PROPERTY RIGHTS AND NATURAL RESOURCE: SOCIO-ECONOMIC HETEROGENEITY AND DISTRIBUTIONAL IMPLICATIONS OF COMMON PROPERTY RESOURCE

MANAGEMENT IN NEPAL1

Bhim AdhikariPhD Student

Environment DepartmentThe University of York

Heslington, York YO10 5DDUnited Kingdom

E-mail: bpa100@york.ac.uk

THE SECOND WORLD CONGRESS OF ENVIRONMENTAL AND RESOURCE ECONOMISTSJUNE 24-27, 2002

MONTEREY, CALIFORNIA, USA

1 This paper is based on a chapter from my progressing doctoral dissertation in Environmental Economics and Environmental Management at the University of York, England. Thanks are due to Jon Lovett, Doriana Delfino, Charles Perrings, N.S. Jodha, and Priya Shyamsunder. Comments on proposal and earlier version of this paper from participants of SANDEE’s research and training workshop and Beijer Institute’s advanced workshop on property rights structures and environmental resource management are also highly acknowledged. The research received generous financial support from the South Asian Network for Development and Environmental Economics (SANDEE). The usual disclaimers apply.

ABSTRACT

The relationship between socio-economic heterogeneity and distributional implications of community-based resource management is becoming a growing concern in issues of local level collective action. This study tries to examine the contested role of heterogeneity and equity of resource distribution in community-based property rights regimes in reference to community-based forest management in Nepal. The analysis is based on field data from 309 households from the mid-hills of the country to investigate stockholder’s incentives in common property forest management. The analysis of household level benefits from community forestry suggests that poorer stakeholders are currently benefiting less from community forestry than relatively better off households. This paper also develops a regression model of determinants of household level income from community forests. Econometric results show that some socio-economic variables of the resource-using group place stringent limits on the extent to which certain groups are able to again access to and benefit from collective action. I reconsider the issue of persistent socio-economic inequality in communities and argue that restricting the access of poor people through changes in property rights structure in common-pool resources is likely to increase the level of poverty unless specific measures of compensatory transfer schemes are in place to safeguard the interests of the most vulnerable section of the community. At a glance, the impact of common property forest management seems to be ambiguous. While community forestry seems to be good for the forest resource itself and local environment, fundamental questions remain about the equity, distribution and livelihood implications of community property resource (CPR) institutions. I argue that clearly defined common property rights on common-pool resources are a necessary but not sufficient condition for equitable resource use. Property rights on natural resources need to be combined with social goals for equity, efficiency and the ecology of environmental resilience. The results show that transaction costs of community-based resource management can be a significant part of resource management costs, which is generally ignored in economic analysis of participatory forest management.

Key words: property rights, heterogeneity, community forestry, forest user groups, transaction costs

1. Introduction

Development of local economy while managing common pool resources has become an integral part of sustainable development policy in the past few years. This initiative has emerged largely due to a strong disillusionment with the performance of the centralized management policy to provide sufficient incentives to the resource users to manage local resources on a sustainable basis. It is argued that organised civil society may play an important role in overcoming many economic problems like internalisation of ecological externalities, the provision of local public goods, and access to credit by the poor that neither the market nor the state can reliably solve (Molians, 1998). Recognising this, much work has been initiated to support community-based resource management with a focus on poverty alleviation and improvements of the local resource base at the community level. Participatory resource management is often seen as an appropriate solution to reduce resource degradation and it was thought that granting community property rights over the local level natural resources would ensure equitable and sustainable use of environmental resources. More precisely, when the responsibility of allocating natural resources is delegated to local organizations, communities tend to appropriate these resources for collective community welfare. However, recent literature on CPR management have indicated a mixed result as to whether resource management and utilization under community-based property rights regimes is equitable and has potential to have a positive impact on the livelihood of the very poor and marginalized section of the community (Campbell et al., 2001). In one hand, it has been often argued that poor people extract more natural resources due to greater reliance on the natural resource base and also due to their high social discount rate. If poverty drives the marginal rate of time preference to infinity, then future environmental effects of the current strategy are optimally ignored. Poor people are often blamed

that they have high discount rates, shorter time horizons and tend to adopt strategies, which yield more immediate results, and they disregard long-term considerations in resource conservation. On the other hand, Dasgupta (1993) posits that compared to non-poor, the poor may depend more on the commons in relative terms, but in the absolute terms their dependency is lower, particularly for resources with good market opportunities. Many scholars conducting empirical analysis of CPR use challenge the hypothesis that only poor people are heavily dependent on local commons and they are the primary agents of resource destruction. (Jodha, 1995; Heltberg, 2001). While poorer households will attempt to minimize risk by using forest resources to mitigate shortfalls in consumption levels, relatively better-off households and local elites are interested in enhancing their earnings by selling these resources.

In many common property literatures, there is a tendency to assume that creating and enforcing formal systems of community-based property rights regime can guarantee the efficient management of common pool resources. However, experience from community forest management from different part of the world so far provides ample evidence that success of common property resource management cannot be guaranteed. It needs to be gauged not only by references to its efficiency, but also by the sustainability of resource use and its success in promoting social goals such as equitable distribution of benefits and function of social security (Adger and Luttrell, 2000). Given the fragility of the resource-base and vulnerability of households, no single form of property right over natural resources or entitlements to particular products has the potential to provide for survival needs of villagers. Poor families require access to different microenvironments to reduce risk and effectively schedule resource-use over time and space. The impact of common property rights on community-based resources, in this context, would not only be judged by the access and assurances available about future returns from present investments, but also by the timing of availability of biomass from commons and difference between the threshold quantity of biomass necessary for survival during distress and total biomass available from the commons during the period. Changing the management regime therefore affects the livelihood system dependent on the resources, and these issues should be investigated empirically through examination of property rights and the dynamics of inequality and income sources (Adger and Luttrell, 2000).

Empirical and theoretical literature emphasize that sustaining the environmental resource is not dependent on a particular structure of property rights regime, rather on a well-specified regime and a congruence of that regime with its ecological and social context. Success of the property rights regime depends upon the congruence of ecosystem and governance boundaries, specification and representation of interests, matching of governance structure to ecosystem characteristics, containment of transaction costs, and establishment of monitoring, enforcement and adoption processes at the appropriate scale (Eggertsson, 1990; Ostrom, 1990; Bromley, 1991; Hanna, 1992; Hanna and Munasinghe, 1995). More importantly, the equity and distributional aspects of a CPR regime is considered to be one of the major determinants of long-term sustainability of the commons. Hanna et al. (1995) argued that property rights regimes are a necessary but not sufficient condition for the equitable and efficient use of environmental resources. Appropriate cost-benefit sharing arrangements, together with empowerment of resource users, technical assistance to develop and strengthen local organizational capacities, and support equitable and sustainable management efforts are examples of other essential elements. Libecap (1989) points out that different property rights arrangements over management of common pool resources will not only have different production effects, but also they will have different distributive implications. While aggregate gains from reducing common pool problems or promoting economic growth through the definition or redefinition of property rights are unlikely to be controversial, the distribution of wealth and political power inherent in the proposed rights structure will be a source of dispute (Libecap, 1989). Since the nature of property-rights regimes and the distribution of access to natural

resources affect both the level of poverty and, quantity and quality of environmental resource base in the long-run (Dasgupta and Maler, 1991), property rights institutions will have to be more egalitarian so that they represent the poorest of the poor and avoid unilateral appropriations of the commons.

Though there has been a flurry of theoretical and empirical research on determinants of successful collective action, none of them have yet paid much attention to equity and distributional implications of community-based commons institutions. Most of these studies focus on communities as opposed to households. Decision and actions of individual households have been given less attention. It is assumed that communities will collectively manage local level natural resources because of the substantive benefits to be derived from these resources. In other words, if property rights over forest resources are granted to the community, the possibility of potential economic benefits will entice communities to practice an efficient and equitable management regime. However, the evidence suggests that in many cases participatory resource management could not demonstrate equitable distribution of benefits among the resource users. There are some references to the relative reliance on these resources of the poor, and some discussion of how community management institutions have worked toward ensuring access for community members, and there are implicit equity issues in many of the studies undertaken different part of the world (Beck and Nesmith, 2001). Explicit discussions on how changing property rights structure on community owned resources (from informal or traditional systems of management to more formal and market oriented systems of management) marginalized the weaker section of the community are rare.

One of the issues related to successful collective action is the contested role of group heterogeneity. Particularly important among these is the question of socio-economic, ethnic and political heterogeneity and their effect on local level collective action and resource management (Baland and Plateau, 1996, 1998; Keohane and Ostrom, 1995; Blomquist and Schlager, 1998; Uphoff, 1998; Bardhan and Dayton-Jonshon, 2000; Velded, 2000; Varughese and Ostrom, 2001). The presumption is that socio-economic differentiation and group heterogeneity makes cooperative arrangements more difficult. Heterogeneity inhibits innovation of local management institutions since it creates distrust and suppresses the level of mutual understanding among community members. In such communities, the process of crafting rules and regulations in respect to how a resource should be managed can involve high levels of local dispute. Divergence of interest among heterogeneous agents is likely to emerge when socio-economically heterogeneous groups are sharing common resources since their interests in resource management may significantly differ from one another, interests being guided by his/her socio-economic reality. Relationships between socio-economic heterogeneity and commons performance are discussed in a greater depth (Baland and Platteau, 1998, Bardhan and Dayton-Johnson, 2000), however, issues like inequality and distributional implications of CPR institutions remain inconclusive.

In this paper, I intended to identify the most important types of heterogeneity that might affect the equity of resource distribution through an empirical study of common property forest management in Nepal. I argue that recent policy shifts towards community-based forest management (from informal systems of management to more formal systems of management) with donor intervention do not have positive impacts on the livelihood of the poorest section of the community. Experience from community forestry so far indicated that household level income from community forestry is associated with household characteristics that determine household level access to and control over local resources. I therefore want to test whether intra-household variation in income from community owned resources could be explained by differences in private asset holdings. In another words, the idea is to explore whether and to what extent socio-economic differences among users

give rise to different outcomes regarding the private pay off from the commons. More importantly, I seek to answer the question (a) how and to what extent does intra-household socio-economic heterogeneity affect equitable benefit sharing arrangements among resource users? (b) how inequality hinders meaningful participation of the most vulnerable sections of the community?; and (c) does existing property rights structure in community forestry increase the access of poor and marginalized people to the local resource base? Scholars on commons have pointed out the problem of collective action in an economy with highly heterogeneous agents (Karaivanov, 2001). In this study I advance this argument by examining the household use of common property forest resources in order to explore how heterogeneity in common property resource management influences the equity of resource distribution, and welfare of community members.

The rest of the paper is organised as follows. In section 2, I discuss the property rights structure over forest resources in Nepal and present some account of problems associated with community-based forest management. In section 3 I review theoretical and empirical literature on heterogeneity and performance of collective action. A review of empirical work on economic analysis of common property resources is presented in section 4. Section five presents analytical and theoretical models. I discuss methodological issues, survey design and socio-economic characteristics of user groups in section 6. Section 7 reports on the results obtained from economic and econometric analysis. Finally, the paper concludes in section 8 with major conclusions and policy implications.

