Ecological Economics 32(2000) 287-300
ANALYSIS
A dynamic approach to forest regimes in developing economies
Faculty of Forestry, University of Toronto, 33 Willcocks Street,
Toronto, Ont., Canada M5S 3B3
Fax: 416-978-3834
e-mail: shashi.kant@utoronto.ca
Abstract:
In the developing economies, optimal forest regimes should incorporate the socio-economic characteristics of the user groups. And, since, socio-economic factors will change with time, optimal forest regimes will also follow a dynamic path. The two most important socio-economic factors are the heterogeneity of the user group with respect to forest management and the direct dependence of the user group on forest. Normally, the heterogeneity will increase and dependence will decrease with economic growth of user group. An optimal control model is used to integrate the dynamics of natural system, such as joint product of forests and its growth function, and the dynamics of the two socio-economic factors - heterogeneity and dependence. The model demonstrates that the dynamics of optimal forest regimes will depend upon the change in natural factors, socio-economic factors, and on the interactions between natural and socio-economic factors. Hence, optimal forest management strategies would require a continuous refinement in forest management regimes, instead of static state regimes, as local communities in developing economies pass through different phases of economic growth.
1. Introduction
The existing forest resource regimes and technology available determine forest resource use. A technological perspective has dominated economic discussions during the industrialisation era. However, in the past decade the resource regime aspect of the institutional perspective has emerged strongly. As a result, the conventional view of the superiority of private or state regimes over community regimes has been challenged by a rich body of empirical evidence from around the world . This evidence points to the successful management of a wide variety of natural resources, including forests, as common or communal property. Game theoretic models have also been developed to explain the observed frequency of collective action in natural resource management (Runge 1986, Ostrom et al. 1994, Sethi and Somanathan 1996, Baland and Platteau 1996). A large number of resource economists have attempted a comparison of different resource regimes while treating the system of "resource regime" as a fixed input. Randall (1987, p.159) argues that any one of the possible specifications of non-attenuated rights would lead to Pareto efficiency, but that the efficient solution would be different for each specification of rights. Thus, he limited himself to a consideration of the locally optimal outcome. Dahlman (1980, p.138) argues the need to identify the exact relationship between production technology versus transaction costs. Cheung (1987) emphasises the importance of identifying transaction costs and their determinants. Thus, though the importance of the relationship between production technology, resource regimes, and associated transaction costs has been recognised since the articles of Coase (1937 and 1960), resource regimes have not been fully incorporated into the economic production models of natural resources that are used to identify the most efficient regime using the full set of options, ranging from open access to private regime. An adequate production model -one which can identify a global maximum - must treat both physical inputs and resource regime as variables, and should account for variation in transaction costs.
Kant 1996, and Kant et al. 1999 argue that the optimal regime for a given resource depends not only on the physical production (transformation) efficiency with which the physical inputs are converted to physical outputs but also on the level of transaction costs (transaction efficiency). Hence, an adequate theory of forest resource use should incorporate the role of institutional structures associated with different forest regimes and their associated transaction costs. The transaction cost of a forest regime will vary with the characteristics of the forest regime and the socio?economic factors (SEFs) of the user group. The authors identified and defined the two SEFs, the user group's heterogeneity with respect to forest management and the degree of direct dependence of the user group on forests . They argue that these two SEFs will be the main determinants of the transaction costs, the heterogeneity of the co-ordination cost and the direct dependence of the exclusion cost, of forest management in developing economies, and suggested a mathematical formulation of the transaction function . Based on the static analysis of the full production process, comprised of transformation and transaction functions, they found that for only a very small range of SEF values, particularly when the dependence of the user group on the resource is very low and heterogeneity very high, will one of a private or a state regime be optimal. In contrast, for a rather wide range of SEFs, some form of joint regime between state and community will be optimal . Baland and Platteau (1996) similarly argue that in selecting a form of resource regulation, a government is not confined to the spurious and simplistic "state vs. community" dichotomy, but can choose among a rather wide range of intermediate options, which will be more or less effective depending on the strength of the collective action of basic user groups.
