Does the Participants’ behaviour affect Management of Community Forestry in Nepal?

Does the Participants’ behaviour affect Management of Community Forestry in Nepal?  

Baikuntha Aryal

Abstract

Forestry plays an important role in rural livelihoods in Nepal. The subsistence income that the rural households get from forests contributes a significant part in rural household economy. Share of forests in national income may be low, but for the rural households depending on forests for the major source of energy, it counts a lot. The role of households in managing the resource is thus an important factor to get maximum benefits from the forests. Community forestry in Nepal is one of the measures to involve the rural households in management of the forests as well as a tool to reduce rural poverty. This small analysis first finds the determining factors of participation in community forestry management and then tries to see the effects of users’ behaviour in management side by using game theory approach. The results show that the access, education, income and gender are the major factors determining the participation. The management is affected by the income level of the households as well as the distance to the forests.

1. Introduction

Forests play a crucial role in livelihoods of rural Nepal. More than 75% of the energy needs come from the forestry sector. Fuelwood alone provides a huge sum of the energy supplies of Nepal (World Bank, 2003). In the fiscal year 2006/07, the total fuelwood consumption in Nepal was 6.45 million tonnes of oil equivalent (MOF, 2007), which is 75% of the total energy consumption. The statistics is even larger in rural parts of the country. Ninety four percent of rural households in the hill and mountain areas of Nepal rely on fuelwood as their primary fuel for cooking and heating (Edmonds, 2002). Similarly, about 40% of the fodder demand is met from natural forest and shrub land adjacent to farms (MFSC, 1988). The forest contributes in government revenue as well. Though the trend is declining these days, until 1950, the revenue collected from the forest resources accounted to more than 40% (Bajracharya, 1983a). In the Fiscal Year 2005/06, the revenue from forest was 2.8% of total non-tax revenue (MOF, 2007).

Forestry and forest resource management are taken as the secondary support activities in Nepal whose economy is based on subsistence agriculture. Agriculture alone accounts for more than 40 percent of the GDP and more than 83 percent of the employment (World Bank, 2003). Local people, nevertheless, depend largely on forest resources for fodder, fuelwood, food, building materials, medicinal plants, and fertilisers. This indicates that agriculture and livestock depend strongly on forest resources. Forest provides a significant amount of income too. Although fuelwood used in the rural areas is seldom traded, there is a significant demand in small urban areas and from brick industries that is met by traders who purchase from rural fuelwood collectors (World Bank, 2003). Other sources of income from forests are timber production by local communities or by commercial private sector agencies. The other part of the forest income comes through NTFPs (Non Timber Forest Products). The trade of NTFPs is being practised legally and illegally. Because of dominancy of illegal trade, the major chunk of the income from NTFPs does not appear in the national accounting system. In some part of the country, NTFP provides more than 50 percent of total household income.

Community forestry has been a priority programme area of the forestry sector in Nepal for over two decades now. This concept was incorporated in Nepal’s First National Forestry Plan (1976), and its related legislation of 1977. This legislation, the rules and the regulations framed under it, and further modifications of these, and the ensuing programmes have made it possible for the development of community forestry in Nepal. Considerable successes have been achieved in the development of community in the country. Nepal has also earned international credibility for her achievements in community forestry development. At the end of Tenth Plan of Nepal, more than 14,000 community forest users groups are working to manage around 1.3 million hectare of forestland. As the mandate of this program is “To meet the basic needs of the local people while conserving the forest resources of the country” and the main objective is “To involve and participate community members in the conservation and management of natural resources in a sustainable manner in order to fulfil the daily requirements of fodder, forages, bedding materials for animals, firewood and timber” the participants are believed to be benefited from the easier access to forest products for household use and the benefit sharing.

This short paper tries to assess the effects of participants’ behaviour in management of community forestry. For this purpose, it uses small set of data from Dakshinkali and Chhaimale VDCs of Kathmandu district. The paper first finds the determinants of participation in community forestry and then it analyzes the participants’ behaviour in the management side by using game theory approach.

2. Determinants of participation in community forestry management

The data for the analysis is taken from Dakshinkali and Chhaimale VDCs of Kathmandu district. 39 households were taken from Dakshinkali VDC while 36 households were taken from Chhaimale VDC. This data was collected by the author in 2004/05. Although the sample size is small, it is believed to be helpful in determining the factors of participation. Simple probit analysis was done to find the major factors to determine the participation in community forestry.

