Ecological Economics 32 2000 287 – 300
ANALYSIS
A dynamic approach to forest regimes in developing economies
Shashi Kant
Faculty of Forestry, Uni6ersity of Toronto,
33
Willcocks Street, Toronto, Ont., Canada M
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S
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Received 18 March 1999; received in revised form 27 July 1999; accepted 28 July 1999
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. © 2000 Elsevier Science B.V. All rights reserved.
Keywords
:
Economic growth; Forest management; Institutions; Optimal control; Socio-economic factors www.elsevier.comlocateecolecon
1. Introduction
The existing forest resource regimes and tech- nology available determine forest resource use. A
technological perspective has dominated economic discussions during the industrialisation era. How-
ever, 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 com-
munity regimes has been challenged by a rich body of empirical evidence from around the
world.
1
This evidence points to the successful management of a wide variety of natural re-
sources, including forests, as common or commu- nal property. Game theoretic models have also
1
These include forests in India Kant et al., 1991; Poffen- berger and Singh 1991; Campbell, 1992, Kenya Castro,
1995, Mexico Alcorn, 1989, Nepal Gilmour and Fisher, 1991; water in the Philippines Cruz, 1989; Ostrom, 1990,
and India Wade, 1987; grazing lands in Botswana Peters, 1987 and swamplands in Borneo Vondal, 1987.
Fax: + 1-416-9783834. E-mail address
:
shashi.kantutoronto.ca S. Kant 0921-800900 - see front matter © 2000 Elsevier Science B.V. All rights reserved.
PII: S 0 9 2 1 - 8 0 0 9 9 9 0 0 1 0 0 - 7
been developed to explain the observed frequency of collective action in natural resource manage-
ment Runge, 1986; Ostrom et al., 1994; Baland and Platteau, 1996; Sethi and Somanathan, 1996.
A large number of resource economists
2
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 iden- tifying transaction costs and their determinants.
Thus, though the importance of the relationship between production technology, resource regimes,
and associated transaction costs has been recog- nised since the articles of Coase 1937 and Coase
1960, resource regimes have not been fully incor- porated into the economic production models of
natural resources that are used to identify the most efficient regime using the full set of options, rang-
ing from open access to private regime. An ade- quate 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 transforma- tion 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 struc-
tures associated with different forest regimes and their associated transaction costs. The transaction
cost of a forest regime will vary with the character- istics 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
3
and the degree of direct dependence of the user group on forests.
4
They argue that
3
User group heterogeneity with respect to forest manage- ment: Members of the user group will often have somewhat
different preferences regarding resource management, or as- sign different priorities to the various objectives of resource
management, either because of differing personal interests in the resource or differing degrees of involvement in the social
group. People think of themselves both as separate ‘individu- als’ and as ‘members of a social group’. In traditional societies,
where people see themselves first as members of the group and only afterwards as independent individuals, an inherent spirit
of co-operation is generally present even in the face of large economic differences and social stratification. This spirit is
muted in modern industrial societies, where people are first and foremost ‘individuals’ and more truly homo-economicus.
The heterogeneity of individual interests with respect to how a resource is managed reflects both economic differences e.g.
income level and social and cultural traditions or norms; the extent to which ‘personal’ interest fully determines an individ-
ual’s behaviour with respect to the resource depends on the degree of ‘community spirit’, hence, the level of heterogeneity
allowed to range between 0 and 1 will vary inversely with the degree of such ‘community spirit’ as well as with respect to
economic differences. A hierarchy of the levels of heterogene- ity provides linkages between cultural, social and economic
differences and resource management. The basic level consists of cultural, economic, ethical and social differences. Due to
this basic heterogeneity, the members of the user group may have diverse preferences for timber and non-timber products
and hence prefer different product mixes, and this could be termed second level heterogeneity. Diverse product preferences
will result in different preferences for resource management regimes, which can be labelled third level heterogeneity. In
summary, heterogeneity with respect to resource regime can be treated as a function of the product preference differences,
which can in turn be treated as a function of cultural, eco- nomic, ethical, and social heterogeneity. The heterogeneity
with respect to resource management is the inverse of full agreement on, and support for, the same resource management
regime. Kant, 1996; Kant et al., 1999.
4
The degree of direct dependence of user groups on forests: Everyone depends on forests in some way. Forests provide
many values such as consumption, recreation, environmental, and spiritual. In developing economies, some tribal groups
depend on forests, located close to their habitations, for their consumption items such as food, fuel, medicines, and even
monetary income from the sale of minor forest products that are necessary for their subsistence. These groups have a one
2
Including Krutilla and Fisher, 1975, pp. 19 – 38; Scott and Johnson, 1985; Bromley and Szarleta, 1986; Fortmann and
John, 1988; Magrath, 1989; Pearse, 1990, pp. 173 – 93; Brom- ley, 1991; Luckert, 1992.
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 devel-
oping economies, and suggested a mathematical formulation of the transaction function.
5
Based on the static analysis of the full production pro-
cess, comprised of transformation and transaction functions, they found that for only a very small
range of SEF values, particularly when the depen- dence 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.