Hence, the static analysis of the total production process of forests provides useful insights into the relationship between the socio-economic environment of the user groups and the globally optimal forest regimes in developing economies. However, communities are dynamic and their socio-economic environment changes over time, hence, optimal forest regimes will also have an evolutionary nature. Even though evolutionary economics have been gaining importance in the last decade, the evolutionary nature of resource, forest, regimes has been unable to attract the attention of either economists or forest managers. Evolutionary theories have been used to explain social conventions and norms (Axelord 1986, Sudgen 1986, 1989), law (Posner 1980), property rights (Schotter 1981, Barzel 1989, Libecap 1989, North 1990), and various forms of social and economic organisations (Williamson 1975, 1985, Nelson and Winter 1982). Bromley (1989) called these writings the "property right school" of institutional change, and summarised other contemporary writings in two categories: the "induced institutional innovation approach" associated with Hans Binswanger, Vernon Ruttan, and Yujiro Hayami, and the "North Theory". The property rights school is based on transaction costs, the induced institutional innovation approach is based on the supply and demand theory of institutional innovations. North started with relative prices being a major source of institutional change (North and Thomas 1973), and brought in many other factors such as technology, information, institutional inertia, and path dependence as sources of institutional change in his writings (North 1990). However, all of these writings have been focused on explaining the existence of different institutions or explaining the institutional changes that have already occurred. Hence, these evolutionary approaches have been criticised for their limitations in suggesting policy measures for correcting the existing inefficiencies in institutional arrangements.
Another stream of economists, now known as ecological economists, make strong arguments to move away from implicit assumptions of neo-classical economic analysis which eliminate the links between natural and socio-economic systems because, due to the strength of the real-word interactions among these components, failure to link them can cause severe misperceptions and policy failures (Costanza and Daly 1987, Norgaard 1989).
In the case of forest resources, local communities in developing economies, during pre-colonial periods, were engaged in management practices based on their specific socio-economic environment (Castro 1995, Kant and Berry 1999). The colonial administration undermined communal bonds, traditional authority, and indigenous management systems, leading to the decline of communal controls and Brightman 1987 has termed it as the tragedy of invasions. The governments of independent countries continued the same exclusionary state regimes, mainly due to past practices and prescriptions from neo-classical economic analysts and policy makers that are based on the segregation of natural and socio-economic systems. In many cases, these state regimes have become de-facto open access regimes, and are one of the main factors for global deforestation and forest degradation (Kant and Redantz 1997). Hence, the challenge to resource economists and forest managers is to integrate the socio-economic context with the natural system, and to design and refine the forest regime arrangements as the socio-economic context of the user group changes.
This paper is focused on dual objectives: to integrate the dynamics of natural and social systems, and to develop an evolutionary approach of forest regimes that can provide useful policy measures to design and refine optimal forest regimes within varying socio-economic environments. Hence, the dynamic nature of the two socio-economic factors that are the pillars of our optimal forest regime theory are first discussed. Second, using the optimal control theory, the linkages between natural factors, such as the composite product of a forest and its growth function, and the two SEFs are established in the context of the dynamics of an optimal forest regime. Next, the impact of natural and socio-economic factors on the dynamics of optimal regimes is discussed. Finally, some suggestions for designing optimal forest regimes in developing economies are presented.
2.0 The Dynamic Nature of Socio?economic Factors
Communities are dynamic and their SEFs change with time. In the present era, as communities pass through different phases of economic development, the two SEFs -heterogeneity and dependence - change. The nature of these changes is discussed herein.
