COMMON PROPERTY RESOURCES, POVERTY AND ENVIRONMENTAL DEGRADATION: A CASE STUDY IN WEST BENGAL THESIS SUBMITTED FOR THE FULFILMENT OF THE DEGREE OF PHILOSOPHY IN ARTS (ECONOMICS) AT THE UNIVERSITY OF BURDWAN, WEST BENGAL By Soma Saha Department of Economics The University of Burdwan February, 2014
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COMMON PROPERTY RESOURCES, POVERTY AND ENVIRONMENTAL DEGRADATION:
A CASE STUDY IN WEST BENGAL THESIS SUBMITTED FOR THE FULFILMENT OF THE
DEGREE OF PHILOSOPHY IN ARTS (ECONOMICS) AT THE UNIVERSITY OF BURDWAN, WEST BENGAL
By Soma Saha
Department of Economics The University of Burdwan
February, 2014
Pravat Kumar Kuri Phone: 0342-2556566 Ext 438 Associate Professor Email: Department of Economics [email protected] University of Burwan Golapbag, Burdwan Date: West Bengal-713104
TO WHOM IT MAY CONCERN This is to certify that Ms. Soma Saha has duly completed her research work for the thesis entitled “Common Property Resources, Poverty and Environment Degradation: A Case Study in West Bengal” under my supervision. I have approved the thesis and permitted her to submit it for the Ph.D. degree in Economics to the University of Burdwan. Further, I certify that neither this dissertation nor any part thereof was submitted to this or any other University in this country or abroad for Ph.D. or any other degree. It may also be noted that Ms. Soma Saha had delivered two seminar lectures on this research work on 30th October, 2009 and 22nd November, 2011, at the Department of Economics, Burdwan University, in partial fulfilment of the requirement for the submission of the Ph.D. thesis. She has also complied with other relevant conditions specified in the regulations of the University of Burdwan including the residential requirements.
Pravat Kumar Kuri
i
Acknowledgement
I have accumulated many debts of gratitude in the course of my research studies.
Foremost, I would like to express my humble gratitude to my mentor and supervisor
Prof. Pravat Kumar Kuri for his scholarly guidance and constructive supervision. His
invaluable advice, critical revision, perpetual inspiration and consistent
encouragement were necessary for me to complete my dissertation in time. Heartfelt
thanks to him for his invaluable comments and suggestions. In addition, I express my
sincere gratitude to Prof. Arup Chattopadhyay, Head of the Department, Economics
and all the teachers of the Department of Economics, Burdwan University for their
kind support at various phases of my work. I remain thankful to my Principal, Dr.
Amal Kanta Hati and all my colleagues of Tarakeswar Degree College for their
support and good wishes.
Since empirical study is solely dependent on the access to the data, I would like to
acknowledge the help that I had received during my fieldwork from the forest officers
of Bankura and Purulia districts; panchayat office bearers and Head Masters of our
surveyed villages. I am also grateful to all the village respondents of the study area
who took out time to answer the lengthy questionnaires. Without their active
participation and support, the research would never have taken this shape. My special
appreciation to Mr. Suvendu Chel, part-time professor of Bankura Women’s College
and local students for their jovial assistance while I was working at the forest villages.
No research is possible without the library, the centre of learning resources. For the
secondary data sources of my research study, I have consulted many libraries viz.
Central Library of Burdwan University; National Library; Central library of Indian
Statistical Institute, Kolkata. I am indebted to the authorities and staffs of these
institutions for their active cooperation and services. I am very much privileged to
have learned effective use of several econometric software packages from the
Workshop conducted on Research Methodology, by Department of Economics,
University of Burdwan. In this matter my guide, Prof. Pravat Kumar Kuri was a great
help to me in various ways.
I owe a lot to my parents, Sri Rebati Mohan Saha and Smt Anjali Saha; my in-laws,
Sri. J. K. Saha and Smt. Dipali Saha who always encouraged and helped me at every
stage of my personal and academic life and longed to see this achievement come true.
ii
Most gratefully, I acknowledge my immense debt to my dear husband, Jayanta, who
gave me whole hearted support during the research work. In spite of his busy official
schedule, he gave me his helping hand whenever I was in need. I am also grateful to
my daughter Sukrita and son Soumil for the love and encouragement they offered me
while carrying out my studies. I also acknowledge the well wishes of my elder sister,
Supta Manna; sister-in-law, Jayashree Poddar and my dear friend, Suparna Pal.
Finally, I beg to be apologised for any shortcomings.
Soma Saha Department of Economics
The University of Burdwan
Contents
iii
Contents Page Number Acknowledgement i-ii List of Contents iii-vii List of Tables viii-xi List of Figures & Maps xii Chapter 1: Introduction 1-7 Chapter 2: Review of Literature 8-34 2.1: Pioneering Works on Common Property Resources 8 2.2: CPR, Poverty and Environmental Degradation 10 2.3: Agricultural Risk and CPR 17 2.4: Common Forest and Participatory Management 20 2.5: Common Property Resources and Gender 30 Chapter 3: Objectives, Data Source and Methodology 35-51 3.1: Objective of the Study 35 3.2: Data Source 36 3.3: Methodology 40
3.3.1: Conceptual Framework 40 3.3.2: Econometric and Statistical Specification 46
3.4: Hypothesis Tested 51
Contents
iv
Page Number
Chapter 4: Common Property Forest Resources: 52-93 Contribution and Crisis 4.1: Introduction 52 4.2: Data and Methodology 55 4.2.1: Conceptual Framework 55 4.2.2: The Empirical Model Specification 60 4.2.2.A: Determinants of CPR: Multiple Regression Model 60 4.2.2.B: Determinants of Poverty: Poverty Environment 62 Nexus 4.3: Results and Discussion 64 4.3.1: Nature of Dependency on CPRs 64 4.3.2: CPRs and the Contribution to the Household 68 Income 4.3.3: CPRs and the Contribution to the Consumption 71 Expenditure 4.3.4: CPRs and the Contribution to the Employment 73 Generation 4.3.5: Household Energy Consumption and the Extent 74 of Dependency on CPRs 4.3.6: CPRs and Animal Grazing 76 4.4: CPRs and Rural Poverty 78 4.5: Determinants of CPR Extraction 81 4.6: Poverty-Environment Nexus- Logit Model 85 4.6.1: Determinants of Poverty 87 4.7: Conclusion 92
Contents
v
Page Number Chapter 5: Agricultural Risk and Common Property 94-119 Resources 5.1: Introduction 94 5.2: Data and Methodology 97 5.2.1: Conceptual Framework 98 5.2.2: The Empirical Model Specification 102 5.3: Results and Discussion 105 5.3.1: Nature of Agriculture in Bankura & Purulia 105 District 5.3.2: Agricultural Productivity 108 5.3.3: Labour Allocation in CPR Collection 110 5.3.4: Agricultural Risk and CPR 111 5.3.5: Association between CPR Extraction and 116 Agricultural Risk: Count Data Regression Model 5.4: Conclusion 119 Chapter 6: Common Forest and Participatory 120-150 Management 6.1: Introduction 120 6.2: Data and Methodology 121 6.3: Forest Cover and its Management in India: An 122 Interstate Analysis 6.3.1: Forest Cover in India 122 6.3.2: Introduction of Joint Forest Management in India 126 6.4: Forest Cover and Joint Forest Management in 128 West Bengal 6.4.1: Forest Cover in West Bengal 128
Contents
vi
Page Number 6.4.2: Joint Forest Management in West Bengal 131 6.5: Forest Management in the Study Area 133 6.6: Collective Action in Joint forest Management 138 6.7: Collective Action and Forest Conservation 145 6.8: Conclusion 150 Chapter 7: Women’s Participation in CPR 151-170 Management 7.1: Introduction 151 7.2: Role of Women in CPR Collection in the Study Area 154 7.3: Women’s Participation in Forest Resource Management 160 7.4: Women’s Participation in JFM and Sustainability in 163 Forest Resources 7.4.1: Empirical Model Specification 163 7.4.2: Results and Discussions 166 7.5: Conclusion 170 Chapter 8: Summary, Conclusion and Policy 171-187
Page Number Bibliography 188-204 Appendices 205-230 Appendix- I: Village Characteristics of Study Area 205 1.1: Characteristics of the Population in the 210 Study Area in Bankura and Purulia 1.1.1: Family Size and Literacy Rate 210 1.1.2: Caste Composition 211 1.1.3: Occupation 211 Appendix -II: Price List of CPRs 212 Appendix-III: Summary Statistics 213 Appendix-IV: Land Ownership Pattern 215 Appendix-V: Property Rights and ‘The Tragedy of 218 the Commons’ Appendix-VI: Joint Forest Management in India 223
List of Tables
viii
List of Tables Page Number Chapter 4: Common Property Forest Resources: Contribution and Crisis Table 4.1: Description of Variables of Multiple Regression 61 Model Table 4.2: Household Collection of Common Property 65 Resources in Last 1 year (Rs) Table 4.3: Annual Income from Various Sources (Rs) 68 Table 4.4: CPRs and its Contribution to Total Consumption 72 Expenditure (Rs) Table 4.5: Employment Provided by CPR Based Activity 73 (in last 1 year) Table 4.6: Household Energy Consumption and the Extent 75 of Dependency on CPR Table 4.7: Dependency on CPRs for Animal Grazing 77 (in last 1 month) Table 4.8A: Distribution of Monthly per Capita Income of 78 the Sample Households in Bankura District (including income derived from CPRs) Table 4.8B: Distribution of Monthly per Capita Income of 79 the Sample Households in Purulia District (including income derived from CPRs) Table 4.9A: Distribution of Monthly per Capita Income of 80 the Sample Households in Bankura District (excluding income derived from CPRs)
List of Tables
ix
Page Number Table 4.9B: Distribution of Monthly per Capita Income of the Sample Households in Purulia District 80 (excluding income derived from CPRs) Table 4.10A: Determinants of CPR Extraction-Bankura District 81 Table 4.10B: Variance Inflation Factors (Bankura District) 82 Table 4.11A: Determinants of CPR Extraction-Purulia District 82 Table 4.11B: Variance Inflation Factors (Purulia District) 83 Table 4.12: Extent of Depletion of Common Property Resources 86 (during 1990-2010) Table 4.13: Description of Variables of Logit Regression Model 88 Table 4.14A: Determinants of Poverty-Bankura District 89 Table 4.14B: Determinants of Poverty-Purulia District 90 Chapter 5: Agricultural Risk and Common Property Resources Table 5.1: Description of Variables in Count Data Model 104 Table 5.2: Crop Productivity 108 Table 5.3: Agricultural Implements Used 109 Table 5.4: Agricultural Labour 110 Table 5.5: Labour Allocation in CPR Collection 110 Table 5.6: Agricultural Production and CPR Collection 112 Table 5.7: Agricultural Shortfall and CPR Collection 114 Table 5.8: Forest Collection as a Function of Agricultural 116 Risk (Bankura District)
List of Tables
x
Page Number Table 5.9: Forest Collection as a Function of 117 Agricultural Risk (Purulia district) Chapter 6: Common Forest and Participatory Management Table 6.1: Forest Density Classification 122 Table 6.2: Forest Cover in India 124 Table 6.3: Forest Cover in States/UT of India 125 Table 6.4: Status of JFM in Different States in India 127 Table 6.5: District Wise Forest Cover in West Bengal 129 Table 6.6: Degraded Notified Forest Land in West Bengal 130 Table 6.7: Forest Protection Committees in West Bengal 131 Table 6.8: Status of JFM Committees in West Bengal 132 Table 6.9: JFM Participation in the Study Area of Bankura 136 and Purulia district Table 6.10: Forest Management and Enforcement of Forest 137 Protection Scheme Table 6.11: Description of Variables in Censored Tobit Model 141 Table 6.12: Determinants of Collective Action-Bankura 142 District Table 6.13: Determinants of Collective Action-Purulia District 143 Table 6.14: Description and Hypothesis in Logit Regression 146 Model Table 6.15: Determinants of Forest Degradation –Bankura 147 District Table 6.16: Determinants of Forest Degradation –Purulia 148 District
List of Tables
xi
Page Number Chapter 7: Women’s Participation in CPR Management Table 7.1: Women Headed Household and CPR Collection 157 Table 7.2: Women and CPR Collection in Last One Month 158 of the Date of Survey
Table 7.3: Participation of Household Members of Study 161 Area in JFM Table 7.4: Description of Variables in Binary Probit Model 165 Table 7.5: Determinants of Forest Sustainability-Bankura 166 Table 7.6: Determinants of Forest Sustainability- Purulia 167 Appendices Appendix-I: Village Characteristics of Study Area Table A1.1: Village Wise Characteristics 210 Table A1.2: Village Wise Occupation Composition of 211 the Surveyed Population Appendix-II: Price List of CPRs Table A2.1: Price List of Common Property Resources 212 in the Surveyed Villages Appendix-III: Summary Statistics Table A3.1: Descriptive Statistics of Quantitative and 213 Dummy Variables for Bankura District Table A3.2: Descriptive Statistics of Quantitative and 213 Dummy Variables for Purulia District Appendix-IV: Land Ownership Pattern Table A4.1: Land Ownership Pattern 215 Table A4.2: Land Ownership Pattern (Own land) 216 Table A4.3: Land Ownership Pattern (Operated land) 217 Appendix-V: Property Rights and ‘The Tragedy of the Commons’ Table A5.1: Prisoner’s Dilemma 222
List of Figures & Maps
xii
List of Figures & Maps Page Number Chapter 3: Objectives, Data Source and Methodology Photo 1: Interview with the household head at Panjhoria 39 Photo 2: Interaction with a villager at Dulaltora 39 Chapter 4: Common Property Forest Resources: Contribution and Crisis Photo 3: Villagers collecting leaves from common forest area in Seolibona 67 Figure 4.1: Percentage contribution to household income by different 69 income generation activities in the study area of Bankura and Purulia districts Figure 4.2: Percentage contribution to household income by different 70 income generation activities in Bankura district Figure 4.3: Percentage contribution to household income by different 70 income generation activities in Purulia district Photo 4: Villagers at Jiyathole using fuelwood 71 Photo 5: Common forest area in Jiyathole 71 Chapter 5: Agricultural Risk and Common Property Resources Figure 5.1: Index number of agricultural production (Cereals) 107 Photo 6 &7: CPR collection by rural households at Ramjibanpur 111 Figure 5.2: Agricultural production & CPR collection in survey area 113 of Bankura district Figure 5.3: Agricultural production & CPR collection in survey area 113 of Purulia district Figure 5.4: Agricultural shortfall and CPR collection in Bankura district 115 Figure 5.5: Agricultural shortfall and CPR collection in Purulia district 115 Chapter 6: Common Forest and Participatory Management Map 6.1: Forest cover map of India 123 Map 6.2: Forest cover map of West Bengal 128 Chapter 7: Women’s Participation in CPR Management Photo 8: Interaction with rural women in Jiyathole 156 Photo 9: Women collecting cowdung in Baldanga 156 Appendix-I: Village Characteristics of Study area Map A1.1: Map of West Bengal- Bankura 206 Map A1.2: District map of Bankura 206 Map A1.3: Map of West Bengal- Purulia 209 Map A1.4: District map of Purulia 209 Appendix-V: Property Rights and ‘The Tragedy of the Commons’ Figure A5.1: Relationship among effort, cost and revenue 220
Introduction
1
CHAPTER 1
INTRODUCTION
The concept of Property rights has an important implication to the use of natural
resources, rural poverty, degradation and conservations. Bromley (1990) describes
property, not as a natural resource but as a benefit stream that arises from that
resource. With property, comes the right to use or access, which can be defined as
one’s claim to a benefit stream. Based on the different access regime and the rights
and duties governing them, the different resource regimes are i) State property ii)
Private property iii) Common property and iv) Open access resource (Bromley and
Cochrane, 1994). In the state property regime, the state has full ownership and control
over the property, while in private property regime it is privately used and controlled
by individuals. In the case of common property, individuals within a group have
access, rights and duties and all others are excluded from its use and decision making
(Ciriacy-Wantrup and Bishop, 1975). Here the group of people who have the right to
its collective use is well defined, and the rules that govern their use of it are set out
clearly and followed universally. In an open access regime, nobody owns as there is
no property right and hence everybody has access to it.
Ostrom (1990) uses the term "common pool resources" to denote natural resources
used by many individuals in common, such as fisheries, groundwater basins and
irrigation systems. She sets a ‘design principles’ which includes clearly defined
boundaries, monitors who are either resource users or accountable to them, graduated
sanctions, and mechanisms dominated by the users themselves to resolve conflicts and
to alter the rules. Ostrom observes that the biggest challenge in a common property
regime is to foster contingent self-commitment among the members.
It is now well established that Common Property Resources (CPRs) are the natural
resources belonging to every community that each member could access purposefully
with specific obligations since no one could exercise their own right exclusively over
them monopolising them as their own property (Jodha, 1986). An identifiable
community alone holds the power to access and manage these resources collectively
Introduction
2
and to which no individual has exclusive property rights. In rural India, the commonly
seen resources endowed by nature such as the abundant lands in the form of village
pastures and grazing grounds, common forest areas in the form of village forests,
protected and un-classed forests, ponds, rivers, rivulets and waste lands used for
agricultural practices form the first and foremost property of the rural common man.
The Common Property Resources are the singular source of human sustenance in the
households that constitute a large section of rural India. CPRs are integral part of the
social and institutional arrangements made to meet the day to day requirements of the
rural poor. The rural poor, especially the landless, are highly dependent on the CPRs
for their subsistence. Earlier studies have also suggested that both the poor and not so
poor also depend on the CPRs for their livelihood. CPRs not only act as a buffer
during the economic crisis arising due to crop failure but also act as an additional
source of income during normal times. Forests have provided ample resource in the
form of Non Timber Forest Products (NTFPs) for the subsistence of the rural poor.
The rural poor collect several NTFPs in the form of fuel wood, shrubs, dry leaves
which are used by them for cooking and heating. The bamboo and cane are used for
construction of house, while the wild grasses and shrubs are used as animal fodder.
The forest is also a rich source for several medicinal plants used for curing diseases.
Fruits, vegetables and roots are collected by the rural poor for consumption and sale.
The critical role of natural resources in the sustenance of the rural livelihood can be
traced to time immemorial.
However, efficient use of the natural resources and a critical balance between stock
and flow of resources is essential. Indiscriminate use of natural resources leads to over
exploitation and then scarcity. The concept of over exploitation of common natural
resources was first published by Hardin (1968) in the article titled ‘The Tragedy of the
Commons’. The parable demonstrates that free access and unrestricted demand for a
finite resource ultimately results in the depletion of the resource through over-
exploitation. Here the author advocates that individuals with a group, acting
independently and rationally according to one’s own interest and with no regard for
others leads to depletion of the shared natural resources, despite their understanding
Introduction
3
that the depletion of the common natural resource is contrary to the group’s long term
best interest.
