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Environmental and Resource
Economics
The Official Journal of the European
Association of Environmental and
Resource Economists
ISSN 0924-6460
Volume 53
Number 1
Environ Resource Econ (2012) 53:73-95
DOI 10.1007/s10640-012-9548-4
Socioeconomic Impacts of Public Forest
Policies on Heterogeneous Agricultural
Households
Bhubaneswor Dhakal, Hugh Bigsby &
Ross Cullen
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Environ Resource Econ (2012) 53:73–95
DOI 10.1007/s10640-012-9548-4
Socioeconomic Impacts of Public Forest Policies on
Heterogeneous Agricultural Households
Bhubaneswor Dhakal ·Hugh Bigsby ·Ross Cullen
Accepted: 11 February 2012 / Published online: 28 February 2012
© Springer Science+Business Media B.V. 2012
Abstract Nepal has a long history of returning public forests to local people as part of its
community forestry programme. In principle the community forestry programme is designed
to address both environmental quality and poverty alleviation. However, concern has been
expressed that forest policies emphasise environmental conservation, and that this has a det-
rimental impact on the use of community forests in rural Nepal where households require
access to public forest products to sustain livelihoods. To study the effect of government
policies on forest use, an economic model of a typical small community of economically
heterogeneous households in Nepal was developed. The model incorporates a link between
private agriculture and public forest resources, and uses this link to assess the socioeconomic
impacts of forest policies on the use of public forests. Socioeconomic impacts were mea-
sured in terms of household income, employment and income inequality. The results show
that some forest policies have a negative economic impact, and the impacts are more serious
than those reported by other studies. This study shows that existing forest policies reduce
household income and employment, and widen income inequalities within communities,
compared to alternative policies. Certain forest policies even constrain the poorest house-
holds’ ability to meet survival needs. The findings indicate that the socioeconomic impacts of
public forest policies may be underestimated in developing countries unless household eco-
nomic heterogeneity and forestry’s contribution to production are accounted for. The study
also demonstrates that alternative policies for managing common property resources would
reduce income inequalities in rural Nepalese communities and lift incomes and employment
to a level where even the poorest households could meet their basic needs.
Keywords Community forestry policy ·Poverty reduction ·Linear programming ·
Agroforestry
B. Dhakal (B
)·H. Bigsby ·R. Cullen
Faculty of Commerce, Lincoln University, PO Box 84, Lincoln, Canterbury 7647, New Zealand
e-mail: Bhubaneswordhakal@gmail.com
H. Bigsby
e-mail: Hugh.Bigsby@lincoln.ac.nz
R. Cullen
e-mail: Ross.cullen@lincoln.ac.nz
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1 Introduction
Since the 1970s, forest policies in many developed countries have been reformed to address
growing problems of environmental degradation and wood product demands (Dhakal 2009;
Strassburg et al. 2009;Master Plan 1988). The reforms have substantially changed production
systems in community and public forests, and potentially changed supplies of various kinds
of forest products including non-wood products. For example, forests in Nepal, which occupy
40% of the land area, have traditionally supplied inputs such as firewood, fodder/pasture,
timber, charcoal and other non-wood products that are useful for rural households. However,
recent Nepalese government policies, designed to protect forests, have reduced rural com-
munities’ access to local forest products and further marginalized poor people (Thoms 2008;
Shrestha and McManus 2007;Maskey et al. 2006;Hjortso et al. 2006;Dhakal et al. 2011).
Similar issues have arisen in other countries (Kumar 2002;Agrawal 2001).
Public forest resources are crucial for sustaining rural economies and improving the well-
being of poor rural people (Graner 1997). Agriculture is an important part of Nepal’s economy
but the average private landholding is less than 0.8ha and 47% of land-owning households
own 0.5 ha or less (CBS 2003). Off farm employment opportunities are not accessible for
many people and their private landholdings are generally inadequate to sustain their families.
Due to the absence of motorized transport, and poor access to markets and other support
services, many communities are required to be locally self sufficient. Many social problems
in Nepal including armed conflict, frequent public demonstrations, and people trafficking
are associated with limited access to resources and increasing unemployment (Murshed and
Gates 2005;NPC 2003;Graner 1997).
A number of studies have assessed the economic impacts on resource-based households
caused by reforms to public forest policies, and have reported mixed results, particularly in
developing countries (Karky and Skutsch 2010;Strassburg et al. 2009;Thoms 2008;Adhikari
et al. 2007;Kumar 2002;Aune et al. 2005). These studies measure the impacts of changes in
quantities of products or other direct economic returns from public forests that are available to
households. However, the studies do not consider the economic effects of the complementary
relationship between public forest resources and private farm resources. This relationship is
often critical for rural households to sustain livelihoods, particularly when there are fac-
tors such as income constraints or remoteness from markets that mean households cannot
source resources from external markets. Furthermore, few studies have assessed the effect of
forestry policies across household income groups and their impacts on income inequalities
within communities.
In cases where agriculture and forestry resources are complements, a model with endog-
enous consideration of inter-sector relationships can provide a better account of economic
impacts of forest policy changes (Alig et al. 1998). Accounting for household economic
heterogeneity and levels of dependency of users is crucial for a robust understanding of the
economic effects of changes in the management of common property resources (Baland and
Platteau 1999). Anthon et al. (2008) developed a model that includes household economic het-
erogeneity, and integrated agriculture and forestry components to explain economic impact
of public forest policy changes on farming communities in developing countries. However,
their model is theoretical, not empirical, and could not be used to evaluate the impacts of
different policy scenarios. Computational general equilibrium (CGE) models, often used
to assess socioeconomic impacts of forest policy (Shen et al. 2009;Stenberg and Siriwar-
dana 2007), are also not appropriate in developing economies. This is because the economy
responds poorly to changing market prices or induced markets of forestry products. We believe
our study is the first to assess the socioeconomic impact of changes of forest policies in a
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Heterogeneous Agricultural Households 75
developing country using an empirical model that comprises a link between agriculture
and public forestry resources and accounts for household heterogeneity in private resource
endowments.