2.1 The dynamic nature of heterogeneity
The presence of diversity in language, culture, religion and race, but strong "primordial attachments" of kinship, race, language, religion and custom are the features of many developing economies. Hence, these economies have cultural, social, and economic heterogeneity at the macro-level but a high degree of homogeneity at the micro or community level. Other features of these economies are the pooling of family's resources to hedge economic uncertainties, the system of self-help to hedge other hazards and difficulties of life, and non-integration with market and market economies. The process of economic growth attempts to bring these economies within the frontiers of market. However, market arrangements reduce the need for compassion, patriotism, brotherly love and cultural solidarity, as motivating forces behind social improvement (Schwartz 1987, p.247), and favours social stratification and the dissolution of ethnic bonds and customs (Seeland, 1991). In the early stages of growth, the community moves from an agricultural to an industrial foundation, and machines and non-human factors take the role of nature and human factors which leads to impersonal relationships, competition, and absence of altruism. On conversion of subsistence farming to commercial farming, members of rural communities leave for urban areas without their immediate family members resulting in a disruption of existing social relationships and a decline in the quality of personal existence. Hence, these new processes of economic growth lead to social and cultural heterogeneity. In addition, the initial stages of urbanisation and industrialisation may also intensify awareness of religious, racial, and cultural differences, and thus produce social tensions (Adelman and Morris 1973, p.31). An increase in agricultural productivity, due to commercial farming initiatives, tend to benefit the larger, more progressive farmers disproportionately in both absolute and relative terms, and hence tend to increase income inequalities (Adelman and Morris 1973, p. 18). Similarly, dualism, seen in the joint existence of traditional sectors and rapidly growing exchange sectors, is accompanied by inter-sector differences in factor productivity and per capita income (Adelman and Morris 1973, p.20). The availability of new resources such as a physical infrastructure, opportunities for income generation and socially-sanctioned access to valued jobs and administrative positions, creates conflicts of interest among various groups, and thus leads to social stratification. The new employment opportunities created through the development process require specialised knowledge that is not equally distributed, and hence gives rise to social as well as economic heterogeneity. Thus, normally, within the development process, first level heterogeneity will increase. However, the rate of change of heterogeneity will depend upon the rate of economic growth of the community and the internal inertia of the community against this change. Forest product preferences are dependent on the economic as well as the social and cultural conditions of a community. As communities pass through different stages of economic growth, product preferences of people move from unprocessed raw products such as non-timber forest products, fuelwood, and poles for house construction, to quality products such as furniture, and paper products, and finally to outdoor recreation and environmental values. Hence, even in small traditional communities, differential impacts of economic growth will increase product preference heterogeneity.
Forest management practices vary from traditional management based on the concepts of subsistence, respect for nature, minimal timber harvesting, and intensive labour, to modern western forest management practices that are based on profit maximisation and modern technology, and are export oriented and capital intensive. The intensity of these variables of forest management practices varies across communities that are under different phases of economic growth. Hence, diverse forest product preferences and preference for different management practices by the people in different economic groups will increase the diversity of forest management practices. Normally, third level homogeneity of resource management will depend upon the first and second levels of homogeneity. However, the third level homogeneity may sometimes be imposed upon by external factors such as mutual dependencies over social, economic, or cultural heterogeneous groups. But, these are exceptions to general rules, and are not of direct concern to the present discussion.
2.2 Dynamic nature of the direct dependence on forests
Economists have discussed the role of natural resources in different stages of economic development. Rostow (1956) attributed the critical role of natural resources in the first and third stage of development. In the first stage (traditional societies), natural resources offer a quick yield of increased productivity to new techniques and permit the application of innovations. In the takeoff (third) stage, foreign trade of natural resources contributes significantly to enhanced investment. Schultz (1961) observed that, at a particular time, the proportion of natural resources to all resources employed for income generation is greater in poor countries than in rich countries. The share of natural resources declines with economic growth due to improvements in the efficiency of resource use, substitution of natural resources by man-made resources, and the service sector taking a leading role over the manufacturing sector. Adler (1961) argued that in the earliest stages of organised society?? "collectional" economy of hunters and "pre?cultural" nomads?? economic activity was entirely dependent upon natural resources, and in each subsequent stage, dependence upon the resource?base of a particular location diminishes. A rise in the national or per capita income, an increased share of industrial production in GDP, urbanisation, a higher rate of literacy, increased nutritional awareness, and an improved information media are associated with economic growth. The change in individual income transforms the composition of the utility bundle, and increased and diversified industrial production enhances the range of the substitute product. An inclusion of monetary income in the utility bundle of traditional, resource-dependent communities enhances the possibility of substitution of forest products by man-made products. Nutritional awareness will encourage the substitution of raw forest products by quality products with desired nutritional values, and an improved information media will extend the knowledge of substitute products. Urbanisation reduces the direct pressure of local populations on forests. Hence, economic growth will lead to a reduction in the direct dependence of such communities on forests. However, higher per capita consumption, including the consumption of pulp and paper and other wood products, and increased environmental awareness and recreational values are associated with economic growth. But these associated phenomena will increase the one-to-many or many-to-one indirect-dependence on forests, and not the direct one-to-one dependence. Assuming that economic growth is a continuous process, the direct dependence of a forest-dependent community will decrease continuously. However, this rate of decrease may not be the same for all communities in a country. The rate of decrease will depend on the rate of economic growth. However, economic growth may not have a direct relationship in some special cases such as a community's dependence upon spiritual values. But, indirectly, the economic growth may reduce the spiritual values, and hence, may subsequently also decrease the direct dependence also.
