international migration and environmental degradation—the case of mozambican refugees and forest...

Journal of Environmental Management (1995) 43, 233-247

International Migration and Environmental Degradation--The Case of Mozambiean Refugees and Forest Resources in Malawi

Suresh Chandra Babu

International Food Policy Research Institute, 1200 17th Street, NW, Washington DC 20036-3006, U.S.A. and Bunda College of Agriculture, Malawi

and Rashid Hassan

CIMMYT, P.O. Box 25171, Kabete, Nairobi, Kenya

Received 19 January 1994

Considering the continuous influx of Mozambican refugees to Malawi as an external shock to the forest ecosystem, a dynamic model of optimizing the use of forest tree resources is developed in this paper. Land clearing for refugee camp sites, construction material, fuelwood and agricultural crop production constitute a major threat to forest resources in the refugee populated areas. The model presented in the paper provides a framework for analysing various afforestation and technology policies to increase the sustainable use of forest tree resources. The optimal conditions for choosing the levels of land clearing for various uses of refugee population are derived. The model parameters are used to identify the optimal timing and rate of afforestation that will attain a dynamic equilibrium of forest tree resources. Several policy implications are derived from the model results for reducing the environmental degradation of forest resources due to the presence of refugees. It is argued that the general environmental regulation policies based on user-pay principles may not be appropriate under the refugee situation and that additional intervention is needed by the host government and international relief agencies for reversing the trends in deforestation.

Keywords: refugees, deforestation, dynamic optimization, environmental policies.

I. Introduction

It is generally accepted that the degradation of renewable resources in developing countries is deep and widespread. Population pressure has been frequently suggested as one of the major causes of environmental degradation in developing countries (Southgate et al., 1990). While some researchers are sceptical about assigning total blame on populat ion growth for resource depletion, various forms of increase in the number of users do have significant effect on the sustainable use of these resources.

233 0301-4797/95/030233 + 15 $08.00/0 © 1995 Academic Press Limited

234 Migration and environmental degradation

This is more so when the resource in question is under open-access regime (Bromley and Cernea, 1989). However, the analysis of these problems and their causes is rudimentary at best (Southgate et al., 1990). This paper addresses the problem of forest resource degradation due to an exogenous shock in the population growth in the form of refugees from a neighbouring country. A case study of Mozambican refugees and forest resources in Malawi is presented.

Degradation of natural resources as a major cause of environmental migration has been recognized for some time. However, environmental degradation by the people displaced due to drought, underdevelopment, civil conflict and political insecurity has not been studied adequately. Thus, there is a need to respond to the movement of these people with policies that minimize the negative effects of such migration on the environment (RPG, 1992). The presence of refugees from a neighbouring country influences several aspects of the life of local population. The impact of refugees on the land pressure, soil fertility and environmental degradation, is immediately felt and has serious implications for the survival of the local population.

The impact on forest resources is profound due to the need for more energy for fuel and lighting. This impact is directly reflected in the increased demand for the forest resources and acceleration of deforestation in the refugee areas. The refugee assistance by relief organizations in general involves distribution of the essentials like staple food and cooking oil. In some cases, fuel-efficient stoves are given to mitigate the effect of fuel demand on forest resources (UNHCR, 1990). However, development of coherent policies towards reducing the environmental degradation and resource depletion due to the presence of refugees, either by the host country governments or by the agencies assisting in relief activities, is largely missing (RPG, 1992). The purpose of this paper is to develop a framework for analysing alternative policies for sustainable use of forest trees in the presence of refugees.

2. Refugees and resource degradation in Malawi

The population of Mozambican refugees outside their home country is the highest in Malawi among southern African countries; 780000 in 1989 compared to 31 000 in Zambia for the same year. The value of deliveries to the World Food Program in Malawi, both for development and emergency projects, most of which are distributed to refugees, increased from US$1-6 million in 1986 to US$142 million in 1992. Of all the countries receiving food aid from the World Food Program in sub-Saharan Africa, Malawi ranked first in funds dispersed for protracted refugee and displaced persons in 1992 (WFP, 1993). A comparison of the stress caused by the presence of Mozambican refugees in various districts of Malawi is presented in Table 1. The stress factor is expressed as the number of Mozambicans present in a district for 100 Malawians. The stress factor ranges from 3 to 130 in 1992, reflecting a large variability in the extent to which the presence of refugees influences the local population.