2. Property Rights Structure and Forest Resources in Nepal

Property rights structures over natural resources in general and forest resources in particular have been frequently changing over time in Nepal. These changes are associated with exploitation and degradation of mountain forests and its biological diversity. Various legislative measures were enforced to ensure clear ownership over the forest. The Private Forest Nationalization Act in 1957 was a very controversial step in the history of forest management in Nepal under which huge tracts of forest previously managed as private and common property were brought under state control. After nationalization, local communities throughout the country reacted negatively believing that their traditional rights of access and use had been curtailed. While the stated objectives of the nationalization were noble, the effects were often the opposite of what was intended. The Nationalization Act increased the rate of forest destruction as villagers hurried to convert affected lands into agricultural uses so as to exempt them from the transfer (Bromley, 1991). Moreover, nationalisation along with undermined security of tenure led to further degradation. Although the villagers may have overused the open-access forests, the origin of the problem lies in the government policy of not recognising traditional community management systems. Failure to distinguish between common property regimes and open access situations has been identified as the main reason behind forest nationalization, which speeded up exploitation of forest resources due to lack of individual/community control over resource use as exercised through the traditional property rights institutions. Studies undertaken in different parts of the mid-hills have revealed that in many rural areas the indigenous management system collapsed after forest nationalisation, mainly because the informal institutions, which had looked after the protection and management of forest, were broken down. As a consequence, most of the forest previously managed as common properties were turned to open access as a result of the failure of enforcement of state property rights.

After experiencing failure following the forest nationalization, the government introduced another act, the Forest Act 1961, which was more focussed on the forest administration. Inclusion of different forest management regimes like Panchayat Forest (a local level political unit), Panchayat Protected Forest, Private Forest, Leased Forest, and Religious Forest were important components of this act first amended in 1978. By the mid 1970s the government realised that local people had to be

involved in forest management and passed the new and far-sighted Community Forestry (CF) Legislation and Decentralization Act (1982). The Forestry Master Plan (1988) spells out the comprehensive policy statement for community-based forest management, which emphasized that control of forests should be turned over to local user groups. After restoration of democracy in 1990, the government has further framed the Forest Act (1993) for the sustainable management of forest resources under community-based property rights regimes. The Forest Act vests more legal authority in the forest user groups so that they may manage the community forests on a sustainable basis. This legislation was given greater coherence by the Forest Rules 1995, which further clarified the powers and duties of Forest User Groups. As per these policies, local communities are organised as Forest User Groups (FUGs) and accept the responsibility for protection, management and sustained utilization of forest areas under community-based property rights regimes. To date more than 9000 FUG are managing about 660,000 hectares of community forest in the country (CPFD database, 2000). Based on conceptual schema to analyse property rights regimes proposed by Schlanger and Ostrom (1992), I observe the following collective rights held by Forest User Groups in the management of community forestry (CF)2 in Nepal.

A. Operation-Level Property Rights

Access (all defined users have a right to enter into community forestry as per specified rules and agreed upon operational plan i.e. block, time, months, season, etc.)

Withdrawal (all defined users are entitled to harvest forest products from CF)

B. Regulation Rights

Management Decisions regarding operational rules on forest protection, harvesting, utilization and

sanctioning of rule infractions are made by Forest Users Forest User Group can plant long-term cash crops like medicinal herbs and other NTFPs

without disturbing the main forestry species (collectively owned) Forest User Groups can establish forest-based industries Users can amend the Operational Plan simply by informing District level forestry authority FUG can fix the price of the forest products irrespective of the government royalty FUG can use surplus funds in any kind of community development work

Exclusion Users identify the traditional users of community forest themselves The community reserves the right to form Forest User Groups and Committees through

consensus within the community by which they define who are the included users and who are excluded person

Forest Users can provide membership to new entrants under certain conditions

Alienation There is no mechanism by which user group members could sell or lease his/her share of their

rights to other users of the same group Users are not allowed to sell their private share of the produce in the market and there is

strong argument that community forestry in Nepal is incentive-incompatible

2 Community Forest is actually is a common property resource (CPR). Forest User Groups (FUGs) have usufruct rights over the biomass of the community forest as laid down in operational plans, however, the ownership of the forestland on which the forest biomass stands belongs to the government (Chapagain, 1999).

However, despite having the most innovative policies to promote community-based resource management in place, community forestry is said to be unable to provide a significant contribution to the livelihood of poor and marginalized people due to its failure to take into account boarder socio-economic issues. Although improvement in the physical situation of forest and trees resources on both public and private lands have been reported (Branney et al., 1994), equitable use of forests products such as fuel wood, fodder, timber and other non-timber forest products within the community has not been clearly demonstrated. Poor users are not actually benefiting when all opportunity costs are accounted for in the assessment of costs and benefits of forest management. There are some cases that people who could not contribute the costs of resource management have given up their participation. The landless, and household belongs to particular ethnic groups like blacksmiths, and other politically and economically marginalized ones (mainly occupational households) are not able to take advantage of incentives for tree growing. The amount of forest products harvested at present is insufficient to meets the need of the users and the process involved in the distribution of these products (like auction, contracts, free distribution and equal distribution) favours wealthier households (Malla, 2000). This has proved that clearly defined rights on common property resources are a necessary but not sufficient condition for efficient, equitable and sustainable resource use.

Various authors noted that recent policy shifts have not helped needy people, but often have worked to their disadvantage. They are often not included in the users committee which influences forest management decisions, and so they have now lost even their traditional access to forest resources, as fuel wood sellers and livestock herders are not effectively represented in the operational regimes. Elites and traditional decision-makers often dominate the users’ committee. Marginalized and poor people are usually neglected during the planning and operational plan preparation that undermines their role and excludes them from getting a fair share of forest products. The limitations on fuel wood collection have a more profound impact on households whose livelihoods traditionally were closely linked to its collection. The most obvious group affected are fuel wood sellers, who now have left very few alternatives to their livelihoods. It also affects others, such as raksi (a local liquor) makers and blacksmiths, both of which need large quantities of fuel wood (or charcoal) in their trade (Soussan, 1998). A priori, one would expect the CF restrictions to have had less impact on the wealthier groups, since, with more private land to satisfy their own requirements; they were less dependent on the national forest area (Richards et al., 1999). Very few FUGs make any special provision for these groups, who find their livelihoods jeopardised by the introduction of community-based management regimes. While FUG management has lead to a marked improvement in the forest condition, the concern is that this is at the expense of welfare or equity objectives (Branney and Yaday, 1998). Restricting access through changes in property rights is likely to increase poverty. Though the poor would be doubly disadvantaged without common property access to forest products, conservation measures entailing curtailment in the right to common access pose a dilemma (Reddy and Chakravarty, 1999). Based on cased studies from India and Nepal, Agrawal (2001) shows how “participatory institutions” can exclude significant sections of the community, such as women and poor.

Analysis of the socio-economic impact of community forestry is becoming a central issue since management objectives and the nature of dependency on common property resources is somewhat different for different income groups. Since a community forest management regime is mainly oriented towards the production of intermediate forest products that are inputs in the farming system, and towards subsistence rather than cash generation, households with more livestock, farmland and people naturally benefit more (Richards et al., 1998). In many villages, institutional arrangements for distribution of benefits have been designed in such a way that would distribute

products of community forest in direct proportion to private holdings of agriculture lands and livestock. The distributive consequences of management regime might not be only a crucial determinant of the extent of resource utilization but also an indicator of the level of poverty. There is little understanding of how poor people’s livelihood strategies are constructed and what forms of management regime might complement and strengthen their livelihood security and enhance equity while restructuring the local institutions of common-pool resource management. What is required is a better understanding of how community-based property rights fit with different people’s lives – this implies an understanding of how the poor themselves evaluate trade-offs between various costs and benefits (Bird, 2000). Understanding of these limitations on community-based property rights structures can help provide the necessary leverage to local forest-dependent communities so that their interests are fairly represented in forest planning and management decisions.

However, in the context of participatory forest management in South Asia, there is a tendency to assess impact of community-based resource management in terms of biophysical and institutional change rather than impacts on villager’s livelihood. Davies and Richards (1999) extensively reviewed the literature on economic analysis of community-based forest management to understand stakeholder’s incentives for participatory forest management. They conclude that most of these studies tend to biased towards i) reviews of valuation studies as opposed to providing clear methodological guidance; ii) non-market valuation for global and national stakeholders as opposed to how to add marketable value for local stakeholders; iii) benefits in general as opposed to costs like transaction costs; iv) sophisticated high-cost methods as opposed to more accessible low-cost methods; v) ex-ante studies for project preparation as opposed to ex-post monitoring and impact analysis; vi) treating forestry as a separate enterprise as opposed to a more holistic livelihood focus; vii) efficiency and profitability as opposed to equity, gender and institutional issues and; viii) returns to land and capital as opposed to returns to labour. The major questions still to be answered is how great are the real costs and benefits of participation, and how they are distributed amongst the various actors (Hobley and Wollenberg, 1996). There is less attention to the fact that households might not be better off at all from changing the property rights institution. The more ambiguous nature of community-based forest management on distributional grounds, therefore, points out the need for further research to include specific measures to safeguard the interest of those who may lose from community-based resource management regime, especially as they are often the poorest and most vulnerable in the community.

3. Review of Selected Literature

Despite an apparent consensus that individual resource users unite collectively and manage common pool resources efficiently, many unresolved theoretical issues still exist. Among these, the relationship between socio-economic heterogeneity and distributional implications of community-based resource management is becoming a growing concern in issues of local level collective action. An increasing number of economists are interested in understanding the role of group heterogeneity in the success or failure of collective action. There is widespread realization that productivity-enhancing CPR governance is difficult when appropriators are heterogeneous. The source of heterogeneities are diverse, and include differences in assets holding, appropriation skills and access to technology, caste, gender, ethnicity, opportunity cost, political influence, and local differences, which might influence the equity of resource distribution and thus performance of collective action.

Resource users will often have somewhat different preferences regarding resource management, or assign different priorities to the various objectives of resource management, either because of differing personal interest in the resource or differing degree of involvement in the social group

(Kant, 2000). The heterogeneity of individual interest with respect to how a resource is managed affects individual incentives and thus income from local commons. As rightly pointed out by Seabright (1993), the degree of trust economic agents, participating in some form of collective action, have in one another serves a crucial role in common property regimes. He developed a model of “habit forming” co-operation. The model revealed the fact that a player’s belief about each other’s trustworthiness is confirmed and contributes to co-operative behaviour. Such a “habit forming” process is, however, unlikely to work in a community, which starts with a high level of heterogeneity with respect to resource management preference (Kant, 1998). Moreover, economic inequality or socio-economic heterogeneity among the members of a resource-using group might be associated with different degrees of access to and control over the local commons. Intra-group heterogeneity in terms of private payoffs can often lead to conflicts of interests and thus hinder the performance of any cooperative arrangements. Given the more likely scenario of socio-political heterogeneity within spatially defined community groupings, participation in community decision-making can be skewed in favor of more powerful subgroups to the cost of vulnerable sections of the community (Guggenheim and Spears, 1991). Greater homogeneity, on the other hand, promotes both equity and efficiency by facilitating adoption of more coordinative and cooperative arrangements at the local level.