Hardin introduces a hypothetical example of a pasture shared by local herdsmen. Each
herdsman will try to maximize his yield and will therefore increase the size of his
herd whenever possible. The utility of each additional animal has both a positive and
negative component; Positive: the herdsman receives all of the proceeds from each
additional animal; Negative: the pasture is slightly degraded by each additional
animal. The division of these costs and benefits is unequal: the individual herdsman
gains all of the advantage, but the disadvantage is shared among all herdsmen using
the pasture. An individual herdsman therefore continues to add additional animals to
his herd. Since all herdsmen reach the same rational conclusion, overgrazing and
degradation of the pasture is its long-term fate. Since this sequence of events follows
predictably from the behaviour of the individuals concerned, the author describes it as
a ‘Tragedy’. The metaphor illustrates the argument that free access and unrestricted
demand for a finite resource ultimately dooms the resource through over-exploitation.
This occurs because the benefits of exploitation accrue to individuals or groups, each
of whom is motivated to maximize use of the resource to the point in which they
become dependent on it, while the costs of the over exploitation are borne by all those
to whom the resource is available. This, in turn, causes demand for the resource to
increase, which causes the problem to snowball to the point that the resource is
exhausted. The rate at which exhaustion of the resource is realized depends primarily
on three factors: the number of users wanting to consume the commons, the
consumptiveness of their uses, and the relative robustness of the commons. The
author also addresses potential management solutions to the problems of the
commons through resource management solution like privatization, polluter pays, and
regulation. The author argues against relying on conscience as a means of policing the
commons, suggesting that this favours selfish individuals – often known as free riders
– over those who are more selfless.
However, Hardin’s theory of ‘The Tragedy of the Commons’ has been severely
criticised by social scientists for his failure to recognise that the local commons were
most often CPRs and not open-access. Further the decline of the commons system
(Details discussed in Chapter 7 in the Section 7.4.1)
3.3.2 Econometric and Statistical Specification Statistical analyses are applied to represent a clear idea of our hypothesis of the study.
We have used both Statistical and Econometric techniques to analyse our specific
objectives. The several Econometric and Statistical specification applied are as
follows:
I) Multiple Linear Regression Analysis We have used Multiple Linear Regression Model in our study to examine the
determinants of Common Property Resource extraction. The general form of the
multiple regression models is
1 2( , ,...., )ny f x x x= +∈
1 1 2 2 ..... n nx x xβ β β= + + + +∈
where y is the dependent or explained variable and 1 2, ,..., nx x x are the independent
or explanatory variables. ∈ is the disturbance term which arises mainly to capture the
influence of omitted factors on an economic variable. In our study the dependent
variable is household income from common forest and few village and household
characteristics i.e. family size, female percentage in household, age, education, own
land, livestock, poverty, distance to the nearest forest and market are the explanatory
variables. We have explained the relationship between dependent and explanatory
variables through Multiple Regression Model. We have used R-squared to confirm the
goodness of fit of the model and statistical significance can be checked by an F-test of
the overall fit, followed by t-test of individual parameters.
Objectives, Data Source and Methodology
47
II) Logit Regression Model In statistics logistic regression is a type of regression analysis which is used for
predicting the consequence of a categorical dependent variable based on one or more
predictor variables i.e. it is used in estimating empirical values of the parameters in a
qualitative response model. In binary logistic regression, the outcome generally coded
as ‘0’ or ‘1’. If a particular mentioned outcome for the dependent variable is the
notable possible outcome it is usually coded as ‘1’ and contrary outcome as ‘0’.
Logistic regression is employed to anticipate the odds of being a case based on the
values of the explanatory variables. The odds are defined as the probability that a
particular outcome is a case divided by the probability that it is a non-case. In our
study we have applied binary logistic distribution to examine the determinant of
poverty.
The probability that a household will be poor can be specified as:
( ) ( )11
1 ii i Xi
P E Y F XX e α βα β− +
= = = + = +
Where iP is the probability that thi household will be poor given iX , where X is a
vector of explanatory variables and e is the natural logarithm.
Since the actual estimation of the logit model is done using Maximum Likelihood
Estimation (MLE), conventional R2 is inadequate measure of goodness of fit; we have
used McFadden R-squared measure
2
int
ln ( )1
ln ( )
full
ercept
L MR
L M
∧
∧= −
where fullM = Model with predictors
int erceptM = Model without predictors
III) Count Data Model In statistics, count data is a type of statistical data in which the observations can take
only the non-negative integer values (0, 1,2,3,.…) where these integers originate from
counting rather than ranking. We have used count data model to capture the impact of
agricultural risk on CPR collection. Here the dependent variable is forest collection
Objectives, Data Source and Methodology
48
labour which is measured by the number of major forest collection trips. We have
considered household and village characteristics with agricultural risk and shortfall as
explanatory variables. The Poisson Regression Model has been used to study count
data.
Assuming that the annual number of NTFP collection trips ( in ) follows a Poisson
distribution, with observed frequencies iN , the probability density function of the
Poisson is described by equation (A1), with parameter iλ (Greene, 2003)
( )!
i ini
i ii
eP n NN
λ λ−
= = ………………………………….….…….[A1]
In the Poisson Count Data model, the characteristic of probability density function is
equidispersion with single parameter iλ equal to both mean and variance of the trip.
An adjustment to the variance covariance matrix, where k = number of observations
and l =number of parameters, is used to determine the Statistical significance of the
coefficients in the Poisson model. 1 1
2' ( )1' 'var( ) i
i i
nx xk li i
x x x xλβ λλ
λ λ− −
− = −
∑ ∑ ∑ ∑ ……….[A2]
As the count model very often detect over dispersion or variance greater than the
mean, it is easier to estimate the parameter with maximum likelihood techniques.
The common alternative of Poisson regression model is negative binomial. As the
distribution of forest collection trips has a large concentration of households taking
zero trips as well as large number of trips, it is better to use Negative-Binomial model
which is a mixture distribution of the Poisson with gamma heterogeneity. For the
Negative Binomial model, the densities for positive and zero trips are given in
equation [A3] and [A4] (Green, 2003).
Objectives, Data Source and Methodology
49
'
( )( )( ) ( 1)
in
iNB i i
i
n iP n Nn
i i
θ
θθ
λθθ λ θ λ
−
Γ += = Γ Γ +
+ +
…………………...[A3]
( 0)NB iP n
i
θ
θθ λ
= = +
…………………………………………………….[A4]
As assumed for a negative binomial model, our response variable is a count variable
and the variance of the response variable is greater than the mean of the response
variable. In statistic a zero-inflated model is a statistical model based on a zero-
inflated probability distribution i.e. a distribution that allows frequent zero value
observation. In our study we have applied Zero Inflated Negative Binomial Model
(ZINB) because the number of households taking zero trips and more than zero trips
can be explained in a better way through this model.
The expected count is conveyed as a combination of the two processes i.e.
household’s CPR collection trip against no trip.
E (to take a trip) = prob (not take any trip) * 0 + prob (take any trips) * (E y x=
take any trip)
IV) Censored Tobit Model The Tobit model is a statistical model proposed by James Tobin to describe the
relationship between a non-negative dependent variable and an independent variable.
The Tobit model is also named Censored Tobit Regression Model because few
observations on the dependent variable are censored. In Censored Data model, when
the dependent variable is censored, values in a certain range are all transformed to a
single value (Greene, 2003). We have applied censored Tobit model to explain the
relationship between forest dependency and active forest management. Here the
dependent variable is the number of man days per year a household involves in forest
management activities.
Objectives, Data Source and Methodology
50
From the surveyed data, we observe that about 25 percent of the total respondent in
Bankura district and 15 percent in Purulia district allocated zero man-days to JFM
activities. Since the dependant variable is censored from below, we observe some
estimation problems. Censoring implies expected value of ( )ijME L is non-linear in Y
and constant partial derivatives and the expected value of the dependent variable for
most combinations of parameter estimates and explanatory variable may be negative.
Here we have applied maximum likelihood estimation to estimate a censored Tobit
model. The regression is obtained by making the mean in the preceding correspond to
a classical regression model.
The general formulation is usually given in terms of an index function.
iM iL Yb= +∈
0iML = if 0
iML ≤
*i iM ML L= if 0
iML >
( ) exp( )i viVar vλ∈ =
V) Binary Probit Model In statistics, a Binary Probit Model is a type of regression where the dependent
variable can take only two values and is used to estimate the probability that an
observation with particular characteristics will fall into a specific one of the
categories.
The functional form of the Probit Model is 1 2 2
212
ixz
P e dzβ β
π
+−
−∞
= ∫
We used this model to analysis the determinants of sustainability of forest resources.
Here the dependent variable is sustainability of forest resources where we coded ‘Yes’
response as ‘1’ and ‘No’ response as ‘0’.
Objectives, Data Source and Methodology
51
3.4 Hypothesis Tested
In order to examine the crucial role of Common Property Resources in rural
livelihood, we have tested the following hypothesis in our study:
H1: Common Property Resources (CPRs) have a positive impact on income and employment of rural poor in Bankura and Purulia districts of West Bengal.
H2: CPRs have an immense role in alleviating rural poverty in the study
villages of Bankura and Purulia districts. H3: High extraction of CPRs in the surveyed villages has resulted in
degradation of the environment which further aggravates poverty. H4: CPRs acts as a safety net especially in times of agricultural crisis. H5: There is a strong relationship between forest dependency and
participation in forest management. H6: Active participation in forest management plays a positive role in
alleviating the environmental degradation. H7: Women’s participation in forest management improves the
sustainability of forest resources.
Common Property Forest Resources: Contribution and Crisis
52
CHAPTER 4
COMMON PROPERTY FOREST RESOURCES: CONTRIBUTION AND CRISIS
4.1 Introduction
Common Property Resources (CPRs) can be defined as a ‘community’s natural
resources, where every member has access and usage facility with specified
obligations, without having an exclusive property right over them’(Jodha, 1985b).
Common Property Resources are those resources that are accessible to and
collectively owned or held or managed by an identifiable community and on which no
individual has exclusive property rights. Accessibility to this resource is determined
either by legal status or by convention.
The earliest literature on Common Property Resources (CPR) can be credited to
Hardin for his celebrated work ‘Tragedy of the Commons’ (Hardin, 1968). It
demonstrates that free access and unrestricted demand for a finite resource ultimately
results in the depletion of the resource through over-exploitation. Cox (1985) in the
literature “No Tragedy on the Commons” questions the Hardin’s theory and states that
the decline of the commons system was not due to an inherent flawed land-use policy
but a widespread abuse of the rules governing them, land reforms, improved
agricultural techniques and the effect of industrial revolution.
CPRs are integral part of the social and institutional arrangements for the user
community. The rural poor, especially the landless, are highly dependent on the CPRs
for their subsistence. Several empirical studies have been carried out in India dealing
with the subject of poverty, inequality and dependency of rural households on CPRs
(Jodha, 1986, 1990, 1995; Beck, 1994, 1998; Singh et al., 1996, Iyengar and Shukla,
1999). These studies have postulated that rural poor depend heavily on the CPRs and
these resources provide a source of consumption and income (Ostrom, 1990; Brara
1987, Dasgupta 2006). In fact, in rural areas there are complementarities among
livelihood opportunities like agricultural and livestock incomes and protection of
Common Property Forest Resources: Contribution and Crisis
53
upper catchments for fodder collection and common water resources for irrigation
(Chopra, Kadekodi and Murty, 1989).
The rural poor are highly dependent on the forest for their subsistence. In India,
studies on poverty with relation to CPR collection from forest indicate that when
income from forest is set to zero in poverty calculations, poverty increases by as much
as 28 percent (Reddy and Chakravarty, 1999). Forests contribute a large part of CPRs
especially with the collection of Non Timber Forest Products (Chopra and Gulati,
2001). CPRs supplement rural livelihood and act as safety net for the poor especially
in the time of agricultural crises. Beck and Ghosh (2000) carried out field survey of
seven villages across the agro-ecological zones of West Bengal in India and based on
their findings they estimated that CPR adds about US $ 5 billion a year to the income
of the rural poor or about 12 percent of the household income of the rural poor.
Poverty is often associated with environmental degradation. Roughly half of the
world’s poor live in highly degraded environment. The World Commission on
Environment and Development (Brundtland Commission) wrote (1987): ‘Poverty is a
major cause and effect of global environmental problems. It is therefore futile to
attempt to deal with environmental problems without a broader perspective that
encompasses the factors underlying world poverty’. In recent times, there has been
increasing recognition that the relationship between poverty and environment is
complex and is strongly influenced by economic, social, local demographic,
institutional and cultural factors.
Rural poor are heavily dependent on forest. The household labour allocation decisions
and extraction of forest products are dictated by various socio-economic and
today’s poverty makes it extremely difficult to care for or restore the agricultural base,
to find alternates to deforestation and control soil erosion. Forest degradation refers to
reduction in optimum capability or productivity of the forest. Grazing of domestic
cattle, goat, sheep, etc. causes major problem in forest areas. Over grazing also
adversely affects the soil properties. The adverse effects on soil cause formation of
gullies, loss of top soil and reduction of porosity.
Common Property Forest Resources: Contribution and Crisis
54
The environment matters a lot to the rural poor. The well-being of the poor is strongly
related to the environment in terms of their health, security and earning capacity. The
environment not only provides the sources of livelihood to the rural poor but also
affects their health and influences their vulnerability. Poverty also affects
environment by forcing the rural poor to degrade the environment. Environmental
degradation largely affects the livelihood of the poor. The rural poor are most
vulnerable to environmental degradation because they depend heavily on natural
resources, have less alternative resource, and most often exposed to environmental
hazards, and are least capable of coping to environmental risks (Dasgupta and Mäler,
1994; Lopez Roman, 1997). There is a widely held view that poverty is the main
cause of environmental degradation, because the rural poor are not in a position to use
the natural resources available to them in a sustainable manner (Duraiappah 1996).
This degradation further leads to aggravate the rural poverty.
Under this backdrop, this chapter attempts to explore the nature and pattern of CPR in
Bankura and Purulia districts of West Bengal and the implication of CPR extractions
on rural poverty and environmental degradation.
Specifically, this chapter attempts to explore the
i) nature of dependency of the rural poor on CPRs
ii) determinants of CPR income
iii) role of CPR in poverty reduction
iv) environmental impact of poverty by analysing the relationship among CPR
extraction, rural poverty and environmental degradation
Common Property Forest Resources: Contribution and Crisis
55
4.2 Data and Methodology
The evidence presented in this chapter is based on the primary data collected from
two districts of West Bengal in 2011. The field survey was undertaken in 6 villages in
the district of Bankura in West Bengal, India; viz. Panjhoria, Ramjibanpur
(Bandhghat), Seolibona, Baldanga, Dulaltora and Tantirdanga and 3 villages in the
district of Purulia in West Bengal, viz. Jiyathole, Marbediya and Ambari. Total 300
households were surveyed. These villages were selected for the survey because they
were economically highly backward and the households residing in these villages are
highly dependent on forest resources for their livelihood.
Two types of questionnaire were used in the survey: household schedule for sample
households and village schedule which was administered to Panchayat office bearers,
Head Masters and other educated persons in the village for obtaining village specific
information. For the household survey, information on caste/religion, demography,
education, occupation, land holding, annual income, asset ownership, collection of
CPRs, monthly expenditure, etc. was collected from all the households in each
village. We have examined the importance of CPR in all the study villages in detail.
We have classified the households into two groups; viz. ‘poor’ if household belong to
BPL (Below Poverty Line) and ‘non-poor’ if the household belongs to APL (Above
Poverty Line). Out of the 300 surveyed households, 240 households are considered as
poor and 60 are non-poor. An attempt has been made to quantify the level of
dependency of the rural poor households on common forest resources through tabular
method. The extraction of common property products has serious implications to
poverty. The determinants of CPR extraction have been analysed using multiple
regression technique while the association between poverty and environmental
degradation has been estimated using logit regression method.
4.2.1 Conceptual Framework: In this section attempts have been made to conceptualise the problem of association
among rural poverty and extraction of CPR. The conceptualisation of the problem has
been done following the framework of Bardhan et al. (2002). Households derive
utility by means of commodity consumption. However consumption bundle depends
Common Property Forest Resources: Contribution and Crisis
56
on a variety of goods and services including the consumption of goods collected from
the common land and forests, consumption of produced / market goods, size and
composition of the households and the leisure time. Usually the villagers use the CPR
for their own consumption, but in few cases they sell it in the market or to their
neighbours.
The utility function of the household H in village K can be shown as:
( ), , ,HK HK HK HK HKU u C A L S= ……………………………………………….(1)
where HKC = Consumption of goods collected from the CPR
HKA = Consumption of produced goods
HKL = Leisure
HKS = Family size and composition
It is to be noted that the consumption of goods collected from the common forest
depends on the time spent in collection and sale activities.
Thus,
( ),HK HK HKC F R T= ………………………….……………………..(1a)
where HK CHK SHKT T T= +
= Total time spent in collection activities,
i.e. for Consumption purpose and for the purpose of sale
CHKHK
HK
TRT
= = Proportion of time spent in collecting CPRs for self-
consumption out of the total time spent in collection activities.
It is often found that the use of CPR is guided by the well-defined rules and
regularities of the community. If any individual member overuses the village
commons, he/she is punished according to the provision of the customary rule.
Certainly, the provision of punishment affects the household’s utility. To incorporate
this in our utility function, we have assumed that in normal circumstances an
individual can extract CPR to the level maximum up to the village average extraction
Common Property Forest Resources: Contribution and Crisis
57
rate. If he/she violates the village norms, he/she will be punished. The severity of
punishment depends on the gap between actual rate of collection HKC and the village
average K
K
CN
.
Thus the household utility function can be written as
( ), , ,HK HK HK HK HK EU u C A L S Sα= − ⋅ …………………..…………………(2)
where ES = Quantity of over extraction from CPR. The magnitude of ES is
determined by the village norms.
α = a positive constant exogenously determined by the management
(cost of over-extraction).
In our model, it is assumed that the prices of produced goods ( )KP , collected goods
( )CP and CPR consumption of the rest of the village are fixed and given. The indirect
utility function for the household family size and composition HKS can be represented
as:
( ), , , ,HKHK HK K HK HK EV v C L P Y S Sα= − ⋅ ……………..……………(3)
where (.)v is obtained by maximising (.)u subject to K HK HKP A Y⋅ ≤
The cost of using the CPR depends on the time it takes to collect and the opportunity
cost of this time for the rural household. The opportunity cost of time to collect CPR
depends on the household’s asset, employment opportunities tasks.