The presence of refugees from a neighbouring country influences all spheres of life of the local population. The first and direct impact is on the land availability for cultivation of agricultural crops. The existing agricultural land is used for building camping sites and associated facilities such as distribution centres, hospitals and schools for refugee children. This increases the need for additional land to be cleared which is either bushes under fallow or forest lands. Given the already existing population pressure in Malawi, the new land cleared for agricultural purposes is usually the forest land in the refugee inhabited districts. Once registered by relief agencies delivering

S. C. Babu and R. Hassan

TABLE 1. Mozambican refugees in Malawi

235

Refugees in Local Malawians Stress

Districts 1988 1992 in 1992 factor

Nsanje 219 243 291 518 223 654 130 Mwanza 21 839 87 975 140 439 63 Mulanje 40 745 51 890 739 243 7 Thyolo - - 39 819 499 763 8 Chikwawa 31 032 87 982 370 337 24 Mangochi 27 088 44 434 574 272 8 Machinga 13 985 27 396 595 920 5 Ntcheu 135 788 137 072 416 472 33 Dedza 120 570 153 059 475 800 32 Lilongwe 26 748 38 565 1 423 358 3 Mchinji 3 129 21 039 287 394 7 Nkhata-Bay 487 4 395 157 552 3

Total 640 167 985 144 5 904 204 17

foods on behalf of U N H C R and WFP, the refugees start to receive food rations. The fuelwood for cooking these foods is also given as a ration. But because of the reduced frequency of fuelwood distribution compared to the food rations, and a general underestimation of its demand, the forest trees around refugee populated areas which are open-access resources are cut for fuelwood. The forest trees are also used for home construction by the refugee population. The local population, which cultivates small areas of land, runs out of food well before the next harvest. For instance, a food security and nutrition monitoring survey conducted in June 1990 indicated that about 80% of the rural households in the refugee populated districts run out of their food stock just five months after the harvest (MOA, 1991). These households depend on other non-farm income, earned either in kind or in cash, to meet their food needs for the rest of the period before the next harvest. In the refugee populated districts, the rural households exchange fuelwood, which is needed for cooking, for some of the food from the refugees given to them as rations. While insufficient data on the forests in the refugee populated areas prevent precise estimation of forest resource depletion due to its use for the refugees, there exists a general consensus in Malawi that forest land clearing induced by the influx of refugees is widespread and endangers sustainable use of forest tree resources.

In some refugee populated parts of Malawi, the fuelwood crisis is so bad that the butter fat distributed to the refugees for cooking is used as a source of fuel. This use partly reflects the increase in the price of fuelwood due to its low availability. As the forest land near the refugee areas is cleared, the remoteness of the source of forest trees increases. However, the level of fuelwood price and the increase in its cost merely reflect the increase in the cost of harvesting and transportation. The choice of food commodities distributed to the refugees as rations also influences the need for fuelwood resources by them. For example, pigeon peas distributed in Malawi require at least 50% more fuel for cooking than maize flour. This factor has also aggravated the problem of forest tree depletion in some parts of Malawi.

A large quantity of forest tree resources are already exploited in Malawi for curing the fire-cured tobacco, one of the major export crops. In some areas, due to the increased


pressure on forest resources, the Government of Malawi is seriously considering a policy of importing fuelwood from Mozambique.

A major part of the problem could be attributed to the under-pricing and the over- exploitation of forest tree resources in Malawi. Several policy alternatives are being considered by the Government of Malawi in association with the aid agencies to combat the degradation of forest resources. While it is recognized that the price of forest tree resources should reflect their true social costs, and the cost to future generations of cutting forests today, it is not clear what parameters enter the estimation of the true price. The associated uses of forest tree resources such as hut making and the clearing of forests for agricultural purposes add complexity to the calculations.

Serious efforts have been made in Malawi to include a policy of afforestation in its refugee populated areas to reduce the impact of deforestation. However, information on the optimal rate of afforestation and its timing in various parts of the country is not known. Increasing the efficiency of fuelwood burning by research on fuel-efficient stores and charcoal-burning technologies presents some promise to reduce the intensity of deforestation. Little is known, however, on the optimal rate of investment in such research efforts by the host country government. To address these issues, and to help design specific policy options towards attaining a sustainable use of forest tree resources, a dynamic model is developed in the next section.

3. The model

The model discussed in this paper maximizes the social welfare at a dynamic equilibrium considering the costs of under-pricing and over-cutting of forest tree resources to the future generations. The model has three major production components: the production of forest trees for fuelwood; the production of forest trees for charcoal; and generation of land area through forest clearing for agricultural crop production. The planning horizon for the society is assumed to be the time interval [0, T], TE[1, o0]. The planning horizon for the purposes of this paper is taken as finite, as the analysis presented in the subsequent sections becomes impractical under the fictitious infinite planning horizon. Also, given the expected return of refugees to their home country, either through voluntary repatriation, or when the solution to the problem which gave rise to the displacement of people is found in the future, finite time planning is more appropriate. For any function f (x , u), f~ = afqax and where the meaning is clear, the time subscripts have been dropped 0c,",, =f~).