Evaluation of the likely economic impacts of alternative forest policies on rural communi-
ties is thus an important topic for investigation. An empirical model that recognises household
heterogeneity,1and that links agriculture and forest resources, is needed to evaluate alterna-
tive forest policies in Nepal. The objective of this study is to develop an empirical model that
will allow the socioeconomic impacts of public forest policies in agriculture-based commu-
nities to be assessed, where there are limited opportunities to sustain livelihoods. A requisite
of the model was to capture variation in household reliance on public forest resources to
assess the impact of changes of government forest policies on individual households. This is
accomplished by looking at changes to household income and employment. We assume that
policy alternatives influence a household’s behaviour, particularly how they manage their
livestock and allocate time. Households strive to maximize their income subject to the con-
straints they face. Alternative forestry policies are evaluated in the paper by formulating and
solving an optimization model. The following sections outline the analytical model, policy
scenarios, data sources and results of simulations of the policy scenarios.
2 Community Forest Based Economies
The economy of a representative Nepalese rural community includes the private resources
of its member households, markets for labour and local products, and access to commu-
nity resources including forests. Members of the community use public forest resources to
complement private land resources to sustain livelihoods. The community economic model,
therefore, is an extension of a household production function model. However, the production
function is quite different from other forest-based household models in that it incorporates
the community management, distribution and use of products of the community forest, as
dictated by government policies. There are many different forest policies for different local-
ities and characteristics of the specific forest resources. Alternative forest policy options
included in this study are discussed later. The following sections outline the structure of the
model.
3 Household Resource and Production System
Each household in the community maximizes its income to meet its consumption require-
ments. In the household model, private land, community forest land and household labour are
the key factors of production. Household consumption can be met by using its private land
area (ap)to produce goods, by forest products from community forestland (ac)or by pur-
chases in nearby markets. The private land area used to produce each of the different outputs
(ito I) cannot be greater than its private endowment (Eq. 1). For modelling purposes, there
are three different income groups, with different private landholdings between groups, and
the same private landholding within a group. Our model also includes different categories
of private lands (e.g. upland, lowland, grassland and private forestland), which have distinct
features in production systems, as explained in the Sect. 6.
1Land resources are the main source of income and employment in rural Nepal. Rural households are
heterogeneous in private landholdings, which influences the impact of forest policies on household income
and employment.
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76 B. Dhakal et al.
I
i=1
api ≤ap(1)
For the following discussion, we drop the private and community land area subscripts, cand
p, and refer to a generic land type kthat can refer to a category of land and its ownership.
Output of any good iunder production system ton land type kdepends on the yield
per unit area using a production system on a land type (Ritk)and the area of land type k
allocated to a particular production system by a household (atk). As in many linear program-
ming studies, it is assumed that marginal product (yield) is constant (e.g. Das and Shivakoti
2006). Land can include private land, land used under sharecropping and public forest land
that is allocated to a household to use. Products can be a single output from a production
system or byproducts. Agriculture and forestry production systems can produce more than
one product simultaneously (Amacher et al. 1993). The outputs can include a range of cereal
crops, livestock and forest products. Total output of any particular good by a household (qi)
is then a function of how much land of various types the household allocates to different
production systems.
qi=
K
k=1
T
t=1
(Ritkatk)(2)
Community forest land can be used for multiple objectives, however this can be constrained
by government policy. Two types of policies are considered here. The first policy affects the
area of land type kthat can be used for a particular output (G1ki ). In this policy, some pro-
portion of community forest land may be allocated or restricted to achieve particular policy
objectives (eg. erosion control). As such G1kranges from 0 to 1. The other type of policy
constrains the level of production from an area that is being used for an output (G2ki).An
example of this constraint is where the government limits forest harvests to a proportion of its
mean annual increment (MAI), such as for a contribution to global climate change mitigation.
Again, the value of G2ki can range from 0 to 1. The constrained production of output due to
government policy is then,
qi=
K
k=1
T
t=1
(atkG1ki )(RitkG2ki)(3)
Livestock farming is done by stall feeding of fodder, grass and crop by-products. Because
of the differences in nutritional value of these feeds, their use is standardised to total digest-
ible nutrients for that feed type (TDNi). Farmers can also purchase supplementary nutrients
(TDNSN)as a substitute for fodder, grass and crop by-products. The total digestible nutrients
requirements differ for each livestock type (TDNu). The livestock unit holding of particular
type (LUu)can be calculated as,
LUU= I
i
qiTDNi+TDNSN
TDNu(4)
In a subsistence agricultural household, household labour can contribute to a range of activ-
ities ranging from entrepreneur, manager and labourer (Taylor and Adelman 2003;Bardhan
and Urdy 1999). In this model, the amount of labour required for the production of an output
depends on the area of land area that is planted or managed, and on the volume harvested. The
labour required to get a particular output ready for harvest is then a function of labour hours
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Heterogeneous Agricultural Households 77
required per unit area (ha
tk)to manage a production system ton land type k,andthelandarea
under management (atk). The labour required to harvest a particular output is a function of
output (qi)and the labour hours per unit output for that good (hv
i). Total household labour
(Lq)required is then:
Lq=
T
t=1
K
k=1
(ha
tkatk)+
I
i=1
(hv
iqi)(5)
In this model, only labour that is hired (Lh)is incorporated as a cost. The amount of hired
labour required is a function of total available household labour days (L), labour required
for production, leisure days (L0), and days contributed to community forestry (Lc).
Lh=L−Lq−Lc−Lo(6)
Similar to labour, only the production expenses that require cash purchases are defined as
costs. The cost of inputs required by a household for a particular output may be a function
of either the area under production or the quantity of output. Area-related cash costs (Stk)
depend on the input cost per unit area of land type k,allocated to a particular use t,by a
household and the area allocated to that use (atk). When cash input costs are related to output
then the cost depends on the costs per unit output for that good (Sik)on land type k,and the
amount of output (qik)from that land type. Total cash input cost (i)is,
i=
K
k=1
(qik ·Si)+
K
k=1
(atk ·Stk)(7)
A household consumes goods from their own production and from purchases in local markets.