Household maximise utility (.)v subject to two constraints:
i) Budget constraints and
ii) Time constraints
The opportunity cost of time to collect CPR depends on the household’s alternate uses
of time. The income of household is earned by allocating the family labour into
different occupations. The different occupations denoted by 1,2,3,4,5i = respectively
are (i) Self-employment in agriculture 1( )HKS , ii) Wage labour in agriculture 2( )HKS ,
(iii) Wage labour in non-agriculture 3( )HKS , (iv) Self-employment in non-agriculture
4( )HKS and (v) Self-employment in livestock grazing 5( )HKS . Besides the above
Common Property Forest Resources: Contribution and Crisis
58
occupational activities, time is allocated to CPR collection for consumption ( )CHKT
and sale ( )SHKT and Leisure ( )HKL .
Now total time taken for CPR collection ( )HKT can be shown as:
HK HK HK CHK HK SHK HKT t C t C t C= ⋅ = ⋅ + ⋅ ……………………………(4)
were HKt = time taken to collect one unit of CPR. The labour allocated to occupation i
is denoted by iHKS .
Now the time constraint is 5
1
iHK HK HK HK
iT S S L T
=
= = + +∑ …………………….………(5)
It is to be noted that total time available for different activities depends on the family
size and composition ( )HKS .
The budget constraints show that the households’ expenditure must be less than the
sum of net income ( )HKY from different sources. In equality form we can write:
Net Income = Expenditure = Income from agriculture 1( )β + Income from non-farm
business 4( )β + Income from livestock activity 5( )β + Income from CPR products
( )C HKP C⋅ + Wage income from agriculture 2( )w + Wage income from non-agriculture
3( )w . We can thus rewrite the equation as follows:
1 1 1 2 2 3 3 4 4 4( ; , , , ) ( , , , , )HK HK HK HK K K K HK K HK HK HK HK K KY S v d P I W S W S S v d P Iβ β= + + +
5 5 5( ; , , )HK HK K K C HKS v P I P Cβ+ + ⋅ ……………………………..(6)
where 1β =Returns to agriculture which depends on labour allocated in agriculture1( )HKS , land 1( )HKv , education ( )HKd , price of non-collected goods ( )KP , village
infrastructure ( )KI
2 2K HKW S =Income of wage labour engaged in agricultural activities where wage
rate is 2KW
Common Property Forest Resources: Contribution and Crisis
59
3 3K HKW S =Income of wage labour engaged in non-agricultural activities where
wage rate is 3KW
4β = Returns to non-farm business which depends on labour allocated in non-
farm business 4( )HKS , non-farm business assets 4( )HKv , education ( )HKd , price of
non-collected goods ( )KP and village infrastructure ( )KI
5β = Returns to livestock activity which depends on labour engaged in
livestock activity 5( )HKS , livestock owned by the household 5( )HKv , price of non-
collected goods ( )KP and village infrastructure ( )KI
C HKP C⋅ =Income from CPR products ( )HKC by selling at the price rate CP .
Now the problem of the household is to select CPR ( )HKC and labour allocation HKL ,
, 1, 2,..5,iHKS i = to maximise its utility (2) subject to constraints (5) and (6).
The optimization of utility function subject to the budget and time constraints would
give us implicitly the determinants of the collection of the CPR goods ( )HKC by the
households. This can be approximated as
( , , , )HK HK HK HK HK HKC C Y S t v=
where HKY =given level of expenditure
HKS =family size and composition
HKt = time taken to collect one unit of CPR and
HKv = village level characteristics, i.e. land holding pattern, livestock,
education, distance between house and common forest, sex / gender, etc.
In this chapter, we have tested the following hypothesis:
H1: Common Property Resources (CPRs) have a positive impact on income and employment of rural poor in Bankura and Purulia districts of West Bengal.
H2: CPRs have an immense role in alleviating rural poverty in the study
villages of Bankura and Purulia districts. H3: High extraction of CPRs in the surveyed villages has resulted in
degradation of the environment which further aggravates poverty.
Common Property Forest Resources: Contribution and Crisis
60
4.2.2 The Empirical Model Specification CPRs are the life support system in rural Bengal. CPRs act as not only a regular
source of income and employment but also a safety net in periods of drought and
other natural calamities. The extractions of CPRs are invariably linked with the
characteristics of household under a specific socio-economic condition. In this section
an attempt has been made to identify the factors determining the extent of forest
product collection. The extractions of products from the common forest depend on
the factors relating to household and village characteristics, i.e., family size and
composition, household labour, land holding pattern, livestock unit, occupational
structure, opportunity cost, economic status, the existence of the market, technology,
education, age, distance between forest and house and institutional factors like
management rule, civil law, etc.
4.2.2.A Determinants of CPR: Multiple Regression Model A multiple regression model has been used to examine the determinants of CPR
Note:# A grazing day implies that an animal has remained in the grazing field of the CPR at least for 5 hours in a dayand the animal has not been fed separately. Animal grazing days (number of animals x number of grazing days)has been calculated by changing the no. of animals into animal units as per the basis as shown below:1 animal unit=1 bullock /cow or 4 goats or 4 pigs or 100 chicken/hens/ducks
Dependency on CPRs for Animal Grazing (in last 1 month)
Household category
(no. of HH)
Panjhoria
Dulaltora
Tantirdanga
Bankura Saltora
Seolibona
Baldanga
Ramjibanpur
Grand Total
Marbediya
Ambari
Bankura Total
Purulia Santuri
Jiyathole
Purulia Total
Common Property Forest Resources: Contribution and Crisis
78
4.4 CPRs and Rural Poverty: The objective of this study is to analyse the extent of Poverty in the study villages and
to examine if the income derived from CPRs had any role to play to alleviate the
poverty. The monthly per capita income including the income from CPRs for the 150
households in the study villages have been arranged in the ascending order and then
grouped into 10 classes. As per the Tendulkar Committee report published in
November 2009 and now approved by the planning commission, the revised poverty
line (rural) with the base year 2004-2005 for West Bengal is Rs 445.38. The estimated
monthly per capita income of the households in the study area has been compared
with the revised poverty line for the state. In order to analyse the extent of poverty
and to quantify the role of income from extraction of CPR products in poverty
mitigation, we have used two sets of data i) per capita income of the households
including the income derived from common property resources and ii) per capita
income of the households excluding the income derived from the common property
resources.
Table 4.8A & 4.8B shows the distribution of monthly per capita income including the
income derived from CPRs for Bankura and Purulia district.
Total 150 100.00 102627 100.00Source: Field Survey 2011
Distribution of monthly per capita income of the sample households in Purulia district( excluding income derived from CPRs)
Common Property Forest Resources: Contribution and Crisis
81
4.5 Determinants of CPR Extraction We have assumed that collection of CPR is determined by socio-economic and
demographic variables. We have explained the determinants of CPR extraction
through econometric analysis to give an understanding of the relationship between
forest dependency (measured by the household income from the community forest)
and socio-economic variables.
Regression Results and Discussion
The regression model has been tested using the household level data through field
survey in Bankura and Purulia district. Multiple regression analysis has been made
using EViews 7 computer package. The result for the determinants of the household
income from the community forest for Bankura and Purulia district is given in the
Table 4.10 & 4.11 below:
TABLE 4.10 A
Determinants of CPR extraction-Bankura District
Source: Estimated by EViews7 computer software using field survey data of 2011 Note: 1.*Significant at 1 percent level, ** Significant at 5 percent level, *** Significant at 10 percent level 2. Summary statistics has been presented in Table A3.1 in Appendix III
Source: Estimated by EViews7 computer software using field survey data of 2011
TABLE 4.11 A Determinants of CPR extraction-Purulia District Dependent Variable: CPRIN; Method: Least Squares Sample: 1 150; Included observations: 149
Adjusted R-squared 0.669825 S.D. dependent var 2125.682 S.E. of regression 1221.434 Akaike info criterion 17.11819 Sum squared resid 2.07E+08 Schwarz criterion 17.31980 Log likelihood -1265.306 Hannan-Quinn criter. 17.20010 F-statistic 34.36086 Durbin-Watson stat 1.566364 Prob(F-statistic) 0.000000
Source: Estimated by EViews 7 computer software using field survey data of 2011 Note: 1.*Significant at 1 percent level, ** Significant at 5 percent level, *** Significant at 10 percent level 2. Summary statistics has been presented in Table A3.2 in Appendix III
Common Property Forest Resources: Contribution and Crisis
83
TABLE- 4.11 B Variance Inflation Factors Sample: 1 150 Included observations: 149
Source: Estimated by EViews 7 computer software using field survey data of 2011 The R-square is as high as 65 percent in Bankura district and 68 percent in Purulia
district. The F-statistics for overall goodness of fit of the model is highly significant in
both the districts. Tables 4.10B & 4.11B represents Variance Inflation Factor (VIF)
for explanatory variable. We have observed from our results that VIF is very low i.e.
around 1 in all the cases. Hence we conclude that we do not have multicollinearity
problem. It is evident from the analysis that most of the important variables are
significant with the expected sign. The CPR collection is a labour intensive activity.
Household members collect a lot of CPR products viz. fuel wood, fodder, vegetables,
bamboo, etc. from the forest. They also hunt animals and catch fishes from the
community forest area. All these activities take a lot of time. The larger the family
size, the higher is the labour time available for the collection of community forest
products. In both the districts of Bankura and Purulia, the family size ( FSIZE ) has a
positive impact on community forest income. In Bankura and Purulia districts, the p-
value indicates that the association is significant.
From the regression analysis, we observed that there is a positive relationship between
average age of the household ( AVRAGE ) i.e. experience in collecting CPR products
and CPR income. It is easier for an experienced household member to collect more
Common Property Forest Resources: Contribution and Crisis
84
CPR and thus smooth their consumption and livelihood. In line with our expectation,
the result is positive and significant in Purulia district. However the result is negative
and insignificant in Bankura district. Further it is observed that household with larger
size of livestock ( LIVESTOCK ) collect more fodder to feed the animals. They also
require higher quantity of fuel wood to prepare concentrated food for the animals. So
there is a positive relation between the CPR income and the size of the livestock. The
impact of the number of livestock on CPR income is significant in Bankura district,
but insignificant in Purulia district.
We have hypothesised a positive relationship between female percentage in the
household ( FEMPER ) and CPR income. From our study area in Bankura district, we
observe that female members are mainly involved in collection of CPRs. So the
households with higher percentage of female members collect more CPR products
and hence earn higher income as compared to households with lower percentage of
female members. As per the result, though the percentage of female members in the
household is found to be positively associated with the household level income from
the community forest, the p-value indicates that the association is statistically
significant only in Bankura district.
Education ( AVRSCH ) i.e. average years of schooling of the household has a negative
impact on the income from CPR. Further, the p-value for Bankura and Purulia
districts indicates that it has a significant impact on the income from CPR. Household
members who are better educated get better job opportunities and therefore are less
interested in collection of CPR products. We have hypothesised a negative
relationship between land ownership ( OWNLAND ) and CPR income as household
who own more agricultural land spend more time in cultivation and less time in CPR
collection. In line with our expectation we have observed coefficient of OWNLAND is
negative and significant in Bankura district. However, we observe contradictory
results in case of Purulia district. Here the households with larger ownership of
cultivated land ( OWNLAND ) collect more fuel wood. This is mainly due to the fact
that land in Purulia district is mostly infertile and so mere ownership of land fails to
reduce the dependency on CPR. It is also observed that the forest distance
( FORESTDIST ) i.e. distance between the residence and the common forest area has a
Common Property Forest Resources: Contribution and Crisis
85
negative impact on the CPR income. From the survey, it indicates that households
nearest to the forest area extract more CPR and get more income from the forest
products as compared to the households far away from the forest area. In both the
districts the impact is significant. In the case of distance to the nearest market
( DISM ), the motivation for extraction of forest products is greater when the market
is nearer. This is due to the fact that the rural poor are able to sell the CPR products in
the nearest market and generate income easily. As expected, DISM has a negative
impact on the extraction of CPR product in both the districts. However, the result is
significant only in Purulia district.
The most important finding of this study is impact of poverty on CPR extraction. The
coefficient of dummy variable ( POVR ) is positive and highly significant in both the
districts, which implies that BPL household are more dependent on CPR as compared
to the APL household. Household with low income extract more community forest
product for their consumption purposes and also sell it to increase their income.
Hence in the case of the poor, the income from community forest has a higher
percentage as compared to that of the ‘not so poor’.
4.6 Poverty-Environment Nexus-Logit Model Several literatures have discussed the inter-linkage between poverty and
environmental degradation. While some authors argue that poverty leads to
environmental degradation, others argue that environmental degradation leads to low
productivity which results in increase in poverty. Several concepts have been put forth
by authors to illustrate the over-exploitation in fisheries, forests, over grazing, air and
water pollution, abuse of public land and problems of resource misallocation
(Stevenson, 1991). The inter-linkage between poverty and environmental degradation
has been defined as a ‘vicious circle’ by Dasgupta and Maler (1994). In their study,
the authors argue that the rural poor pushed by increase in population and poverty,
extend their cropping onto fragile marginal lands resulting in further degradation. This
results in reduced yield and this further impoverishes them. It can also be stated that
the environmental degradation adversely affect poverty, because the poor are the most
vulnerable to environmental degradation, due to their heavy dependence on natural-
resource base, and limited resource to cope with adverse environmental effect.
Common Property Forest Resources: Contribution and Crisis
86
We have made an attempt to quantify the diminution of common property resources
and the extent of degradation of common forest in the study villages. We have
gathered information from Panchayat Pradhan, Head Master, Public leaders and
household head about the relative position of forest resources comparing present state
with that of twenty years back.
We have shown the extent of depletion of common property resources during 1990-
2010 in our surveyed villages in the following Table 4.12 below:
From our field survey report we have observed that the forest area had declined as
compared to earlier times of 1990s in both the districts. However, the extent of
depletion of forest area is high in Bankura district as compared to Purulia district.
Severe deforestation was detected in three villages viz. Ramjibanpur, Seolibona and
Baldanaga of Bankura district and Marbediya of Purulia district. Village Ramjibanpur
TABLE 4.12
Common Forest area (in Sq. Km)
Common Village land (in Sq. Km)
Common grazing land (in Sq. Km)
Source: Field Survey, 2011
Bankura Saltora
Purulia Santuri
Bankura Total
Baldanga
Panjhoria
Ramjibanpur
Purulia Total
Grand Total
Jiyathole
Marbediya
Extent of Depletion of Common Property Resources (during 1990-2010)
13.25 12.81 10.75
Ambari
Dulaltora
Tantirdanga
Seolibona
Percentage Decline District Block Name of
village
17.13
16.87
9.24
8.18
13.25
13.75
10.53
6.25
12.99
10.18
12.05
8.28 7.53
8.78 7.05
10.69 8.93
8.31 7.65
14.35
11.76 9.63
11.72
14.05 10.86
8.57 8.64
7.62 4.78
10.43 8.85
9.8811.64
Common Property Forest Resources: Contribution and Crisis
87
of Bankura district witnessed the highest depletion of common forest resources.
Interestingly, no noticeable deforestation was found in Jiyathole village of Purulia
district. The common forest area declined around 12.05 percent in the study area
during 1990-2010.
The villagers of Ramjibanpur of Saltora block in Bankura district, Haren Kora and
Anil Mudikora, have raised their concern on depletion of the common forest area and
have shared their view:
“We now have to walk 2 – 2.5 km more as compared to earlier period (1990s)
in order to gather fire wood and fodder and graze our livestock. This has
resulted in lot of time and energy being spent for reaching the forest area.
Also, several medicinal herbs have become almost rare at the common forest
area” (Dated 28th July, 2011, Medium of language was Bengali / Santhali).
The depletion of common forest resources viz., the forest resources in both the
districts are mainly responsible for absence of any alternative income or employment
opportunities, growing commercialisation of CPR products, emergence of market, and
presence of middle man for market sale. We have also found an enormous pressure on
common forest in our study villages because of the illicit collection of fuel wood,
fodder and small timber by the households. The problem has been tackled by the
formation of Forest Protection Committee under the purview of Joint Forest
Management in our study area of both the districts.
4.6.1 Determinants of Poverty To examine the determinants of poverty a qualitative response model like logit model
is proposed in this study. We consider a range of socio-economic as well as
environmental variable which enable us to express the rural poverty conditions as well
as the extent of environmental degradation in the region. In our study we have
considered forest degradation as a measurement of environmental degradation. The
logit regression model has been tested using the household level data through field
survey in Bankura and Purulia districts. Specification of the regression model has
been presented in the following table where the expected sign and description of the
dependent and explanatory variables are explained.
Common Property Forest Resources: Contribution and Crisis
88
TABLE 4.13
Description of Variables of Logit Regression Model Variables Expected
Sign
Variable description
Dependent variable
POVR
Poverty of the household
POVR =1; if the household belongs to BPL
POVR =0; if the household belongs to APL
Explanatory Variables
FSIZE + Average number of population of the household
(size of the family)
AVRAGE _ Average age of household, i.e. experience in
collecting CPR product
AVRSCH _ Average years (number of years) of schooling of
household
OWNLAND _ Total land owned by the household
LIVESTOCK _ Total livestock of the households converted into
animal units
FORESTDIST + Distance of the CPR field from the residence of
the households (km)
*ENVDGR +
Dummy for extent of environmental degradation
ENVDGR =1; if environment is more degraded
ENVDGR =0; if environment is less degraded
*Measuring Environmental degradation
In this study, we have considered forest degradation as a measurement of
environmental degradation. Forest Degradation is measured on the basis of the data
collected in the village survey from three different variables:
i) Extent of forest damage visually seen (FD)
ii) Condition of the forest informed by the respondents as compared to that of
earlier times (FC)
iii) Forest use penetration i.e. the depth into the forest from the village
boundary where use pressure was evident (FP)
Common Property Forest Resources: Contribution and Crisis
89
For the purpose of regression analysis we have constructed a composite measure
called Forest Degradation Index (FDI) which is sum of the above three variables i.e.
FDI=FD+FC+FP. All these three variables (FD, FC, FP) are coded (using four point
scale) so that increasing values shows more forest degradation. Each variable has a
substantive impact on the index and they are positively correlated.
The regression result is given in the following Table 4.14A and 4.14B below.
