0853-A1

Production functions for multiple outputs of joint forest management

Dinesh Misra and Shashi Kant ¹

Abstract

Forests, even though critical for survival of mankind due to their multiple outputs, are shrinking at an alarming rate all over the world, most likely because of inappropriate institutional arrangements. Joint Forest Management (JFM) has been argued to be an optimal institution for economic, ecological and social sustainability. However, this argument has not been supported by holistic studies covering all three types of outputs and factors other than physical inputs. In this paper, production functions, covering economic, ecological and social outputs, are estimated for the forests managed under the programme in Gujarat state of India. The estimation of production functions includes physical factors as well as social, political, economic, institutional and organizational factors. The indicative measures of all the outputs and factors are identified, and methodologies for their quantitative or qualitative measurements are discussed. Summary statistics of data from 50 randomly selected JFM villages, in Gujarat state, are provided. Results of the production functions and their policy and management implications are discussed.

1.0 Introduction

Joint forest management (JFM), characterised by multiple - social, economic, and physical (biological) - outputs, has emerged a promising approach to address the problems of forest degradation in developing economies, and has attracted the attention of scholars, forest managers, and donors. In the last decade, numerous studies (Kant et al. 1991, Chaturvedi 1993) have focussed on issues associated with JFM. But, most of these studies are single-dimensional: sociologists have examined social issues such as caste composition and gender distribution (FPCs) (Brahmi et al. 1997), economists have addressed economic issues such as income generation (Datta and Varalakshmi 1999), and foresters have confined themselves to silvicultural or technical issues (Chaturvedi 1993). Similarly, all the studies have focussed on physical outputs such as timber (Li and Lofgren 2000), and wildlife (Hof and Joyce 1992) or environmental services. No study has attempted to analyse multiple-outputs of JFM together and establish relationships between multiple-outputs and a set of inputs containing social, economic, cultural, organizational, market related and physical inputs of JFM. However, JFM is not limited to physical products only, and includes community empowerment, in terms of sharing power and responsibilities related to forest management, economic development of local communities, and meeting the local requirements of forest produce.

In the context of forest resources, Kant (1999) demonstrated that total production process would also include non-neo-classical inputs such as homogeneity of the user group with respect to resource and the direct dependence of the user group on the forest resource. But, none of the existing studies on JFM has attempted to include these inputs. Hence, economic analysis of JFM requires inclusion of physical, social, and economic outputs as well as neo-classical factors (land, labour, and capital) and non-neo-classical (social, cultural, organisational, and institutional) factors.

This paper attempts to fill this gap in forest economics literature by developing a theoretical framework for production functions for multiple outputs of JFM that captures transformation process as well as transaction process and to empirically estimate the production functions for multiple outputs of JFM in Gujarat state of India.

Next, preliminary theoretical concepts of production functions of multiple outputs of JFM and associated neo-classical and non-neo-classical factors are developed. Second, a methodology to empirically estimate the production functions is discussed. Third, estimated production functions for three outputs are presented and discussed. Finally, significance of the research is highlighted.

2.0 Theoretical Framework for Production Functions of JFM

A theoretical framework for production functions of JFM will involve identification of outputs, and a theoretical model explaining relationships between outputs and factors.

2.1 Multiple Outputs of JFM

The outputs used in production analyses should capture the objectives of JFM and the prevalent forest policies. Hence, the three outputs of JFM that cover the main objectives of the 1988 Indian National Forest Policy (NFP) (GOI 1988) are - social empowerment (Y1), forest canopy cover (Y2), and supply of forestry products to meet the local requirement (Y3). Each of these outputs and theoretical arguments for their inclusion are briefly explained below.

2.1.1 Social Empowerment (Y1): The first (motivation of the local people to identify themselves with forests) and the second (sharing of power and management responsibilities with local communities) objectives of the NFP imply sharing of mainly protection responsibilities between the Government and the local community. The co-operation of the villagers is mostly sought by forming a village level committee, which collectively guards a particular forest area in lieu of a share in the final produce. In literature, close correlations have been demonstrated between empowerment, community action and identification with a common good (Itzhaky and York 2000). Perkins and Zimmerman (1995) defined empowerment as "a process by which people gain control over their lives, democratic participation in the life of their community, and a critical understanding of their environment" (p 570). The connection between participation and empowerment finds support from many other studies also (Zimmerman 1990). Thus, participation in communal activities has strong linkages with empowerment, and implies inclusion of this variable as an output in our analysis.

2.1.2 Forest Canopy Cover (Y2): The third objective (protection and development of forests) of the NFP implies inclusion of physical outputs such as improvement in canopy cover, growth and regeneration status of forests. This objective will be captured by forest canopy cover (Y₂) as a physical (biological) output, and will be expressed as a percentage.