The forest tree production for firewood in any period t is given by Ql(x, U, t) and the production of forest trees for charcoal is given by Q~,(x, U, t), where x is the state variable reflecting the biomass content of the forest trees and U is a vector of control variables [u~, u2, u3]; uj is the reduction in the forest trees due to forest land occupation by the influx of refugees, u2 is the reduction in forest trees due to clearing of land by refugees for crop production and u3 is the reduction in the forest tree biomass for the uses other than fuel such as hut making and house construction. Although all three control variables are directly influenced by refugees' presence, the level of refugee population is not treated as a separate variable in the model. Alternatively, the impacts of refugees on forest tree resources such as ul, u2, u3 are treated here differently to derive policy implications for regulating the use of forest land and resources. The additional reduction in the forest area due to the increase in the host country population has not been explicitly modelled here, although inclusion of such variables to the model is trivial.

S. C. Babu and R. Hassan 237

The crop production in the refugee populated areas is given by Y(x, U, t). While the crop production also depends on other variable inputs, for the exposition of linkages between forest resource depletion and agricultural production in the presence of refugees, they are not explicitly stated. The benefits to the host country and to the refugees by clearing the forest land for their inhabitance, cultivation of agricultural crops and construction material is given by increases in the land area L(x, U, t). The land area for the above uses decreases if it is used for increasing the stock of biomass of forest tree resources, through afforestation; Lx<O. For any period, the following relations are assumed to hold:

Q~>__O Q2~O Yx~O (1)

Q~,<O Q~<O Q~,_<O (2)

¢,_<o (3)

Y,,<0 Y~>0 Yu~<0 (4)

L.,>O L,,2>O L.3>O (5)

The first set of relations state that the marginal increase in the production of tree resources for fuelwood, charcoal and in crop production due to an increase in forest tree biomass, is non-negative. Crop production, particularly in semi-arid tropics, depends on the rainfall which is influenced by the forest cover (Ehui and Hertel, 1989). The reduction in the availability of forest tree resources for fuelwood and charcoal production due to an increase in the control variables is given by the relations (2) and (3). Although clearing of forest land through ul, u2 and u3 would generate some tree resources initially, the organized production of fuelwood or charcoal cannot be undertaken in the future due to the other uses of forest land. Crop production, in the refugee populated areas and in areas where population is rapidly increasing, is expanded largely by clearing the forest land (Armitage and Schramm, 1989). While this provides additional land for cultivation, and thereby increases the crop output as given by Y,2, clearing of forest land for non-agricultural purposes may increase soil erosion and result in reduced yields of future crops grown in these areas [Y~,, Y,~] (Stryker, 1989). Land area increase for the use of refugees due to increase in their population is given by condition (5).

The stock of biomass of forest tree resources is assumed to have the following rate of growth over time:

dx ~--~=~,=f(x, U, t)+ A , - W(Q,, Q2, K,) (6)

The following relations hold for this function: fx > 0; f~, < 0; fu2 < 0; and fu3 < 0---the stock of biomass increases with regeneration (fx) and decreases with influx of refugees 0ru,). The biomass added to the forest tree resources by afforestation is given by A, and the rate of wood cutting for fuelwood and charcoal is given by W. The technology available for wood burning including the charcoal production technology is given by a composite measure K,, which can increase over a range from 0 to 100% (Hassan and Hertzler, 1988). The rate of increase in the efficiency of technology is given by:


K, =g(R,, Rz, K,) (7)

The rate of increase in the efficiency of technology due to improved research in the wood-burning stove, RI, and in charcoal production technology, R2, is also dependent on the stock of existing technology, K,.