From their own production of particular products (qi), the household sells surplus goods (qs
i)
such as food, firewood, timber and fodder in at the market wholesale price (Pi). A household
can also make purchases (qm
i)to cover deficiencies in supplies at the retail market price (pi).
For household income analysis purposes, the goods produced and consumed at home can
be valued at either the wholesale farm gate price or retail market price. The retail market
price is the sum of transaction costs, intermediary’s profit and the wholesale farm gate price.
We use wholesale farm gate price in our analysis because this is typically the price received
by subsistence farmers. Therefore the value of home consumption of any good (Di)can be
written as,
Di=Pi(qi−qs
i)+piqm
i(8)
Net household income (y)is the difference between revenue and costs. In addition to pro-
ducing outputs, households are able to earn external income in the labour market (Lm)at rate
(w). It is assumed that a household will either earn outside income (Lm)or employ outside
labour (Lh), but will not do both. There are no taxes applicable on wages or farm product
incomes.
y=
I
i=1
Di+
I
i=1
(Pi×qi)+(Lm×w)−(Lh×w)−
I
i=1
i−
I
i=1pi×qm(9)
4 The Community Economic Model
Community forest user groups are composed of households of various income levels
(Adhikari et al. 2004). In the model, the community is structured as (Z)different income
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78 B. Dhakal et al.
groups with (N)households in each group. For simplification it is assumed that a community
has households that fall into three income groups (high, medium and poor). In subsistence
farming communities, land is the most important source of income and food self-sufficiency
is an important determinant of household wellbeing. Income groups are categorized as poor,
medium and high based on sufficiency of household income to meet basic needs. In this study
poor households are defined as having insufficient private land to meet basic needs, medium
households have sufficient land, and high households have a surplus of land to meet basic
needs. Income groups in terms of land are then defined as,
aPn
p≤aMn
p≤aRn
p(10)
where land area of high-income households is aRn
p, medium income households is aMn
p,and
poor income households is aPn
p.
In the model, the community is treated as another household. Similar to a household, the
community forest can use its land for production and sell goods to earn income. It can also
lease land to households, who then make individual decisions over a particular area. The
labour endowment of the community forest is the sum of compulsory contributions by indi-
vidual member households to the community forest. As the model considers the community
forest as another source of household income, total community income (Y)captures income
from the community forest.
The community objective is to maximize community income. This is the sum of the income
from all households in each income group, including the community forest, subject to con-
straints on area, labour availability, employment opportunities, the need to meet basic food,
heating and housing needs, and a restriction against making individual households worse
off to maximize community income. Following relevant literature (Abdelaziz et al. 2004;
Buongiorno and Gilless 2003), forest policy was incorporated into the income maximization
function as follows,
MaxY =⎡
⎣
J
j
Z
z
N
n
Caj Xznj +
J
j
Z
z
N
n
G(Ccj Xj)⎤
⎦(11)
where the term (Xj)is a vector of decision variables, (Caj)is a coefficient matrix of decision
variables for private endowments, (Ccj)is a coefficient matrix of decision variables for the
community endowment, (G)is the forest policy weighting for output from the community
forest.
Income maximization is subject to a number of constraints.
Z
z=1
N
n=1
K
k=1
T
t=1
ac
tkzn ≤ap
Z
z=1
N
n=1
K
k=1
T
t=1
ac
tkzn ≤ac
Lqzn +Lczn +Lmzn +Lozn ≤Lzn
Z
z=1
N
n=1
(Lmzn)≤
Z
z=1
N
n=1
(Lhzn)
qizn +qm
izn ≥dizn i=food,firewood and timber
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Heterogeneous Agricultural Households 79
yzn ≥y0
zn
apzn,ac,Lzn,qizn and yzn ≥0
The first constraint states that the total amount of private land type kused in production
system tby nhouseholds in zincome groups, cannot exceed the total amount of private land
available (ap). Similarly, the total amount of community land used cannot exceed the total
amount of community land type available in the (ac). This condition permits share cropping
or rental arrangements. The second constraint is that the labour allocated by any household to
their own farm (Lqzn), to community forest activities (Lczn), to outside employment (Lmzn),
or to leisure (L0zn )cannot exceed available labour for that household (Lzn). The third con-
straint states that employment opportunities are limited to those available in the community
so off-farm employment (Lmzn)cannot exceed local employment opportunities (Lhzn).The
fourth constraint states that a household is required to meet minimum quantities for food,
heating and housing basic needs (dizn)from either their own production (qizn)and/or market
purchases (qm
izn). The fifth constraint is a restriction that prevents individual households from
becoming worse off by the maximization of community income.
Equation (11) is a general model used to study alternative government policies that are
modeled as varying constraints on production from the community forest. Although the
alternative policies are notionally unconstrained, because the objective is to maintain envi-
ronmental benefits, cereal production is constrained to private land and the only unconstrained
activities allowed on community forests are some combination of fodder, firewood and timber
production. As such, the alternatives represent an unconstrained agro-forestry option that is
considered sustainable (Narain et al. 1997;Montagnini and Nair 2004;McNeely and Schroth
2006).
5 Policy Scenarios
Seven policy scenarios are evaluated, representing current government policy, actual forest
use arrangements in particular communities, and other possible alternatives that are not in
current practice. As was discussed earlier, in the linear programming approach, each scenario
reflects differences in the application of constraints on the amount of land that can be allo-
cated to particular type of use, or the proportion of the output available from a particular land
use that can be harvested. As constraints are changed, the community has different options
available to it to maximise income by changing the land use mix or the level of production
from a land use. The only output constraint included the scenarios in this study is for tim-
ber production, along with the impact this has on byproducts available from timber harvest.
Otherwise, the constraints are generally on allocation of land to different uses.