Bardhan and Dayton-Johnson (2000) extensively reviewed the case-study literature on heterogeneity and commons management. They noted a U-shaped relationship between inequality and commons management. Very high and very low levels of inequality are associated with better commons performance, while mid-range levels of inequality are associated with poor outcomes. Putting much emphasis on economic inequality, they further clarify many relevant types of economic inequality, like inequalities in the sacrifices community members make in cooperating with commons- management regime, inequalities in the benefits they derive from such regimes, and inequalities in outside earnings opportunities (“exit options”). If resource users have relatively lucrative earnings outside the commons, this can affect their individual incentives, as well as their opportunity to exercise power to influence benefit-sharing processes in the local commons. As the household income increases, their social and political position in a community is likely to be improved and their access to and control over common pool resources is also increased. As they become socially and economically empowered, they represent the local institutions responsible for natural resource management and influence the management regime as per their needs. Certain sub-groups, on the other hand, may be unable to participate in protection system and management decisions, because they cannot meet the costs involved, and as a result they are deemed ineligible for benefits. For example, groups that depend heavily on daily wage labor or seasonal migration sometimes find it difficult to contribute their share of costs of protection (Conroy et al., 2000).

Baland and Platteau (1999) investigated the impact of inequality on the ability of resource users to undertake successful collective action with special reference to overexploitation of common property resources. They argue that in a voluntary provision problem, inequality has an ambiguous impact on the efficient outcome, while in regulated settings it tends to reduce the acceptability of available regulatory schemes which makes collective action more difficult (Baland and Platteau, 1999). Changes that disequalize distribution of access rights through the definition or redefinition of property rights will have two different effects. First, the agents who benefit from such a change have a larger stake in the common property resources and therefore have a greater incentive to take part in conservation effort. While the same change has a corresponding disincentive effect on the other agents whose endowments have been reduced. Since the increasing inequality redistributes incentives in a different direction, it may have an ambiguous effect on the ability of users to initiate collective action towards conserving and devising an appropriate mechanism to ensure the sustainability of the commons. Under such circumstances, a homogeneous group may better

succeed in designing and enforcing equitable conservation measures than a heterogeneous one (Baland and Plateau, 1996). In his simple numerical model, Kanbur (1992) investigated the role of group heterogeneity in the success or failure of common property resource management. He argues that cooperative arrangements are less likely to come when agents are highly heterogeneous and existing arrangements is also likely to break down as a group becomes more heterogeneous.

Drawing upon recent theoretical advances in the analysis of cooperation, (Molians, 1998) undertook an econometric analysis of the determinants of successful collective action based on a survey of 104 peasant cooperative institutions in Paraguay. Molian’s study shows that controlling as much as possible for the specific characteristics of the community and peasant committee, there is a U-shaped relationship between community inequality and cooperative performance. It was evident that community members with bigger land holdings are expected to benefit proportionally more from the committee’s activities than members with smaller holdings. Since provision of community infrastructure will increase the average price of land in the community, users who own more land naturally benefit more. In addition, the benefits accruing from joint commercialization of the outputs and collective buying of input are proportional to the scale of production, which in turn depends upon the size of the land holding. The study concludes that local level cooperation is not monotonically related to either the degree of inequality of endowments within the community or the local intervention; rather, it is of an inverted U-shape form. Boyce (1998) argues that inequality may have a negative effect on collective action. Inequality may increase the scope for a powerful minority to impose rules of the game that benefit them at the expense of the large majority in the community. Based on twenty-three community managed irrigation systems in developing countries, Tang (1991, 1992) concluded that a high degree of rule conformance and good maintenance tend to be associated with a low variance of the average annual family income among irrigators.

Dayton-Johnson (2000) develop a simple model of individual household’s incentives in a community owned irrigation system and found that social heterogeneity, measured by the number of different villages from which the users of a given system are drawn, is consistently and significantly associated with lower levels of infrastructure maintenance. While inequality in landholdings has a negative, though complicated, effect on maintenance. Similar to Molian’s findings, his model shows that the effect of economic inequality is complicated and not monotonic (Dayton-Johnson, 2000). In their study of community forest management in Nepal, Richards et al. (1998) observe that household members with bigger land holdings benefit proportionally more from community forestry than members with smaller holdings. Because community forestry is mainly oriented to the production of intermediate products that are inputs in the farming system, and towards subsistence rather than cash generation, households with more farmland naturally benefit more (Richards et al., 1998). On the other hand, the landless and economically marginalized user household may not be able to take advantage of tree growing. Moreover, the difference in number of livestock that households raise may be associated with the extent of use of local level natural resources. People’s interests in forest resource differ based on whether or not they raise cattle. In many cases, the differences in wealth are evident more by the extent of land and livestock holdings. Wealthier households have greater need for animal fodder and agriculture compost (Varughese, 1999), which, in turn, encourages inequitable use of the community resource base. Poorer households extracted least from the forest, mainly because they had less livestock and farmland, which provide the main farming system demand for intermediate forest products (Richards et al. 1999). Asymmetry in individual endowment therefore seems to be associated with different access to, and control over, the local commons. Adhikari (1996) noted that equitable and sustainable management of forest resources under community-based property rights in the mid-hills of Nepal is dictated by socio-economic status of the resource user. Gaspard et al. (1997) have studied community-based watershed management and drainage channel development in Ethiopian

highlands. They found that those households with bigger land holdings, or owing land centrally located in the basin, gain more from the collective endeavour. This is another example of what Dasgupta (1999) termed as “a built-in asymmetry”, which give rise to an asymmetric outcome.

Bardhan (1997) posits that types of heterogeneity that are not strictly or even primarily economic will also have important economic consequences, as in the case of ethnic heterogeneity. In his study of 48 irrigating villages in the South Indian state of Tamil Nadu, Bardhan (2000) observes caste homogeneity (in the form of 75 % or more of the farmers belonging to the same caste group) is significantly and positively associated with the absence of community conflicts. Beteille (1983) points out that in Indian villages access to local common-property resources is often restricted to the privileged (for example, caste Hindus) caste groups. The outcasts or schedule castes are often among the poorest of the poor. Socio-cultural differentiation in communities may increase social distance between individuals, which may hinder the cooperative arrangement. Cultural differences may have a negative impact in collective action as they leave room for different interpretation of the rules of the game being played due to different perceptions of social conventions and norms supporting cooperation (Baland and Platteau, 1996). Moreover, differences in views, which relate to knowledge and information, affect choice in resource management and capacity to agree on collective action (Velded, 2000). It may also be that occupational caste households have different access to local environmental resources than higher caste households (Cooke, 2000). The traditional elites in rural society are not only the category of persons to benefit from the newly channeled resources, they are also frequently involved in tactical alliances with educated people and politicians operating outside the village (Abraham and Platteau, 2000) in order to make unilateral appropriation of the commons. However, heterogeneity and income inequality in community-based property rights structure is also said to be conducive to the successful outcome of the collective action. Olson (1965) hypothesized that the possibility that groups where considerable heterogeneities exist may be privileged if those with the most economic interests and power were to initiate collective action to protect their own interests. Wealthy users tend to be more concerned for resource conservation and therefore have more incentive to contribute to the local commons. Baland and Platteau (1997) also discuss the theoretical possibility of Olson’s hypothesis especially when management of common pool resources involves important “non-convexities” in its production function. Non-convexities indicate the large start-up costs, which are likely to be incurred in setting up a community-based management regime. In a related vein, Baland and Platteau (1999) revealed that increasing inequality could stimulate the incentive of the big users to voluntarily contribute and simultaneously encourage the small users to free ride on the former’s contribution. However, despite impressive advances in our understanding of the impact of institutional form on the performance of collective action, the relationship between intra-household heterogeneity and distributional implications of CPR regime is still under researched.

Most of these previous studies do not explain well the distributional implication of CPR regime in light of local level inequality, which is undoubly an important determinant of successful collective action. It is implicitly assumed that once the criteria for successful collective action are met, there will be egalitarian distribution. The main thesis in this study is that household level benefit from common property forests is almost inextricably associated with household characteristics like land and livestock holdings, appropriation skills, caste, gender, education, ethnicity, political influence, and other local differences, which influence the nature and extent of resource appropriation and exploitation. In other words, variation between different income groups with respect to forest product entitlement and use can be explained by socio-economic status of user groups.

4. Distribution of Benefits From CPR: Insights from Empirical Literature

Consistent with growing theoretical literature on common-pool resource management, there is large quantity of empirical research in India dealing with dependence of poor on the CPRs (Chen, 1991; Pasha, 1992; Jodha, 1985a, 1985b, 1986, 1990, 1995; Iyengar, 1997, 1989; Beck and Ghosh, 2000; Beck, 1994, 1998; Agarwal, 1991, 1995, 1997; Singh et al., 1996; Iyengar and Shukla, 1999). Beck and Nesmith, 2000 note that, common property resources currently contribute some USD 5 billion a year to the income of poor rural households in India, or about 12% to the household income of poor rural households. Jodha’s (1986, 1995) study from 80 villages in 21 districts in India concluded that CPR is contributing 15-25% of total income of poorer households. Jodha found that the privatization of CPRs as a strategy to help the rural poor yielded negative results and also reduced productivity of the commons. In his study of common pool resources in West Bengal, India, (Beck, 1998) observes that access to CPR by the poor is gradually decreasing across all study villages and agro-ecological regions. There is a very clear differentiation between benefits gained from CPR by poor and non-poor households.

In a study of 29 villages in South-eastern Zimbabwe, Cavendish (1998, 1999) arrived at even larger estimates. He observes that the proportion of income based directly on the commons is about 35%. Moreover, the figure for the poorest quintile being 40 percent. Based on a qualitative assessment of babassu products in Maranho, Brazil, Hecht et al. (1988) also conclude that the products offer support to the poorest of the poor, especially the women. In their study of valuation of Mangrove resource use in Kosrane, Micronesia, Naylor and Drew (1998) estimate that direct economic benefits from mangrove is about 75 percent for subsistence households, 21 per cent for households in the private sector and 4 per cent for households working in the government sector. However, McKean (1992) argued that entitlement to products of the commons varies to a surprising extent. She concludes that distribution of benefits in collective action reflects inequalities in private wealth. Hill and Shields (1998) observed that community incentives in JFM in India are not so clear-cut, however, the main losers in JFM are fuel wood head loaders who are often from the poorest subgroup within the village. Moreover, it may be the richer members of the community who dominate local politics and organizations as found in JFM in India where benefits from the system go to certain sectors of the community (Saxena, 1989). Ribot (1995) for Senegal and Andersen (1995) for India report how wealthy and influential villagers in control of supposedly democratic forest councils are able to use state resource laws for their personal benefits. Based on review study on CPR management in Zimbabwe, Campbell et al., (2001) argue that there is a fair degree of misplaced optimism about CPR management since the formal rule-based system that forms the cornerstone of CPR institutions is gradually replaced by donor-assisted intervention rooted in norm-based controls. Though the management of CPRs and its implication for environment and poverty has been well studied in India, no systematic effort has yet been undertaken in Nepal. Some of the studies have only touched upon the issue of CPRs and role of common property institutions in regulating access and conservation rules (Soussan, 2000; Malla, 2000) but no comprehensive effort has been made to integrate the impact of local management institutions on equity of resource distribution and sustainability of common property resources at the community level. Moreover, most of the previous studies (both in Nepal and India) do not explicitly analyze the equity of resource distribution within the community. Very few studies on equity and distributional implication of participatory forest management exist.

5. The Analytical and Econometric Models

5.1. The Analytical Model

The main thesis in this study is that household level benefit from common property forests is almost inextricably associated with household characteristics like land and livestock holdings, caste, gender, education, ethnicity, political influence, and other local differences, which influence the nature and extent of resource appropriation and exploitation. So the variations between income groups with respect to forest product entitlement and use (output from CF) can be explained by socio-economic status of user-household. Here, my working hypothesis is that demand for forest products is a function of a number of socio-economic characteristics that provide a measure of household dependency on the local commons. This in turn determines household level benefits from the commons. In other words, I hypothesizes that poorer households are currently benefiting less from community-based forest management than relatively better off households.