Let PI, P2 and P3 be the market prices of forest resources used for fuelwood and for charcoal production and crop output, respectively. Note that each of these prices is an inverse demand system and function of Qb Q2 and Y. Although the functional forms for the inverse demand system are not specified, it should be noted that the prices are treated endogenously in the model. Let PL be the rental rate of land also determined endogenously. Let C~ and C2 be the cost of harvesting and transporting the tree resources for fuelwood and charcoal production, respectively; (::3(Y) be the cost function of crop production; CL be the cost of land clearing; Ca(A) be the cost of afforestation; and C(Rt), C(R2) be the cost function for research relating to wood- burning and charcoal production technologies. The costs Cb C2, C3(Y) are assumed to be functions of the control variables u~, u2, u3 and the stock of biomass of forest tree resources. It is usually the forest land near the major transportation routes that is cleared first, and the deforestation extends to remote places increasing the cost of harvesting and transportation of the fuelwood from the forests. It is also easy to see that increase in the biomass of forest tree resources would be beneficial to crop production by reducing the costs associated with soil erosion and land degradation.

The social welfare maximization at a dynamic equilibrium, considering the costs to future generations of over-exploitation of forest resources in the present is to establish the level of x, ul, u2 and u3 with the social opportunity cost of capital 6. This requires identifying the optimal quantities of forest tree resources used for fuelwood and charcoal production, optimal rate of afforestation, policies for regulation of land clearing in the refugee populated areas and optimal investment in technological research in wood burning and charcoal production. This could be achieved by maximizing the societal welfare given by:

ft T J(xo) = M(~x =o e-6t[P, Q, + P2Q2 + P3 Y+ PLL-- C, - C2 -- C3( Y) - CL-- C.(A) - Z C,(R~)]

Max f r = e-rt~tdt Qi t=o

(8)

To maximize the present value of its profit stream, the society will maximize J plus the present value of the forest tree resources in period T. Let S(xr) be the terminal value of the forest tree resources at the end of planning horizon. This implies that the value the society would place on the forest tree resources depends on the stock of biomass. The society will then maximize

J(xo) + S(xr) e -6' (9)

Subject to (6), (7) and the initial stock of forest tree biomass:

x(O)=xo and [x,,U,]>_O (10)

S. C. Babu and R. H a s s a n 239

The maximization of (9) subject to (6), (7) and (10) is an optimal control problem (Chiang, 1992). The Hamiltonian function associated with the above problem is:

H,=e-(s'r~,+ q~[f(x. U, t ) + A , - W,(Q,. Q2. K)] + zg,(R,. R2, K,) (11)

where 4, is the costate variable associated with the equation of motion of growth of stock of biomass x and z is the costate variable associated with improvement in the efficiency of wood-burning and coal production technologies. According to the maximum principle (Kamien and Schwartz, 1992), the optimal paths of x, U, 4, and z satisfy the following conditions:

Hu, = e-(s'[P, Q~., - C~, + P2 Q~, - C~, + P3 Yu~ - C~, + PLL.,] (12) + 4~[f~,-- WQ, Q'.,- Wq2Q~.,] =0

--(St 1 I H.=e [?, Q.,- C~, + ? ~ l - ~, + ?~ r. ,- ~, + P~Lj +¢k[f.2- WQ, Q~.- WQ2Q~j = 0 (13)

- - 6 t I 1 3 Hu3=e [P,Q.,-C~3+P2Q~-C~.~+P3Y.,-C~+PLL.~] I +~[fu,- WQ, Q~3- w ~ j = o

Hx= -;k=e-(S'[P,Q~ + P2Q2~+ P3Yx+ PLL~] +ck[f~ - WQ, Q~- W~Q2~]

H . = f ( x , U, t) + A , - I.V,(QI, Q2K)

HA,=0= -- e-(s'CoA, +,/,

HR,=0= --e-(stCR,+zgR, i=1 ,2

Hx,= - ¢ =(~Wx, + zgx,

n~ = g t ( R l , R2, Kt)

OSIx( r)] 4(T) Ox(T)

(14)

(15)

(16)

(17)

(18)

(19)

(2o)

(21)

Assuming that the second-order conditions are also satisfied, the conditions (12)-(22) are necessary and sufficient to obtain socially optimal solutions of the welfare maximization problem. Before attempting to interpret these conditions for their policy implications, it is helpful to examine the multipliers, 4, and z. In general, at the dynamic equilibrium, the optimal level of control variable uj is chosen by equating the discounted net marginal benefits to the society from its use (=.j) to the marginal effects of its use on the stock of biomass of forest tree resources represented by the change in the growth of the state variable x multiplied by the corresponding costate variable ~f,j. Then, represents the marginal value of one unit of biomass of forest tree resource at any period t. The sign of ~fuj depends on the sign off . r

8g[K(T)] (22) • (T)= aK(T)