5.1 Base Case
This scenario models current government community forest policy. In this case community
forestland is constrained to a timber production objective, with all land being allocated to
timber production, and other products arising from under-story activities and residual out-
puts from timber production. Timber production is constrained to an annual harvest of 30%
of the potential yield, or MAI, for hardwoods and mixed deciduous forests, and 50% of
MAI for pine forests.2Byproducts, including firewood from off-cuts or residuals, and fodder
harvested from under-story species are produced for sale. Forest products are available at
2This was government policy at the time the study was carried out.
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80 B. Dhakal et al.
subsidised prices for members of the community group and at full market price for others.
The income of the community forest is modeled as a separate household.
5.2 Community Full Use
The community forest is modeled as a separate household, similar to the Base Case. In this
scenario, the community forest has no policy constraints on land allocation for any product.
This is also no constraint on the level of harvest of any product and full potential sustainable
yield is available if desired. The land allocation for production of firewood, tree fodder or
timber and their harvest is based on maximizing income through product sales. The commu-
nity forest is assumed to have no compulsory labour supply, and it must employ labour for
all production activities. As is common practice, households can purchase community forest
output at subsidised prices fixed for community members and surplus products are sold at
market prices.
5.3 Lease Full Use
Similar to the Community Full Use scenario, there are no constraints on the allocation of
community forest for firewood, tree fodder or timber production, and the full potential sus-
tainable yield is available if desired. However, in this scenario the community forest can
be leased to individual households for the management plan period. This scenario allows
households with surplus labour to use community forests as if the land was under private
management, effectively increasing the land available to a household. The community earns
a rental on the area leased to households, and also earns income from products from the land
remaining in community management. This scenario is different from the current leasehold
forestry policy in Nepal.
5.4 Full MAI
The community forest is modeled similar to the Base Case, where community forest use
is constrained to timber production. However, the full MAI of the forest is allowed to be
harvested. By-products, including firewood produced from off-cuts or residuals, and fodder
harvested from under-story species, are also produced for sale.
5.5 Firewood
This scenario is similar to the Base Case but with the constraint on the level of firewood
production relaxed to allow additional firewood harvesting to meet household requirements.
In the Base Case households were strictly limited to residuals from timber harvest and dead
branches. In the Firewood scenario, the maximum limit of firewood harvest was constrained
to maximum annual firewood demand (2,040 kg air dry weight per household as per Graner
1996).
5.6 No Log Market
The difference between this scenario and the Base Case is that the level of timber production
in this scenario is constrained to the level of household consumption and no external market
sales of logs are permitted. The scenario represents the forest management policy dictated by
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Heterogeneous Agricultural Households 81
the National Parks and Wildlife Conservation Act 1973, and applies to areas where commu-
nity forests are located in national parks or wildlife buffer zones. The government expanded
protected areas from 7 to 20% of national area between 1990 and 2007, and part of the
expansion occurred in community forests.
5.7 Zero Income
This scenario applies where the community forests are completely restricted from any kind
of use. This situation was the case for some community forestry user groups at the time of the
field survey, and involved forests with particular characteristics, such as having rare species.
There are a number of assumptions that are common to all the policy scenarios. Forest user
groups, in collaboration with government agencies, monitor the ongoing forest production
and utilization activities in the community forest to ensure that there is no overuse or misuse
of the forest. In communal management the forest user groups distribute community forest
products equally between users when the supply of forest products from the community for-
est is insufficient to meet all households’ needs. When there is sufficient supply of products
from community forests each household is allowed to harvest or collect whatever they need.
6 Data and Methods
To study the various scenarios, a range of primary and secondary data was collected. The
primary focus was on the use of secondary sources of data and where this was not available,
primary data was collected. The biophysical parameters relating to productivity and produc-
tion were obtained from a variety of sources. These include FAO (2000,2003), DOF (2000),
Master Plan (1988), MacEvilly (2003), Paudel (1992), and Paudel and Tiwari (1992). Infor-
mation on forest production labour requirements was adopted from Kayastha et al. (2001).
Socioeconomic information was collected from the National Planning Commission (NPC
2003) and the Central Bureau of Statistics (CBS 2003).
Data not available from secondary sources was collected by a household survey, a forest
user group survey and a key informant survey. A summary of the information collected in
Tab l e 1 Surveys and types of
information collected Survey type Information type
Household Land holding
Crop yields
Forest products uses
Household size
Labour endowment
Livestock holding
Key informant Wage rate
Prices of products
Cost of other inputs
Productivities of forest
and crop products
CFUG Executive Committee Forest management practices
Forest utilization rules
Prices of product
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82 B. Dhakal et al.
each of these surveys is shown in Table 1. A structured, pretested survey instrument was
used to collect household data using personal interviews. The household survey instrument
was divided into three parts: forest and agricultural product consumption, farm production,
and household socioeconomic attributes. Surveys were carried out by professionally trained
enumerators working with local NGOs. The enumerators were coached on how to carry out
this survey. Data was collected from 259 households in six forest user groups covering three
districts, Dolakha, Kavre and Nuwakot.
Key informants in the communities that were surveyed were asked to categorize the house-
holds in their community in terms of poverty. They used two main criteria to do this: suffi-
ciency of household food production from their own land, and annual household cash income.
In the households that were surveyed, income was strongly correlated with landholding size.
ThisformedthebasisoftheclassificationusedinEq.(10).
Members of the Executive Committee of each forest user group were interviewed to collect
information on management rules and forest production. A market survey of key informants
was also done to collect information on forest and farm product prices, costs of different pro-
duction levels, agricultural and off-farm wages, and farm byproduct and crop productivities
on different land categories. The information from forest user groups provided the basis for
scenario development and validation of the model. The lead author of this paper carried out
the key participant interviews and local market surveys.
The empirical model was formulated in a linear programming structure. The objective
function is to maximize the sum of household incomes, with forest resources under com-
munity management treated as an additional household. A description of the parameters and
values used in the linear programming model are given in the “Appendix” (Tables 5,6,7,8,
9,10). The policy models were evaluated with the 32 decision variables listed in Table 11 of
the “Appendix”.