The theoretical framework for understanding household production decisions is based on profit-function approach. Profit function models are useful in analysing the effects of price changes and changes in fixed factors (e.g. changes in the amount of land) (Peerlings and Lansink, 2001). This approach assumes that farmers choose a combination of variable inputs and outputs to maximize profit, subject to technological constraints. Profit maximization should be understood in the broad sense of farmers using limited resources as efficiently as possible to meet their livelihood objectives (Yanggan and Reardon, 2001). Furthermore, we do not need to assume that farmers strictly maximize profit to specify our output-supply and factor demand equations, as long as individuals agents behave in a manner that is sufficiently stable over time and can be aggregated over farmers (Sadoulet and de Janvry, 1995). So in this context, profit function gives the maximum profit a participating household can get from community forestry subject to the input and outputs prices and the quantity of fixed factors available to the farm households. Fixed factors are those that household cannot change in shorter time frame and include private factors (e.g. land, livestock, education, household labour) and public factors (quality of forests, stock density etc.) as well as exogenous factors (institutional regime, distance, etc.). Since quantities of fixed factor use in exploiting the local commons is exogenous to households in the short run, a short-term profit function is used. The profit function can be given as follows

= py – wl (1)

Where, p = vector of prices for outputsy = vector of forest products (outputs) produced by households w = vector of input price l = vector of inputs

Household’s profit maximizing behaviour is constrained by the production technology. Fuel wood, tree fodder, cut grass and leaf litter production technology is given by a continuous quasi-concave production function that describes collection forest products from common property forests. Representative household maximize profit by collecting (harvesting) various products from community forest by employing variable inputs, l (like labour, tools etc.). Forest product collection is also conditioned on vector of fixed socio-economic characteristics, z, (i.e., land and livestock holding, ethnicity, gender, educational level, institutional constraints, including forest stock and access condition, leadership quality of household head, etc.) which drive the biomass need of user households. Production function for households engaging in gathering and collection activities can be written as

y = f (l; z) (2)

Farm household chooses the optimal level of input l and output y to maximize profits from collection and gathering activities. The input-demand and output supply functions can be given as follows. The supply and demand functions show the relation between output supply and input demand and the prices (both input and output) and the quantities of fixed factors.

l = l (p, w; z) (3)y = y (p, w; z) (4)

This indicated that the optimal level of inputs and outputs are a function of output price, input price and fixed factors of production used in forest product collection. Substituting (3) and (4) in profit function, we get the new profit function.

= py (p, w; z) – wl (p, w; z) (5)

Differentiating this profit function with respect to output and input price, we can get the following first order conditions that give rise to the output supply and factor demand function.

/pi (p,w,z) = yi (6)/wi (p, w, z) = -li 7)

As we have seen, profits are not only affected by input and output price but also socio-economic position of households (fixed factors) by its affects on demand and level of dependency on the commons. Demand of forest products is indeed a function of increasing wealth (land, livestock etc.), which, in turn, is a driving force in exploiting resources from the commons. The econometric model in subsequent section analyses the determinants of household level benefits from the local commons.

5.2. The Econometric Model

Based on the analytical model that I have discussed in previous section, I specify an econometric model in order to analyze determinants of household level income (output) from CF. Outputs refer to various forest products such as fire wood, tree fodder, grass fodder, timber, leaf litter and other non-timber products that households used to collect from community forests. However, the only ones of significant economic value are firewood, tree and grass fodder, and leaf litter due to intermediate forest products oriented forest management regime. The forest users committee, dominated by elite as they usually are reinforce such practices in community forestry that promotes timber and biomass production rather than non-timber forest products which are extra source of income for poorer households. A highly protective silvicultural regime, of the sort that is practiced in most community forest areas, is more likely to lead to the early closing of forests, and this potentially reduces the harvest of non-timber forest species from which opportunities for the poorer is reduced (Kumar, 2002).

The scatter plot method was used for preliminary scrutinizing the independent variables, as there is limited knowledge about the relationships. The dependent variable, Y, measures the household return from CF (value of outputs) obtained through an economic analysis as described in the previous section. Independent variables in this model are: the land ownership (LANDHO); the amount of capital owned (number of animal unit owned by household, LIVESTO); exit option for household (off-farm income, EXITOP); ethnicity of household (lower caste dummy, ETHNI); education (number of school years of household head, EDU); household labour (number of person

in work force, HSIZE); gender of respondent (male dummy, GEND); distance between forest and house (DIST); and the price of fuel wood. Since there are no actual market prices for other forest products (e.g. tree and grass fodder, leaf litter etc.), it is assumed that these prices are the same to each participating households. The leadership quality of households (MEMTYPE) is measured by household head’s position in executive committee as dummy variable. I initially include a number of independent variables, however, due to correlation between dependent and explanatory variables, I have restricted myself to those, which are not correlated and are hypothesized to be the most influential factors. These relationships can be represented in following linear equation:

OUTPUTij = f (household labouri, land holdingi, livestock uniti, ethnicityi, educationi, genderi, leadership qualityi, exist optioni, fuel wood pricei, distance between forest and housei, transaction costi, institutional constraintsi) (8) Where j = forest products (fire wood, tree fodder, grass fodder, leaf litter etc.) and i = 1,…n observations.

A few comments are in order at this stage. Household members with bigger land ownership are expected to benefit proportionally more from CF because management regime of CF is mainly oriented to the production of intermediate products that are inputs in the farming system, and towards subsistence rather than cash generation (Richards et al., 1998). The poorer households extracted least from the forest, mainly because they had less livestock and farmland, which provide the main farming system demand for intermediate forest products. In many rural settings, households invest surplus income to increase the size and scale of production systems. They may invest a substantial amount of their income either on buying agriculture land or raising productive and improved varieties of cattle. This proves that dependency on forest does not necessarily reduce as household income increases up to certain limit. Under such circumstances, forest extractive activities remain as important for the household economy as off-farm income opportunity and agriculture itself (Hecht et al., 1988). An ethnicity variable may also affect the preferences of the household and thus influence consumption decisions. I want to see whether education of member of resource using group is associated with extent of common property resource use. There are actually several ways to test such a hypothesis. It may be argued that higher education in the rural community leads to the extraction of fewer forest resources since education opens up better employment opportunity diverting people from subsistence agriculture and gathering (see Gunatilake, 1998).

Harvesting the various forest products are labor-intensive activities because people have to walk some distance to reach CF as well as searching and harvesting the products. In a time allocation framework, more labor in the family means the household’s time constraints are set at a higher level and that may lead to extra extraction (Gunatilake, 1998). Thus, a family with more labor can mobilize household labor in forest extraction activities and get more income than households with less labor force. In many forest resource systems, users who live closer to the forest have a more secure and accessible supply of produce regardless of whether or not there are allocation rules in place (Varughese, 1998). Families living close to the forest have the advantage of less time being required to reach a particular forest resource. Their links with forests are, therefore, expected to be high (Gunatilake, 1998). The distance some users have to travel, or their relative proximity, to CF areas they use in relation to that traveled by others users affects the symmetry of income distribution among the users.6. Study Sites, Methods, and Data Collection6.1. Study Sites

This study was undertaken in two selected districts of the mid-hills of Nepal where community

forestry intervention has been implemented for last two decades. The Middle Mountain region occupies the great central belt of Nepal where the country’s origins and character are mostly rooted and comprises about 30 percent of the whole area of the country (MFSC, 1988). The land –uses of the Middle Mountains are categorized as cultivated land, non-cultivated inclusions, grasslands, forestland, shrub lands and other types of land use. The area is home to an extremely heterogeneous, multi-caste society with a significant number of people belonging to ethnic groups such as Brahmins, Chhetris, Newars, Tamangs, Thakalis, Magars, Gurungs, Rais and Limbus. Most of the populations in this area are subsistence farmers and pastoralists with few options for changing their livelihood. All accessible hill forests in the study area are surrounded by agricultural land and are under heavy pressure to meet the primary forest product needs of the households. Livestock is an integral part of a subsistence farming system, which provides sources of protein like milk and meat, draft power, and manure for soil fertility maintenance. Firewood is the main source of energy and more than 80 per cent households rely on fuel wood for cooking and heating. The demand for livestock fodder and forage is met through grazing on forestland, and by feeding livestock on agricultural residue, grass and edible leaf materials from community forestry. According to a study carried out in one of the study areas, 75 percent of the total livestock feed is grass and green fodder collected from the nearby forests (Maharjan, 1991). The collection of leaf litter from the forest as a source of nutrient for the farming system is a very common phenomenon because of the difficulty and costs associated with transportation of chemical fertilizers. These diverse ethnic groups exhibit different forest use-patterns, which directly affect cost and benefit sharing patterns. The household’s dependence on community forests in most of the study sites is for fuel wood, tree fodder, cut grass, leaf litter and in some extent auxiliary non-timber forest products with a major proportion of household benefits contributed by fuel wood, fodder, grass and leaf litter.

6.2. Data Collection

Primary data on household level variables and use and management of community forestry was collected through a household questionnaire survey between for a period of 4 months from September to December 2000, in eight villages, in Kavrepalchowk and Sindhupalchowk districts of the mid-hills of Nepal. From the lists user groups in these two districts, 8 user groups were randomly selected. The survey was based on stratified random sampling. A stratified sample of households was chosen by compiling a census of village households with participatory rural appraisal (PRA) techniques. Participants of PRA exercise were asked to categorised all households into three different stakeholder groups i.e. poor, middle wealth and richer households based on certain criteria that villagers think important while assessing individual’s socio-economic position in the village. Main criteria used were the amount of land owned, the number of livestock owned, loan given and taken, and income from off-farm agricultural activities. Land quality and household food sufficiency is also taken into account in order to categorize the socio-economic position of the household and to assign individual households to ranks identified (Richards et al., 1999). Poor households own between 0 to 5 Ropani1 of land, with a mean of 2.95 Ropani. Middle-wealth households own between 5.5 to 15 Ropani, with a mean of 10.12 Ropani. Richer households own between 15.5 to 85 Ropani, with a mean of 26.65 Ropani.

A checklist of all potential products that user-households extract from community forestry was prepared to avoid underestimation of forest products harvested. Household questionnaire were designed to elicit forest use information from the respondent households. Pre-testing of the questionnaire was undertaken in one of the randomly selected villages outside the sample frame. The response to pre-testing of the questionnaire resulted in the revision of sensitive questions such

1 20 Ropani = 1 Hectare

as gender bias in the forest products extraction. The focus of the survey was to value the contribution of forestry products to the household economy. Forest products are defined as products found and used by local people in community forest areas. These include wood products as well as non-timber products such as tree and grass fodder, leaf and bark for medicinal purpose, medicinal plant and other plant products. Income for each household was measured in terms of all market as well as subsistence products from community forests. However, only few products i.e. firewood, tree fodder, grass fodder, and leaf litter have been found significance to household economy after the pre-testing of questionnaire.

Field data collection was carried out during September, October, November and December 2000. The main fieldwork was supplemented by two short visits: September-October (by two research assistants) and February (PI with research assistants) to clarify various concern rose during main survey and to perform barter game method in order to value some forest products. A total of 20 per cent households were randomly selected from each group. So the household level data for this analysis comes from a survey of 309 households belongs to three different stakeholder groups. Questions were asked to obtain information on four general areas: 1) demographic information; 2) land holding, tenure and off-farm production systems; 3) natural resource management and utilization; and 4) household awareness/participation in community forest management. Questions were asked on the household size, land and livestock holdings, firewood, grass and tree fodder and leaf litter collection and utilization pattern. Since both on-farm and off-farm agricultural activities are seasonal, care was taken to consider allocation of family labour seasonally. A large set of data related to consumption, production, and forest management decisions of household was generated. Thus, the data on biomass use are a combination of the survey questionnaire data and monitoring of actual use carried out by research team in the study sites.