The optimal land allocation to the refugee occupation by reducing the forest land for camp sites and other facilities for their living is characterized by condition (12). It states that the level of forest land cleared for providing land for refugees' living should be chosen so that the discounted marginal benefits of increasing the land availability by clearing the forest trees e-6'PLL,,~ be equal to the discounted net value loss of forest trees for fuel e-~'[PiQ~,- C~,]; the discounted net value lost of forest trees for charcoal production e-tt[P2Q~,,-~,]; the discounted net value lost in crop production e-~'[P3 Yu,-~,] plus the cumulative loss in value of the forest tree resources to the society represented by ~[fu,- Wo.~Q~,- Wo.2Q~2]. Rewriting the optimality conditions for forest clearing for various uses of refugees as described above gives:

e-tt[-PiQ~,+ C~,-P2Q~,+ c-~,- P3 Yu,+ C~,] (23) e-"eLLu,= -¢ t f~ , - we, a~,- W~Q~] i= i, 2, 3

Combining this result for two different uses of forest land cleared, such as land for crop production and for use of construction material, we have:

PLLu2- Z~ + Z~2 + Z~'-~k[fu2- W°'~Q"~- WQ'Q2J (24)

where Z',~j = ~ j - P~Q',: i = 1 . . . 2; j = 2, 3. The left-hand side of (24) is the ratio of the marginal value of land area generated by land clearing for agricultural production and the marginal value generated by land clearing for the use of construction material. This is equated to the ratio of the changes in the growth function of stock of biomass of forest tree resources and the associated changes due to reduction in the production of forest trees for fuel, charcoal production and crop production. The right-hand side of the above equation could be approximately interpreted as the marginal rate of technical substitution between these two land-clearing activities as inputs in the production of land area. While this condition is important for choosing the right combination of forest land-clearing activities for meeting various needs of the refugee population, it should be noted that the land cleared for one purpose could be used for other purposes, depending on the level of scarcity of land and the quality of cleared land for crop cultivation.

The optimal conditions given by (15) shows the change in the value of costate variable if, over time, as the implicit price of scarce forest tree resource. Two major components determine the growth rate of the opportunity cost of the biomass of the forest tree resource. The first term on the right-hand side is the discounted value of trees for fuelwood and charcoal production, the increase in value of crop production and land availability due to increase in one unit of stock of biomass of forest tree resource. The second term on the right-hand side is the value of the net effect of the stocks of biomass on its own growth after accounting for the reduction in the biomass due to cutting of forest resources for fuelwood and charcoal. In dynamic terms, the above two terms represent the discounted marginal value product minus the marginal costs of forest tree resource stocks for various uses. The optimality condition for deriving afforestation policy is given by (17). It states that the discounted marginal cost of afforestation should be equal to the value of the implicit price of one unit of scarce forest tree resource. Thus, the model suggests that the value of one unit of the forest tree resource should be equivalent to the marginal value product of afforestation. This result also shows that the policy of afforestation should take into account the appropriate


prices of the scarce forest tree resources for it to be optimal at the dynamic equilibrium. The choice of wood-burning and charcoal production technologies and the optimal

level of investment into the research in such technological development is given by the condition (18). The discounted marginal cost of research activities is equated to their marginal product of research multiplied by costate variable ~ which reflects the implicit price of the research activity. The changes in the opportunity cost of research in the wood-burning technology and the charcoal production technology are determined by two components as shown in condition (19). First is the effect of technological change on the amount of wood cut for fuelwood and charcoal production multiplied by the implicit price of one unit of biomass of forest tree resource. The second component is the value of the effect of technological change on the future improvements in the efficiency of the technology.

The optimal condition for choosing ~b is given by (16). The transversality conditions (21) and (22) state that, at the end of the planning horizon T, the value of the implicit price of forest resource and the research activity would be the marginal effects on the terminal value of the growth of forest tree resources and the growth in the efficiency of wood-burning technology due to changes in the stock of forest biomass, x,, and the state of technology, K,, and period T.

4. Optimal rate and timing of afforestation

The degradation of forest resources due to the influx of refugees is generally recognized only when there is an apparent increase in the price of fuelwood resources which reflects the scarcity and the remoteness of its accessibility. Interventions in reversing the degradation of forest land in the form of afforestation are not nearly sufficient by the time the problem is recognized. For efficient planning of afforestation activities, however, the planners and policy makers must have information on the rate of deforestation, the appropriate rate of discount and the loss in value to the society due to deforestation. Even with such information, appropriate tools of analysis should be used to identify the optimal timing of interventions and the rate in which the afforestation activities should be implemented. In the absence of such planning, and because of the inadequate resources of the host country government, past efforts in afforestation of refugee populated areas have not been successful (RPG, 1992). To gain better insights for designing afforestation policies, a model is developed in this section which could be used to identify the optimal timing of afforestation in the refugee populated areas.