6
Baland and Platteau 1996 similarly argue that in selecting a form of resource regula-
tion, a government is not confined to the spurious and
simplistic ‘state
versus community’
di- chotomy, 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.
group to one forest direct dependence on the forest. In developed economies, most user groups depend on forests for
derived items such as pulp and furniture, and these items may be available from any forest area. The derived items from one
forest area may be available to many user groups, or one user group may get derived items from different forests. These
groups also depend on forests for recreational values, but they again derive these values from different forest areas. Hence, in
this case, there is a one group to many forests or many groups to one forest indirect dependence relationship be-
tween the user group and the forest. In developed countries, some aboriginal groups have a one to one direct-dependence
relationship with the forest. Similarly in developing economies, some groups may also have a one to many or many to one
indirect-dependence relationship with the forests. Here, my interest is in the degree of the one to one direct dependence of
the user group.
The degree of direct dependence is defined as the share of direct returns from forests in the total utility bundle. Its range
is also defined as 0 to 1, and may be reasonably measured by the fraction of the user group’s gross local production con-
tributed by the forest. The degree of direct dependence will depend on the substitutability of forest returns that, in turn,
will depend upon the availability of substitutes and the capac- ity of the user group for substitution. The capacity of the user
group will depend on the composition of the utility bundle. In the case of the utility bundle being comprised of forest returns
only, there is no possibility of substitution and hence, the degree of direct dependence will be very high and equal to one.
The case of subsistence dependence of tribal communities will fall in this category because there are substitutes, but the user
group is unable to acquire the substitutes because of their limited monetary income. In some cases, utility bundle may
consist of returns from different sources including monetary income, but there may not be any substitute for forest returns
such as spiritual values. In such cases, the degree of depen- dence will depend upon the share of spiritual values in the
utility bundle. However, the share of spiritual values may not be quantified in monetary terms, but its share in the utility
bundle can be determined by Participatory Rural Appraisal methods Kant, 1996; Kant et al., 1999.
5
A resource regime typically has several economically im- portant dimensions
— comprehensiveness, exclusiveness,
benefits conferred etc. each of which may vary across a spectrum. However, in the case of developing economies, the
most important dimension is exclusiveness, and hence the focus is on this dimension only. Thus R is the continuous
resource regime variable representing different level of exclu- siveness, scaled for simplicity between 0 to 1 but excluding the
end points. On this scale, open access no exclusion is represented by a number near zero, and a private regime,
which means full exclusion, by a number close to 1. Given the way the two costs — exclusion cost and co-ordination cost —
are linked to forest regime, the most plausible simple assump- tion is that the transaction function is either monotonically
increasing, monotonically decreasing, or has a single maxi- mum value somewhere in the domain ranging from open
access to private regime. Such a transaction function GR can be expressed by the mathematical form:
GR = dR
a
1 − R
b
The parameter a is the heterogeneity of the user group with respect to forest management, and b the degree of direct
dependence on forests. d is a scaling factor that normalises the maximum value of the transaction function. Readers interested
in more details of this function can refer to Kant, 1996; Kant et al., 1999.
6
As mentioned in footnote 5 on the exclusion dimension, the resource regime varies from open access to private regime.
In operational aspects, in the case of open access, there are no restrictions on the use of any output from forests. Under the
community regime, the user group is entitled to all the prod- ucts, but use is typically regulated in terms of harvesting time
and quantities to be harvested during a particular time. In the case of a joint regime between the state and community in
India, the user group and the state both get a share of timber products and of nationalized non-timber products, while non-
nationalized non-timber products go to the user group. Under a state regime, the local community is totally excluded from
timber and nationalized non-timber products, but not from the actual use of non-nationalized non-timber forest products.
Under a private regime, the user group is excluded from all products.
Hence, the static analysis of the total produc- tion 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 so-
cio-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; Nelson and Winter, 1982; Williamson, 1985.
Bromley 1989 called these writings the ‘property right school’ of institutional change, and sum-
marised other contemporary writings in two cate- gories:
the ‘induced
institutional innovation
approach’ associated with Hans Binswanger, Ver- non Ruttan, and Yujiro Hayami, and the ‘North
Theory’. The property rights school is based on transaction costs, the induced institutional inno-
vation approach is based on the supply and de- mand 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 oc- curred. Hence, these evolutionary approaches
have been criticised for their limitations in sug- gesting 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-clas- sical economic analysis which eliminate the links
between natural and socio-economic systems be- cause, due to the strength of the real-word inter-
actions 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 communi- ties in developing economies during pre-colonial
periods were engaged in management practices based on their specific socio-economic environ-
ment Castro, 1995; Kant and Berry, 1999. The colonial administration undermined communal
bonds, traditional authority, and indigenous man- agement systems, leading to the decline of com-
munal controls that has been termed as the tragedy of invasions Brightman, 1987. The gov-
ernments 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-eco- nomic systems. In many cases, these state regimes
have become de-facto open access regimes, and are one of the main factors in 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 sys-
tems, and to develop an evolutionary approach of forest regimes that can provide useful policy mea-
sures to design and refine optimal forest regimes within
varying socio-economic
environments. Hence, the dynamic nature of the two socio-eco-
nomic 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. The dynamic nature of socio-economic factors