TABLE 4.14 A
Determinants of Poverty-Bankura District Dependent Variable: POVR Method: ML - Binary Logit (Quadratic hill climbing) Sample: 1 150 Covariance matrix computed using second derivatives
McFadden R-squared 0.910470 Mean dependent var 0.766667
S.D. dependent var 0.424370 S.E. of regression 0.134763 Akaike info criterion 0.203945 Sum squared resid 2.578856 Schwarz criterion 0.364512 Log likelihood -7.295869 Hannan-Quinn criter. 0.269178 Deviance 14.59174 Restr. deviance 162.9818 Restr. log likelihood -81.49092 LR statistic 148.3901 Avg. log likelihood -0.048639 Prob(LR statistic) 0.000000
Obs with Dep=0 17 Total obs 150
Obs with Dep=1 133 *Significant at 1 percent level, ** Significant at 5 percent level, *** Significant at 10 percent level
Source: Estimated by EViews 7 computer software using field survey data of 2011
Common Property Forest Resources: Contribution and Crisis
90
TABLE 4.14 B
Determinants of Poverty-Purulia District Dependent Variable: POVR Method: ML - Binary Logit (Quadratic hill climbing) Sample: 1 150 Included observations: 150 Covariance matrix computed using second derivatives
McFadden R-squared 0.691794 Mean dependent var 0.620000
S.D. dependent var 0.487013 S.E. of regression 0.232767 Akaike info criterion 0.516004 Sum squared resid 7.693599 Schwarz criterion 0.676571 Log likelihood -30.70031 Hannan-Quinn criter. 0.581237 Deviance 61.40061 Restr. deviance 199.2192 Restr. log likelihood -99.60962 LR statistic 137.8186 Avg. log likelihood -0.204669 Prob(LR statistic) 0.000000
Obs with Dep=0 43 Total obs 150
Obs with Dep=1 107 *Significant at 1 percent level, ** Significant at 5 percent level, *** Significant at 10 percent level
Source: Estimated by EViews 7 computer software using field survey data of 2011 From the above Tables 4.14A & 4.14B we observe that in most of the cases, the
results are consistent with our hypothesis. As expected, i.e. experience in collecting
CPR products ( AVRAGE ) has been found to be a negative influence on poverty
( POVR ) in both the districts. The experienced elder members of the household can
earn more income as compared to the younger one thus helping to reduce poverty.
However, the result is insignificant in both the districts. In line with our expectation
households with more own land ( OWNLAND ) and larger number of livestock
( LIVESTOCK ) have a negative impact on poverty. This indicates that wealthier
households have several options to earn money and therefore the probability of the
Common Property Forest Resources: Contribution and Crisis
91
incidence of poverty is low. In Bankura district, both have significant impact on
poverty; however in Purulia district we have observed significant result only in the
case of OWNLAND . We have hypothesized that educated people ( AVRSCH ) get
better job opportunities and thus help to reduce the probability of incidence of
poverty. In Purulia district although the result is consistent with our hypothesis, the
impact is insignificant. In Bankura district, the result is contradictory but insignificant
and therefore can be ignored. It is obvious that households residing closer to the forest
collect more CPR and thus reduce their poverty level. As expected, Forest distance
( FORESTDIST ) has positive impact on poverty ( POVR ) in both districts. However,
the result is significant only in Purulia district. The households with larger family size
( FSIZE ) the probability of incidence of poverty is high. In fact large family size puts
additional financial burden on the earning member which in turn increases their
poverty level. The result is consistent with our hypothesis in both the district.
However the impact is significant only in Bankura district.
The coefficient of environmental degradation is positive and significant which imply
that with more environmental degradation the probability of the incidence of poverty
increases. In fact, households in the study villages live under acute poverty and hence
they are heavily dependent on the natural resources for their subsistence. Under the
circumstances, the level of extraction of the CPRs is higher than their regenerating
process and thus the environment gets further degraded. However, poverty is not the
sole cause for degradation. There are several other factors like rising population,
growing commercialisation of agricultural and forest products and emergence of
market, etc. which leads to forest degradation.
Common Property Forest Resources: Contribution and Crisis
92
4.7 Conclusion
This study investigates the dependency of the rural poor on CPRs and the relationship
between rural poor and environmental degradation. The result of the survey of 300
households in Bankura and Purulia districts indicates a very high dependency of the
rural poor on CPR products. The field survey data shows that the average percentage
of CPR income to total income in Bankura and Purulia district is 19.04 percent and
18.11 percent respectively. For BPL households, 27.28 percent in Bankura district and
27.92 percent in Purulia district of the total household income comes from CPR based
activities whereas in case of APL households it is 2.31 percent and 7.71 percent
respectively. Hence poor households enjoy a greater proportion of income from CPRs
both in relative as well as absolute terms. The survey data further reveals that 21.28
percent of the total consumption expenditure of household is supported by CPRs,
which indicates high dependency of the rural households on CPRs for their
consumption.
CPR has also played an important role in employment generation. As per the survey
data, in an average, rural household generate around 116 and 95 employment man
days per annum from CPR based activities in Bankura and Purulia district
respectively. The households collect fuel wood and cow dung from the common
forest area for the purpose of cooking. As per the survey report, an average of 79.35
percent and 76.78 percent of the total household energy consumption were met by the
CPR products collected from the common forest area in Bankura and Purulia districts
respectively. Here we observed that both the poor and not so poor households use fuel
wood gathered from CPRs to cater to their household energy needs. Our survey data
confirms a high dependency of the rural households on the CPRs for animal grazing
with an average of 88 and 114 animal unit grazing days per household in Bankura and
Purulia districts respectively in the last 1 month.
The survey data also shows the immense role of CPRs in alleviating the poverty in the
study villages. As we exclude the income derived from CPRs from the total income of
the households, we observe that the extent of poverty in both the districts have
increased by around 26 percent.
Common Property Forest Resources: Contribution and Crisis
93
The most important finding of our multiple regression model is the impact of poverty
on CPR extraction and the result indicate that the coefficient of dummy variable
( POVR ) is positive and significant in both the districts. Therefore we can conclude
that BPL households are more dependent on CPR as compared to the APL
households.
The high extraction of CPRs in the surveyed villages has resulted in degradation of
the environment. Environmental degradation has adversely affected poverty because
of high dependence of the rural poor on the natural resources and this further
impoverishes them. We have used logit regression model to analyse the relationship
between poverty and environmental degradation. The important finding of this
analysis is that the coefficient of environmental degradation is positive and significant
in both the districts which show a strong positive relationship between poverty and
environmental degradation. It is thus desirable to ensure conservation of CPRs in
order to maintain the sustainable livelihood of the rural poor.
We have hypothesised that CPRs have a positive impact on income and employment
of rural poor and have an immense role in alleviating rural poverty. We further
hypothesised that high extraction of CPR has resulted in degradation of the
environment which further aggravates rural poverty. Our survey results are consistent
with our hypothesis. Further, our findings on the high dependency of the rural poor on
CPRs and the subsequent degradation of the environment are in conformity with the
results of similar studies carried out in other Indian states viz. Rajasthan, Karnataka,
(Jodha, 1986); Gujarat (Conroy, 1991); etc. However, our empirical results goes
against the findings of Chopra and Dasgupta (2003) and Kuri (2005) who postulated
that non-poor are equally benefited by extraction of CPRs and are also responsible for
forest degradation.
We can conclude that dependence of the rural poor on Common Property Resources
is a basic necessity and cannot be denied.
Agricultural Risk and Common Property Resources
94
CHAPTER 5
AGRICUTURAL RISK AND COMMON PROPERTY RESOURCES
5.1 Introduction
Agriculture is the predominant economic activity in West Bengal. However there is
wide fluctuation in the agricultural productivity in many parts of West Bengal. The
problem of fluctuating crop yield can be attributed to vagaries of the weather and land
degradation in the form of soil erosion, salinity, water logging, etc. The yield is also
affected by outbreak of diseases, pests and other hazards like flood, droughts and fire.
In our study villages in the districts of Bankura and Purulia in West Bengal, the rural
households are heavily dependent on agriculture. These districts have the problem of
‘dry land’ which have low moisture retaining capacity in the soil, thereby leading to
fluctuating crop productivity. Water storage facilities which are the ‘lifeline’ of
irrigation are also lacking in many parts of both the districts. Crop failure also occurs
due to low rainfall. The instability in the crop production raises the agricultural risk
which adversely affects the livelihood and income of the rural households and in turn
also effects their decision to use high technology in farming, thereby impeding the
development process. The fluctuating crop production also affects the price stability.
The rural households have to incur costs for smoothening consumption across income
shocks. The households therefore look for safety net to mitigate the income shocks.
In our study villages of Bankura and Purulia, most of the households live below the
poverty line. The main occupation of the household is agriculture, although they also
engage in off farm wage labour. There are several risks associated with the harvesting
of crops such as weather, seasonal flooding, unpredictable soil quality, crop diseases,
price shocks and forest pests. Under these circumstances, forest acts as a security
especially against crop failure. Households having limited credit and insurance
facility, extract Non Timber Forest Products (NTFP) which not only reduce their
agricultural risk but also help to smooth out their consumption. Hence NTFP has a
supporting role in the wellbeing of the rural poor in the form of ‘natural insurance’.
Agricultural Risk and Common Property Resources
95
By collecting NTFP, rural households smooth their income as well as consumption in
the period of agricultural shortfall.
The collection of forest products is a common phenomenon to support the livelihood
of the rural poor. In rural area, Common Property Resources (CPRs) are critical
resources for the poor households. CPRs are vital resources for the poor primarily
because the cost of using the CPRs are low and these involve only human labour as
the input. CPRs supplement the rural livelihood and act as safety net for the poor
seasonally or during the agricultural crisis.
Several literatures have discussed the importance of Common Property Resources as
insurance. Based on the survey of rural households living on the margin of Tapajós
National Forest in the Brazilian Amazon, Pattanayak and Sills (2001) had put forth a
positive correlation between collection of NTFP, shortfall in agriculture and the
expected agricultural risk. The advantage of common property resources arises
because of its superior insurance properties which tend to provide income
maintenance to the rural poor (Baland and Francois, 2004). The study on the potential
impact of extraction of NTFP on land use choice was carried out by Delacote (2009).
The study revealed that the rural poor collect forest products in order to reduce the
agricultural risk. If the agricultural risk is reduced, then the households reduce the size
of the safety activity thereby being less dependent on the forest products as compared
to agricultural activities.
Informal insurance arrangements are affected by sustainability constraints, often
excluding the poor from these arrangements (Dercon 2002). Both ‘forest dependent’
and ‘forest related’ people depend on forest for a supplementary source of income and
there is a varied nature of relationships of people to forest and forest products (Byron
and Arnold, 1999). In Sierra Leone, a country in West Africa, the farmers in order to
cope agricultural shocks arising due to irregular rainfall often resort to mortgaging or
pledging cocoa or coffee trees or selling timber to buy food (Leach 1990). Tropical
forest resources are known to reduce the vulnerability of the rural poor to income
shocks. Based on the field study of rural households in Eastern Honduras in Central
America, McSweeney (2004) emphasised that the nature and intensity of the calamity
Agricultural Risk and Common Property Resources
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experienced by the rural households as well as the household attributes in the form of
capital and land, affects the extent to which the forest resources are used by them to
insure against the risk.
In a study in Honduras, Godoy et al. (2002) emphasised that in spite of the fact that
extraction of NTFP brings low annual earnings, it still plays an important role in
mitigating the unexpected loss due to agricultural risks. There is increased recognition
to the concept of ‘Natural Insurance’ where even a small amount of earnings from the
forest help to bridge the income gap and thereby acts as a safety net. Hence several
initiatives are taken by the forest communities to promote sustainable use of forest
resources. Takasaki et al. (2002) examined the vulnerability and responses to
covariate flood shock among peasant households in the Amazonian tropical forests.
The study reveals that forest extraction acts as a coping strategy against shocks. The
study also discussed that conservation and development initiatives can help to
mitigate shocks by targeting and deploying contingent support.
Several Indian literatures have also supported the view that common forest products
provide security or insurance against contingencies. Based on survey of semi-arid
regions in India, Jodha (1978) observes that the rural households adopt different
adjustment mechanism like reduction in consumption levels, asset depletion &
replenishment, periodic out migration and traditional informal cooperation. However,
the shortfall in agricultural production is mitigated by collection of common forest
products. Dasgupta and Mäler (1994) had emphasised that the common property
resources provide the rural poor with partial protection in time of unusual economic
stress. In the study of tribal groups of Bihar, Agarwal, (1991) revealed that
communally held forests provided the only means of subsistence during income
shocks. This natural insurance brings an important twist to the discussion by
connecting rural poverty in risky environments with environmental degradation
(Dasgupta, 1993; Duraiappah, 1996). During a localised drought in eastern Gujarat,
majority of the population who experienced acute shortage of food sold trees to buy
food and meet their subsistence (Conroy 1991). The smoothing of the income of the
households arising due to agricultural shocks is done by the labour markets allowing
the households to shift labour from farm to off-farm employment (Kochar 1999).
Agricultural Risk and Common Property Resources
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The role of CPRs in rural livelihood is very critical and it act as safety nets especially
in times of agricultural crisis. In our study area of Bankura and Purulia districts of
West Bengal, agricultural activities are subjected to low fertility of soil, scarcity of
water and high dependence on weather. This results in wide variability in production
and productivity in agriculture. Due to the non-availability of alternate income
opportunities, the farmers in the study area fall back on Common Property Resources
to mitigate the agricultural risk.
Under this circumstance, the objective of our study is to determine how and to what
extent agricultural shortfall affects the collection of common forest resources.
Another important objective is to examine the inter relationship among agricultural
risk, non-timber forest collection and the extent of rural poverty.
5.2 Data and Methodology The study is based on primary data collected from field survey on Common Property
Resources conducted in Bankura and Purulia district in 2011. The field survey was
undertaken in 6 villages in the district of Bankura in West Bengal, India; viz.
Panjhoria, Ramjibanpur (Bandhghat), Seolibona, Baldanga, Dulaltora and
Tantirdanga and 3 villages in the district of Purulia in West Bengal, India; viz.
Jiyathole, Marbediya and Ambari. Total 300 households were surveyed.
Majority of the household respondents have listed agriculture as one of their primary
sources of income. Paddy is their main crop. Almost all the households use forest
products. Most of the households (80 percent) made major collection trips to the
forest in the surveyed year. On an average, the distance between common forest and
village community is 2-3 km and the households spend around 2.5 hours to collect the
forest products. During the survey, the households have indicated that they are very
much dependent on nature for all agricultural activities. The households face
agricultural risks which are primarily due to weather risk i.e. rising temperature,
erratic rainfall pattern and increase in severity of drought, flood and cyclones. The
rural households therefore depend on forest products to reduce the risk inherent to
subsistence agriculture. They are therefore dependent on the forest for food or
Agricultural Risk and Common Property Resources
98
medicine which they cannot produce or purchase. They also sell forest products such
as fuel wood, honey, fish and fruits in the market. The rural households also resort to
wage labour as an alternate source of income. However this is done only for a short
period of time. Moreover the rural households do not get the facilities of insurance
and credit. Therefore the rural households having limited credit and insurance
facilities have to depend on common property resources at the time of agricultural
crisis. These characteristic of the surveyed area makes it an ideal setting for testing
the hypothesis on natural insurance.
We have measured agricultural production in terms of rice equivalent production. We
have collected the data on agricultural production for the current year and last four
consecutive years to determine the agricultural shortfall and risk. We have also
collected the data on different types of CPR products which are collected by the rural
households and the total time spent for the collection of the forest products by each
family unit (monthly basis on an average) for the same period. We have used a tabular
method to quantify the pattern of agriculture and the relationship between agricultural
risk and common property resources in the surveyed area. The importance of CPR as
a safety net during agricultural risk has been analysed using count data model
technique.
5.2.1 Conceptual Framework
Based on the stylized features of the backward rural agrarian economy of Bankura
and Purulia district of West Bengal, an attempt has been made in this section to
develop a conceptual framework to examine the inter relationship between
agricultural crop failures and the collection of common property forest products
following the principles of ‘new home economies’ (Barnum and Squire 1979;
Pattanayak and Sills 2001). In other words, it attempts to examine the effect of
unexpected agricultural shortfall and the expected agricultural risks on the collection
of Non timber Forest Products. Efforts have also been made in this section to examine
the insurance strategy which causes over exploitation of the resources and finally
leads to a poverty trap.
Agricultural Risk and Common Property Resources
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In poor agrarian economy the objective of the household is the maximization of utility
subject to full income constraint. Full income includes income from agricultural
production, off-farm wage income, collection of forest products and the opportunity
cost of leisure time (Pattanayak and Sills (2001). The households primarily depend on
agriculture (A). The off-farm wage income (W) and the collections of common forest
products (F) act as a supportive secondary livelihood activities to the rural poor.
The utility function of the household depends on the consumption of agricultural
products ( AC ), consumption of forest products ( FC ), leisure ( LC ) and a numeraire
( NC ) that represents all other commodities and the household characteristics affecting
preferences ( CH ).
The utility function is given by
( ), , ,A F L N Cu f C C C C H= ………………………………………………….(1)
Household maximize utility ( u ) subject to three constraints.
(i) Production function which assume that Agriculture and Forest products
depend on labour input ( AN and FN ), Capital input ( AK and FK ) and
household characteristics ( CH ) such as age, education, experience in
agricultural activities and collection of forest products. Hence the
agricultural and forest production function takes the form
( ), ,A A CA f N K H= …………………………..………………………..(2)
( ), ,F F CF f N K H= ………………………………………………..….(3)
Since the rural poor are very much dependent on nature for agricultural
activities, they are very often subjected to agricultural risk in the form of
drought, flood or attack of pests.
Hence our agricultural production function at equation (2) can be rewritten
as
( ), ,A A CA f N K Hξ= ………………………………………..………...(4)
where ξ measures agricultural risk
Agricultural Risk and Common Property Resources
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(ii) The rural poor engage in different household activities in the form of
agriculture, forest collection, off-farm wage labour and leisure or other
household activities. A time constraint implies that sum of households’
allocation of labour into agriculture ( AN ), forestry ( FN ), off-farm wages
( WN ) and leisure or other household activities ( LN ) cannot exceed the
household endowment ( N ).
A F W LN N N N N+ + + ≤ ………………………………………….…….(5)
(iii) The budget constraint which shows the households’ expenditure measured
using existing prices must be less than the sum of net income (Y ) from
*Significant at 1 percent level, ** Significant at 5 percent level, *** Significant at 10 percent levelSource: Estimated by Stata 8 Computer Software using Field Survey Data of 2011
Forest Collection as a Function of Agricultural Risk(Bankura District)
POISSON REGRESSION NEGATIVE BINOMIAL ZERO INFLATED NEGATIVE BINOMIAL
Agricultural Risk and Common Property Resources
117
From the above Tables 5.8 and 5.9, we have observed that the results are consistent
for most of the variables in both the districts. However our choice of the best model is
Zero Inflated Negative Binomial model (ZINB). To compare the negative binomial
and ZINB model, we apply the Vuong statistic. The Vuong test compares the ZINB
model with a standard Negative Binomial model. A significant Z test indicates that
the Zero Inflated Negative Binomial model is better. Hence we have turned to the
estimated results of ZINB model. We have detected that the association between
forest collection trips and age of the household ( AGEHEAD ) is positive and square
age of the household head ( SQAGEH ) is negative. In our analysis of both the
districts, we have observed significant result. The coefficients on age and the square
of age imply that households with older heads normally take more trips on forest
collection except the oldest household. Household’s accumulated knowledge about
the local forest make it easier for them to take more trips and collect huge amount of
forest products. In fact, younger generation are more comfortable with commercial
substitutes of the traditional forest product. Almost all the household members in the
study area collect CPRs. Hence the larger the family size ( FAMSIZE ) the more is the
forest trip for the collection of CPR products. The result is significant in Purulia
district, but insignificant in Bankura district. Education ( AVGSCH ) i.e. the average
*Significant at 1 percent level, ** Significant at 5 percent level, *** Significant at 10 percent levelSource: Estimated by Stata 8 Computer Software using Field Survey Data of 2011
Forest Collection as a Function of Agricultural Risk(Purulia District)
POISSON REGRESSION NEGATIVE BINOMIAL ZERO INFLATED NEGATIVE BINOMIAL
Agricultural Risk and Common Property Resources
118
years of schooling of the household has a negative impact on forest collection trips in
both the districts which indicated that households who are better educated get better
job opportunities and therefore are less interested in collecting CPR during
agricultural crisis. The result is significant only in Bankura district.