Major constraints in the collection of household level data on forest use were the paucity of information about non-marketed forestry products, and in many cases lack of records on the inventory and extraction of subsistence products like fodder, grasses and leaf litter. In order to overcome this difficulty, the research team spent some time on consumption assessment at 24-hour intervals to collect supplementary information through weighing of household level use of forest products. Firewood was weighted at the sample household (only in three house in each group). On the day of measurement, the sample households were asked set aside the amount of firewood that would be used in that day. The wood was weighted and left next to the door. Households were asked to burn only the weighted wood or request to remember if the extra wood was burnt. On the following day the research team returned to each sample household and weighted the remaining wood or amount of firewood estimated to have been burnt. Since the amount tree fodder, grass fodder and leaf litter use is highly seasonal; respondents were asked to state their daily average consumption of these products both from community forests and private source. This was elicited mainly from household questionnaire (recall) survey. The Tole (hamlet) level meetings were held separately for men and women in a smaller and homogenous group. Key informant interviews were conducted to collect specific community level information and activities of the FUGs. Complementary information based on sample plot inventories assessed in one of the districts in eastern Nepal was referred to in order to check the validity of this data. Twenty-one out of 330 household questionnaires was discarded for the final analysis since they were incomplete.

6.3 Analysis of Household Benefits (Direct Returns) from Community Forestry

Economic analyses were performed in terms of use of different forest products such as firewood, tree fodder, cut grass, leaf litter, medicinal herbs and plants, timbers and some other direct and tangible benefits. In most of the sites, gathering activities include collecting firewood, tree and grass

fodder, leaf litter; and some herbal plant for medicinal purpose. However, the only ones of significant economic value are firewood, tree and grass fodder, and leaf litter. Biomass inputs in this analysis broadly categorised as tree woody biomass (for fuel wood and construction/fencing), tree leafy biomass (mulch and manure), shrub biomass (manure), and grass (mainly fodder/forage). Firewood includes freshly cut wood (kacho daura), dead branches and twigs (sukay daura) and crop and plant residue (jhikra) as described by Bajracharya (1980). Firewood is the main source of energy and used mainly for cooking household meals and snacks; animal feed preparation (kudo preparation for working oxen and lactating animals), space heating, some occupational use like firewood consumed by blacksmiths, local raksi (alcohol) maker and performing household ritual activities. Ground grass or grass fodder (ghas) refers to all non-woody herbaceous plants cut for animal feeding. It includes members of the grass and sedge families, a variety of legumes, and other broad leaf plants (Jefferson, 1983). Tree fodder comes from wide varieties of trees found in private land and community forests. Households in the study area use a combination of dry leaf litter, non-palatable green vegetative materials, crop residues and the remains of the uneaten fodder as animal bedding. The majority of bedding materials originates from forests, shrublands and grasslands. It is harvested by lopping and is gathered as litter.

Some direct costs; like labor costs and benefits such as; forest products have no fixed market price, as there is no bank credit, no paid labor force, or commercial product. In this context, a “shadow price” or opportunity costs of labor were used to estimate the total costs of resource extraction incurred by the user households. Firewood extracted by household from community forests were valued using the nearest market price deducting the costs associated with head transportation (Godoy et al., 1993) since forest-gate price was not available. Tree and grass fodder were valued through barter game method. It involves dividing the participants of group discussion into two groups i.e. buyers and sellers, with buyers purchasing the forest products in terms of commonly consumed goods with a well-known market value (Richards et al., 1999). Bags of rice were used in order to derive the market value of tree and grass fodder. Leaf litters were valued based on the opportunity costs of time spent in collecting a bhari (head load) of leaf litter. The cost involved in the entire process was divided into labor costs, cash or kind payment to FUG, and opportunity costs of labor time involved in traveling, collecting and processing of forest products.

a. Calculation of gross value of forest products: In order to measure year-round forest products harvested, the questionnaire were designed to elucidate information for 12 consecutive months because the amount of forest products collected varies with the season due to climate changes, user group regulation and seasonal agriculture work. The share of forest product going to household consumption and to market was evaluated separately. The distinction is important because goods for market and for the home should be valued differently. Fire wood consumed at home or exchanged with kin was valued at their retail purchasing price in the village, while quantity sold in the market were valued at their selling price (Chibnik, 1978 and Painter, 1986). Non-marketed NTFPs were valued by barter game method (Godoy et al., 1993).

b. Calculation of a gross margin from the CF: Gross margins from CF were calculated by substituting the cash costs associated with forest product harvesting and processing from the total gross value of the CF. To get an accurate measure of the marginal costs of extracting and processing forest products, the cost of materials (tools etc.), the labor time directly associated with finding, extracting, processing and transporting the goods from the forest to the village or to the market were evaluated. Since village wage rates vary with seasons, the average wage rate throughout the year is employed.

c. Calculation of gross value of products: The gross value of products of CF was calculated as

described above. Attention was paid to avoid unrealistic estimation because the accuracy of recall information drops when people are asked to remember events in the distant past (Bernard et al., 1984).

6.4. Socio-Economic Characteristics of Households

The unit of analysis is the household. Household head (generally husband and in some cases wives) was chosen as the respondent since they are the decision maker on behalf of the family. The major caste/ethnic groups in the area are Brahmin2, Chhetri, Tamang, Sarki and Damai. The predominant ethnic group of the study site is Brahmin, Chhetri, Tamang, Damai and Sarki. Mean household size was 6.38 persons. The average household size for the sample is greater than that of Nepal’s average of 5.3 members per household (Center Bureau of Statistics, 1995). Most interviewees could speak Nepali (more than 98 %), but some women belongs to some ethnic groups could not speak good Nepali. They speak their won local dialogue. Mean age of the interviewees was 43.7. The age distributions of sample households are presented in the following graph.

Graph 2 Age distribution of respondents   

AGE

85.080.0

75.070.0

65.060.0

55.050.0

45.040.0

35.030.0

25.020.0

60

50

40

30

20

10

0

Std. Dev = 12.88

Mean = 43.7

N = 309.00

The caste and ethnic groups represented, the number of households in each groups, and the percentage of the total households for the sample of 309 households are shown in Table 1. These data illustrate the diversity of caste groups in each study site. Caste determines cultural attitudes about cleanliness and religious ritual, and about dependency on milk as a major source of protein, characteristics that have some implications for fuel wood use for bathwater heating and livestock holding respectively (Lele, 1997). The data reflects the dominance of upper caste (Brahmin and Chhetri), which represented more than half of the sample of 309 households. Several minority ethnic groups appear under the Baisya and Sudra caste group in the sample for household included in the study. However, these ethnic groups are not mentioned in this table. The settlement patterns of each caste/ethnic group differ in a way that lower caste or households belonging to ethnic groups live in more isolated or higher altitude locations and the Brahmins and Chhetries frequently live near more accessible valley floors, which are often productive, and with infrastructure facilities.

2 Caste is centred on Hindu society, based on four primary divisions. These are the Brahmin (priests and religious leader), Chhetris (military and political leaders), Baisya (artisans) and Sudra (service people like blacksmiths, tailors etc.) (Collet et al., 1996). Traditionally Brahmin is higher caste and Sudra is lower caste and is considered to be untouchable.

Table 1 Distribution of household by caste (ethnic) group in eight study sites

_________________________________________________________________________User Groups Brahmin Chhetri Baisya Sudra_________________________________________________________________________1. Saradadevi FUG 15 11 2 22. Jayala Chiti CFUG 4 19 14 63. Mahadevsthan CFUG 21 3 2 54. Thuli Ban CFUG 39 9 2 85. Gaurati CFUG 0 4 25 06. Shree Chhap CFUG 21 10 11 07. Janghare CFUG 4 18 11 148. Karki Tar CFUG 14 11 2 2_________________________________________________________________________Percent in all sites 38 28 22 12_________________________________________________________________________

Table 2 presents the educational backgrounds of respondents in eight different study sites. About 30 per cent of respondents were illiterate, 40 per cent had some years of school education, 22 per cent had secondary level schooling, and only 8 per cent had college and university level education.

Table 2 Average educations of the respondents in eight study sites_________________________________________________________________________

Illiterate Literate High School College University (1-5 years) (6-10) (10+2)

________________________________________________________________________1. Saradadevi FUG 7 13 8 2 02. Jayala Chiti CFUG 4 22 10 2 53. Mahadevsthan CFUG 5 15 10 1 04. Thuli Ban CFUG 14 15 20 5 45. Gaurati CFUG 18 8 3 0 06. Shree Chhap CFUG 18 16 6 2 07. Janghare CFUG 19 21 7 0 08. Karki Tar CFUG 7 12 6 3 1_________________________________________________________________________% of household 30 39 23 5 3________________________________________________________________________

Table 3 illustrates the pattern of ownership of common domestic animals. Households owned livestock, regardless of whether or not they owned land. However, many lower caste households do not have any cattle. In general, households were more likely to have goat/sheep than any other farm animal followed by cattle and buffalo. Buffalo was the third most popular animal because it needs a substantial amount of fodder to survive well, and fodder is not easily available. Even then, the households kept buffalo for milk and manure. For many households, goat and sheep is a source of cash income as they can sell meat very easily in the local market. Goat and sheep, being small animals consume less fodder and unlike cattle, there is no religious restriction on slaughter. Very few sample households raised pigs. Animals were essential to the maintenance of hill agricultural systems and they provided animal traction for cultivation and were often used to assist in the threshing of grain. Livestock converted a combination of crop residue and tree, shrub and grass

products into manure and compost. Finally, they provide milk and meat products and a source of income and savings for household subsistence and economic and social obligation. Animals generally were managed under a combination of tethered or stall feeding and free grazing on pasture and private land. It was observed that those households owing larger areas of land also owned larger numbers of animals.

Table 3 Average livestock holding per household in study sites _________________________________________________________________________Income Group Cattle Buffalo Goat/Sheep Pig_________________________________________________________________________Poor 0.7 0.6 2 0.24Middle 1 1 3 0.06Rich 2 2 4 00_________________________________________________________________________

Table 4 provides a summary of the land tenure and land ownership the sample household for each stakeholder group. It was expected that the areas of land owned or farmed might influence forest, tree, and vegetation resource use directly through relationships between compost use and land area cultivated, number of trees on private land and area owned, possibly between animal numbers and land area. The average areas of irrigated land (khet) owned were 1, 4, and 11 for poor, middle and rich stakeholder respectively. Khet is land easily irrigated and predominately used for paddy rice production; bari land is commonly located higher on valley sides and is generally not irrigated but used for rain fed cropping. Kharbari land consists of grassed areas and fuel wood and fodder trees managed for thatch and grass cutting and supply fodder and fuel wood. Like in other parts of the country, it was observed that upper caste groups (Brahmin and Chhetri) hold more land in the study area than lower and occupational caste households.

Table 4 Average land holding according to income group. Land area in ropanis.