A number of key assumptions are summarized here. A household is assumed to have the
equivalent of five adults in terms of food consumption and the equivalent of three adults in
terms of labour supply. Food requirements are 2,350kcal per person per day. Wood require-
ments are 408 kg of air dry firewood and 0.01 m3of timber per person per year (Graner 1997;
Master Plan 1988). The study uses the National Planning Commission survival income stan-
dard of 33,626 Nepalese rupees (NRs) per household per year (NPC 2003), inflation adjusted.
This income level is the official minimum for supplying food calories and other basic non-
food requirements. Table 2summarises the area of landholding by land type for different
household income groups used in the model that were obtained from the surveys. The average
landholding size from the survey is 1.0ha, which is slightly greater than the national average
Tab l e 2 Household and community forest land areas by land type
Land types Average household landholding (ha)
Poor Medium Rich
Lowland 0.28 0.60 0.64
Upland 0.07 0.28 0.72
Non-crop (marginal) land 0.07 0.10 0.14
Sharecropping upland 0.06 0 0
Sharecropping lowland 0.04 0 0
Community forestland area with hardwood 1.5
Community forestland area with softwood 1.5
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Heterogeneous Agricultural Households 83
Tab l e 3 Agroforestry systems production parameters
Output Units Annual volume
Hardwood yield from log system in broadleaf forest m3/ha/year 4
Softwood yield from log system in pine forest m3/ha/year 8
Fodder yield from fodder system TDN kg/ha/year 2,400
Firewood yield from firewood system kg/ha/year 8,446
Firewood yield from log system in broadleaf forest kg/ha/year 2,484
Firewood yield from log system in pine forest kg/ha/year 4,968
Firewood yield from fodder system kg/ha/year 156
Grass yield from fodder system TDN kg/ha/year 200
Grass yield in broadleaf forest from log or firewood system TDN kg/ha/year 50
Grass yield in pine forest from log or firewood system TDN kg/ha/year 0
Source Master Plan (1988)
0.8 ha (CBS 2003). The average community forest area as per survey results equaled 1.5 ha
per household, which is equivalent to the national average.
Each household voluntarily contributes four working days per year to community forest
activities. This contribution maintains a household’s interest in the benefits from the commu-
nity forest. In practice, the income from the community forest goes into a fund that is used
for communal infrastructure development and payment for other community services. For
modeling convenience each household is assumed to benefit equally from this community
funding. To be representative of all agro-climatic zones, forest composition is considered as
half broadleaf species and half pine species.
In all scenarios, including the unconstrained policy scenarios, the community forest was
evaluated as in an agroforestry model. An agroforestry system is able to maintain environ-
mental services of forests, such as reduced soil erosion, biodiversity maintenance and carbon
sequestration, under a production regime (Narain et al. 1997;Montagnini and Nair 2004;
McNeely and Schroth 2006). In this study this means that the community forest was con-
strained to forest crops being managed in timber, firewood or fodder systems. In each case,
there are multiple products from each system. Table 3outlines the maximum outputs of the
various products for the agroforestry systems used in the study. With these output constraints,
environmental services are maintained.
Private land uses were constrained to food, timber, firewood, and fodder/grassproduction,
and some private land was required to be allocated for homestead use. Fodder production
was evaluated for buffalo and goat farming systems. For lowland areas, a rice-based cropping
system using irrigation and following a maize–rice-fallow crop cycle each year was assumed
for the study. Upland areas were assumed to be completely rain-fed and follow a maize–
finger millet-fallow cycle each year. Typical intercrop species, such as beans and peas, were
also assumed. By-products of crops are used as fodder resources. Households were able to
purchase inputs or products, or to produce them from their own land.
In some scenarios households were also able to buy products from the community forest.
Following common practice in forest user groups, the prices of community forest products
sold to local members are negligible. Most community forests contain naturally regenerated
timber and firewood species, so the forest has no cost of production except for conversion
for fodder forest. Food and livestock product prices and wage data were averaged from the
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Tab l e 4 Use of community forest land resources by agroforestry system (ha)
Agro-
forestry
system
Base
Case
Community
Full Use
Lease Full Use Full
MAI
Firewood No Log
Market
Zero
Income
Firewood NA 0.00 0.00 NA 0.11 NA NA
Fodder NA 2.52 1.73 NA NA NA NA
Pine 1.25 0.00 0.18 1.50 1.25 0.00 NA
Hardwood 0.75 0.48 1.09 1.50 0.75 0.31 NA
Unavailable 1.00 0.00 0.00 0.00 0.89 2.69 3.00
Total community forest area in each case is 3 ha
NA means agroforestry system is not allowed due to forestry policy
Unavailable means effectively unavailable for community use due to forestry policy constraints
surveyed forest communities. Farm and tree products prices were collected from business
people and community leaders of the surveyed communities.
The model was validated with data collected from 259 households in six communities.
Validation of the model showed that the prediction error was 3% in the aggregate analysis
of all households, but varied between household income groups and characteristics of com-
munities. Greater errors were shown in forest user groups closer to the district headquarters
where other income and employment opportunities were more available. The errors were
least for medium income households and highest in rich households. On average the model
under-predicts income levels by 13% for poor households. This indicates the confidence
limits under which results should be considered while interpreting the results. The validation
details are available from the authors on request.
7 Results and Discussion
The allocation of community forest land to different agroforestry systems under each of the
policy scenarios is shown in Table 4. As was discussed earlier, the Base Case reflects the
current policy where communities are constrained to log production systems and limited use
of the potential output of logs, firewood or fodder from the system. The summary of forest
products produced under different scenarios is given on Appendix Table 12. As constraints
are changed, the agroforestry systems chosen can change. When comparing the changes to
income resulting from the different policy scenarios, the changes will reflect the combined
effect of the different outputs associated with each agroforestry system (Table 3), the amount
of the potential output that the policy allows a community or individual to harvest, and the
area of land allocated to the agroforestry system (Table 4).