We have predicted that both wage income and the number of livestock have a
negative impact on forest collection trip to extract NTFPs. In line with our
expectation, wage income (WAGE ) is negatively related with forest collection labour.
The result is statistically significant in Bankura district, but insignificant in Purulia
district. In fact households who have a sufficient wage income are less interested in
forest collection trip. Thus creation of job opportunities in non-farm sectors is
expected to have a significant role in CPR extractions. However, the coefficient of
livestock ( LIVESTOCK ) is observed to be positive, but insignificant. The positive
relation indicates that the household with larger size of livestock take more trips to the
forest in order to gather fodder to feed their farm animals. We have further observed
that forest distance ( FORESTDIST ) i.e. the distance between the residence and the
common forest area have a negative relationship with major forest collection trips.
From our study area, we infer that household who live nearer to the common forest
area extract more CPR and hence generate more income from it and thus help to
mitigate agricultural crisis. Household who live farther away from the forest area are
unable to smooth their income and consumption by collecting CPR products during
agricultural shock. However, the result is significant only in Purulia district.
The key findings of our regression results indicate that the coefficients on agricultural
risk parameters ( AGRIRISK ) and shock parameter ( AGRSHTFALL ) are positive and
significant in both Bankura and Purulia district, which suggest that household with
greater agricultural shortfall and risk are likely to take more forest collection trips.
This result supports our hypothesis that CPR product is used by rural households as a
safety net during the time of agricultural crisis. Thus CPRs help to mitigate
agricultural risk by smoothening the income and consumption of the rural poor.
Agricultural Risk and Common Property Resources
119
5.4 Conclusion
In this study we investigated the impact of agricultural risk on the collection of
common forest products based on our surveyed villages of Bankura and Purulia. Most
of the households in the surveyed area are very poor. Agriculture is their main
occupation and therefore they depend on nature for any agricultural activities. There
are several agricultural risks associated such as adverse weather, seasonal flooding,
unpredictable soil quality, crop diseases, price shocks, etc. The rural poor have limited
credit and insurance facility and therefore they extract forest products not only to
reduce their agricultural risk but also help to smooth their income. As per the
surveyed data, the percentage of CPR collection with respect to agricultural
production is very high in the year 2010 due to lower agricultural production as
compared to the previous years 2008 and 2009.
Since agricultural practice in the study area is backward in nature and subjected to
weather risk in the form of agricultural shock in times of production shortfall, the
farmers fall back upon CPRs for their survival and also addresses significantly their
agricultural risk. As established from our field data in the year 2010, the agricultural
production variability resulted in agricultural shortfall of Rs 209032 in Bankura and
Rs 164391 in Purulia as compared to the normal year (2008). Interestingly, it is
observed that during this period the extraction of CPR is also high compared to the
normal year. To capture the impact of agricultural risk on CPR collection, we have
considered the Count Data model using STATA computer software package. The key
findings of our regression results indicate that the coefficients of agricultural risk
parameters ( AGRIRISK ) and shock parameters ( AGRSHTFALL ) are positive and
significant in both Bankura and Purulia districts, which suggest that household with
greater agricultural shortfall and risk are likely to take more forest collection trips, i.e.
the result goes with the hypothesis..
Hence we can conclude that CPRs supplement the rural livelihood and act as safety
net for the poor seasonally or during the agricultural crisis.
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120
CHAPTER 6
COMMON FOREST AND PARTICIPATORY MANAGEMENT
6.1 Introduction
A majority of the rural poor in India are largely dependent on common property
resources such as forest resources. Forests contribute extensively to the social and
economic well-being of the rural poor. One fifth of the land area of India is covered
by forest. As per World Bank Report (2006), an estimated 275 million people in rural
areas of India depend largely on forests. According to the report, about half of India’s
89 million tribal people, the most disadvantaged section of the Indian society, live in
forest fringe areas, and they tend to have close cultural and economic links with the
forest. Forest products, including the non-timber forest products (NTFPs) like food,
fruits, flowers, medicines etc., provide the means of subsistence for the rural poor.
Forest dwellers, which also include a high proportion of tribal, are among the poorest
and most vulnerable groups in society.
The incentive involved in common property resource management was first
established by Gordon (1954) and later by Hardin (1968). Hardin formulated that over
exploitation of the common property resources led to depletion of shared limited
resources as several individuals acted independently in their own self-interest. The
concept of decentralized collective management of the common property resources
was postulated by Berkes (1989) and Ostrom (1990). Ostrom (1990) was of the view
that the CPR management would be successful if there were defined boundaries, an
efficient and effective conflict-resolution and monitoring mechanism. Gibbs and
Bromley (1989) have advocated that institutions, through rights and rules, provide
incentives for the group members to take certain actions to achieve a desired outcome.
Common property rights and Hardin’s theory of ‘The Tragedy of the Commons’ has
been discussed in Appendix-V.
Several empirical researches dealing with the dependence of common property
resources of the rural poor were conducted in different regions in India. Noteworthy,
Common Forest and Participatory Management
121
amongst them are the Jodha (1986), Iyengar (1997), Beck and Ghosh (2000), whose
theories highlighted the danger of depletion of the common property resources due to
pressure from privatization. The importance of participatory management in resolving
the crisis of CPRs in India was postulated by Chopra et al. (1989). On the study of
historical perspective of Joint Forest Management, Sarker and Das (2006) observed
that resistance movement of the forest communities in Midnapore in West Bengal was
the key to the success of the Joint Forest Management programme. The authors were
also of the view that the immediate survival needs, generating mainly subsistence and
income from non-timber forest products (NTFPs) for the forest protection committee
members were the key to the long term sustainability of Joint Forest Management
system. Balloni (2002), in the study of participatory forest management in India
stresses on the need for equity in the participation and representation of the
marginalised classes (poor and women) with equal benefit between the forest
department and the forest communities. The author also suggests the need for
formulation of new and effective silvicultural practices in order to increase the
productivity of Non-Timber Forest Products (NTFPs).
Highlighting the extent of forest cover and the practice of JFM across the states of
India in general and West Bengal in particular, this chapter assess the nature of
participation in forest management and examines the relationship between forest
dependency and participation in forest management in our study area. The chapter
also focuses the relationship between the intensity of management practice and the
degradation of forest resources.
6.2 Data and Methodology
In our study area we have captured demographic and socio-economic characteristics
of rural households, their dependence on forest products and their participation and
involvement in Joint Forest Management. On the basis of this information, we have
analysed how the socio-economic factors and dependency on forest products affect
the level of participation and collective action in Joint Forest Management. We have
used a tabular method to quantify the Forest Management and enforcement of forest
protection scheme by comparing JFM in 9 villages of these two districts. We have
Common Forest and Participatory Management
122
used both statistical and econometric techniques (Censored Tobit Model) to analyse
the determinants of collective action in JFM and to test several hypotheses. Logit
Regression Method was used to analyse the nexus between active forest management
and forest degradation.
In this chapter we have tested the following hypothesis:
H1: There is a strong relationship between forest dependence and active
participation in JFM
H2: Active participation in forest management plays a positive role in
alleviating the environmental degradation.
6.3 Forest Cover and its Management in India: An Interstate
Analysis
6.3.1 Forest Cover in India
The forest resources play an important role in the environmental and ecological
security of India. Indiscriminate and massive (approximately 4.3 million hectare)
diversion of forest land during 1950-1980 for non-forestry purposes, necessitated the
need for conservation and development of the forest resources. This led to the
enactment of the Forest Conservation Act, 1980 whose primary objective was to
provide a higher level of protection to the forests and to regulate diversion of the
forest land in India for non-forestry activities. However there is depletion of the forest
resources in view of increasing population pressure and development activities.
The forest cover as per Forest Survey of India (FSI) denotes all lands which have a
tree canopy density of more than ten percent when projected vertically on the
horizontal ground, with a minimum areal extent of one hectare. The assessment of
forest cover of the entire country is carried out by FSI at an interval of two years by
interpretation of satellite data. The classification scheme adopted in the assessment is
shown in Table 6.1 below:
TABLE 6.1
Very Dense Forest All lands with tree canopy density of 70% and aboveModerately Dense Forest All lands with tree canopy density between 40% and 70% Open Forest All lands with tree canopy density between 10% and 40% Scrub Degraded forest lands with canopy density less than 10%Non-Forest Area not included in any of the aboveSource: ISFR 2011
Forest Density Classification
Common Forest and Participatory Management
123
As per the India State Forest Report 2011 (ISFR 2011), the forest cover assessment is
based on the IRS P6 LISS-III satellite data in digital form corresponding to the period
October 2008 to March 2009 procured from National Remote Sensing Centre (NRSC)
at Hyderabad.
The Forest Cover Map of India depicting the forest cover in all the states and Union
Territories is shown below:
MAP 6.1
Forest Cover Map of India
Source: India Forest Report 2011
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As per the assessment of 2011 (ISFR 2011), the forest cover is shown in Table 6.2
below:
As per the assessment of 2011, the total forest cover is 692,027 km2 which is 21.05
percent of the total geographical area of the country. Based on the density classes, the
area covered by Very Dense Forest is 83,471 km2 (2.54 percent), Moderately Dense
Forest is 320,736 km2 (9.76 percent) and Open forest is 287,820 km2 (8.75 percent).
The forest cover in the different Indian states and Union territories of India is shown
in the Table 6.3 below. As per the FSI assessment of 2011, in terms of area-wise,
Madhya Pradesh has the largest forest cover (77,700 km2) followed by Arunachal
Pradesh (67,410 km2), Chhattisgarh (55,674 km2), Maharashtra (50,646 km2) and
Orissa (48,903 km2). However, in terms of percentage of forest cover to the total
geographical area, the state of Mizoram is the highest with 90.68 percent, followed by
District wise forest cover in West Bengal (Area in Sq. Km)
District Geographical Area (GA)
Assessment 2011 Total forest cover
Percentage of Forest cover to Geographical
Area
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Table 6.6 below shows the degraded notified forest land in West Bengal:
From the Table 6.6 above, we observe that in the surveyed districts of Bankura and
Purulia, the extent of degraded land is very high as compared to other districts of
West Bengal. Encroachment into the forest for agricultural, settlement and other
purpose along with rampant extraction of forest products are responsible for the
degradation.
TABLE 6.6
Bankura 203.64Bardhaman 20.34Birbhum 39.99Kolkata 0Coochbehar 0.15Dakshin Dinajpur 0Darjeeling 21.82Howrah 0Hoogli 0Jalpaiguri 23.32Malda 0Mednipur 110.7Murshidabad 1.57Nadia 0.25North 24 Pargana 0.21Purulia 114.29South 24 Pargana 0.98Uttar Dinajpur 0Grand Total 537.25Source: Wastelands Atlas of India, 2011Published by Ministry of Rural Development , Deptt. of Land ResourcesGovt. of India and NRSA, Deptt. of Space, Govt. of India
Degraded Notified Forest Land in West Bengal (Sq. Km)District Unit (in Sq. Km)
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6.4.2 Joint Forest Management in West Bengal West Bengal is the pioneer state for initiating Joint Forest Management in India. The
data on the number of Forest Protection Committees (FPC) and the number of
members participating in them, for different divisions of West Bengal is shown in
Forest Management and Enforcement of Forest Protection Scheme
District Name of VillageNo. of Households
No. of Households participated
in JFM (2010)
Active JFM participants
(2010)
Incidents of cases of
violation of rules
No. of Overuse caught, warned
and freed
No. of cases imposed penalty
No. of cases refused to pay
penalty
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138
the year 2010, the number of incidents of ‘refused to pay penalty ’ is nil in the villages
of Dulaltora in Bankura district and Jiyathole in Purulia district where forest
degradation is least as compared to other villages (Table 4.12 in Chapter 4). This
implies that forest management is more active in these villages as compared to other
villages in the study area.
The members of Forest Protection Committee in Seolibona village of Bankura district,
Rajesh Mudikora, Dilip Mudikora and Jodeswar Mudikora gave their opinion:
“Involvement of community members need to be organised and the position of
job creation for forest protection need to be made compulsory” (Dated 24th
September, 2011, medium of language was Bengali)
We can therefore infer that with the establishment of Joint Forest Management,
enforcement of forest protection has shown a very positive trend. Further the
households have realised that protection of the common forest is in their own interest
and violating the rules has an adverse effect to them. Forest management thus plays
an instrumental role in forest preservation and conservation. More active the
management greater is the possibility of forest conservation and vice versa.
6.6 Collective Action in Joint Forest Management
Collective action refers to concerted actions of people that share a common interest,
perceive that interest and act to achieve it (World Bank, 1998). It is voluntary or
mandatory depending on the type of action being executed and the institutions within
or through which the action is executed (Gregario, et al., 2004). Our primary focus in
this study is to explore how forest dependency influences household’s active
participation in Joint Forest Management. Local communities, whose income from
agriculture or other sources is uncertain, are very much dependent on forest for their
income and consumption and are thus more interested to conserve forest resources.
Initially, the households who were very much dependent on the forest and whose
income from forest resources was high could not afford the cost of restrained forest
use. These households therefore did not show any interest in the conservation of the
forest resources as they stayed out of the JFM programme and collected forest
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139
products illegally. Later they realised that if they did not conserve the forest resources
then it was not possible to smoothen their income and consumption during the period
of agricultural uncertainty.
The forest scarcity and degradation is the crucial factor to inspire the villagers to join
JFM. The Joint Forest Management becomes effective only if the local rural
community whole heartedly participates in the managing of the common forest
resources. In order to protect the forest from illegal felling of the trees, the forest
patches has to be guarded and monitored day and night by the villagers as per the
guidelines laid down in the JFM. Further, the collection of common forest products
like fuel wood, fodder, fruits, vegetables, etc. is restricted to only certain specific
areas of the forest as per the guidelines of the JFM and thus the local rural villagers
have to travel a longer distance in order to collect the common forest products. The
villagers are to be involved in plantation and regeneration of the high value forest in
order to generate economic gain through the usufructs in the long run. Since a large
part of their participatory labour is to be involved in JFM activity, there is always a
question of trade off with that of agricultural operations. The villagers are involved in
agriculture primarily for their own consumption. The agricultural activity is seasonal.
This is due to the fact that there is lack of proper irrigation facility in the villages and
the villagers have to depend heavily on the rain for their cultivation. Moreover, the
rural households do not have any work during the non-agricultural seasons. Hence the
villagers have to decide about allocating their endowed labours either in agricultural
activities or in forest protection activities that also produces means for their
subsistence. Now, the forest resources that can be managed effectively by the local
rural communities depend on the strength of the collective action i.e. joint action of
the community to conserve forest resources as well as improve rural livelihood.
We have explained the determinants of collective forest management through
econometric analysis to give an understanding of the relationship between forest
dependency and active forest management. Collective action in forest management is
measured by time involvement in the management of forest resources. The 9 villages
in our study area from the two districts of Bankura and Purulia have been considered
separately and their results have been compared. Attempt has been made to capture
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140
the relevant socio-economic variables that influence the strategy of collective action
in forest management in the study area. In this context following Bwalya (2004), we
have specified an econometric model of collective action and discuss the choice and
expected signs of explanatory variables. We estimate the following econometric
model of collective action
12
i
n
M i ij ijj
L a b Y=
= + +∈∑ ………………………………………..….(1)
where 1ia denotes community dummies, ijY is set of explanatory variables including
the index of individual organisational experience, livelihood activities, socio-cultural
heterogeneity, age, gender, household size, wealth, forest condition and ∈ is the error
term. ML is the dependent variable defined as the amount of labour household
contributes to local management and i and j indexes communities and individual
variables respectively. Our intension is to examine the impact of forest dependency on collective action in
JFM. Here the dependent variable is the number of man days per year involves in
JFM activities. Field survey data shows that about 25 percent of the total respondents
in Bankura district and 15 percent in Purulia district allocated zero man days to JFM
activities. Hence we have applied Censored Tobit model as it makes survey data more
convenient to analyse. Since the dependent variable is censored from below, we apply
maximum likelihood estimation to estimate the Censored Tobit model.
Our specified model is
0 1 2 3 4 5iML a b FSIZE b FEMPER b AVRAGE b AVRSCH b PERAGRIN= + + + + +
6 7 8b PERCPRIN b PERCPRCSM b WEALTH+ + + +∈
Here 0a is constant and ( 1,2,...,8)ib i = are the coefficients associated with the
explanatory variables and ∈ is the random disturbance term.
The households devote their time in JFM activities like planning and implementation,
monitoring, silvicultural activities at the cost of other livelihood activities i.e.
agriculture, off farm wage labour, etc. and leisure.
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141
In the following Table 6.11, we present the dependent and explanatory variables and
their description, measurement and expected signs.
TABLE 6.11
Description of Variables in Censored Tobit Model Variables Variable Description Expected Sign
Dependent Variable
Collective Action ( ML )
Number of man days i.e. Labour
contribution in monitoring, planning
& implementation and management of
community forest resource
Independent Variables
1. FSIZE Average number of population of the
household (Size of the family) +
2. AVRAGE Average age of the respondent -/+
3. AVRSCH Average year of schooling of
household +
4. PERAGRIN Percentage of Agricultural income to
Total income -
5. PERCPRIN Percentage of income from common
property resources to Total income +
6. PERCPRCSM Percentage of CPR consumption to
Total consumption +
7. WEALTH Total household assets
WEALTH = 1 for ‘Well to do’
household
WEALTH = 0 for poor household
-
The key independent variables are percentage of Agricultural income to total income
( PERAGRIN ) and CPR income to total income ( PERCPRIN ). It was expected that
households whose agricultural income is steady are less interested in active
participation in JFM. On the other hand household whose percentage of CPR income
to Total income are high i.e. more dependent on forest resource are actively involved
in collective action in Joint Forest Management.