For the purposes of illustration, assume that the societal profit from maintaining an optimal rate of deforestation combined with an optimal rate of afforestation before the influx of refugees to the currently refugee populated areas is given by ~* (Figure 1). Due to the presence of refugees, and the associated increase in the demand for the forest tree resources, both for hut making and cooking, the societal profit goes down when the deforestation rate increases, while the afforestation rate has remained the same. This is depicted by the curve (re*-T) which shows that the profit will be zero in T when there will not be any forest resource left that is economically beneficial to the society. Thus, there should be an increase in the rate of afforestation. While the rate at which the forest trees should be replanted is obvious--the rate at which it is deforested--there may be several constraints which prevent the agencies involved in refugee relief from adopting this rate of afforestation. Because of the open-access nature of forest resources, there is no incentive for private individuals to plant trees. Also, there may not be enough land available for afforestation due to the land occupation


r~

to

I

t I t** T t 2

I I

I I I I I I

,,

I I

I

1 t*

I II / /

Figure 1. Optimal timing of afforestation.

by the refugees and land reallocation for cultivation of crops. Thus, it becomes essential to identify the optimal time for which the enhanced afforestation could be put off. In other words, the question is how much time one could borrow before attaining the initial equilibrium of fuelwood resources.

The broken lines I and II in Figure 1 indicate two different rates of afforestation which are initiated when the profit of the society declines to n~ and re2, respectively, due to the influx of refugees. For example, if the rate of decline in profit is n~, the loss to the society due to the increased deforestation by the refugees is (n*-rq). The optimal timing to start an enhanced reforestation programme in this case is given by t*. This will reverse the situation to the natural and initial equilibrium in period t~. Similar timings for the rate of decline in profit to n2 would be t** and t2. It can be seen that the greater the depletion of forest resources and the more time taken to start afforestation, the more will be the time taken to restore the initial balance between tree planting and fuelwood harvest. The model results indicate that it is essential to identify the problem and to quantify the damage caused at the earliest possible time. This would provide an indicator of the need for enhancing the afforestation programmes in the refugee populated areas.

To present the above situation more formally, a simplified version of the model presented in the earlier section is used here. The clearing of forest land for agriculture, a source of deforestation is considered as the only control variable (u2) influencing the stock of biomass of the forest tree resources. Also, it is assumed for simplicity, that the equation of motion of the stock of biomass of forest tree resource is a linear function of the land cleared for agriculture,

= m + n u 2 (25)


where m and n are constants. The decision problem for the society is to maximize the social welfare by choosing the optimal time of afforestation to maintain the original dynamic equilibrium of forest tree resource which existed before the influx of the refugee population. This is given by:

J(xo) = max,~.r f re - 6'z~/, + e-6VS(x~) (26)

and

[-1, = [P, Q, - C, + PEQ2 - C2 + P3 Y - C3 + PI.L] + ®,(m + nu2)

The first-order conditions of the problem are:

[-I~=[P,Q~2- C~2 + P2Q~.,- ~2 + P3 Y.,- C~2 + P2Lu~] + ®,n=O

-/=/x = 0 , - 60, = -[P,Q!~+P2Q].,.+P3Yx+PLLx]

noting,

®~=S~ (30)

Solving the above for u*, the optimal level of forest land-clearing activity for agricultural use and thereby the sustainable level of deforestation and plugging back in (26), we have (assuming concavity of this function with 7):

dJ(xo) dT

-O=e-6~[P,Q,+P2Q2+P3Y+PLL-C,-Cz-C3]v+S~vX~-rS~e -'~ (31)

Sx~= Or; X~v=J(~=m+nu*,

[P, QI+ P2QE+ P3Y+ PLL-C , -C2-C3]v+O~(m+nu2~)=rS~ (32)

The term on the left-hand side of (32) is the current value Hamiltonian at T. Thus,

[-I~= 6S~ at T (33)

Condition (33), which states that the value of dynamic profit to the society of clearing the forest land for agricultural production (deforestation) at T should be equal to the change in the terminal value of the forest tree resource due to change in time (Sv) multiplied by the social discount rate 6. Thus, for any time time t,

[-1, > 6S,; for t < T (34a)

and

(27)

(28)

(29)

To maximize (26) subject to (25), the current value Hamiltonian (/4,) is formed (Arrow and Kurz, 1971).