2.1.3 Supply of Forest Products to Meet the Local Requirement (Y₃): The fourth objective of the NFP (supply of forest products to meet local requirements) would justify inclusion of physical outputs such as timber and minor forest produce (MFP) as one of the outputs of production process of JFM since the forest dwelling communities are dependent upon forests primarily for food and shelter (Kant et al., 1996). For the MFP output, a composite basket of produce will have to be constructed based on the economic contribution of some of the important MFPs that the people collect in the area. If some of the local requirement of above outputs is being met from non-forest areas also, only the contribution from forest under JFM to the total requirement (Y₃) will be taken as the output.

2.2 Theoretical Model for Production Functions:

The complete production model requires the relationships between these three outputs and all factors, social, economic, cultural, organisational, market factors, and physical factors, associated with transformation and transaction processes. These factors and their relationships with the three outputs are discussed next.

2.2.1 Social factors: Normally, homogenous user groups, due to low transaction costs, find it easier to organize and sustain collective action and JFM. Homogeneity with respect to income disparities and locational differences (Verughese, and Ostrom, 2001), and in terms of ethnicity, caste, and religion, existence of marginal groups play an important role in collective action. Hence, the homogeneity of the user group (X₁) in terms of ethnicity, caste, and religion, existence of marginal groups, economic diversity, and spatial distribution of the user group with respect to the forests is taken as a factor, and it is hypothesized that the social empowerment will increase with homogeneity.

2.2.2 Economic factors: Dependence of the user group on forestry outputs both for consumption items as well as for monetary income as measured by share of forestry income in total income have been recognized as important factor for JFM (Kant et al. 1991). The total dependence of the user group on forests will be taken as a factor (X₂). The greater the dependence, the higher is the stake in sustainable management of the resource and, therefore, it will have positive bearings upon both canopy cover as well as the supply to meet primary local requirements of forestry products.

2.2.3 Cultural factors: The village leadership and its support to forest management have been found to be important factors for JFM (SPWD 1992). Village leaders were important in overcoming intra-village tensions over resource use and promoting successful forms of community action (Jewitt 1995). Hence, existence of village leadership and its dispensation towards JFM will be an input (X₃) affecting canopy cover and the supply of forest produce to meet demand.

Conflicts are bound to arise in JFM where different groups of appropriators draw competing outputs from the resource. Appropriators should have rapid access to low-cost conflict resolution mechanisms for effective JFM (SPWD 1992; Ostrom 1992; Rastogi 1999). Hence, existence of effective conflict resolution mechanisms (X₄) is another cultural factor that will increase social empowerment.

2.2.4 Organisational factors: The support of forest bureaucracy (X₅) is a critical factor in the JFM (Kant et al. 1991). However, this will mainly affect the canopy cover output only. However, knowledge and clarity of government orders (X₆) is another organisational factor (Kant et al. 1991), which will have positive impact on empowerment as well as canopy cover. Existence of non-government organisations as an input (X₇) finds support from Shah (1996) among others and will affect the supply of forest produce to meet local demand. However, the sign of the coefficient of this factor will depend upon the nature of NGOs, economic development based NGOs will lead to increase in supply of forest produce while forest conservation oriented NGOs will contribute to the reduction of forest produce. Similarly, existence of forestry enterprises (X₈) is other organisational factor affecting the JFM in two ways: (i) it is an indicator of economic development and subsequent social empowerment, and (ii) it provides a ready market for forest produce and may divert the forest produce from meeting the household requirements to the industry. At the same time, it may encourage preservation of the resource in the long run and, therefore, it will affect the supply of forest produce to meet the primary requirement of forestry produce. The sign of the coefficient associated with it will depend upon the types of enterprises existing in the area as well as their level of operation.

2.2.5 Market factors: Similar to the existence of forestry enterprises variable, the existence of local markets of forest products and the distance of market from the forest areas will affect the JFM through their influence on the management and institutional arrangements for exploitation and appropriation of produce (Verughese, and Ostrom, 2001). Hence, the existence of local markets (X₉), the distance of market from the forest areas (X₁₀), and the ease of access to the markets (X₁₁) are treated as factors. If a particular forest produce has a market and it is easily accessible, there will be a tendency to over harvest the produce, and a negative effect on the resource. On the other hand, it might encourage the appropriators to manage the resource sustainably. The existence of local markets of forest products will have a bearing on social empowerment, as it is an indicator of increased economic activity. It, along with the distance of market from the forest areas, would also tend to divert the forestry goods away from meeting the local demand to the market and thus would effect the supply of forest produce to meet the primary local requirement of forestry produce. The ease of market access would influence social empowerment due to frequent contacts with the outside world and proximity to the economic mainstream. Hence the signs of the coefficients of these two variables are difficult to predict since they would depend upon the characteristics of the market as well as those of the produce.

2.2.6 Physical factors: Total forest area (X₁₂) and the condition of the forest before the JFM (X₁₃) will affect the collective action (Verughese, and Ostrom, 2001) and hence the social empowerment. Also they will obviously affect the canopy cover and the availability of forest products to meet local requirements and therefore will be taken as inputs to all three outputs. In addition to these factors, time (X₁₄) is one of the important factors in forest production process (Nautiyal, 1988).