A comparison of the effects of different policy scenarios on total community and house-
hold incomes (in Nepalese rupees3) shows that higher total community income is obtained
from the Community Full Use and Lease Full Use policies (Fig. 1). Neither of these policy
alternatives is currently used in Nepal. The smallest predicted income resulted from both
the Zero Income and No Log Market scenarios. Compared to the Base Case (current policy),
the total community incomes are 21.1, 11.4, 4.0 and 0.6% higher under the Lease Full Use,
the Community Full Use, Full MAI and Firewood scenarios respectively. Total community
and household incomes decreased as more restrictive forest policies were imposed. The result
3USD 1 equivalent to NRs 72.0 at the time of the survey.
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Heterogeneous Agricultural Households 85
Fig. 1 Effect of policies on household and total community incomes
showed that total community and household incomes increase by a small amount when the
forests are managed for timber production alone or to provide sufficient firewood for house-
hold use.
Compared to the Base Case, incomes for poor and medium income households increase by
83.6 and 25.1% respectively with the Lease Full Use policy, and 48.3 and 19.4% respectively
with the Community Full Use policy. Incomes for the poor and medium income households
increase by only small amounts with the Full MAI and Firewood policies. The income of
rich households has negligible changes in each of the policy scenarios. The results indicate
that the potential contribution of community forest resources to household income is highest
for poor households, and that policy constraints on community forest use have a relatively
higher impact on poorer households.
The Family Basic Need line in Fig. 1indicates the income required to provide mini-
mum calories and other basic non-food items. The survival income baseline comes from
the National Planning Commission (NPC 2003). In the Community Full Use and the Lease
Full Use scenarios, all households have more than sufficient income to meet these minimum
requirements. In the Full MAI model and Firewood scenarios, the income barely meets the
minimum needs of poor households. Under the Current Policy, the No Log Market and the
Zero Income scenarios provide insufficient income to meet the needs of poor households.
The results show that poor and medium income households do better under any alternative
policy, but are particularly benefited by the unconstrained policies.
A distinct feature of the Lease Full Use policy is that households are able to lease commu-
nity forest land and manage it as private land. In this scenario, 69% of community forest land
is leased to households (Table 3), with the difference remaining in community management.
Of the land that is leased to households 55% goes to poor households, 33% goes to medium
income households and 12% goes to rich households. This is a key factor in the increase in
benefits flowing to poor and medium income households from this policy.
Income distribution across the household groups under the different policy scenarios is
showninFig.2. The greatest income inequality is produced by the Zero Income scenario,
followed by the No Log Market scenario. The least income inequality is found in the Lease
Full Use and Community Full Use policy scenarios. In effect, income inequality increases as
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Fig. 2 Share of total community income by household
Fig. 3 Effects of forest policies on household unemployment
forest policy constraints are imposed, and the impact is greatest on poor households. Forest
policies affect poor households the most because their private land holdings are small and
insufficient to meet their income needs, and they have the potential to benefit most from
access to community forest resources.
Figure 3shows annual household unemployment under the different policy scenarios. The
results show that community forestry policies can have a big effect on household employ-
ment. The level of employment is directly related to household access to land resources.
Under the Community Full Use and Lease Full Use scenarios, unemployment within the
community disappears and there is a net requirement of labour from outside the community.
In all other scenarios there is significant unemployment, with generally only small differences
between scenarios. High income households are net employers in most scenarios because of
the relative size of private land holdings and family labour supply.
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Heterogeneous Agricultural Households 87
8 Conclusions
The purpose of this study was to evaluate the impacts of existing and alternative forest policies
governing the use of community forests on economically heterogeneous, agriculture-based
households in Nepal. The findings indicate that forest policies which are aimed primarily at
environmental conservation, as is the case with current policy governing community forestry
in Nepal, substantially affects household income and employment, income inequality in rural
communities, and aggregate economic benefits. Our findings show that current policies con-
strain the poorest households’ ability to meet even survival needs. The impacts on households
of current Nepalese forest policies aimed at conserving environmental resources are much
greater than previously recognised, particularly for poor and medium income households.
The findings imply that the socioeconomic impacts of public forest policies may be underes-
timated in developing countries unless forestry’s contribution to agricultural production and
household economic heterogeneity are accounted for.
Among the policy options that were analysed, allowing the leasing of community forest-
land by individual households (Lease Full Use) provided the greatest benefits in terms of both
income and employment generation, and reducing household income inequality. This policy
is potentially also superior to alternative policies in terms of reducing the administrative costs
of management and in reducing social barriers in forest product distribution, which will have
the greatest benefits for the poorest households. The Community Full Use policy also has
significant benefits, and could also eliminate the potential for conflicts created by leasehold
forestry. The Community Full Use policy would be most effective in communities where
forests require closer or stricter management than could be achieved under individual man-
agement. However, both of the full use community forest management models are based on
agroforestry practices which minimize over-use and other environmental degradation prob-
lems in public forests. The findings indicate that there are alternative policies for managing
common property resources that would reduce income inequalities in Nepalese rural commu-
nities and lift incomes and employment to a level where even the poorest households could
meet their basic needs.
The conclusions are similar to the theoretical, integrated integrated agriculture and forestry
model used by Anthon et al. (2008) which concluded that public forest policy, biased towards
environment conservation, affect the economies of forest based communities and has the
greatest impact on the poorest households. There are no similar studies in Nepal that could
be used to directly compare the findings of this study. However, our findings challenge the
general conclusions of previous studies that have examined the impact of community for-
estry policies on direct economic returns from public forests to households, including Thoms
(2008), Adhikari et al. (2007), Adhikari et al. (2004), and Varughese and Ostrom (2001). For
example, Adhikari et al. (2007) reported that current forest policies increased benefits for
rural households despite reducing household livestock holdings.
Another important result of our study is that it showed that household and community
wellbeing would change by only a small amount even if forest policies were relaxed to allow
communities to harvest timber volumes equal to the MAI. This casts doubt on the conclusions
about the economic profitability of forest carbon trading as reported by Karky and Skutsch
(2010) because the benefit is evaluated without taking into account the opportunity costs of
alternative land uses to timber. Alternative policies evaluated in our study would provide
greater immediate benefits to poor households and increase income for rural communities
where poverty and unemployment are of critical importance than would other policies or
programmes.
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88 B. Dhakal et al.