_______________________________________________________________________Income Groups Land holding (ropani)*

Irrigated Land Unirrigated Land Privateforest _______________________________________________________________________Poor 1 5 1Middle 4 5 1Rich 11 13 2_________________________________________________________________________*20 Ropani = 1 hectare

Household ownership of the different classes of land is summarized for the sample as a whole in Table 5. Some questions arise as to the accuracy of areas of private forest (kharbari) as these areas are not generally certified/titled on a household basis for taxation purposes. An examination of the table reveals that almost 15 per cent of the sample households do not have irrigated land (khet) – the most productive and hence valuable land suitable for multiple and intensive cropping of staple cereals including rice. An even larger percentage, 75 percent, claims no individual ownership of the private forest (kharbari) though it is quite likely many households have access to communally owned kharbari and pasture land.

Table 5 Distribution of household by land quality in all sites. Land area in ropanis._________________________________________________________________________

Land area Irrigated Land Unirrigated land Pvt. ForestNo. of HH % No. of HH % No. of HH %

_________________________________________________________________________0 45 15 10 3 231 74.8> 0 – 5 149 48 164 53 68 22> 5 – 10 80 25 76 25 5 1.62> 10 – 15 21 7 38 12 4 1.3> 15 – 20 9 3 13 4 0 0> 20 5 2 8 3 1 .33_________________________________________________________________________

Nearly all sample households, except landless, with private land holding (either khet or bari) have grown some trees in their private land. Most commonly these trees were grown around houses on the borders of household land and on bari land. Very few trees were grown on irrigated land (khet) due to the high value placed on productivity of this land and the unwillingness to reduce yields through competition or shading from trees. These trees were usually species valued for their fodder, timber or fruit. Households usually had somewhere between 20 and 100 trees on their private land, with most households growing between 20 and 50 trees. Although the number of trees grown by households at each site appears comparable, the species grown varies significantly between sites due to number of factors: local climate, household need, availability of alternatives, and intervention of forestry related development organizations like NGOs and forestry projects.

Table 6 Distribution of households by study site and the number of tree grown on private land_________________________________________________________________________User Group Number of trees

0 <20 21-50 51-100 > 100_________________________________________________________________________1. Saradadevi FUG 2 7 7 8 62. Jayala Chiti CFUG 6 14 10 5 83. Mahadevsthan CFUG - 3 8 7 134. Thuli Ban CFUG 1 13 17 10 175. Gaurati CFUG 1 11 7 5 56. Shree Chhap CFUG 1 10 18 9 47. Janghare CFUG 1 21 7 10 88. Karki Tar CFUG - 3 5 4 17_________________________________________________________________________Totals 12 82 79 58 78_________________________________________________________________________

The nature of local economies and variety of commercial and employment opportunities are reflected in the occupations reported by household members. The sites selected for the study are broadly representative of the village economies found in the two study districts. The most important occupations were farming and livestock production (more than 75 per cent), business (14 per cent), service in private sector (4), government service (4 per cent), and small-scale cottage industry. Wealthier households depend on agriculture, business and public service with better positions. Though some poorer households also reported employment as a public servant, they are engaged in blue-collar jobs like cleaner and office guard with low level of salary.

Table 7 Household occupations by income group_________________________________________________________________________

Occupation (%)*User Group 1 2 3 4 5 6__________________________________________________________________________Poor 67 7 5 7 9 1Middle 79 15 2 5 - -Rich 77 16 6 1 - -_________________________________________________________________________*Occupation: Agriculture = 1; Business = 2; Public Service = 3; Private Service = 4; Cottage Industry = 5 Agriculture + Business = 67. Results and Discussion7.1. Analysis of Household Level Benefits from Community Forests

Descriptive statistics of the study site provides information on heterogeneity among the households in terms of socio-economic endowments. There are large differences among households on land ownership, land characteristics (i.e. irrigated, unirrigated and private forest land), annual agriculture and livestock income. The large standard deviation in land endowments (11.24 ropani) of users provides a measure of inequality within the community. The differences between non-agriculture income (availability of alternative income-generating opportunity other than subsistence agriculture, ‘exit option’), number of trees in private land, livestock ownership and average distance between forest and household were noted. A large difference in quantity of various forest products distributed among the user households is also evident.

Table 8 Descriptive Statistics

Variables N Minimum Maximum Mean St DeviationEthnicity (1= Brahmin, 2=Chhetri, 3= Baisya, 4= Sudra) 309 1.00 4.00 2.08 1.03Age 309 22.00 84.00 43.63 13.07Sex (Male=1, Female= 2) 309 1.00 2.00 1.07 .26Education (# of school years) 309 1.00 5.00 2.12 .99Occupation* 309 1.00 6.00 1.45 .97Household size 309 1.00 16.00 6.5 3.4Total land holding (Ropani**) 309 00 85.00 12.86 11.24Irrigated land holding (Ropani) 309 00 50.00 5.39 5.88Unirrigated land holding (Ropani) 309 00 42.00 6.62 5.88Land occupied by private forest (Ropani) 309 00 30.00 0.90 2.72Livestock unit owned 309 00 15.00 3.06 1.98Annual income from livestock 309 00 156,000.00 21435.92 27366.77Annual income from agriculture 309 00 210,650.00 12912.03 24064.07Food security (< 3 months = 1; 3-6=2; 6-9=3; 9-12=4; > 1 year=5) 309 1.00 5.00 3.13 1.14Number of trees in private land 309 00 1632 87.91 142.42Cash income from forest products 309 00 30000.00 338.67 2028.35Non-agriculture income (exit option) 309 00 420,000.00 44264.26 58651.8Distance between CF and house 309 0.01 3.00 0.72 0.54Hired labour for CF (value) 309 00 480.00 16.02 62.11Type of membership in CF (member =1, 0=otherwise) 309 00 1.00 0.18 .38Seasonal migration (if) (migration = 1, 0 = otherwise) 309 00 1.00 0.83 0.38Annual transaction days spent in CF activities 309 1.00 149.00 13.5 16.58*Occupation: Agriculture = 1; Business = 2; Public Service = 3; Private Service = 4; Cottage Industry = 5 Agriculture + Business = 6**20 Ropani = 1 hectare

Households were asked to choose the most important activities in community forests according to their level and extent of active participation. I found that about 29 % of households belonging to poor stakeholder groups do not participate in any activities though they are eligible members of the group and pay monthly fees to the user groups. Due to a low level of representation of poorer stakeholders in the policy debate, they are unable to influence decision-making at all levels.

Records of the FUGs show that women and lower caste people are attending meetings, but often they –and also higher caste women- leave immediately after signing the register (Poudel, 1999). There are very few households from middle and rich stakeholder groups who do not participate in the stated activities. As high as 6 per cent, 17 per cent and 24 per cent of households think that they participate in every aspect of community forestry respectively from poor, middle and richer income group. Table 9 below shows the participation of households in various forest management activities according to stakeholder group.

Table 9 Percentage of households participating in various community forestry activities

________________________________________________________________________FUG activity Stakeholder group (%)

Poor Middle Rich________________________________________________________________________1. Does not participate 29 5 12. Forest management plan preparation 41 56 483. Implementation of decisions 20 16 214. Benefit sharing rule formulation 3 4 55. Monitoring and evaluation 1 2 16. Participation in all activities 6 17 24________________________________________________________________________

Interest in common property forests seems to vary for different income groups in conspicuous ways. It very much appears that poor stakeholders see forests as a source of their livelihoods more than anything else while for the elites, forests represent not only a source of forest products but they also have environmental value. Despite the difference in interest, it appears that the elite tends to take most of the decisions in user groups. The economically and politically empowered section of the community influences the entire decision-making process of community forestry. The management regime is directed towards production of intermediate forest products rather than cash generation, which is crucial for livelihoods of the poor. During the group discussion, it came to my attention that the poor marginalized and women members tend to remain away from meetings or remain mostly as silent observers. The active role of elite’s is partly because they tend to be nominated as committee members who are formally assigned to a more active part in decision-making process. Therefore, apart from the inequality within community, another major factor limiting equity within community is the exclusion of the poor from decision-making processes. During the group discussion, it is revealed that richer people tend to favor a higher price for the forest products, or at least they have no problem if the price is fixed at a higher rate owing to their greater wealth. They favor more restrictions on availability or would not mind restrictions because of the alternative forest products for them from their private land. Poor people, on the other hand, normally favor lower prices and less restricted access.

7.1.1. Average Values Extracted from Community Forests

Average gross value per household and per hectare of community forest is illustrated in Table 10. I also estimate average gross margin per person per day from community forests. There appear to be four distinct forest user groups based on gross value of products for each household. Shree Chhap and Karki Tar FUGs get considerably higher gross values per household than remaining user groups. This implies that households are more dependent on forests in these sites despite the low level of gross value per hectare of forest. A very low return to the labor in Shree Chhap and Karki Tar FUG is observed despite a very high level of gross value per household. This can be explained

by the fact that subsistence forestry activities are very attractive in these two sites where opportunity costs of labor is relatively lower than other sites. FUG members had very few alternatives in spite of the low per hectare value of their forest. There is also noticeable variation in the values per hectare of forests. This is due to the forest type, quality and species diversity, which may influence forest productivity.

Table 10 Gross values per household and per hectare of community forest, and gross margin per person per day (in Nepalese rupees*)________________________________________________________________________________User Group Gross value Gross value Gross margin

Per household per hectare of forest per person/day________________________________________________________________________________Saradadevi CFUG 5589 3810 125Jayala Chiti CFUG 5828 9668 111Mahadevsthan CFUG 13917 5971 106Thuli Ban CFUG 9875 10607 100Gaurati CFUG 16398 5355 98Shree Chhap CFUG 33177 - 73Janghare CFUG 17418 6602 97Karki Tar CFUG 29857 4674 94________________________________________________________________________________Average for all sites 16507 - 101________________________________________________________________________________* 1 USD = 73.00 Nepalese Rupees

7.1.2. Gross Margin Per Household

Gross margin from community forestry to different stakeholder groups is presented in Table 11. Gross margin value was computed as gross value of production for each household minus the cash costs like hired labor costs, direct cash payment to FUG for various forest products like fuel wood, fodder and grass and forest user group membership fee. The results confirm that poorer households are getting lower gross margins from community forestry. Income from community forests increases gradually as I move from lowest to the highest income group. This may be due to the fact that poorer households have less land and livestock ownership and they could not use intermediate forest products like fodder, leaf litter and grasses3 which constitute a major portion of the income from common property forestry. Although poor households are more dependent on community forest for fuel wood, in addition to fuel wood big farmers graze more animals, collect tree and leaf fodder and sell milk, which has a good market opportunity (see Jodha, 1995, Heltberg, 2001). My finding are similar to that of Richards et al. (1999) who confirm that poorer households are currently benefiting less from community forestry mainly because they have less livestock and farm land, which provide the main farming system demand for forest products.

Table 11 Average gross margin per household (undifferentiated by study sites)________________________________________________________________________Income Group N Gross Margin per household (Rupees*)________________________________________________________________________3 As estimated by Central Bureau of Statistics (CBS), the value of fodder obtained from the community forest (grass, tree fodder and leaf litter) was about Nrs. 2.3 million in 1994. Leaf litter is collected from the forests as bedding material, which is subsequently used as organic manure to be applied in the field. Similarly, about 40 % of livestock feed is obtained from the forests and trees grown on the farms. The net nutrient return to agricultural fields from the forest is estimated to be about four tons per hectare per annum in the eastern hills (Chapagain et al., 1999).

