceteris paribus poorer

households are more likely to attend CFA meetings.

Distance to market was found to have a significant positive effect on participation in

meetings as households located in remote villages tend to be dependent on forests and

have a lower opportunity cost for time. Households from larger memberships within the

community tend to “free ride” in the sense that they tend to participate less in meetings.

Efforts to promote female participation in the decision making process by making

provisions in the committees are overshadowed by the male dominance nature of the

traditional society. Our results indicate that male members are more likely to influence

decisions. This result should also be viewed in light of the finding of elite capture in the

devolution process. Our results point to the difficulty of imposing democratic institutions

in traditional societies characterized by hierarchies.

To conclude, an important policy implication from our empirical results is that there is

need to tackle the issue of elite influences in the decision making process so that the

concerns of the poor and poverty alleviation aspect of forest reform is well taken care of

in the final resolutions. Measures that seek to garner the participation of communities in

CFA, but underplay the importance of well functioning institutions (i.e. rules and

regulations underpinning CFA, local and traditional governance structures and their roles

in building community social capital, democratic and accountable CFAs, etc.) are bound

to fail. The success of CFA initiatives therefore calls for measures to strengthen all

manner of institutions that promote community cooperation and participation for

community forestry, and in particular measures to improve household income and asset

bases to lower transaction costs in community forestry.

Another interesting result emerging from the study is that education is a crucial

determinant of the households’ ability to influence decisions. This points to strong

synergies between overall policies aimed at improving access to education for poor

people and the success of forest reforms in truly assuring full participation of these

groups in forest management.

References

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