The study has used a linear programming model to account for the effects of government
forest policies on households using community forests. The model captured the economic
effects of forest policy changes across households that have different endowments of private
land resources. The model accounts for the effect of policy on supplies of public forest prod-
ucts, and shows how public forests can complement private land resources and contribute to
meeting the basic needs of local people. To our knowledge, this is the first application of this
approach to the study of community forestry.
There are a number of potential extensions of this model. Most of the parameters avail-
able to model policies could be considered to be for most likely scenarios and for an average
community forest. To understand the effect of policies on specific local situations, a similar
study could be done including factors specific to that community.A lack of data prevented the
inclusion of commercial, non-timber forest product options. The model would also be useful
to assess policy impacts of payment for ecosystem services implemented in developing coun-
tries or an estimation of ecosystem services. The model could be extended to examine the
tradeoffs between different environmental services from community-based forest resources
under different policy scenarios, and economic benefits under different payment options for
environmental services.
Acknowledgments We acknowledge the generous financial assistance provided by Winrock—Nepal and
Lincoln University, New Zealand, for the field survey.
Appendix
See Tables 5,6,7,8,9,10,11 and 12.
Tab l e 5 Conversion factors
Information type Value Unit
Per capita/day calorie requirementa2,350 kcal
Per capita firewood kg requirementb408 kg per year
Per capita construction and building timber materialb0.05 m3per year
Softwood forest MAI useable as log in timber systemb60 Percent
Hardwood forest MAI useable as log in timber systemb60 Percent
Forest MAI useable as firewood in firewood systemc85 Percent
Finger millet-refined yield proportion from raw yieldc90 Percent
Rice-refined yield proportion from raw yieldc70 Percent
Maize-refined yield proportion from raw yieldc80 Percent
Beans and peas-refined yield proportion from raw yieldc100 Percent
Nutritional value of maized4.056 Mega calories/kg
Nutritional value of riced2.821 Mega calories/kg
Nutritional value of finger milletd2.822 Mega calories/kg
Nutritional value of peas and beansd1.735 Mega calories/kg
One goatb0.2 Stock unit
One female buffalob1 Stock unit
Source aNPC (2003), bMaster Plan (1988), cKey informant survey, dMacEvilly (2003)
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Tab l e 6 Agricultural production parameters
Value Unit
Crop production parameters
Maize seed used (self produced)a22 kg/ha
Rice seed used (self produced)a55 kg/ha
Finger millet seed used (self produced)a8 kg/ha
Pulse seed used (self produced)a5 kg/ha
Maize yielda1,729.3 kg/ha
Rainy season rice yielda2,680.6 kg/ha
Finger millet yielda1,107.7 kg/ha
Pulses yielda801 kg/ha
Animal production parameters
Average milk production per yearb980 Liter
Meat yield per goatb24 kg
Goat manure production per dayc0.3 kg/day/adult
Buffalo manure production per dayc3.0 kg/day/adult
Goat production to sale stock ratiob50.0 Percent
Goat annual nutrient (TDN) requirementd70 kg/adult
Buffalo annual nutrient (TDN) requirementd1,013 kg/adult
Concentration feed supplementb5% Percent
Land area required to shelter and handle a unit buffalob10 m2
Land area required to shelter and handle a unit goatb4m
2
Source aFAO (2004),bKey informants’ value converted into TDN using conversion factors of Master Plan
(1988), cOli (1987), dMaster Plan (1988)
Tab l e 7 Forest production parameters
Parameter Value Unit
Hardwood productivitya4m
3/year/ha
Softwood productivitya8m
3/year/ha
Fodder yield in fodder foresta2,400 kg/ha
Firewood production in firewood foresta8,446 kg/ha
Firewood production from fodder foresta156 kg/ha
Intercrop grass in tree fodder systema700 TDN kg/ha
Grass production in broadleaves forest for log or firewooda50 TDN kg/ha
Grass yield under pine forest for log or firewooda0 TDN kg/ha
Maize and wheat strawa280 TDN kg/ha
Rice strawb660 TDN kg/ha
Millet strawb610 TDN kg/ha
Grass production with cropsb1,400 TDN kg/ha
Intercrop tree fodder in uplandb150 TDN kg/ha
Inter crop tree fodder in lowlandb50 TDN kg/ha
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Tab l e 7 continued
Parameter Value Unit
Grass product in fodder forestb200 TDN kg/ha
Wood byproduct in fodder forestb0.1 m3/ha
Source aMaster Plan (1988), bKey informants
Tab l e 8 Labour inputs and parameters
Activities Value Unit
Hardwood log harvest from timber system 11.0 Person day/m3
Softwood log harvest from timber system 7.7 Person day/m3
Firewood collection from firewood system 200 kg/person day
Firewood collection as residual from timber harvest 90 kg/person day
Inferior firewood collection 50 kg/person day
Management input for fodder system 24 Person days/ha/year
Management input for firewood and grass system 2 Person days/ha/year
Buffalo tending from private and lease land feeds 8 Head/person/day
Goat tending from private and lease land feeds 35 Head/person/day
Buffalo tending from CF land feeds 6 Head/person/day
Goat tending from CF land feeds 30 Head/person/day
Upland maize–bean intercrop farming 237 Person days/ha/year
Upland rainy season millet–blackgram intercrop farming 255 Person days/ha/year
Lowland maize–bean intercrop farming 201 Person days/ha/year
Rainy season rice–soybean intercrop farming 385 Person days/ha/year