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142
Empirical estimation of model specified in the above equation is described in the
following Tables 6.12 and 6.13:
TABLE 6.12
Determinants of Collective Action (Bankura District) Dependent Variable: LABJFM (Contribution of labour in JFM) Method: ML - Censored Normal (TOBIT) (Quadratic hill climbing) Sample: 1 150 Included observations: 121 Left censoring (value) at zero Covariance matrix computed using second derivatives
Error Distribution SCALE:C(9) 13.76905 1.044966 13.17655 0.0000 Mean dependent var 15.67769 S.D. dependent var 12.84926
S.E. of regression 11.75636 Akaike info criterion 6.971670 Sum squared resid 15617.94 Schwarz criterion 7.179622 Log likelihood -412.7860 Hannan-Quinn criter. 7.056127 Avg. log likelihood -3.411455
Left censored obs 25 Right censored obs 0
Uncensored obs 96 Total obs 121 *Significant at 1 percent level, ** Significant at 5 percent level, *** Significant at 10 percent level
Source: Estimated by EViews7 computer software using field survey data of 2011
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143
TABLE 6.13 Determinants of Collective Action (Purulia District) Dependent Variable: LABJFM (Contribution of labour in JFM) Method: ML - Censored Normal (TOBIT) (Quadratic hill climbing) Sample: 1 150 Included observations: 121 Left censoring (value) at zero Covariance matrix computed using second derivatives
Error Distribution SCALE:C(9) 9.637295 0.656865 14.67165 0.0000 Mean dependent var 18.14876 S.D. dependent var 12.78584
S.E. of regression 9.156199 Akaike info criterion 7.152541 Sum squared resid 9473.466 Schwarz criterion 7.360492 Log likelihood -423.7287 Hannan-Quinn criter. 7.236998 Avg. log likelihood -3.501890
Left censored obs 9 Right censored obs 0 Uncensored obs 112 Total obs 121
*Significant at 1 percent level, ** Significant at 5 percent level, *** Significant at 10 percent level Source: Estimated by EViews 7 computer software using field survey data of 2011
We have observed from the determinants of Collective Action in JFM that most of the
parameter estimates for household variables have expected sign and are statistically
significant. Results show that family size ( FSIZE ) and average age ( AVRAGE ) have
a positive effect on collective action in JFM in the surveyed villages of both Bankura
and Purulia district. Family size ( FSIZE ) is positive and significant suggesting that a
larger family size collects more CPR product and thus increases the scarcity of the
Common Forest and Participatory Management
144
forest resources. So they are bound to actively participate in the JMF in order to
conserve the forest resources. Positive effect of average age of the respondent
( AVRAGE ) implies that aged people, due to their experience, are more interested to
allocate labour in Joint Forest Management. In the cases of AVRAGE , the result is not
significant. In both the districts we have observed that education ( AVRSCH ) has a
negative effect on collective action in JFM. This implies that educated people are
mostly involved in the service sector or off-farm wage labour and hence they get less
time to devote in monitoring or silvicultural activities in the JFM. However, this result
is insignificant in both the districts. Actually in some cases educated household
understand the importance of preservation of forest resources and are thus more likely
to actively participate in the JFM activity and also motivate other villagers to
participate as well.
It is evident from the analysis that collective action in JFM is negatively related to
percentage of agricultural income to total income of the household ( PERAGRIN ) in
both the district of Purulia and Bankura. In Bankura district, it is significant at 1
percent level of significance and in Purulia district it is highly significant. This
implies that household who has steady income from agriculture does not bother much
about forest resources and are therefore less interested in active participation in JFM.
On the other hand, household who depend on CPR products because of uncertain
agricultural income are more interested in conserving forest resources and give more
labour time in different activities of JFM. In line with our expectation, we observe a
positive relation between percentage of CPR income to total income ( PERCPRIN )
and collective action in JFM in both the districts and the result is significant with
Bankura at 5 percent level and Purulia at 1 percent level. This indicates that the
households participate in the JFM, primarily to gain access to the forest outputs from
the forest resources, so as to overcome the uncertainty and insecurity in their
livelihood.
We have hypothesised a positive relation between percentage of CPR consumption to
total consumption ( PERCPRCSM ) and active participation in JFM. In fact the
households who depend more on CPR for their consumption purposes are very much
concerned about forest resource conservation and hence actively participate in JFM.
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145
However, the coefficient is positive in this case in both the districts although the result
is insignificant. The coefficient of wealth (WEALTH ) have the expected negative
signs on collective action management in the two surveyed districts and significant at
1 percent level in Purulia and 10 percent in Bankura. This signifies that wealth
reduces the incentive among the households to actively participate in the JFM. In few
cases ‘well to do’ households participate in the JFM only for social capital i.e.
personal interest, self-esteem, respect, etc. or for their compulsion of strong ties with
the Government officials. The above result indicates a strong relationship between
forest dependence and active participation in JFM.
6.7 Collective Action and Forest Conservation
Forest management has its inherent impact on the conservation of forests. More active
the management practice is, greater is the probability of efficient use of forest
resources. Forest management lowers the degree of over exploitation and hence the
degradation of forest resources. We now examine the role of forest management to
reduce forest degradation by using logit regression model. A range of socioeconomic
and environmental variable has been considered.
The logit-regression model has been fitted as follows:
1 2 3 4log( )1
i
i
P a b AVRAGE b AVRSCH b FSIZE b OWNLANDP
= + + + +−
5 6 7b LIVESTOCK b POVR b FMACT+ + +
Here the dependent variable is forest degradation ( FDGR ) which is a dummy
variable equal to ‘1’ if there is ‘more degradation’ and equal to ‘0’ if there is ‘less
degradation’.
Forest Degradation is measured on the basis of the data collected in the village survey
from three different variables - Extent of forest damage visually seen (FD), Condition
of the forest informed by the respondents as compared to that of earlier times (FC)
and Forest use penetration i.e. the depth into the forest from the village boundary
where use pressure was evident (FP). All these three variables (FD, FC, FP) are coded
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146
(using four point scale) so that increasing values shows more forest degradation
(Detail in Chapter 4 in Section 4.6.1).
In the following Table 6.14 we have explained the explanatory variables, their
descriptions and expected signs:
TABLE 6.14
Description and Hypothesis in Logit Regression Model Variables Variable Description Expected
Sign
Dependent Variable
1. FDGR
Forest Degradation
FDGR =1, if there is more degradation
FDGR =0, if there is less degradation
Explanatory Variables
1. FSIZE Average number of population of the
household (Size of the family) +
2. AVRAGE Average age of the respondent _
3. AVRSCH Average year of schooling of household +
4. OWNLAND Total land owned by the household _
5. LIVESTOCK Total number of livestock condensed
into animal units +
6. POVR Poverty of the household
POVR =1; if household belongs to BPL
POVR =0; if household belongs to APL
+
7. FMACT Active Forest Management
FMACT =1 in case of active forest
management
FMACT =0 in case of inactive forest
management
_
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147
The logit regression model has been tested using the household level data through
field survey of Bankura and Purulia districts. The result is given in Table 6.15 below:
TABLE 6.15
Determinants of Forest Degradation (Bankura District) Dependent Variable: FRDGR Method: ML - Binary Logit (Quadratic hill climbing) Sample: 1 150 ; Included observations: 150 Covariance matrix computed using second derivatives
McFadden R-squared 0.897336 Mean dependent var 0.673333 S.D. dependent var 0.470565 S.E. of regression 0.139214 Akaike info criterion 0.236391 Sum squared resid 2.752054 Schwarz criterion 0.396958 Log likelihood -9.729344 Hannan-Quinn criter. 0.301625 Deviance 19.45869 Restr. deviance 189.5379 Restr. log likelihood -94.76893 LR statistic 170.0792 Avg. log likelihood -0.064862 Prob(LR statistic) 0.000000
Obs with Dep=0 49 Total obs 150 Obs with Dep=1 101
*Significant at 1 percent level, ** Significant at 5 percent level, *** Significant at 10 percent level Source: Estimated by EViews 7 computer software using field survey data of 2011
From the analysis it can be observed that forest degradation ( FDGR ) is positively
related to average age ( AVRAGE ), family size ( FSIZE ), number of livestock
( LIVESTOCK ) and poverty ( POVR ) whereas negatively related to education
( AVRSCH ), total land owned ( OWNLAND ) and Forest Management activity
( FMACT )in both the districts. In fact every family member of the household engages
themselves in collecting forest products and thus degrades the environment to a large
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149
extent. Hence in the case of households with large family size ( FSIZE ), the
probability of the incidence of forest degradation is high. However, the result is
significant only in Purulia district. The positive relation between ( AVRAGE ) and
( FDGR ) suggest that experienced elder members degrade the forest resources
critically by collecting more CPR products from forest. However, the result is
insignificant in both the districts. Again, households with large number of livestock
( LIVESTOCK ) damage the environment badly by accumulating fodder to feed
animals. Hence larger the number of livestock more is the probability of incidence of
forest degradation. The coefficient of poverty ( POVR ) is positive and significant in
both the districts which suggest a strong positive relationship between poverty and
forest degradation.
As expected education ( AVRSCH ) is negatively related to forest degradation.
Educated people have many alternative income opportunities and hence less interested
in collecting forest products. Thus educated people help to reduce the incidence of
forest degradation. However, the result is significant in Bankura district only. In the
case of ( OWNLAND ), the negative relationship indicates that the household who own
large agricultural land get less time to collect CPRs from forest and hence causes less
forest damage. Here the impact is insignificant in both the districts.
The most important finding of this study is the role of active Joint Forest Management
(JFM) in reducing the forest degradation. In line with our hypothesis, Forest
Management activity ( FMACT ) has the expected negative sign i.e. active forest
management is associated with a smaller extent of forest degradation.
This result demonstrates that improved management has a positive role to check
environmental degradation. Again it is observed that the association between Forest
Management activity ( FMACT ) and forest degradation ( FDGR ) is negative and
significant in both the districts. It is observed that most of the rural poor depend on
common property resources for their livelihood. Hence the CPRs should be properly
managed so that the rural poor can get maximum benefit but not at the cost of nature.
Common Forest and Participatory Management
150
6.8 Conclusion
The empirical evidence based on the survey of 6 villages in Bankura and 3 villages in
Purulia suggest that the rural households are highly dependent on Common Property
Resources for their subsistence and are therefore very much concerned about the
regular depletion of the forest resources. In order to ensure the availability of the
forest resources in the long run, the rural households have actively participated in the
Joint forest Management activity in the study area. Empirical evidence suggests that
75.33 percent of the surveyed household in Bankura district and 85.33 percent of the
surveyed household in Purulia district participate in JFM. We have explained the
determinants of collective forest management through censored Tobit model to give
an understanding of the relationship between forest dependency and active forest
management. It is evident from the analysis that income from agriculture plays an
important role in the participation of JFM. In those households where the percentage
of the agricultural income to the total income is very low, the participation in JFM is
very active. We further observed that collective action in JFM is positively related to
percentage of CPR income to total income and the impact is significant in both the
districts. Therefore the result is consistent with our hypothesis. In fact, the households
participate in the JFM activity to gain access to the forest resources and thus mitigate
any uncertainty and insecurity in their income. We had hypothesised that active
participation in forest management plays a positive role in alleviating environmental
degradation. The logit regression result confirms that Joint Forest Management has a
critical role in reducing forest degradation. Improved forest management plays a
positive role in sustainable forest ecosystem.
Women’s Participation in CPR Management
151
CHAPTER 7
WOMEN’S PARTICIPATION IN CPR MANAGEMENT
7.1 Introduction
Forests are a vital livelihood support system for the rural poor. Rural women are
highly dependent on forest resources as it plays an important role in the viability and
subsistence of the households. Every day early morning, groups of women set out
towards the forest to collect firewood and several non-timber forest products like
fruits, medicines. The extreme heat, lack of water and difficult terrain make this work
of CPR collection extremely difficult. Degradation of forest leads to forest produce
being available further away from the place of dwelling, thereby increasing the
drudgery of the women. However, the rural women continue to do so since it provides
them with firewood, food and income through sale. A study in Uttar Pradesh, India
showed that rural women obtained 33 to 45 percent of their income from forests as
compared with only 13 percent in the case of men (IUCN-factsheet-gender and
forestry, 2010). Empirical evidence from southern districts of Bihar, suggest that rural
women collect mahua flowers (Madhuca indica), kendu leaves (Diospyros
melanoxylon) used in making indigenous cigarettes, mushrooms and mahua seeds,
tamarind (Tamarindus indica) (Rao, 1996). In West Bengal, tribal women gather sal
(Shorea robusta) leaves for six months of the years (Poffenberger, 1993). Based on
the empirical study of tribal women in Jharkhand, Kelkar and Nathan (1991), assert
that "within the family the income from sale of forest produce tends to be counted as
the income of the individual who gathers and sells the produce. Increasing the income
from forestry will thus also help strengthen the position of women within the family."
Rout et al. (2010) opine that collection of Non Timber Forest Product provides
employment for the tribal women and they have larger potential for generating
employment in future.
However, lack of rights and responsibilities to control and use the common property
resources make them highly vulnerable. Rural women consider the forest as their
source of livelihood and hence are very much concerned about the long term
sustainable governance of the forest resources. Indiscriminate collection of forest
Women’s Participation in CPR Management
152
resources leads to degradation of forests and the rural women have to travel longer
distance from their home to collect them. Women consider that the environmental
degradation can lead to their reduced supplementary income and community forest
management can help to reduce it. Thus any environmental policy should not only
take into account the economic impact of the women and but also leverage the role of
women in the protection and management of the forest resources (Agarwal, et al.,
2006). Understanding of women’s relationship with the environment needs to
recognise the "relationships of power and authority, negotiation and bargaining and
the wider social relations in which 'decisions' about land and trees are embedded"
(Leach, 1990). Jamisolamin (2012) believes that women can play a key role in
ensuring environmental protection and conservation provided they are allowed to take
decision in the management process. Thus women can play a critical role in the Joint
Forest Management for long term sustainability of the scarce natural resources.
For a sustainable forest management, women should not only have access to the forest
and accrue the benefits from it but also the right and authority to take decisions (Giri,
2012). Securing tenure and access rights to forest resources is a critical step towards
achieving environmental and social justice (Buchy, 2012). The author opines that
there is widespread discrimination against rural women as they face exclusion on
gender and ethnicity grounds and are denied some of the basic rights due to the
unclear, unsecured and unequal tenure rights. Women normally encounter negative
perception not only from the village men but also from the male officials of the forest
department. In West Bengal, for instance, there were many complaints from the rural
women that the male officials discouraged them from coming to the forest office and
also rebuked them if they came in the evening (Narain, 1994). Further, rural women
were also excluded from several other activities like water users associations, village
councils, etc. (Agarwal, 2001).
Active participation of women in forest management involving local decision-making
can not only have a positive impact on the resource related outcomes but also
significantly increase the effectiveness of the institution involved in forest governance
and protection through greater control of illicit harvesting of forest products and
regeneration in the forest (Agarwal, et al., 2006). Women can also play a greater role
Women’s Participation in CPR Management
153
in co-management of forests by increasing their collective bargaining power (Yadama
et al., 1997). Rural women play an important role in the development and peace
process by mediating during conflict situations. Women’s participation in forest
management through Mahila Mandals has led to active monitoring, protecting and
managing the common forest area (Bingeman, 2003). Women Self-Help Groups
(SGHs) play an important role in maintaining and protecting the common forest
which not only helps to generate income but also to their empowerment (Murugesan
& Namasivayam, 2012).
Participation of the women in forest management differ from one region and culture
to another, by one caste and tribe to another, by class position and by position in the
household and hence the forest department and NGOs should bring forth sensitive and
local specific strategies for them (Patricia Jeffery, et al., 1998). Women tend to avoid
participation in the forest management primarily due to lack of security, lack of
confidence, social and cultural restrictions (Dasgupta, 2006). Low participation of
women in Joint Forest Management programmes can be attributed to social and
cultural constrains (Godbole, 2002). In a study of 20 Community Forest Groups, Sarin
(1998) found that 60 percent had no women, and only 8 percent of the 180 Executive
Committee members were women. According to Dasgupta (2006), women
participation in JFM can be enhanced by imparting a simple and low-cost technology
based training programme.
In Bankura district of West Bengal, the District Forest Officer had issued a circular
stipulating that there should be a minimum of 30 percent women in the general body,
which had resulted in raising the female membership in several villages (Viegas &
Menon, 1993). Das & Sarker (2008) opine that communal solidarity, mutual trust and
coordinated actions exits in JFM villages, thereby increasing the social capital.
According to the authors, those Forest Protection Committees (FPCs) where social
cohesion and community solidarity is weak, effective leadership and local support can
bring about in improving the social capital.
Despite the fact that women are the major users of common property resources, their
involvement in Joint Forest Management is generally marginal in India. To regulate
Women’s Participation in CPR Management
154
illicit grazing and removal of forest products, direct involvement of women in JFM is
essential.
Under this backdrop, based on our primary data, this chapter attempts to explore the
role of women participation in sustainability of the common property resources in the
study area. In specific terms the objective of the study are as follows:
i) To explore the role of women in CPR collection
ii) To examine the performance of women in JFM committees
iii) To investigate empirically the effect of women’s active participation in
JFM on forest resource preservation and conservation.
In order to study the impact of women’s participation on sustainability of the forest
resources, we have planned to estimate a binary probit model.
In this chapter we have tested the following hypothesis:
H1: Women’s participation in forest management improves the
sustainability of the forest resources
7.2 Role of Women in CPR collection in the study area
Forests contribute critically to the survival of the rural poor and the women who own
little private land. The common forest resources in the study areas of Bankura and
Purulia provide the rural poor with food, medicine, fodder, firewood, etc. The women
collect firewood for domestic as well as for commercial purposes. They collect certain
tree barks and medicinal herbs which are used as industrial raw material as well as for
medicinal purposes. Apart from collection of firewood, the rural women are also
involved in the collection of fodder from the common forest area. Sal and Kendu
leaves used as vegetables are also collected by the rural women in the study areas on a
regular basis almost throughout the year. The Sal leaves are stitched by hand to make
Sal plates, which are then sold in the local market. The rural women also sell their
collected products like firewood, Sal stick (used as tooth brush) and wild vegetables at
the local market. However, due to poor transportation system and lack of organised
Women’s Participation in CPR Management
155
market in the study areas, they are forced to sell the forest products to mobile agents
or middlemen, who visit their village quite often, even if they receive a lower price.
Generally the men collect forest products only when they are not engaged in
agricultural or other off-farm activities. Thus CPR collection for men is a secondary
job. However, collection of forest products for rural women living in the forest
fringes is always a primary occupation. Thus forest plays a crucial role in their daily
lives.