Thus, the two SEFs, the heterogeneity of community and the direct dependence upon forests, will change over time; and their rates of change will depend upon the rate of the economic growth process, as well as some social and cultural attributes of communities. Hence, one of the main tasks of forest managers in developing economies is to design forest regimes in such a way that they remain optimal with respect to the evolving socio-economic environment. In the next section, the dynamic nature of these two SEFs is incorporated into a model that helps to explain the dynamic nature of optimal forest regimes.
3.0 Optimal Control Model of Dynamics of Forest Regimes
Many authors have used optimal control theory for modelling forest stands (Anderson 1975, Clark 1976, pp. 263-269, Sethi and Thompson 1981, pp. 287-294, Synder and Bhattacharyya 1990); however, these models are based on a traditional production function, which includes only the transformation function. The concept of the transaction function, and hence, resource regime, is missing from these models. An optimal control model of the full forest production process, which is described by the non-separable (across time) transformation and transaction functions, is developed in this section, and the dynamic path of optimal resource regime for a given forest and user group environment is examined.
I assume, for simplicity and clarity of analysis, a composite forest product which comprises all timber and non-timber products, with a net value per unit area, at time t, of V(t). The timber is removed on a rotation period, whereas NTFPs are removed continuously. Hence, V(t) represents the sum of the net value of standing timber at time t and the net value of all NTFPs removed and available to be removed up until time t. As V(t) is the net value, all costs, such as regeneration, harvesting and land rent, except the cost of a resource regime (the transaction cost), are accounted for in this formulation of V(t). The cost of the resource regime Pr(R) will be treated separately. It is also assumed that there are only two production factors: time and the resource regime. It is further assumed that, in the absence of the effect of the resource regime, the rate of change of value is represented by the logistic function: (dV/dt) = m.V.(1-V/Va) = f(V(t)), where m is the positive growth parameter and Va is the asymptotic value of V, and f(V(t)) is the growth function of the value of the composite product.
Due to the non-separable nature of transaction and transformation functions, resource regime arrangements (the transaction function) will affect the growth rate of forests as well as the net value of the composite product available to the legal right holder. As per the definition of the transaction function, the net value available to the legal right holder will be the product of the natural net value V(t) times the transaction function G(R(t),t). It is also assumed that the effective growth rate will also be the product of the natural growth rate times the transaction function. In this context, policy makers or forest managers will likely design and modify forest regimes in such a way that the legal right holder can maximise the net returns from forests. Hence, the policy maker or forest manager problem is to maximise:
ò0T [V(t).G(R(t),t) - Pr(R)]exp(-rt) dt
subject to (dV/dt) = f[V(t)].G[R(t),t],
where f[V(t)] = m.V(t)(1-V(t)/Va),
G((R(t), t)) = d(t).Ra (t) (1-R)b(t)
and V(0) = Vo.
This is a standard optimal control problem, in which V(t) is the state variable, and R(t), which is bounded within 0+ and 1-, is the control variable. This optimal control problem can be solved by a standard method. The current value Hamiltonian of this optimal control problem can be written as:
H = [V(t).G(R(t),t) -Pr(R(t))] + l(t).f(V(t)).G(R(t),t) (1)
where l(t) is known as the co-state variable, which is the marginal valuation of the state variable V(t), and is also known as the shadow price of the state variable. In the case of the current value Hamiltonian, l(t) gives the current marginal value of the state variable at time t. I also assumed that the objective function and the function which is describing the law of motion of the state variable (f(V(t)).G(R(t)) are concave, hence the necessary first order conditions of the optimal control problem will also be the sufficient conditions (Lambert 1985, p.175). First order conditions are given next.