Hence, production functions for three outputs can be expressed as:

Y₁ = F₁ (X₁, X₄, X₆, X₈, X₉, X₁₁, X₁₂, X₁₄)_.
Y₂ = F₂ (X₂, X₃, X₅, X₆, X₁₃, X₁₄)_.
Y₃ = F₃ (X₂, X₃, X₇, X₈, X₉, X₁₀, X₁₂, X₁₃, X₁₄).

3.0 Empirical Estimation of Production Functions

3.1 Data collection

Data regarding the outputs and factors was collected from forest and JFM dominant three eastern forest circles, viz., Gandhi Nagar, Surat and Vadodara, of Gujarat, India. In these three circles, the JFM movement has been particularly vigorous since its inception. Fifty JFM villages were selected randomly. Three data collection tools were used: (i) secondary sources like village and census records for the extent of forest area, species composition, and other demographic information; (ii) questionnaire survey to collect data on indicators such as empowerment, the social structure etc., and (iii) participatory Rural Appraisal (PRA) techniques, such as open-ended discussions, focus-group interviews, and discussions with forest managers, to estimate variables such as the dependence on the forestry resource, contribution to the village income, etc. The questionnaires were administered in each village to approximately 20% of individuals (maximum 20 and minimum 5) selected randomly.

3.2 Data Analysis

Social, economic, and spatial homogeneities are included. Gini mean relative difference (MRD), a relative measure of inequality (Coulter, 1989) and which facilitates comparison of inequality across villages with differing number of castes, is used. Number of households belonging to different cases is used to calculate social Gini MRD. Number of household in five income classes (very poor, poor, average, high, and very high income) is used for economic Gini MRD. Similarly number of households in four spatial classes (households living < 0.5 km, 0.5 - 1.00 km, 1.00 - 1.5 km, and > 1.5 km, from the forest) is used for spatial Gini MRD. The three inequality indices are used to calculate an overall homogeneity index.

3.3 Functional Form

We do not have any a priori functional form suggested by previous studies. The linear form is too restrictive and its assumption of fixed absolute changes across observations does not accommodate diminishing returns. The Cobb-Douglas function is theoretically sound, simpler to interpret and gives the elasticities of independent variables directly and hence was selected for this exploratory study.

4.0 Results

Results of the estimation of three production functions are given in Table 1. All the three equations have adjusted R² greater than 0.5, and the production function of canopy cover has the highest adjusted R². The production function of the empowerment function has significant coefficients of homogeneity of user group, knowledge of Government orders, existence of local markets, ease of market access, total forest area and time while the coefficients of existence of conflict resolution mechanisms and existence of forestry enterprises are insignificant. The production of empowerment is inelastic with respect to all the factors. However, the elasticity with respect to ease of market access is highest (0.353), and second highest with respect to total forest areas (0.104). The elasticity with respect to homogeneity is 0.010, while the elasticities with respect to other factors are very small (smaller than 0.010).

Similarly, the production of canopy cover is inelastic with respect to the dependence of user group on forests, support from the forest bureaucracy, knowledge of Government orders, and forest conditions before JFM while the coefficients of leadership and time are insignificant in this equation. The elasticity is highest with respect to support from forest bureaucracy (0.863), and second highest with respect to dependence (0.676). However, the magnitude of other elasticities are also bigger compared to the elstaicities of empowerment.

The supply of forest products to meet local requirements is elastic with respect to dependence of user group on forests, and is inelastic with respect to existence of non-government organisations, existence of local markets, forest condition before JFM while coefficients of existence of forestry enterprise in the area, existence of local markets, total forest area and time are insignificant. An interesting feature of this analysis is that only supply of forest products is elastic with respect to dependence of user group on forests, and all the outputs are inelastic with respect to all other factors.

Table 1: Coefficients and the significance levels for the three production functions

5.0 Conclusions:

The results have provided enough evidence to our initial argument that social, economic, cultural, organisational, and market factors, in additional to physical factors, should also be included in the production functions of JFM. However, the different non-neo-classical factors may have different contributions to different outputs. For example, an increase in the dependence of the user group on forest resource by one percent will increase the supply of forest produce by 2.92% and forest canopy cover by 0.67%. Similarly support of bureaucracy is very important for forest cover and not for other outputs. Time is significant in empowerment and but not in two other outputs.

Hence, designing of JFM planning and management strategies will require output specific focus of forest managers, representative of local communities and NGOs. Due to the similarity of forest regimes in most developing countries, this research has the potential to set a benchmark for JFM all over the world. However, these are our preliminary results, and detailed analysis of data for production possibility frontiers will also provide results about the efficiency outcomes of the JFM.

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¹ Faculty of Forestry, University of Toronto, Earth Sciences Centre, 33 Willcocks Street, Toronto, ON, Canada, M5S 3B3. [email protected]