The women villagers of Panjhoria village of Saltora block in Bankura district, Bani
Mudikora and Durga Hembram, share their views with us:
“We collect fuel wood, fodder, sal and kendu leaves, mahua fruits and flowers
from our nearby forest for domestic as well as commercial purposes without
harming the whole plant. Except during monsoon, we gather forest products
all the year round. When we need money we have to sell the forest products
immediately. Most of the time we do not get the correct price.” (Dated 4th
October, 2011, medium of language was Bengali)
Forest women collect NTFPs as much as possible for commercial purposes. However,
they also gather the same in a restricted way for their own consumption. Although
women are the major collector of NTFPs and have good knowledge about the forest,
they cannot actively participate in JFM which is in general male dominated in our
surveyed area. During the fieldwork a number of women member highlighted the fact
that their opinion was not considered in JFM meeting. When the Forest Department
officers arranges meeting, it is mainly attended by the male villagers. The Beat
officers also meet with male villagers only.
Women members of JFM in village Ambari of Purulia district, Mongala Kora and
Sabita Hansda, have commented in the group discussion:
“We gather fallen seeds, leaves, grass, fruits and flowers so that plants are not
damaged. We collect only those NTFPs which are permitted by the FPC. We
obey them because if Forest Department take any action against us we will
suffer a lot. We are very poor and solely dependent on forest products. Hence
we have to protect the local forest at any cost for our own endurance.” (Dated
28th November, 2011, medium of language was Santali/ Bengali)
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156
PHOTO 8 PHOTO 9
Interaction with rural women in Jiyathole Women collecting cow dung in Baldanga
In our study villages in the district of Bankura and Purulia in West Bengal, we have
analysed the average income and average monthly contribution of CPR to household
income for male and female headed households and is shown in Table 7.1 below. As
per the table, the percentage of Female headed households in the villages of Dulaltora
(27.78) in Bankura district and Jiyathole (29.63) and Ambari (25) in Purulia district is
relatively high. We have observed from Table 4.12 in Chapter 4, the extent of
depletion of common property resources during 1990-2010 is less in the above
mentioned 3 villages where percentage of female headed household is high as
compared to the rest of the villages in the study area. Hence, we can infer that female
headed households are more concerned about forest conservation as compared to the
male headed households.
The average income of male headed households and the female headed household
excluding and including CPR income along with their average monthly contribution of
CPR as depicted in Table 7.1 shows a particular trend. In most cases in the female
headed households, the average contribution of CPR to the household income is high as
compared to male headed household.
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157
In the village of Panjhoria in Bankura district, the average monthly contribution of CPR
in the household income for a female household is as high as 40 percent as compared to
22 percent for a male headed household. Similarly in the village of Jiyathole in Purulia
district, the average monthly contribution of CPR in the household income for a female
and a male headed household is 55 percent and 42 percent respectively. The result from
our surveyed villages in Bankura and Purulia district reveal that the average monthly
contribution of CPR in the household income for a female and a male headed
household is 44 percent and 26 percent respectively. This data implies that the female
headed households depend more on CPR collections as compared to the male headed
households to supplement their household income.
In Table 7.2 below, we depict the time spent by the household members in CPR
collections and the employment days generated thereby.
Sustainability is measured on the basis of the data collected in the village survey from
three different variables:
i) Regulate illicit grazing
ii) Control the extensive removal of forest products
iii) Regenerate the allotted forest
All these three variables is a dichotomous variable where we coded ‘Yes’ response as
‘1’ and a ‘No’ response as ‘0’. To construct the sustainability of forest index, we have
created a dummy variable that takes the value of ‘1’ if all the three variables related to
forest sustainability have value’1’ and otherwise have value ‘0’. Thus if the responses
to all the three variables were ‘Yes’, the value of sustainability of forest index would
be ‘1’. If one of the variables were coded as ‘0’, the value would be ‘0’.
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165
The Explanatory variables are defined in Table 7.4 below:
TABLE 7.4
Description of Variables in Binary Probit Model Explanatory
variables
Description Expected
Sign
SEXR Sex Ratio i.e. ratio of the female to male in the
household +
FHEAD
Female Headed Household
FHEAD =1, if the household head is female
FHEAD =0, if the household head is male
+
FLIT Female Literacy rate i.e. number of years of schooling
of the female members of the household +
DEPR
Dependency Ratio which indicates the employment
condition of the household i.e. proportion of number of
non-working members to the total number of family
members in the household
_
PCATTLE
Per Capita cattle unit which is the ratio of cattle unit to
the family size i.e. 1 cattle unit= 1 bullock /cow or 4
goats or 4 pigs or 100 chicken /hens/ducks
_
WACTPM
Number of women member actively participating in the
Joint Forest Management. Active participation of
women implies they participate in meetings of the
forest protection committees; they are involved in
planning, decision making and implementation of the
forest conservation programme.
+
DISM Distance to the closest market (in km); i.e. measure of
market pressures by variation in distance from markets +
PUNSHM
Punishment against violation of CPR rules
PUNSHM =1, if the JFM committee impose fines on
members who break CPR rules
PUNSHM =0, if no fine is imposed on members who
violates CPR rules
+
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166
Here 0α is constant and iα ( i = 1, 2, …,8) are the coefficients associated with the
explanatory variables and ∈ is the random disturbance term.
7.4.2 Results and Discussions We have tested this regression equation using household level data collected through
field survey in Bankura and Purulia districts in West Bengal. We have estimated the
regression equation by binary probit model using EViews 7 economic software. The
results of our analysis are presented in Table 7.5 and Table 7.6.
TABLE 7.5
Determinants of Forest Sustainability (Bankura District) Dependent Variable: SFOREST Method: ML - Binary Probit (Quadratic hill climbing) Sample: 1 150; Included observations: 150 Covariance matrix computed using second derivatives
McFadden R-squared 0.922108 Mean dependent var 0.426667
S.D. dependent var 0.496250 S.E. of regression 0.133702 Akaike info criterion 0.226300 Sum squared resid 2.520560 Schwarz criterion 0.406938 Log likelihood -7.972472 Hannan-Quinn criter. 0.299687 Deviance 15.94494 Restr. deviance 204.7058 Restr. log likelihood -102.3529 LR statistic 188.7609 Avg. log likelihood -0.053150 Prob(LR statistic) 0.000000
Obs with Dep=0 86 Total obs 150
Obs with Dep=1 64 *Significant at 1 percent level, ** Significant at 5 percent level, *** Significant at 10 percent level
Source: Estimated by EViews 7 computer software using field survey data of 2011
Women’s Participation in CPR Management
167
TABLE 7.6
Determinants of Forest Sustainability (Purulia District)
*Significant at 1 percent level, ** Significant at 5 percent level, *** Significant at 10 percent level Source: Estimated by EViews 7 computer software using field survey data of 2011
From the above tables 7.5 & 7.6, we observe that in most of the cases, the results are
consistent. However, in some cases we have got contradictory results. As expected,
Sex Ratio ( )SEXR has been found to have a positive influence on Sustainability of
Dependent Variable: SFOREST Method: ML - Binary Probit (Quadratic hill climbing) Sample: 1 150 Included observations: 150 Covariance matrix computed using second derivatives
squared 0.792005 Mean dependent var 0.486667 S.D. dependent var 0.501497 S.E. of regression 0.202104 Akaike info criterion 0.408195 Sum squared resid 5.759286 Schwarz criterion 0.588833 Log likelihood -21.61462 Hannan-Quinn criter. 0.481582 Deviance 43.22924 Restr. deviance 207.8375 Restr. log likelihood -103.9187 LR statistic 164.6082 Avg. log likelihood -0.144097 riProb(LR statistic) 0.000000
Obs with Dep=0 77 Total obs 150
Obs with Dep=1 73
Women’s Participation in CPR Management
168
forest resources in Bankura and Purulia district. As the number of female members in
the family increases relative to the male members, the Sex Ratio increases. Since the
women are mainly involved in collection of forest products, the forest degradation
affects them badly and they are more conscious about forest conservation. Therefore
we observe that there is a positive relation between Sex Ratio and sustainability of
forest resources. Our result is significant in Bankura district but insignificant in
Purulia district.
In the case of female headed households ( FHEAD ), we noticed positive relation with
sustainability of forest resources as female members are more interested to improve
forest quality. In line with our expectation, we have observed positive and significant
result in Purulia district. However, the impact is negative and insignificant in Bankura
district.
The regression results shows a positive relationship between female literacy ( FLIT )
and sustainability of forest resources. As expected we observe that the coefficient of
female literacy has positive and significant impact on sustainability of forest resources
in both the districts. In fact educated female members understand the importance of
forest conservation. Hence with increase in female literacy the probability of forest
sustainability also increases.
In line with our expectation, Dependency Ratio ( DEPR ) is found to be negative in
case of forest resource conservation. As dependent member increases in the family,
burden on the forest products increases which ultimately decreases the probability of
forest resource sustainability. The result is significant in Purulia district and
insignificant in Bankura district.
From the regression analysis, we observe that there is a positive relationship between
per capita cattle unit ( PCATTLE ) and sustainability of forest resources. In fact,
household with higher per capita cattle unit collect more fodder to feed animals and
require higher quantity of fuel wood to prepare concentrated food for the animals.
Hence there is a negative relation between the two. However, in contrary to our
expectation, we have observed positive but insignificant results in both the districts. It
Women’s Participation in CPR Management
169
may be possible that household having large number of cattle become more conscious
about forest conservation for the survival of their livestock.
In the case of distance to the closest market ( )DISM we assume that when markets
are nearer, the motivation for extraction of forest resources is much greater. Contrary
to our expectation, DISM has a negative impact on sustainability of forest resources
in both the districts suggesting that as distance to markets decreases; control of forest
degradation is more prominent. This can be explained by the fact that as distance to
market decreases, the probability of inspection of Government officials to monitor the
forest protection committee increases.
As expected, punishment against CPR rule breakers ( PUNSHM ) has positive and
significant impact on forest resource sustainability in both the districts. In fact, if
forest protection committee imposes fine on rule breakers, illegal extraction of CPR
products is controlled.
The most important finding of this study is impact of active participation of women
member in JFM (WACTPM ) on sustainability of forest resources and the result has
been found to be positive and significant in both the districts. Greater and effective
involvement of women member in planning, decision making and implementation
activities improve the forest quality. Since the women are involved in collection of
NTFPs like firewood and fodder which is their means of subsistence and also a source
of income, they are more likely to prevent illegal harvesting of the forest products. It
is also observed that men who are engaged in patrolling the common forest find it
difficult to apprehend women who involve in indiscriminate use of the forest
resources. Thus the patrol team should consist of both men and women.
The results advocate that gender equity in participation in JFM enhances sustainable
governance of the forest resources.
Women’s Participation in CPR Management
170
7.5 Conclusion
Our study has investigated the impact of women’s active participation in JFM on
sustainability of forest resources in our surveyed villages of Bankura and Purulia
districts in West Bengal. The result of the survey indicate that female headed
household depend more on CPR collections as compared to the male headed
households to supplement their household income. Again, female members generate
higher employment man days through CPR collection in comparisons with male
members of the household. Hence we can conclude that women play a significant
role in CPR collection. Despite the fact that the women are the major users of the
common property resources, their involvement in Joint Forest Management is
negligible. We have estimated the impact of women’s active participation in JFM on
sustainability of forest resources through binary probit model using EViews 7
economic software. The most important finding of this study is the positive and
significant impact of active participation of women member in JFM on sustainability
of forest resources in both the districts, which is consistent with our hypothesis.
Women greatly value the forest conservation since forest degradation leads to
depletion of forest resources which ultimately increases the distance to be covered in
order to collect forest products. Hence, women are more concerned about the
improvement of regeneration of forest resources. Therefore, women should involve
themselves in planning, decision making and implementation of forest conservation
programme. Further women should participate in patrolling the forest with male
guards and thus prevent illegal extraction of forest resources in a better way.
Therefore we conclude that gender equity in JFM participation improves the
sustainability of forest resources.
Summary, Conclusion and Policy Suggestions
171
CHAPTER 8
SUMMARY, CONCLUSION AND POLICY SUGGESTIONS 8.1 Summary In the foregoing chapters, the thesis dealt with Common Property Resources (CPRs)
collection and its implications to rural Poverty and Environmental Sustainability.
Attempt has also been made to analyse the association between Agricultural risks and
CPR Collection. The issues of Property Rights, Gender and Resource management
have also been covered in the study with firm field data of Bankura and Purulia
districts of West Bengal. The thesis is made up of eight integrated chapters. However,
the core of the thesis which dealt with major research questions of the study consists
of four chapters (Chapter 4, 5, 6 & 7). The thesis starts with a brief introduction which
deals with the identification of research problem. Chapter 2 highlights an exhaustive
review of the existing literature on the research problem. The objectives, research
questions, sample design and methodology including the conceptual frameworks of
the study have been outlined in Chapter 3. The four main chapters that we have dealt
with in the thesis are Common Forest Resources: Contribution and Crisis (Chapter 4),
Agricultural Risk and Common Property Resources (Chapter 5), Common Forest and
Participatory Management (Chapter 6) and Women’s Participation in CPR
management (Chapter 7). A brief description of conceptual framework has been given
at the beginning of four main chapters along with objectives. We have tested these
objectives on the basis of empirical data and intensive observations from these
villages. The Summary, Conclusion and Policy suggestions of the study appear in
Chapter 8 followed by Bibliography and Appendices.
In Chapter 4 we have explained the nature of dependency of the rural poor on
CPRs and its impact on income, employment and rural poverty. Environmental
impact of poverty has also been explained by analysing the relationship between rural
poverty and environmental degradation. This chapter broadly analyses the
contribution and crisis of CPRs in the study area.
Summary, Conclusion and Policy Suggestions
172
The major findings can be summarised below:
i) Common Property Resources and Rural Livelihood Common Property Resources (CPRs) play a vital role in the rural livelihood of
our study villages. Rural poor are very much dependent on Common Property
Resources for their subsistence. They collected CPRs from the common forest
area, rivers, ponds and common grazing lands. A large variety of CPRs are
gathered by the poor and not so poor households for domestic and commercial
purposes. The rural households collect various CPRs like fuel wood, dry leaves,
shrubs, dung cakes, etc. for cooking and heating purposes. Common forest
supply raw materials like bamboo, canes, logs from trees, dry leaves for
constructing their houses. Their cattle graze in the common forests and the
shrubs and grasses are utilised as fodder for the animals. Fruits, vegetables,
fishes, root, meat from hunted birds and animals are procured from CPRs and
are used for consumption as well as for sale. Few plants and roots are used as
medicines to cure their ailments. Therefore, Common Property Resources are
means of subsistence for all the households in the surveyed villages.
ii) CPRs as Life Supporting Resource The field survey data reveals that around 19.04 percent of the household income
in Bankura district and around 18.11 percent in Purulia district is coming from
the CPR based activities. For BPL households, 27.28 percent in Bankura district
and 27.92 percent in Purulia district of the total household income comes from
CPR based activities whereas in case of APL it is 2.31 percent and 7.71 percent
respectively. This implies that BPL households enjoy a greater proportion of
income from CPRs both in relative as well as absolute terms. Further, the
contribution of CPRs to the total monthly consumption expenditure is around
22.29 percent and 20.17 percent in Bankura and Purulia district respectively.
Thus CPRs act as a life supporting resource in our surveyed villages.
Summary, Conclusion and Policy Suggestions
173
iii) CPR and Employment Generation CPRs play an important role in employment generation. In our study area, there
is very little scope of employment in non-agricultural sector due to high level of
poverty, illiteracy and lack of technical skills of the rural households. Hence
most of people engage themselves in CPR-based activities. It is interesting to
note that an average household could generate around 116 and 95 employment
man days annually from CPR based activities in the study villages of Bankura
and Purulia district respectively.
iv) CPR as a Source of Energy
Almost all the surveyed households collect fuel wood and cow dung from the
common forest area for the purpose of cooking. The households use very little
commercial fuels like coal, kerosene, electricity and cooking gas as they are
very costly and beyond the reach of the poor households. On an average 79.35
percent and 76.78 percent of the total monthly household energy consumption
were met by the CPR products collected from the common forest area in
Bankura and Purulia districts respectively. It is also observed that both the BPL
and APL households use fuel wood gathered from CPRs for their household
energy needs.
v) CPR and Animal Grazing Most of the households in our surveyed villages utilise common forest area for
animal grazing. The dependency of the households on CPR in our study area for
animal grazing has been estimated in terms of the creation of animal unit
grazing days in common grazing land. As estimated, CPR supported 88 animal
unit grazing days per household in Bankura district in last one month during
survey. The dependency of households on CPR for animal unit grazing in
Purulia district is much higher; an average household gets support of 114 animal
unit grazing days per month, which confirms the heavy dependence of the rural
poor on the CPRs for animal grazing.
Summary, Conclusion and Policy Suggestions
174
vi) CPRs and Rural Poverty CPR plays a vital role to alleviate rural poverty. With the exclusion of the
contribution of CPRs to the total household income, the extent of poverty
increases around 26 percent in our study area.
vii) Regression Results: Determinants of CPR extraction The CPR product extraction by rural households in our study area depends on a
host of factors relating to household and village characteristics. The family size,
average age, level of education, female percentage, land holding pattern,
livestock unit, the distance between dwelling place and the common forest,
market distance are some of the socio-economic, demographic and geographical
factors, which determine the extraction of CPR products. We have used multiple
regression model to examine the determinants of CPR extraction. It is evident
from the analysis that most of the important variables are significant with the
expected sign. From the regression analysis we observed that the family size
( FSIZE ), size of livestock ( LIVESTOCK ), female percentage in the household
( FEMPER ) have a positive impact on community forest income in both the
districts. Since CPR extraction is a labour intensive technique, larger the family
size higher is the labour time available for the collection of community forest
products. Again households with larger number of livestock collect more fodder
to feed the animals. We further observe that female members are mainly
involved in CPR collection in our surveyed villages in both the districts.
Education ( AVRSCH ) i.e. average years of schooling of the household, forest
distance ( FORESTDIST ), distance to the nearest market ( DISM ) have
negative impact on CPR income in both the districts. Household members who
are better educated get better job opportunities and therefore are less interested
in CPR collection. Household nearest to the forest area extracts more CPRs than
the household far away from the forest area. In the case of distance to the
nearest market, the motivation for extraction of CPR product is greater when
market is nearer due to greater marketability of the CPR products. We observed
that there is a positive and significant relationship between average age of the
household ( AVRAGE ) i.e. experience in collecting CPR products and CPR
income in Purulia district. It is easier for an experienced household member to
Summary, Conclusion and Policy Suggestions
175
collect more CPRs and thus smooth their consumption and livelihood. However,
the result is negative and insignificant in Bankura district. Again, we have
observed that the coefficient of OWNLAND is negative and significant in
Bankura district. However the result is contradictory in Purulia district which
implies that households with large ownership of cultivable land collect more
fuel wood. This is mainly due to the fact that land in Purulia district is mostly
infertile and so mere ownership of land fails to reduce the dependency on CPRs.