Poor 81 7755.82Middle 136 14814.58Rich 92 24466.43________________________________________________________________________

7.1.3. Share of Livestock Related Products

As I discussed earlier, a higher proportion of household level income from community forestry comes from either fuel wood or livestock related products such as tree fodder, cut grass and leaf litter. Table 12 shows the percentage of gross value for each stakeholder group coming from the extraction of tree and grass fodder and leaf litter. In most cases livestock-related products represented more than 60 per cent of the gross value of production. However, proportion of gross value from livestock related products increased with wealth, as richer household’s income constitutes almost from tree and grass fodder and leaf litter as bedding materials. It is apparent that richer households are more dependent on community forestry in absolute terms than poorer households. It is also clear that non-timber forest products (NTFPs) do not contribute to household income despite government’s recent effort to assist forest user groups to manage community forests in such a way that it generates cash income for the poorer households.

Table 12 Percentage of CF gross values from tree and grass fodder and leaf litter ________________________________________________________________________Income Group N % of gross values from livestock products________________________________________________________________________Poor 80 63Middle 134 78Rich 92 85________________________________________________________________________

7.2 Transaction Costs and Community Forestry Management

The concept of transaction costs originated from Coase’s 1937 article “The Nature of the Firm”. Coase underlines the important role of transaction costs in the organization of firms and other contracts. He found that firms emerge to organize whenever their costs were less than the costs of carrying out transactions through the market. He explain the firms emerge to economize on the transaction costs of market exchange and that the “boundary” of a firm or the extent of vertical integration will depend on the magnitude of these transaction costs (Kherallah and Kirsten, 2001). Coase’s theory has been later developed by Coase (1960), Alchian and Demsetz (1972), Cheung (1969, 1983), and Williamson (1975, 1985). Arrow (1969) defines transactions costs as the costs of running the economic system. North (1990) divided the total costs of production into transformation costs, the costs of inputs of land, labor, and capital involvement in transforming the physical attributes of a good, and transaction costs, the cost in defining, protecting, and enforcing the property rights to goods. Transaction costs, therefore, include the costs of information, negotiation, monitoring, coordination, and enforcement of contracts (Kherallah and Kirsten, 2001).

Resource users enter into various kinds of explicit and implicit agreements in order to initiate collective action or agree to exchange or transfer goods or services, which requires immediate and costly contributions. These contributions will be incurred in the form of negotiation, monitoring and enforcement costs, which can be a significant part of the resource use. Hanna (1995) describes four different resource management stages in which variable transactions costs are incurred. They are the description of the resource context, regulatory design, implementation, and enforcement of agreed

upon rules. Description of the resource context includes a description of resource users, processors, markets, and the analysis of social and economic characteristics of all resource interests. Designing the regulation requires information describing the resource context and is dependent on the quality of contextual information provided. Implementation of a regulation is a critical test of a regulation’s fit to its contexts. Monitoring and enforcement of a regulation is a final area of transaction costs and monitoring compliance with regulations will be excessively costly if monitoring systems are not designed to be consistent with resource dynamics or users operation (Hanna, 1995).

In many field settings, efficient management of common property resources is often challenged by various sources of uncertainty that result in high transactions costs of resource management. For individual resource users, the transactions’ costs of resource management are related to participation, opportunity cost of time involved in meetings, time required to acquire information and communication, direct monetary expenses for travel, communication and information. These costs are directly related to management effectiveness and efficiency of a collection action, and at the community level these costs are borne by poor community members. It may happen easily happen that benefits from collective action are exceeded by transaction costs (Hanna, 1995). In most of the community-based resource management systems with an initially degraded resource base, the costs associated with management are reported to be higher in respect to the expected benefits. Nonetheless, in many economic models, physical input and property rights are taken as variables and transaction costs of resource management seldom incorporated in the ‘price’ of resource consumption, though they can be a significant component of resource use. Despite the importance of transaction costs on resource management, transaction costs incurred in community-based forest management is often not incorporated into economic analysis. Including these prices in an economic study may enable us to explore the nature of transaction costs in collective action and its significance on local level resource management.

In this section, I attempted to include recurrent annual transaction costs of community forestry into this analysis. Two broad types of transaction costs were considered. Transaction costs of decision-making (TCD) and transaction costs to implement those decisions (TCI). The decision costs (TCD) includes costs incurred during the process of acquiring various information and costs of coordinating the activities like resources spent for meetings, settling conflicts, etc. and transaction costs of implementation (TCI) of those carrying out implementation activities to comply with the management decisions made. Transactions’ costs, therefore, were simply measured in terms of labor opportunity costs of time spent in various community activities like community meetings, time spent to acquire information, communication, and time spent in obligatory forest activities (planting, protection, weeding etc.).

7.2.1 Number of Transaction Costs Days Spent in CF Activities

Table 2 gives a break down of the time spent on the various activities of community forestry. It is clear that meeting, resource maintenance and monitoring take up the bulk of the time as they are continuous activities and crucial for the maintenance of the institution. In most forest user groups, attending the community meetings to decide various implementation activities remains one of the major activities. These activities include the consensus towards operational rules preparation, distribution of products, management of community funds, attending FUG monthly assembly, and so on. Among the most evident transaction costs are effort and time spent in lengthy discussions at the meetings and assemblies as well as in protracted mediation procedures to settle interpersonal conflicts. These costs obviously increase when new economic opportunities cause the value of time to rise significantly.

From the Table 13, it is apparent that resource maintenance is the major activity in which households spend considerable time, followed by meetings and monitoring. In fact, costs incurred due to participation in various forms of meetings and monitoring take up more than half of the total time of the users involved in community forest management. Since social conflicts can emerge in a number of forms within user groups including conflicts between different interest groups, disagreements between the executive committee and the general body of users and conflicts between the user groups and outsiders, community meetings are general features of all FUGs. The large standard deviations for all activities except resource maintenance indicates the disproportionate (higher degree) participation of socio-economically and politically influential households in activities related to decision-making. However, in the case of obligatory forestry works (resource maintenance) every household contributed labour regardless of their wealth. This again confirms that better off households are influential important decision-making. Despite their absence from decision-making (in many cases), however, poorer households equally participate into specific activities like forest resource protection and development. Protection of bounded area is usually done by employing a guard, with CFG members contributing the wage, or by forming a patrol group from among the member households.

Table 13 Breakdown of time spent on activities in community forestry system (days)

User Groups Information Gathering*

Attending Meeting**

Travelling Monitoring! Resource Maintenance+

Mean SD Mean SD Mean SD Mean SD Mean SDSaradadevi 1.03 2.67 5.17 6.33 0.30 1.15 2.53 5.25 1.7 3.22 Jayala Chiti 0.47 2.35 3.05 3.58 0.47 2.39 1.79 5.65 2.54 4.36Mahadevsthan 0.45 1.82 3.68 5.02 0.45 1.43 1.00 2.54 7.32 2.13Thuli Ban 0.38 1.14 2.81 3.4 0.16 0.74 0.38 1.18 5.95 4.91Gaurati 1.79 2.6 6.62 7.56 1.17 3.70 1.52 3.46 4.58 3.77Shree Chhap 0.45 1.71 4.88 4.41 0.41 1.73 4.6 7.61 6.33 2.6Janghare 2.32 9.01 4.36 5.13 1.0 3.23 5.6 12.22 4.74 7.42Karki Tar 1.07 2.39 5.24 4.79 0.79 2.24 6.38 11.47 4.69 2.87Average to all sites

1 2.96 4.5 5.03 0.60 2.08 3 6.17 4.73 3.91

* Including communicating** Including conflict resolution! Protection, watching, patrolling etc.+ Planting, weeding, bush cutting, forest trial route maintenance etc

7.2.3. Transaction costs (differentiated by forest user groups)

Table 14 shows the transaction cost of resource management for different categories of users. Of the 8 forest user groups studied, transaction costs of resource management are lower for the poorer household in 7 forest user groups. This finding indicates that poorer households share less decision-making costs than their richer counterpart and they have less involvement over-all in the community forestry process. This is partly due to the high opportunity costs of labor faced by poorer households who need to work daily as wage-labor in order to raise cash for their subsistence. Transaction costs for rich and elite households seem to be quite high and sometimes can be up to 66 days. This indicates that the economically privileged section of the community makes most of the decisions regarding forest management. Despite having their own resources to fulfill forest product requirements, why community elites tend to invest a considerable amount of time in collective action and whether the dominance of traditional elites is good or bad is not clear.

Table 14 Annual transaction costs (differentiated by user group and stakeholder group)________________________________________________________________________User Groups Annual transaction costs (NRs. 000)

Poor Middle Rich________________________________________________________________________Saradadevi CFUG 392 961 2236Jayala Chiti CFUG 436 756 1023Mahadevsthan CFUG 912 1118 1178Thuli Ban CFUG 821 789 901Gaurati CFUG 1789 1323 1225Shree Chhap CFUG 559 1870 998Janghare CFUG 1077 731 5475Karki Tar CFUG 538 1339 2270________________________________________________________________________Average for all sites 816 1227 1913________________________________________________________________________

7.2.4 transaction costs as a percentage of total costs

I further calculate the annual transaction costs as a percentage of total costs for three different stakeholder groups. This result is presented in Table 15. In contrast to above, transaction costs, as a percentage of total costs is significantly higher for poorer households than those of middle-wealth and richer households. In higher income groups, users are putting much more resources in harvesting various intermediate forestry products and they also employ hired labor for various forestry operations. So the average forest operation cost for richer households is far greater than that for poorer households. Variation in forestry operation costs for the three different stakeholder groups can also be explained by economies of scale of these groups in respect of common property forest use. In this case, transaction costs were relatively low as a proportion of total costs, usually less than 9 %. However, in a situation in which poorer users are getting very few products (mainly firewood as opposed to other intermediate products like fodder, leaf litter and cut grass), transaction costs, as a proportion of total costs can be significant- up to above 13 % of total costs. Since transaction costs of forest management are also a function of social capital within the community and quality of forest resource itself, variation in transaction cost days in different forest user groups can be explained by the level of social capital4 and forest condition in these communities, which reduces the transaction costs of collective action. Table 15 Transaction costs as a % of total costs________________________________________________________________________Income Group N Transaction costs as a % of total costs________________________________________________________________________Poor 81 13.9Middle 136 11.9Rich 92 8.6________________________________________________________________________ 4 Social capital comprises features of social organization such as networks, norms and social trust that can improve the efficiency of community by facilitating cooperation and coordination of relations between actors and among actors (see Coleman, 1990; Putnam, 1993). Social capital is also productive since it makes possible the achievement of certain outcomes that would not be attainable otherwise (Coleman, 1990; Molians, 1998) and it also reduces transaction costs of collective action.

7.3. Determinants of Income from CPR: An Econometric Analysis

In this section, I am interested in exploring the determinants of income in community-based common property forest management through econometric analysis to gain an understanding of the relationship between forest dependency (measured by household level benefit from community forest) and socio-economic variables. Though theory and empirical evidence on the socio-economic factors influencing household level income from community-based forest management have drawn little attention in social science literature, there is limited prior knowledge on socio-economic determinants of forest dependency and nature of their impacts (Gunatilake, 1998). So the scatter plot method was used for preliminary scrutinizing of the independent variables as there is limited knowledge about the relationships. Multicollinearity was checked using the covariance matrix of independent variables. A post-mortem examination of residual squared was done, as there is limited knowledge about possible heteroscedasticity in the data generated for this analysis (see Gujarati, 1995 and Field, 2000). The analysis provides an indication of a situation in which the assumptions of linearity and homoscedasticity have been met. I assume the Cobb-Douglas production function in order to undertake the empirical estimation.