Optimality Condition:
(H/R) = V.(G/R) - Pr/R +l.f.(G/R) = 0. (2)
In the remaining text, the subscript is used to denote the partial derivative with respect to a variable given in subscript. Hence, Equation 2 gives:
l = (PrR - V.GR)/f.GR (3)
Co-state variable (l) Condition:
(l/t) = rl - (H/V) = rl - G - l.fV.G. (4)
This equation gives the motion of the co-state variable. The equation can be written as:
(l/t)(1/l) + fV.G + G/l = r. (4a)
Equation 3 gives the shadow price of the state variable, and is equal to the marginal net value per unit of available growth due to marginal change in the resource regime. Equation 4a gives the motion of the shadow price. The first term in Equation 4a gives the relative rate of change of the marginal valuation (the shadow price) of V(t), the second term gives the value available from the growth of the state variable, and the third term gives the relative available value from one unit of the state variable with respect to the shadow price. The right hand side gives the psychic cost due to time preference. A common understanding of the nature of forest growth (fv being quite high in the early and middle stages of a forest, as compared to r, indicates that the relative marginal value of the stand V(t) will decrease at a decreasing rate along the optimal path. However, even though the value is marginally decreasing, the forest is not cut because the value of available growth is greater than the value obtained by cutting the forest (Donnelly and Betters 1991).
Law of motion:
(V/t) = f.G = m.V(1-V/Va).d.Ra(1-R)b. (5)
On substituting the value of the growth function (f) from Equation 2,
(V/t) = [(PrR - V.GR)/lGR].G. (6)
The Co-state Variable Equation (4) and the Law of Motion Equation (6) give the motion of the co-state and state variables, respectively. The standard practice is to study the paths of the state variable and co-state variable or the path of the state variable and control variable. Hence, one option is to analyse the optimal path of the state and co-state variables. However, even though these two first order differential equations (4 and 6) are autonomous (time does not appear explicitly), both equations contain the control variable (R(t)) in some form. Hence, the analysis of the motion of the state and co-state variables, with the help of a phase diagram of these two equations in the present form, is not feasible. In addition, the main aim of this paper is to integrate natural and social systems, and to study the impact of these systems on the evolution of optimal resource regimes. Hence, I focus upon developing an equation of the dynamics of an optimal resource regime that can aid in evaluating the impact of the dynamics of natural and social factors upon the dynamics of forest regimes.
On differentiating Equation 3 with respect to t, and substituting the value of l, and (l/t) in Equation 4 and further substituting the value of (V/t) from Equation 5, the following is achieved:
-PrR.f.(GR/t) = (PrR. - V.GR).GR.[ft + f(r - fV.G)] (7).
Since, G(R(t)) = d(t)R(t)a(t).(1-R(t))b(t), and GR = G.[(a/R) - (b/(1-R))].
When GR is differentiated with respect to time, the following is achieved:
(GR/t).(1/G) = [{(a/R)-(b/(1-R))}2 - (a/R2) + (b/(1-R)2)].(R/t)
+[{(a/R)-(b/(1-R))}.{(1/d).(d/t)+(a/t).ln(R)+ (b/t).ln(1-R)}] +[(a/t).(1/R)-(b/t).(1/(1-R)] (8).
On substituting the value of (GR/t) in Equation (7), I get
h2 (R/t) = [h1.{(V.GR - PrR)/PrR}.{r + (ft/f) - fv.G}]
- (1/d).(d/ t).h1 + (a/t).[-h1.ln(R)- 1/R] + (b/t).[{1/(1-R)}-h1.ln(1-R)]
where h1 = {(a/R)-(b/(1-R))}.
and h2 = [h12 - (a/R2) + (b/(1-R)2)] (9).
Equation 9 gives the rate of change of the optimal resource regime. The solution to two non-linear differential equations of motion (Equations 6 and 9), subject to the initial conditions, which will prescribe the initial values of the two SEFs (a and b), the scaling factor (d), the state variable, and the transversality conditions, will give the unique optimal path of the state variable V(t) and the control variable R(t). However, as stated earlier, the main objective of this paper is not to find a unique path for given initial and transversality conditions, but rather to develop an understanding of the interactions between natural and social systems, and their impact on the dynamic path of optimal forest regimes. Hence, I examine Equation 9, and evaluate the role of natural and socio-economic factors in the dynamic path of optimal resource regimes.
In brief, Equation 9 can be written as:
(R/t) = function (V, f, P, r, d/ t, a/t, b/t).
Hence, the change in the optimal resource regime will depend upon neither the natural factors, nor the social factors, but rather upon both of the factors as well as upon their interactions .