Purchasing timber from the market 0.25 m3/person day
Purchasing fodder from the market 24 TDN kg/person day
Purchasing animal feed from the market 40 TDN kg/person day
Purchasing firewood from the market 200 kg/person day
Purchasing food from the market 282 mcal/person day
Economically fully active labour 2.5 Persons/family
Working days for a fully economically active person 265 Days/year
Working hours for family labour 10 Hours/day
Working hours for hired labour 7 Hours/day
Compulsory labour for community forestry work 4 Person days/household
Source Key informants
Tab l e 9 Prices and costs parameters for agricultural and forestry production
Item Price Unit
Hardwood timber sale price within community 5,400 NRs/m3
Hardwood timber sale price outside community 3,500 NRs/m3
Softwood timber sale price within community 2,800 NRs/m3
Soft wood timber sale price outside community 1,400 NRs/m3
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Tab l e 9 continued
Item Price Unit
Hardwood timber purchase price outside community 8,000 NRs/m3
Soft wood timber purchase price outside community 5,000 NRs/m3
Firewood price 0.5 NRs/kg
Residual firewood price 0.2 NRs/kg
Forest fodder price 3 NRs/kg
Inferior firewood/byproduct fuel price 0.001 NRs/kg
Community forest grass within community 1.3 NRs/kg
Community forest grass outside community 1.4 NRs/kg
Rice straw 6 NRs/kg
Maize stalk 3 NRs/kg
Finger millet stalk 3.5 NRs/kg
Private land grass 3 NRs/kg
Farm tree fodder 3.5 NRs/kg
Production buffalo price 25,000 NRs/head
Production goat price 3,000 NRs/head
Milk price 180 NRs/kg
Meat price 20 NRs/kg
Maize farm-gate selling price 16 NRs/kg
Maize market purchase price 19 NRs/kg
Rice farm-gate selling price 18 NRs/kg
Rice market purchase price 21 NRs/kg
Finger millet farm-gate selling price 11.50 NRs/kg
Finger millet market purchase price 14.50 NRs/kg
Pulse (average) farm-gate selling price 24 NRs/kg
Pulse market purchase price 30 NRs/kg
Sources Key informants and Executive Members of User Groups
Tab l e 1 0 Price and cost parameters for agricultural and forestry production
Parameter Cost Unit
Regular wage 90 NRs/day/person
Skilled labour cost for timber harvest 3,893 NRs/m3
Net wage working outside the community 80 NRs/day/person
Rice planting wage 120 NRs/day/person
Annual interest rate on cost 20 Percent
Annual costs for goats (e.g housing, medicine, breeding) 200 NRs/head
Annual cost for buffalo (e.g housing, medicine, breeding) 1,500 NRs/head
Cost of maize–bean production excluding labour 3,870 NRs/ha
Cost of rice–soybean production excluding labour 700 NRs/ha
Cost of finger millet–soybean production excluding labour 5,126 NRs/ha
Non-labour cost of natural forest conversion into fodder production 6,583 NRs/ha
Hired labour cost for natural forest conversion into fodder forest 3,893 NRs/ha
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Tab l e 1 0 continued
Parameter Cost Unit
Annual management cost for fodder system on private land 1,900 NRs/ha
Annual management cost for firewood and timber systems on private land 1,740 NRs/ha
Annual management cost for firewood and timber system in community forest 1,400 NRs/ha
Source Key informants and Executive Committee Members
Tab l e 1 1 List of decision variables
Resource category Production activity or source Unit
Private upland use Crop food production ha
Firewood ha
Fodder buffalo ha
Fodder goat ha
Softwood timber ha
Hardwood timber ha
Private lowland use Crop food production ha
Firewood ha
Fodder for buffalo ha
Fodder for goat ha
Softwood timber ha
Hardwood timber ha
Private non-cropping land use Firewood ha
Ownland fodder buffalo ha
Ownland fodder goat ha
Softwood timber ha
Hardwood timber ha
Community forest land use Firewood ha
Fodder buffalo ha
Fodder goat ha
Softwood timber ha
Hardwood ha
Purchased products Food from market mcal
Fodder for buffalo from community forest kg
Fodder for goat from comunity forest kg
Fodder for buffalo from market kg
Fodder for goat from market kg
Firewood from community forest kg
Firewood from market kg
Inferior quality firewood kg
Softwood timber from market m3
Hardwood timber from market m3
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Heterogeneous Agricultural Households 93
Tab l e 1 2 Summary of forest products
Policy scenario Household type Fodder (TDN kg) Firewood
(oven dry kg)
Timber (m3)
Base Case Poor 1,679 (263) 2,040 (1,889) 0.13
Medium 3,222 (263) 2,040 (1,889) 0.25
Rich 4,952 (0) 2,040 (1,754) 0.38
Common 0 10.80
Gross 9,853 (526) 6,120 11.18
Lease Poor 6,490 (2,623) 2,040 (1,443) 0.13 (0.13)
Medium 5,589 (1,536) 2,040 (1,178) 0.25 (0.25)
Rich 4,928 (23) 2,040 (837) 0.85 (0.38)
Common 0 2.25
Gross 17,007 (4,685) 6,120 3.47
Unconstrained community Poor 4,684 (3,331) 2,040 (531) 0.13 (0.02)
Medium 5,371 (2,642) 2,040 (462) 0.25 (0.1)
Rich 4,717 (0) 2,040 (198) 0.38 (0.3)
Common 0 1.15
Gross 14,083 6,120 1.52
Full MAI Poor 1,679 (263) 2,040 (1,372) 0.13
Medium 3,222 (263) 2,040 (1,372) 0.25
Rich 4,934 (0) 2,040 (1,346) 0.38
Common 0 7.80
Gross 9,836 (526) 6,120 8.08
Firewood Poor 1,687 (271) 2,040 (1,687) 0.13
Medium 3,230 (271) 2,040 (1,687) 0.25
Rich 4,952 (0) 2,040 (1,660) 0.38
Common 0 7.80
Gross 9,869 (542) 6,120 8.18
No Log Market Poor 1,651 (234) 2,040 0.13 (0.13)
Medium 3,194 (234) 2,040 0.25 (0.25)
Rich 4,814 (0) 2,040 0.38 (0.38)
Common 0 0.75
Gross 9,659 6,120 0.75
Zero Income Poor 1,357 (0) 2,040 (0) 0.13 (0)
Medium 2,806 (0) 2,040 (0) 0.25 (0)
Rich 4,668 (0) 2,040 (0) 0.38 (0)
Common 0 0.00
Gross 8,831 (0) 6,120 0.75
The figures in parentheses are quantity sourced from private lands
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