/)t < ~S,; for t > T (34b)

Comparing H, for various combinations of rate of deforestation due to the presence of refugees and the rate of afforestation with which government agencies are willing to intervene in the process of preserving sustainability, it is possible to choose an optimal time for intervention. The time of initiating afforestation would also depend on the assumptions on the functional forms of S,(xt), Yet and O (Babu and Hallam, 1989). The optimal timing of implementing afforestation programmes would also depend on the information on the rate of deforestation available to the planners.

5. Poficy implications for forest resource management in the presence of refugees

Several policy implications for maintaining the long-term equilibrium of forest ecosystems in the presence of refugee population can be derived from the foregoing analyses. It is clear from past experience that the influx of refugees from neighbouring countries, either because of drought or war, changes the land-use pattern of the area which hosts the refugees. Owing to the increased pressure on land and forest resources, the forest land is cleared indiscriminately, leaving an ecological imbalance in the refugee populated areas. While the host country governments tend to accommodate the refugee population and collaborate with the international agencies involved in the relief work, very little attention has been given to the e×ternalities in the form of increased deforestation due to the sudden population increase in the areas inhabited by refugees. Adequate planning of resource use and appropriate policies related to pricing of the forest tree resources, rate and timing of afforestation, and provision of appropriate technology that will increase the efficiency of use of forest trees are essential to prevent further degradation of forest resources and to reverse the damage already caused.

In Malawi, at least in the areas where the refugee population is concentrated, the forest tree resources could be considered as open-access property both to the local and refugee populations. This implies that the implicit price of the stock of forest tree biomass (~,) is zero (Heal, 1981; Kamien and Schwartz, 1981). Thus, in the equations (12), (13) and (14), the value of forest land cleared will be equated to the cost of land clearing. Although this value may rise over time, it will be just enough to meet the increase in the cost of labour in land clearing. The costs to future generations of clearing the forest land and the cost associated with scarcity in forest tree resources are not accounted for when their opportunity cost is zero and hence the cleared forest land is overvalued. For example, the second term on the right-hand side would be zero in equation (23). Since this implicit price of forest tree biomass is either kept low or not considered in the decision-ma~ng process in clearing the forest land for various uses of refugee population, the forest tree resources are depleted more than the social optimal rate, resulting in degradation of the forest ecosystem. To achieve the socially optimal rate of forest land clearing in the presence of refugees, the value of clearing the forests in equation (23), should be the marginal costs of land clearing plus the marginal cost of such activities to future generations.

The optimal depletion of forest tree resources is in general described by the Hotelhng rule. For each of the uses of forest tree resources by the refugee population, ul, u2 and u3 described earlier, the equations (12), (13) and (14) are first differentiated with respect to time, and the resulting equation is substituted into equation (15) along with each of these equations to eliminate the costate variable. Under the simplified assumptions of other prices held constant while identifying the growth rate of one market price and


of influence of land clearing for one use (ui) does not influence other production systems (Q~,,=0; Yu,=0; Lu,=0), the Hotelling rule could be written as:

Pi fi+B-CD P,.- E

(35)

where, B =fx- WQ, Q~- WQ, Q2x; C= PIQ~x + PHQ2~ + P3Yx + PLLx; D=f.,- WQ, Q~,- WeQ~,; and e =P,Q~,+P2Q~,+P3Y,,+PzL,,- c',,- ~ , - ~,

The left-hand side of equation (35) is the growth rate of the market price of forest tree resources for fuelwood production (i=1) and charcoal production (i=2). The prices of forest tree resources should grow at the discount rate to reflect the scarcity value of forest tree resources (Hassan and Hertzler, 1988). However, the net growth of stock of biomass of forest tree resources will also influence the growth rate of prices through its impact on the scarcity value. The external impact of the growth of stock of forests on agriculture is positive while its impact on land availability is negative. Thus, the influence of these effects on forest resource prices depend on their net effect. Additionally, the ratio of the influence of land clearing on the growth of forest resources (D) and on the net marginal benefit to society (E) also influences the growth of prices. Thus, it is clear that it is not enough for the prices to grow at the rate of discount to reflect the scarcity value of forest tree resources but should include the influence of deforestation on its growth of stock of forest tree biomass and on other production systems such as agriculture and land availability for other uses by the refugee population.

The general conclusion based on the above type of analysis from the economics of forestry literature would be to recommend imposition of royalty or user fees on deforestation due to land clearing. However, such charges may not be appropriate under the'refugee situation, as refugees come to the host country without any tangible assets. Thus, there is a need for intervention by the agencies operating on behalf of refugees and by the agencies which provide relief to them. Even if the user fee is collected, it should be used for implementing afforestation policies, to reverse the environmental damage caused by the presence of refugees. These agencies should add tree-planting activities to their relief agenda and appropriate the needed funds for afforestation.