The decision of a household to participate in community forestry management is determined by different factors. The results show that the large family households and households with agriculture as main occupation are more likely to participate in community forestry. Similarly, household with young and educated heads are also likely to join the program. It indicates the growing concerns over nature conservation and awareness to safeguard the resources among young and educated households. It is interesting to note that the female-headed households are more likely to participate in the programme. On the other hand, relatively richer households are less likely to join the program as the forest is one of the lowest return activities. Likewise, there is a little chance that the households that are far from forests join the program. This is simply because farther the forest, less concerns of conserving it.

In the following section, the two determinants (income level and distance to the forests) are considered to analyze the individual behaviour of the participants in community forest management.

3. Games and Community Forestry Management

3.1 Game Theory

The game theory suggests different strategies for the players to play for getting the benefits to them. This is the study of multi person decision problems. The famous Prisoner’s Dilemma game was perhaps the beginning of game theory in which the two suspected persons were separately asked about the crime. The police did not have any evidence against them. So they were provided different alternatives about the jail term. This was intended to find out whether the suspected persons were convict or not. But it gave the room to the convicts to find the best outcomes for themselves. They had the options either to cooperate and get the freedom or to defect and be sentenced. They had the option to choose for their betterment. A number of different types of games were developed afterwards but the main objective was to find the better personal/social outcomes.

In the same way, the main objective of the community forestry program is to get cooperation for a better social outcome. The game theory, if applied, can be fruitful in regard to the conservation of forest resources and for the better social outcome. The core idea behind the game theory is to find the Nash equilibrium (an equilibrium where the players do not have incentive(s) to change the strategies). However, Nash equilibrium does not guarantee optimality from a social view but does for the individual. There are different types of games that can be applied in this area. Broadly, there are two types: static and dynamic games.

Static game

In this type, first the players simultaneously choose actions; then they receive payoffs that depend on the combination of actions just chosen. In this study, I restrict attention to games of complete information, i.e. each player’s payoff function is common knowledge among all the players. The assurance game (AG) and chicken game (CG) are these kind of static game. The Prisoner’s Dilemma (PD) game is the first choice for this game and changing the payoffs accordingly we find the way out.

Dynamic game

Since the forest resource is a renewable resource and can be used for an infinite period of time, its users may have the complete knowledge about its use by different users. In this study, I restrict to complete information among the players by which I mean that at each move in the game the player with the move knows the full history of the play of the game thus far. The main dynamic games with complete information are Stackelberg’s sequential move and backward induction.

Since the forest can be used for an infinite period, it is looked for a repeated period. The reason for looking for repeated game is that it captures the facts of life that when people interact over time, threats and promises concerning future behaviour may influence current behaviour. The central issue in all dynamic games is credibility and dynamic game of complete information may have more than one Nash equilibriums, but some of these may involve non-credible threats or promises (Gibbons, 1992). Thus we look for the sub-game (a part of original game, i.e. the part from a particular point in the game and all moves that follows this game). The sub-game perfect Nash equilibriums pass a credibility test. Thus applying the two types of dynamic games mentioned above, we try to find the Pareto optimality through sub-game(s)

Before beginning the discussion of application of game theory in collective action, it is worthwhile to discuss about some of prerequisites for it. The first one is the moral norms:

-          One must always contribute towards public goods, and

-          One must not take a free ride when others are contributing.

The second is a set of conditions as:

-          few information asymmetries (personal relations, observability, transparency)

-          repeated interactions

-          similar norms

-          less or no benefits from free riding

-          possibility of punishment

With these prerequisites the player in a complete information game cooperates if others are suspicious and does not cooperate if others are too generous thinking that even if (s)he does not cooperate, others would cooperate and (s)he gets the benefits. Furthermore, in this type of games, the reputation of the player matters, i.e. if the player is altruist, (s)he always cooperate and if nasty, (s)he always defects.

3.2. Games in the CF management

A number of substantial literatures can be found using the game theory in resource management problems. They are mainly applying binary choice models (Angelsen, 2001). The discussion about the game theory in CF management in this paper is basically focuses how simultaneous and sequential games can be played by the members of the user groups in CF management. From above probit analysis, the factors determining the participation in CF management are found as number of household members, level of education and the occupation of the household members. The income level and the distance to the forest have negative impacts on the participation in the CF management. On the basis of this information, we try to apply the games between

-          Members of the user group  (Rich and Poor)