As stated earlier, the resource regime (R) represents the degree of exclusion of the local user group and varies from 0 to 1. Hence, a positive rate of change of resource regime means more exclusion or a shift towards a private regime, and a negative rate of change means a move towards less exclusion or a community regime. As per Equation 9, four terms contribute to the rate of change of forest regimes. The first term comprises the state variable V(t), growth function (f), transaction function and transaction costs, and one term each represents the contribution of the rate of change of the scalar function, the heterogeneity of the user group, and the dependence of the user group, respectively. The actual contribution of each term will depend upon the initial conditions, and the aggregate rate of change of the resource regime will depend upon the relative contribution of each term. However, an understanding of the main contributors of each term will provide a broad framework to policy makers and forest managers in designing and modifying forest regimes as per the requirements of change in natural and social systems. The impacts of natural and socio-economic factors on the rate of change of resource regime are discussed next.
3.1 Natural and socio-economic factors and the dynamics of optimal forest regimes
Natural factors influence the path of the optimal resource regime through marginal relative return (V.GR - PrR)/PrR} and relative growth (r + (ft/f) - fv.G). The marginal relative return is the relative rate of change of net benefit to the cost of the resource regime due to a marginal change in the resource regime. Thus, if the change in the net benefit, due to a change in resource regime, is higher as compared to the resource regime cost, the rate of change of the resource regime will be higher. In neo-classical economic analysis, the contribution of this term will be independent of the socio-economic conditions of the user group. However, in my formulation, even the contribution of this term will depend upon socio-economic factors because the value of the composite product (V) and the transaction cost (Pr) are sensitive to socio-economic factors. The components of the composite product may change with time depending upon the socio-economic conditions and preferences of the group. For example, in the early stages of economic development, the local people are dependent upon forests for their livelihood and V will include timber, as well as many non-timber forest products which may not have market value. With economic development, many non-timber forest products may not be valuable to the user group anymore, and hence will be excluded from V. Thus, when V includes many high value products, and its value is very high, the rate of change of the resource regime will be highly sensitive to the values of V. As mentioned throughout this paper, the transaction cost is mainly dependent upon the two socio-economic factors. Hence, as user groups pass on to the next economic growth phase, the exclusion cost may be reduced due to a reduction in dependence, but co-ordination cost may increase due to an increase in heterogeneity. Thus, the overall impact of the relative marginal valuation term will depend upon the relative changes in V and transaction costs. If the change in value is higher than the change in transaction costs due to a marginal increase in exclusion, the resource regime should be modified towards more exclusion (private). If the change in values is less than the change in transaction cost due to marginal increase in exclusion, the resource regime should be modified towards less exclusion (community). In other words, in less developed and highly forest-dependent communities, smaller changes in the forest regime in opposing directions than that of economically expected may cause high economic and welfare losses. At the same time, larger marginal costs of the resource regime will logically lead to smaller changes in the resource regime. If there is high cost of change in the resource regime, it will not be optimal to change it. The relative growth term (r +(ft/f) - fv.G) implies that the higher rate of time preference and the higher rate of change of the growth function with respect to time will lead to a higher rate of change of the optimal resource regime, and the effect rate of growth function with respect to time and volume are in opposite direction. Hence, fast growing forests (high ((ft/f)) will require rapid changes in forest regimes as compared to slower growing forests. However, the growth function, f, represents the growth of V. The terms, ft and fv will depend upon the composition of V, and hence upon the socio-economic factors of the user group. The dynamics of the rate of time preference, and hence its impact upon, the dynamics of optimal forest regimes is a controversial issue. Strict neo-classical economists are unwilling to deviate from equating the rate of time preference to the real market rate of return on man-made capital investments. Ecological economists are of the view that man-made capital and natural capital are not substitutes (Costanza and Daly 1992 ), and thus, I subscribe to the view that the real rate of interest is not the correct measure of the rate of time preference for natural capital. Kant (1999) demonstrates that traditional forest-dependent communities normally have a lower rate of time preference for forest resources as compared to industrialised communities . Hence, the impact of the rate of time preference will also vary with the socio-economic environment of the user group. The rate of change of the optimal forest regime will be lower in the case of traditional communities, who have a lower rate of time preference, as compared to economically developed communities.