It should also be noted that there is no incentive for private individuals to plant trees, particularly when under refugee circumstances when the necessary resources are not available. Further, refugee settlements are only temporary arrangements and the long-term benefits associated with afforestation do not accrue to them. Additionally, there also exists an institutional constraint that regards planting of trees by refugees as an attempt to gain individual rights to the land they use. Also, because of the open- access nature of forest tree resources among the refugee population, there is no incentive to incur the afforestation cost if the forest cannot be managed in the future. This is shown by the model result that, when the implicit price of forest tree resource is zero by condition (17), the marginal benefit of afforestation is negative at the dynamic equilibrium.

Similarly, it could be argued that, under zero implicit price of forest tree resources, the benefits of research undertaken to develop technology to preserve the forest resource would have no value (Hassan and Hertzler, 1988). Thus, there is also no incentive to


invest in research if the forest tree resources are not appropriately priced. As discussed earlier, the changes in the land-use pattern and the deforestation associated with the influx of refugees should be recognized and appropriate policy interventions should be evaluated for their potential benefits and costs. By setting parameters and solving the model presented in this paper, such policies could be analysed and the optimal rates of land clearing and afforestation could be identified.

6. Concluding remarks

The influx of refugees from one country to a neighbouring country could be seen as a shock to the ecological system of the host area due to the sudden increase in the human population. Forest tree resources are a major component of the ecosystem that suffers from over-exploitation resulting in deforestation. Because of the increasing needs of forest tree resources and forest lands for various uses such as fuelwood, construction material and crop production, their impact on deforestation is not preventable, at least initially. However, there exists an opportunity to intervene in the markets for fuelwood and land, and through policies relating to afforestation and technological research, to increase the efficient use of forest tree resources.

The model presented in this paper is an attempt to provide a framework for analysing such policy interventions. The optimal conditions for choosing the levels of land clearing for various uses of refugees were presented. These conditions were also used to derive the growth rate of prices of forest tree resources which was shown to be influenced by the impact of land-clearing activities on other production ecosystems and growth of stock of forest resources. The condition for substituting one use of land clearing for the other was also derived which could be used for land use planning in the refugee areas.

The final objective of afforestation policies should be to attain the dynamic equilibrium of forest resources before or by the time the refugees leave for their home country. However, it is not clear to the planners when and who should start afforestation. Using the model parameters, it is possible to identify the optimal timing and the rate of afforestation to achieve this objective.

It has been shown that, because of the open-access nature of the forest tree resources for the refugees and the local population, these resources are underpriced. For the same reason, there is also no incentive for afforestation by individuals, and the return of investment in technological research on wood-burning technology is seemingly negligible. In the absence of such incentives and the lifestyle of refugees, it is unrealistic to expect any action by the refugees towards afforestation. Additional funds should be allocated to invest in afforestation so that the deforestation trend could be reversed and the original equilibrium of forest resources could be restored.

While optimal pricing of forest tree resources, taking into account their true social cost, is suggested as a policy intervention, such policy should not be implemented in a piecemeal fashion (Crosson, 1990). It should be integrated with other environmental policies which address the problems of soil fertility, soil erosion and desertification, as they relate to forest tree resource depletion owing to the concentration of a large number of users in an area who are refugees.

The model developed in this paper, however, does not capture the loss of ecological balance due to the killing of species other than the forest trees. Future research is needed to quantify such losses and the associated reduction in the biodiversity of various animal and plant species of a forest ecosystem (Southgate et al., 1990; Solow


et al., 1992). The model assumes that all refugees come to the host country at the same time. While this may be true for situations of drought and famine, the rate of influx of refugees may vary depending on the state of war and peace in the home country under situations of civil conflict. The uncertainty in such events which may influence the rate of land clearing and the differential impact of the various causes of refugee migration should be recognized in future analyses.

The presence of refugees also influences markets and prices of food and non-food commodities. The labour market and the wage rates in the host region are also influenced. The role of studying changes caused by the presence of refugees and incorporating this information in planning and management of relief efforts for the refugee population and in designing policies to reduce the impact of associated ecological imbalances cannot be overemphasized.

The authors would like to thank Greg Hertzler and Arne Hallam for their discussions on the contents of the paper. Thanks are also due to Joachim Von Braun and Per Pinstrup-Andersen for their support and encouragement. The authors are solely responsible for the contents of the paper.

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