-          Members of the user group (Closer and farther from the forest)

a. Game between rich and poor members of the group

From the probit analysis, it is seen that as the income increases, the probability of participating in the CF management decreases. Whatever the reason maybe, the richer households seem to be less concerned about conserving the forests. But being the member of the same village, they cannot avoid joining it otherwise they cannot extract the forest products as per rule. The poor on the other hand, have subsistence constraint. They have to collect the forest products for their subsistence use. Even if the richer members do not cooperate, the poor have to maintain the forest resources for their own sake. Furthermore, the poor households tend to conserve the forest for the safety nets and rich households tend to convert the forest into money and the riches dominate in the decision-making. So there is a possible free riding over the poor members of the group. It can be illustrated by the following payoff matrix:

Poor
Rich		Maintain	Neglect
	Maintain	15,5	13,2
	Neglect	17,1	2,0

In the above payoff matrix, if Poor (P) maintains, the Rich (R) tends to neglect, as the payoff for him is more than to maintain. If P chooses to neglect then R chooses to maintain. In this case P again has to move to maintain because neglecting is less beneficial than maintaining. When P chooses to maintain, R chooses to neglect. Since R has the complete information about P, it chooses to neglect. So the Nash equilibrium in this case is at (17, 1) where rich free rides over the poor. Let’s look at the other payoff matrix as in below:

Poor
Rich		Maintain	Neglect
	Maintain	15,4	13,5
	Neglect	17, -1	2,2

Here, Nash equilibrium is at (13, 5), i.e. rich maintains but the poor neglects. If R chooses to maintain, P chooses to neglect. If R chooses to neglect, P again chooses to neglect. But if P chooses to neglect, then R should choose to maintain because it has higher payoff in maintaining than in neglecting. Here, poor free rides over the riches. The reason for this is that poor maybe too poor to maintain and hence gives up maintaining.

In the collective action, this is always possible that one free rides over the others. The problem of free riding can be minimized by imposing some type of punishment in the form of fines. In the first example, where rich free rides over poor, let us assume that 3 units be taken from the neglecting member and be provided that to maintaining member in order to provide incentives for the members who maintain it. The new payoff matrix will be

Poor
Rich		Maintain	Neglect
	Maintain	15,5	16, -1
	Neglect	14,4	2,0

Now, both rich and poor tend to maintain. If R chooses to maintain, then P also chooses to maintain. If R chooses to neglect, then P chooses to maintain. When P maintains, R should also maintain, as the payoff is higher there. If P neglects, R maintains that lead P to maintain again. Hence the problem of free riding is solved. The same policy helps to minimize poor’s free riding over rich.

The above games show that playing game in the community forestry management gives the better social outcome as both rich and poor maintain the forest resources and get benefited from it. The main objective of the community forestry is to fulfil the daily requirements of fodder, forages, bedding materials for animals, firewood and timber and hence contribute to the rural livelihood. But he empirical studies do not support it. According to Malla (2000), sustainable management of, and equitable access to, CF has not been a universal result. Some recent studies indicated that CF in the mid hills is not able to contribute significantly to the livelihoods of very poor and marginalized sections of the community due to its failure to tale into account equity and distributional issues (Adhikari, 2002).

b. Game between members close to and far from the forest

The probit analysis clearly showed that the distance matters in the participation in CF management. If the household is far from the forest it is likely that it does not join the CF. Since the interest of these two types of households is different to each other, they prefer different games to play. Chicken game (CG) is preferred for the members who are closer to the forest since they experience more disincentives if the forest is not managed well, i.e. they have to bear immediate effect of the deforestation. The chicken game gives them a kind of security that if one fails to maintain other can take it over. In any case they do not loose the benefits of forest products that can be collected from the forests.

Assurance game (AG) is preferable for the members farther from the forest since they get benefits by the maintenance done by the members closer to the resources. Since the members have complete information about other’s move, one member of the group gets benefit by cooperating if other member cooperates. This is a kind of Tit for Tat. If others maintain, they also maintain and if others neglect they also neglect. This happens within the households far from the forests. But they have to play the game with other members of the group who are closer to the forests, and the strategies then will be different for all. So here we assume two players from two different locations. In this case, there are two players (one is chicken game player and other is assurance game player). This will be a mixed game. Below is the example of payoff matrix that shows how this looks like.

AG
CG		Maintain	Neglect
	Maintain	10,5	8,4
	Neglect	12,0	0,2

With this type of payoff, the players cannot reach at the equilibrium. Neglecting gives the better payoff for the CG player. This leads AG player to neglect. If AG player neglects, then CG chooses to maintain. This forces AG to maintain. But in this case CG does not want to maintain. This goes and goes and equilibrium cannot be attained. So, the simultaneous move does not work and sequential move is needed.

In a sequential game, one player acts as a leader and other acts as a follower. Stackelberg’s sequential game is appropriate in this case. Stackelberg’s sequential move can be better decided by backward induction method.