In addition to these impacts of socio-economic factors through interactions with natural factors, the socio-economic factors also independently contribute to the rate of change of optimal forest regimes. As the transaction function is defined in terms of heterogeneity and dependence, it is natural that the optimal resource regime will vary with the variation in these two socio-economic factors. The change in optimal resource regime is directly proportional to the rate of change in heterogeneity and dependence. However, the increase in heterogeneity will drive the optimal resource regime towards a private regime, while an increase in dependence will drive towards a community regime. The scaling factor (d), which normalises the achievable maximum value of the transaction function, and the maximum value can be different under different socio-economic environments. Therefore, the two socio-economic factors will also affect the optimal resource regime through the scaling factor. This analysis demonstrates that socio-economic factors are critical to the optimality of the total production process of forest resources, and that non-inclusion of the socio-economic environment, and its interaction with natural factors, will result in economic inefficiencies.
The continuous rate of change in the resource regime may be questionable from the practical aspects of designing forest regimes. It is understood that to make continuous changes in the resource regime is not feasible, and this is the main reason why a specific solution to the two motion equations has not been attempted in this paper. However, the broad outcome of the model - the optimal resource regime arrangements not remaining stationary and changing over time according to changes in socio-economic factors - is very critical for efficient forest management decisions, and can be used by forest managers to improve the efficiency of forest management. Forest managers should include SEFs in their set of management variables, and necessary amendments should be made to the resource regime either to increase or decrease the exclusion of local communities as and when required due to change in socio-economic factors.
4.0 Final Comments
The dynamic model of forest regimes has demonstrated that socio-economic factors are interrelated with natural and biological factors in affecting the value and growth of renewable resources like forests, and these factors together affect resource regimes and other institutional structures. Hence, socio-economic factors can and should be incorporated in economic and forest planning processes, and planning and policy decisions neglecting the interactions between the natural system and the social system will be inefficient. The dependence of optimal forest regimes upon socio-economic factors also indicates that uniform solutions, as advocated either by supporters of privatisation or total government control, will not be optimal in all socio-economic environments, and local or community based management will also provide an "efficient" management regime in many socio-economic environments of developing economies. The realisation of the sensitivity of optimal forest regimes to the socio-economic environment also demands the decentralisation of forest planning and management decisions. The decentralisation will help local forest managers in designing and modifying forest resource regimes according to local socio-economic environments and natural factors of the local forests. The non-inclusion of SEFs will lead to slow de-facto conversion of exclusionary regimes, such as state and private regimes, to open access regimes and conflict between local communities and forest managers. Such processes will not only be detrimental to efficiency and sustainability, but would also be responsible for a high rate of deforestation and resource degradation.
The analysis also indicates that the choice of forest managers is not limited to three discrete resource regimes. Hence the amendment in the existing resource regime does not mean change from community control to state control or nationalisation to privatisation. Once an optimal resource regime, according to the local socio-economic and natural factors, is implemented, it will require only marginal adjustments in resource regime arrangement to match the changes in socio-economic and natural factors. These adjustments will be in the terms of degree of exclusion of communities and hence the role of communities and the state in forest management. For example, if certain communities start loosing its control over community-based forest management practices due to increased heterogeneity and reduced dependence on forests, forest managers should help in designing forest regimes based on greater role of state and smaller role of communities. .
Finally, the two necessary conditions for efficient forest use are: firstly, choosing an appropriate technology, and secondly, choosing an appropriate forest regime. Choosing an appropriate resource regime is critical to under-developed and developing economies. The economies of these countries need strategies that will lead to over-achievement if they are to catch up with the developed world. Hence, they require policies which build upon intangible sources of growth. The choice of an appropriate resource regime is one such source. In the early stages of economic growth, natural resources play a very prominent role in economic growth. Hence, an understanding of optimal resource regimes, their linkages with socio-economic factors, and the dynamics of these optimal regimes and SEFs, can play a critical role in economic growth of developing economies.
Acknowledgements: I would like to thank to Albert Berry, G Helleiner, Jagdish Nautiyal, D Nowlan, D Puttock, and three reviewers for their insightful and useful comments. The manner in which their comments have been interpreted is entirely my responsibility. I would like to express my special thanks to one of the reviewers who provided deep insights about the paper's implications. Research Funds from the Social Sciences and Humanities Research Council of Canada (Grant No. 410990343) and the Natural Sciences and Engineering Council of Canada (Grant No. 203032-98 RGPIN) are also greatly acknowledged.
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