The result for determinants of household income from community forestry is given in Table 16. The adjusted R-square for the estimation is as high as 40 %. The difference between R2 and adjusted R2

is small, which indicated that there are sufficient numbers of observation the model given the number of independent variables. It is evident from the analysis that the three most important variables are significant with the expected sign: LANDHT, LIVEST, EDU, ETHNI, DIST and TRANSDAY. In particular, household level income from community forests is directly related to the amount of land owned; number of livestock, ethnicity of the household, distance between forest and household and finally transaction cost days spent by households in various community forest related activities. Difference in benefits from community forest is thus correlated with differences in agricultural assets. Higher caste households are benefiting more from community forestry than lower caste households. This can be explained by the observation that lower caste households have very little influence in decision-making processes so that they cannot influence forest management decisions in their favor. Moreover, poor and lower caste households especially the landless who do not keep livestock are not benefiting from such products. Since lower caste and poorer households appear to extract less fodder, cut grass, and leaf litter, regulated community forest does not contribute significantly to their income. Though they would be doubly disadvantaged without common property access to forest, an unnecessarily protection-oriented management regime could not help the livelihood of particular sub-groups of community. Most of the forest user groups have introduced controls limiting extraction of forest products and introducing payments for extraction rights to some of the products, on which landless people were depending. As a consequence, access of poorer traditional users seems to be somewhat reduced or became more expensive.

Regarding gender, it is noteworthy that those households headed by male members are benefiting more from community forestry than those with female heads. I observe very low level of involvement of women in the entire decision-making process. Women’s absence from FUG decision-making means that they have little to say in distributional rules. Moreover, women may not travel as far as men to extract forest products due to the additional travel time involved, and other household responsibility. During field observations, I observed that female-headed households on average are poorer and they are obviously low on male labour.

Table 16 Econometric estimates of the determinants of income from community forest ________________________________________________________________________________

Independent variables Coefficient Standard error t-ratio P-value________________________________________________________________________________Constant 6.68 0.64 10.47 .000

LANDHO 0.30 0.08 3.53 .001

LIVESTO 0.34 0.10 3.29 .001

GEND 0.87 0.22 3.88 .000

EDU -0.54 0.14 -3.77 .000

DIST 0.12 0.06 1.95 .052

TRANSDAY 0.38 0.07 5.49 .000

EXITOP 6.312E-02 .06 1.06 .29

ETHNI -0.16 0.19 -0.84.40

LQUALITY -0.25 0.18 -1.40 .16

HSIZE -0.18 0.14 -1.22 .22________________________________________________________________________________Log-Log Regression F (10, 211) = 10.69 R2 = .40________________________________________________________________________________

With regard to the ‘transaction costs day (TRANSDAY)’ variable, households who spent a lot of time on decision-making activities often appear to spend more time on forest product collection effort. Households get correct information by engaging in the decision-making process about when and where to collect. This might increase the household’s collection effort. Education is negatively and significantly related to forest income. Better-educated households may have better earning opportunity outside the village commons and forest extraction activities may be less attractive for those households. However, the ‘exit option’ variable is negatively related to forest incomes. This shows that households who enjoying outside income earning opportunities are equally deriving benefits from the commons. Distance shows a positive relationship indicating that households near to the forest resource systems are deriving higher level of income than that of living far away from community forests. Household heads leadership quality and household size are negatively related to income from community forests. This finding is just opposite what was expected before.

There are mixed results regarding distribution of products from community forests among the members. Out of the eight forest user groups, inter-household allocation of forest products is based upon the principle of equality in seven forest user groups. This means every participating household is getting an equal amount of products regardless of their family size and other local differences, even though most of the household belonging to poorer income groups were not able to derive benefit from intermediate forest products. There is great deal of variation among forest user groups in terms of rules for collecting various forest products. In some cases, people are allowed to collect products at certain intervals while in others forests remained open throughout the year for the collection of grasses, leaf litter and dead twigs. There is a common tendency that most of the user’s

committee denied a certain commodity to a specific interest group, for example committee might deny charcoal to the blacksmith despite provision in the operational plan. This raises the important question of equity. Most of the executive committee members are generally more comfortable with equality than equity. However, there is strong debate within the community upon what is equitable and what is not. It was observed that for the elite and wealthier people, equity might equate to equality of opportunity. They assume that there should not be any problem from any corner as long as the norms apply to everyone regardless of their residence, ethnicity, occupation, and economic background. Moreover, according to this view point the system cannot be tagged as inequitable if, for example, forests are closed forever or if products are priced quite high. However, the poor users do not agree with such definitions. For them, increased availability, lower level of restraint and more democratic decisions are prerequisites for an equitable system.

8. Conclusions and Policy Implications

In this paper I intended to address economic condition for exploiting the local commons. I examine the relationship between socio-economic conditions and constraints of household, in particular, ownership of land and livestock assets, and access to and control over local commons. In other word, I have been concerned to examine the relationship between household socio-economic characteristics and access to and income from community-based forest management. It appears that households dependence on community forests in most of the study sites is for fuel wood, tree fodder, cut grass, leaf litter and to some extent auxiliary non-timber forest products with a major proportion of household benefit being contributed by fuel wood, leaf fodder and grass and leaf litter. The result shows that forest product utilization pattern is quite different among the various income groups. I thus claim that the results are in harmony with my theoretical argument that poorer people are currently benefiting less from community forestry than relatively better off household.

Differences in benefits from community forestry seem to be correlated with differences in capital and asset holding. FUG members with big land holdings and ownership of livestock, benefits highly from intermediate forest products like leaf litter for composting, fodder and grass for domestic animals. This study therefore shows that land ownership, livestock holding, and ethnicity of household are important variables that explain household level income from community forests. Those with more land benefit highly from leafy grass biomass, as it maintains physical productivity of depleted soil. Relative to higher land and livestock holders, extraction of various intermediate products (tree fodder, cut grass, leaf litter etc) by poorer households is very little and restricted to certain products, generally lower, with probably no benefits for landless households. Previous explanations on resource dependency hypothesis asserted that poor people are heavily depended on resource and derive considerable benefits from the local common resource. In this paper, I show the peculiar link between household assets and access to and control over resources available from the commons.

I challenge the preposition that poor always benefits more from community owned resources since there is a kind of misconception that all users in a community will get substantial benefits if resources are held under community ownership. Though the traditional systems of forest management were more equitable and accessible to all community members, I observed that formal systems of community-based forest management marginalized the weaker section of the community. Wealth might also affects private benefits from commons indirectly, through social relations with one group to another, when users attempt to deal with collective action dilemmas associated with joint use of the common resources. The initial findings of this study indicate that impact of common property forest management seems to be ambiguous. While common property

forest management seems to be good for the forests and local environment, a fundamental question remains about the distributional aspect of community-based resource forest management. Generally, this study provides empirical evidence that a formal system of community-based resource management does not necessarily support livelihoods of the very poor in contrast to what is generally claimed be to the true in most common property literature. Though the Nepal Government’s Ninth Plan stressed the effective role of community forestry in poverty alleviation and income of the rural poor, this study shows that community forestry is not able to provide a significant contribution to the poorer households.

This study also attempts to incorporate the transaction costs associated with community-based resource management. The results show that transaction costs of community-based resource management can be a significant part of resource management costs, which is generally ignored in economic analysis of participatory forest management. It is often argued that the costs of privatization of communal resources (fences, measurement, title insurance, record-keeping) are greater than those of the collectively managed common property resources. However, when various hidden costs associated with community-based resource management are incorporated into economic analysis, a somewhat modified picture appears. A common property regime would not have the need for extensive records on boundaries and sales, but instead require meetings and discussions where the co-owners decided their strategies for the coming period (Bromley, 1991) which may constitute a significant portion of costs of resource management. Activities like meetings, obligatory forestry activities and monitoring take up the bulk of the time as it is a continuous day-to-day activity and it is crucial activity for the maintenance of CPR institutions.

Regarding heterogeneity and success of collective action, my findings suggest that economic (land, livestock) and social heterogeneity (ethnicity, caste, education etc) has more influential impact on household level income from CPR than other factors as evident from econometric analysis. Household labor contribution to various forms of community forestry activities indicates that wealth inequality does not affect the extent of cooperation as poorer members are equally contributing as much as that of wealthier households. However, wealth inequality does matter especially in time of exploiting the common property resources. The basic reason of this is following. Firstly, most of the poorer households (especially landless) are not able to internalize the benefits generated from intermediate forest products, which provides the biomass need of agricultural households. Management regime of community forest is disproportionably biased towards the production of timber and leafy biomass rather then non-timber forest products, which can contribute income to the poorer households. Secondly, equity aspects of community-based resource management are largely ignored since there is no compensation mechanism to the losers despite their cooperation and contribution to the improvement of resource base. It can be concluded that poverty always do not hinder the cooperation in issues of local level collective action. Although poverty increases the marginal relative value of a unit of resource harvested from commons, it will be prejudicial to view poor people as an agent of resource destruction. Ignoring the institutions that encourages the enegalatarian access to and control over common property resources and blaming poverty might encourages the sub optimal policy prescription. I reconsider the issue of persistent socio-economic inequality in communities and argue that restricting the access of poor people through changes in property rights structure in common property resources is likely to increase the level of poverty unless specific measures of compensatory transfer schemes are in place to safeguard the interests of the most vulnerable section of the community.

My results regarding heterogeneity and distributive issues of collective action have important policy implications for community-based resource management initiatives, especially those aimed at shaping resource use decisions by households and poverty reduction through better management of

local commons. One of the important implications of this study is that intervention seeking to reduce poverty in a forest dependent rural economy need to reduce heterogeneity among user households and improve both productivity of forests and distribution systems. Since poor people do not get substantial benefits from agricultural related forest products, forest management policy needs to be directed at increasing alternative forest products, mainly non-timber forest products (NTFPs) that play a significant role in rural livelihoods. Although the importance of NTFPs is being increasingly recognized for their role in poverty alleviation and biodiversity conservation, existing community forestry policies in general and NTFP regulations in particular seem to be incompatible in meeting these goals. The existing management regime emphasizes control in extraction, use, trade and marketing of NTFPs. Poor people involved in NTFP trade are often discriminated against and excluded from access to available incentives and other forms of support (Sharma, 1999). In most of the cases, private collector parties are given exclusive collection rights in preference to poorer FUG members, which reduce the options for the poorer households. Complex formalities and procedures for transport and trade of products are not conducive to sustainable management of NTFP. On top of that, the Master Plan for the Forestry Sector in Nepal (MPFS, 1988) has emphasized the supply of fuel wood, fodder and timber as a main priority of community forestry, while giving less attention to enhances income and employment from high value NTFPs. In this regard, the criteria of ‘accessibility’ and the size for manageability in case of NTFP focused management of community forests should be different from traditional forestry for timber and fuel wood (Ojha, 2000). This indicates that existing criteria of community forestry in promoting NTFP related products is not compatible and it could not help in designing the support programme to promote income-generating activities through the sustainable use of NTFPs. This means that government policies related to community forestry and NTFPs need reorienting to address these needs, which are ultimately linked to legal access and use rights and availability of such products on a sustainable basis. Another important policy implication of this result is the need to reconsider household and community characteristics and respective management regime while handing over the forests from government ownership to community management. Equally important is supporting and empowering forest users groups in various aspects of community-based forest management, which especially focuses on poorer forest-dependent communities so that their interests are adequately represented in forest planning and management decisions. REFERENCES

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