                                                                                    (10,5)

                                                       AG         M

                                                                        N

                                         M                                        (8,4)

                     CG                                                         

                                                N               M                (12,0)

                                                AG             N

                                                                                    (0,2)

The above tree helps the player(s) to decide to which strategy to adopt. When CG player is the leader, and has the complete information about the AG player, (s)he knows that if (s)he chooses to maintain, AG player also chooses to maintain (5 is greater than 4). If he chooses to neglect, AG player chooses to neglect (2 is greater than 0). Between these two strategies, (s)he will choose to maintain because it gives her/him better payoff (10 against 0). So the optimal strategy is to cooperate for both the players. If the AG player is the leader, then the decision tree will be as follows:

                                                                                    (10,5)  

                                                       CG         M

                                                                        N

                                         M                                        (12,0)

                     AG                                                         

                                                N               M                (8,4)

                                                CG             N

                                                                                    (0,2)

The above tree shows the strategies to be taken if the AG player leads the game. With the complete information of other side, the AG player knows that if (s)he maintains then CG player neglects (because 12 is greater than 10). If (s)he chooses to neglect, then CG player maintains as the payoff is higher (8 against 0). Between these two strategies, AG player chooses to adopt neglecting because (s)he will be better off with this strategy (4 is greater than 0). Hence if the AG player starts the game, CG maintains and AG neglects.

Here, in our example CG players are the households living close to the forests and AG players are the households living far from the forests. If the households close to the forests start the game, then both the households far from and close to the forests are forced to maintain. If the households far from the forests do not maintain even if the households close to the forest maintain, then those who are closer to the forests enjoy most of the benefits. If they do not maintain, then they loose the forest products that should be supplemented by buying in the local market. This leads to increased expenditure and less benefits. Moreover, effect of deforestation and unavailability of forest products lead to less access to the forest for them and hence they suffer. So negligence in conservation means increased negative impact for them. On the other hand, if both cooperate, then both get more benefits resulting in better forest conservation and secured forest products.

If the households far from the forests start the game, then they will neglect but the households close to the forests maintain it. For the households close to forest, the forest is the safety net so that they tend to maintain it. Moreover, the easier access to the forest enables them to collect forest products easier than for the households far from the forest. Also since they have to bear immediate effect of deforestation, they prefer to maintain it. On the other hand, the households, far from the forests get benefits from the forest, which is maintained by the households close to the forests. Also since they know that the households close to the forests maintain it and they don’t bother about it. They are not directly affected by the deforestation like the households close to the forests. So they neglect and the households close to the forest maintain. Hence, in any case, the households close to the forests tend to maintain the forest resources.

4. Role of market in community forestry

The above probit analysis ignores the impact of market on the participation in CF management. As there is a strong linkage between market and the resources, the role of market in CF management cannot be ruled out. Though the necessary data was unavailable to analyse this, from probit analysis and the game between rich and poor members, some conclusions can be drawn.

-          Increase in income leads to the low participation in common property management. This means if the market is introduced, then the rich members tend to commercialise the forest products as they can afford it.

-          The poor members take the forest as safety nets and tend to conserve it. But at the cost of poor, the riches harvest more and exploit the forest more.

-          Unless the reward and punishment system is strong, the bribery (because of free riding problem) and theft of forest products likely to happen.

But these issues need to be examined closely and enough information is needed for it.

5. Conclusion

The main objective of the paper was to find the determinants of the participation in the community forestry management and assess the possibility of applying game theory in the CF management. The analysis is based on the small data set of 75 households of two villages of Kathmandu district. From the probit analysis it was found that the number of household members, the education and agriculture based households increased the probability of participation in the management of community forestry. The age of the household head, income and the distance from the household to the forest decreased the probability of participation.

On the basis of the probit analysis, it was seen whether the game theory could be applied in the community forestry management. On the basis of probit result, the two different sets of different players were assumed. The players were divided into rich and poor members of the user groups in one game and households close to and far from the forest in another game. Though it could not be decided which game is suitable for the better management of community forestry, it was found that the game theory could be helpful in getting the better social outcomes. The first game (between rich and poor) showed that the free riding could be minimized with the provision of strong rules over non-cooperation. It also showed how the non-cooperating members could be motivated to be cooperative one. The second game showed that the better outcomes could be found if the game was led appropriately. However, the paper is unable to decide which game is suitable in the common property management. This raises some policy concerns on how to involve all the participants in better management of community forest and make the maximum out of it.

This simple analysis shows that the more realistic game theory models can be developed and can be played with the real payoffs determined on the basis of the cost and benefits involved in the participation in the community forestry program.

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