Most importantly, CPR acts as a life supporting system to the rural poor. In the
absence of alternate employment opportunities to the rural poor, they are highly
dependent on CPRs. Our regression analysis indicates that there is a positive
relationship between poverty ( POVR ) and the CPR income and the result is
highly significant in both the districts. Hence in the case of the poor, the income
from common forest has a higher percentage as compared to that of the ‘not so
poor’.
viii) Poverty and Environment The environment matters a lot to the rural poor. The wellbeing of the poor is
strongly related to the environment. From our field survey report, we have
observed that the common forest area declined around 12.05 percent in the
study villages during the period 1990-2010. However, the depletion of forest
area is high in Bankura district as compared to Purulia district. To analyse the
relationship between poverty and environmental degradation, we have used
logit regression model. The important finding of our study is that the coefficient
of environmental degradation is positive and significant in both the districts
which imply that with more environmental degradation the probability of the
incidence of poverty increases. In fact, most of the households in our study area
are very poor and are heavily dependent on CPRs for their livelihood. The level
of extraction of CPRs is higher than their regenerating process and thus the
environment gets further degraded. However, poverty cannot be made solely
responsible for environmental degradation. Rise in population, growing
commercialisation of agricultural and CPR products, emergence of market are
other factors responsible for forest degradation.
Summary, Conclusion and Policy Suggestions
176
In Chapter 5, the interrelationship among agricultural risk, non-timber forest
collection and the extent of rural poverty has been analysed.
The major findings are:
i) Nature of Agriculture The economy of Bankura and Purulia districts are primarily based on
agriculture. Paddy is the main crop of both the districts. In addition, wheat,
oilseeds, maize, sugarcane, groundnut and pulses are other important crops
grown in the surveyed villages. Since agriculture is largely dependent on the
vagaries of monsoon and drought, there are several risks associated with it in
our study area such as adverse weather, seasonal flooding, unpredictable soil
quality, crop diseases, price shocks, etc. The high dependence of the rural poor
on the CPRs in the form of Non Timber Forest Products (NTFPs) is primarily
due to uncertainty and low productivity in agriculture.
ii) Agricultural Productivity Most of the farmers in our study area belong to small size category and the
nature of agriculture is backward in nature. The average yield of agricultural
productivity in the surveyed villages of Bankura is 2144 kg/hectare whereas in
Purulia district it is 1594 kg/hectare in the year 2010, which is much lower than
the state average (2708 kg/hectare). Most of the households in the villages are
so poor that they cannot afford to purchase mechanised agricultural implements
like power tiller and pump set and therefore used mainly wooden plough and
bullocks for cultivation. From the surveyed data on agricultural labour in the
surveyed villages of both the districts reveal that men and women equally
participate in agriculture in the process of sowing, weeding and harvesting.
Further it is also observed that children are also involved in agricultural labour
in the several surveyed villages.
Summary, Conclusion and Policy Suggestions
177
iii) Agricultural Risk and CPR CPR in our study area mitigates a sizeable proportion of agricultural risk. Since
agricultural practice in the study area is backward in nature and subjected to
weather risk in the form of agricultural shock in times of production shortfall,
the farmers fall back upon CPRs for their survival and also addresses
significantly their agricultural risk. Here CPRs act as a safety net during the
period of agricultural risk. As established from our field data in the year 2010,
the agricultural production variability resulted in agricultural shortfall of Rs
209032 in Bankura and Rs 164391 in Purulia as compared to the normal year
(2008). Interestingly, it is observed that during this period the extraction of CPR
is also high compared to the normal year.
iv) Agricultural Risk and Extraction of Forest Products: Count Data
Regression Model We have explained the determinants of forest collection labour through
econometric analysis to give an understanding of the impact of agricultural
product risk on the extraction of forest products. The forest collection labour is
determined not only by social, economic, demographic variable but also by
agricultural shock and agricultural risk. We have applied Count Data Model
using STATA computer software package. As per the Count Data analysis, the
association between forest collection trips and age of the household head
( AGEHEAD ) is positive and significant whereas square of age of the household
head ( SQAGEH ) is negative and significant which imply that households with
older heads normally take more trip on forest collection except the oldest
household member. As almost all the household members in the study area
collect CPRs, the larger the family size ( FAMSIZE ), the more is the forest trips
to collect NTFPs. As expected education ( AVRSCH ) i.e. the average years of
schooling of the household has a negative impact on forest collection trips in
both the districts. On the basis of our results we can infer that households with
large number of livestock ( LIVESTOCK ) are equally responsible for excessive
extraction of forest products as they take more trips to gather fodder to feed
animals. It was observed that forest distance ( FORESTDIST ) i.e. the distance
Summary, Conclusion and Policy Suggestions
178
between the residence and the common forest has a negative impact on forest
collection trips. The key findings of our regression results indicate that the
coefficients of agricultural risk parameters ( AGRIRISK ) and shock parameters
( AGRSHTFALL ) are positive and significant in both Bankura and Purulia
districts, which suggest that household with greater agricultural shortfall and
risk are likely to take more forest collection trips. Hence we can conclude that
NTFP has a supporting role in the wellbeing of the rural poor in the form of
‘natural insurance’. By collecting NTFP, rural households smooth their income
as well as consumption in the period of agricultural crisis.
We have examined the nature of participation in forest management and its impact
on resource utilisation and conservation in Chapter 6. The chapter also focused on
the relationship between the intensity of management practice and the degradation of
forest resources.
The major findings are:
i) Joint Forest Management (JFM) in the Study Area The surveyed villages in the study area are covered by vast forest area. Most of
the villages are extremely poor and are highly dependent on forest products for
their subsistence. Since the forest communities have more knowledge about the
forest, their active involvement is necessary for the sustainability of the forest
resources. The Joint Forest Management was initiated in the study villages in
1992 after the JFM resolution (1990) of the Govt. of West Bengal. In order to
ensure the availability of the forest resources in the long run, the rural
households have actively participated in Joint Forest Management (JFM). A
Forest Protection Committee (FPC) in the study areas has been formed whose
prime responsibility is to protect the forest. The FPC involves the local people
in planning, development of the forest and regeneration of the forest through
plantation of trees. The FPC plays a vital role in enforcing the guidelines laid
down by the JFM schemes. In case anyone breaks the rule enforced by the
Forest Protection Committee or engage in illicit felling of the forest trees, then
FPC take away his cutting implements and impose a penalty ranging from Rs
100/- to Rs 500/- depending upon the seriousness of the crime.
Summary, Conclusion and Policy Suggestions
179
ii) JFM Participation As per the surveyed data, 75.33 percent of the surveyed households in Bankura
district and 85.33 percent in Purulia district participated in JFM. The survey
result also shows that the percentage of household involved in planning and
implementation of JFM in the surveyed villages of Bankura were 60.67 percent
and 12.67 percent respectively as compared to 65.33 percent and 16 percent in
the surveyed villages of Purulia. The data reveals that the incidents of cases of
violation of rules have shown a declining trend in most of the surveyed villages
during the period 2008-2010. It is further observed that the Joint Forest
Management is active in the villages of Dulaltora in Bankura district and
Jiyathole in Purulia district. From our surveyed data we can infer that with the
establishment of JFM, enforcement of Forest protection has shown a positive
trend. Further, the households have realised that protection of the common
forest is in their own interest and violating the rules has an adverse effect on
them.
iii) Determinants of Collective Action in JFM Collective action refers to concerted actions of people that share a common
interest, perceive that interest and act to achieve it (World Bank, 1998). The
forest resources that can be effectively managed by the rural poor depend on the
strength of the collective action i.e. joint action of the community to conserve
forest resources as well as improve rural livelihood. We have explained the
determinants of collective forest management through censored Tobit Model to
give an understanding of the relationship between forest dependency and active
forest management. We have observed from the determinants of collective
action in JFM that family size ( FSIZE ) and average age ( AVRAGE ) have a
positive effect and education ( AVRSCH ) has a negative effect on collective
action in the surveyed villages of both Bankura and Purulia districts. The
coefficient of agricultural income to total income ( PERAGRIN ) is negatively
related to collective action in JFM which implies that households with steady
income from agriculture are less interested in forest product collection and in
active participation in JFM. Again wealth (WEALTH ) has negative and
significant impact on collective action management in the surveyed villages of
Summary, Conclusion and Policy Suggestions
180
both the districts. It is evident from the analysis that collective action in JFM is
positively related to percentage of CPR income to total income ( PERCPRIN )
and the impact is significant in both the districts. This indicates that households
whose dependence on forest product is high are more interested in active
participation in JFM to overcome the uncertainty and insecurity in their
livelihood. It is further observed that percentage of CPR consumption to total
consumption ( PERCPRCSM ) has a positive impact on active participation in
JFM which implies that household who depend more on forest products for
their consumption purposes are very much concerned about forest conservation
and hence actively participate in JFM.
iv) Collective Action and Forest Conservation Our field survey data reveals that collective action in forest management has its
inherent impact on the conservation of forests. Active forest management
lowers the degree of over exploitation and hence the degradation of forest
resources. We have explained the role of forest management in the reduction of
forest degradation by using logit regression model. The result demonstrates that
improved management has a positive role to alleviate environmental
degradation. It is observed that the association between Forest Management
activity and forest degradation is significant in both the districts. As most of the
rural poor depend on CPR, especially forest products for their livelihood, CPRs
should be properly managed so that the rural poor can get maximum benefit
maintaining the sustainability of forest resources.
In Chapter 7, we have examined the role of women in CPR collection and their
performance in JFM committees. We further investigated empirically the effect of
women’s active participation in JFM on forest resource conservation.
Summary, Conclusion and Policy Suggestions
181
The major findings are:
i) Female Headed Household and CPR collection Forest plays an important role in livelihood support system for the rural poor
women in our surveyed villages. Our field survey data reveals that the average
contribution of CPR to the total household income for a female headed
household is 44 percent as compared to 26 percent for male headed household.
This implies that female headed household are heavily dependent on CPR
collections to supplement their household income. Further, female members
generate higher employment man days through CPR collection as compared to
the male members in the household. Thus, women are able to supplement the
household income through CPR collection which is used for consumption as
well as a source of income through sale.
ii) Women’s Participation in JFM Despite the fact that the women are the major users of CPRs, their
involvement in JFM is negligible. As rural women are highly dependent on
forest resources, they greatly value the forest conservation since degradation of
the forest not only leads to depletion of the forest resources but increase the
distance to be covered in order to collect them. We have observed from our field
survey report that the number of adult female participants in JFM in 2010 is 65
and 80 in Bankura and Purulia district, which is extremely low as compared to
170 and 205 of adult male participants in the said district. We further observed
that the female participation in JFM has increased in the year 2010 as compared
to the previous years. However, male domination in JFM still remained in the
study area of both the districts.
iii) Gender Equity in JFM and Forest Resource Sustainability We have estimated the impact of women’s active participation in JFM on
sustainability of forest resources through binary probit model using EViews 7
economic software. We have considered some other socio-economic variables
like sex-ratio, female headed household, female literacy, per capita cattle unit,
dependency ratio, market pressure and imposition of fine on CPR rule breaker
on which sustainability of forest resources also depend. Our regression result
Summary, Conclusion and Policy Suggestions
182
indicates that sex-ratio, female headed household and female literacy have a
positive influence on sustainability of forest resources. Again, dependency ratio
( DEPR ) is found to be negative in case of forest resource conservation which
implies that as dependent member increases in the family, burden on forest
products increases which ultimately degrades the forest resources. The per
capita cattle unit ( PCATTL ) also has a positive impact on sustainability of
forest resources. Again, punishment ( PUNSHM ) against CPR rule breaker has
positive and significant impact on forest resource sustainability in both the
districts. However, distance to the closest market ( DISM ) has a negative
impact on sustainability of forest resources. The most important finding of this
study is the positive and significant impact of active participation of women
member in JFM (WACTPM ) on sustainability of forest resources in both the
districts. Active involvement of women in planning, decision making and
implementation prevent illegal harvesting of the forest products and thus
improve forest quality. Hence gender equity in JFM participation enhances
sustainability governance of the forest resources.
8.2 Conclusion
The theme of the research is Common Property Resource (CPR) collection and its
impact on Poverty and Environmental Degradation and Conservation. The use of
CPRs mainly forest resources is manifold in the livelihood of forest fringe people.
Systematic and Sustainable development of CPRs can make better the standard of
living of the rural poor and play a crucial role in the conservation of forest resources.
Our field survey has provided various research findings. Firstly, our survey report
indicates a very high dependency of the rural poor on CPRs. The data reveals that
18.67 percent of household income and 21.28 percent of household expenditure is
derived from CPR extraction. Due to enormous demand, collection of Non Timber
Forest Products (NTFPs) is an important occupation for our surveyed households.
Almost all the households collect fuel wood from the common forest area for the
purpose of cooking. Most of the households utilise CPRs for animal grazing. Thus
CPRs have an immense role in rural livelihood. The data shows that with the access to
Summary, Conclusion and Policy Suggestions
183
common property resources the poverty level reduces by around 26 percent, which
signifies that the extent of poverty increases sharply in the absence of CPR income.
However, the high extraction of forest resources along with population growth,
growing commercialisation of agricultural and CPR products and emergence of
market in our surveyed villages have resulted in the decline of forest area of 12.66 sq.
km which further impoverishes the forest livelihood.
In our study we also investigated the impact of agricultural risk on the collection of
common forest products. Agriculture is the main occupation of most of the surveyed
households and therefore they depend on nature for any agricultural activities. During
any natural calamities they have no other alternate livelihood opportunities except to
extract forest products. We have observed from our field data in the year 2010 that
due to high agricultural shortfall, the households have extracted more CPR as
compared to the normal year.
In order to ensure the availability of the forest resources in the long run, rural
households have actively participated in collective forest management. Our field
survey data reveals that active forest management has a crucial role in reducing forest
degradation. The field survey report indicates that, although JFM is still under male
domination, women being the major users of forest resources greatly value the forest
conservation and therefore participate in JFM activities. However, the female
participation in JFM is far from satisfactory.
In view of the present condition of the forest resources and the rural livelihood in our
study area, there is an immediate need to conserve forest resources through collective
action of rural communities and it is expected that gender equity in participatory
management will improve the sustainability of forest ecosystem.
Summary, Conclusion and Policy Suggestions
184
8.3 Suggestions and Policy Implications
On the basis of our findings of the study, we now propose some important policy
suggestions for the betterment of the rural livelihood in the context of our surveyed
villages of Bankura and Purulia districts of West Bengal.
The rural poor in our study area are highly dependent on Common Property
resources especially forest resources due to the lack of alternative livelihood
opportunities. The wellbeing of the forest communities is strongly related to the
sustainability of forest resources. However, during our research study we have
observed many situations where this dependence of forest products leads to forest
degradation. Non-availability of alternate income opportunities compel the village
dwellers to depend on CPRs for their livelihood. Thus without offering alternative
income opportunities to the villagers, it is not possible to control excessive
extraction of forest resources. Hence there is an urgent need to expand economic
opportunities especially through the development of non-farm activities so that the
dependence of rural poor on CPRs is reduced drastically.
Under this backdrop, we have the following policy suggestions:
1) Small scale eco-friendly industries including handicrafts should be encouraged
and incentivised by the government.
2) Commercialisation of the agricultural crops should be promoted.
3) Awareness about the real commercial value of the NTFPs at the actual market.
4) NTFPs based industries should be established for the economic development
of forest community.
5) Infrastructure in the form of roads, electricity, drainage system and medical
facilities for the poor should be ensured.
6) Awareness about the importance and benefit of conservation of the forest
resources should be propagated.
7) Unconventional energy sources like solar energy and bio gas needs to be
adopted in order to reduce the dependence on the forest resources.
Summary, Conclusion and Policy Suggestions
185
8) Educational opportunities need to be improved in the study area, so that they
realise the economic value of NTFPs as well as the importance and benefit of
conservation of forest resources. Further, education gives better job
opportunities and hence reduces dependency on forest resources.
Our field survey report indicates that CPRs supplement the rural livelihood and
act as safety net during agricultural crisis. Since the villagers in our study area are
dependent on nature for any agricultural activities, there are several agricultural
risks such as adverse weather, seasonal flooding, unpredictable soil quality, crop
disease etc. associated with it. Based on the above research findings we have
proposed few policy suggestions which not only encourage agricultural
development but also reduce rampant extraction of valuable forest products at the
time of agricultural shortfall.
1) Agricultural production needs to be increased by the use of modern
fertilisers and tools.
2) Traditional mode of livelihood of the rural poor should change by
involving them in new agro-economic activities like off-season
vegetables, etc.,
3) Irrigation system needs to be drastically improved including the rain
water harvesting system to cater to agricultural shocks due to drought.
4) ‘Dry land’ farming should be encouraged.
5) Government should take initiative in providing easy credit facilities at
the time of agricultural crisis.
Empirical evidence of our study confirms that collective action of forest
communities in forest management has an important role in forest resource
conservation. Hence there is a need to motivate the local villagers to actively
participate in forest management activities. The suggestions below follow our
research findings of related issues.
1) Motivate the rural households to actively participate in the
conservation and regeneration of the common forest areas, so that they
Summary, Conclusion and Policy Suggestions
186
understand the relationship between environment and their
development.
2) JFM should implement such rules so that indiscriminate felling of trees
or over grazing of the cattle should be prohibited.
3) The policies and strategies for the afforestation programmes should be
formulated in such a manner that it leads to high success rate and
encourages whole hearted participation of the rural poor.
4) The forest policies should cater mainly to the overall conservation of
the ecosystem and ensure that the forest degradation is minimised to
the maximum extent.
5) The forest department officials should be properly trained and
groomed to ensure that they mix well with the rural households and
disseminate the information for development of the forest area.
The most important finding of our research is the lack of active participation of
women in JFM despite the fact that they are the prime collectors of forest
products. Since women are greatly concerned about the forest conservation their
active involvement in forest management improves the sustainability of forest
resources. On the basis of our research findings we have suggested few policy
prescriptions:
1) Women’s active involvement in forest management should be ensured
and they should be encouraged to take decisions.
2) Forest management policies should be directed at favouring the women
to avoid discrimination.
3) Women’s organisation in the villages needs to be strengthened, so that
they are not marginalised.
4) Emphasis should be made on female literacy so that they can get
alternative income opportunities.
Summary, Conclusion and Policy Suggestions
187
Since our research has been conducted in the economically highly backward villages
of Bankura and Purulia districts of West Bengal, collection of data and information
was not an easy work at all. Keeping in mind all the limitations of the research study
we can conclude that systematic and sustainable use of forest products, creation of
alternative employment opportunities and extensive afforestation programme in our
surveyed area can only save the forest environment. Government should take proper
initiative to generate more awareness among forest communities for the protection,
regeneration and development of Common Property Resources.
Bibliography
188
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Village wise occupation composition of the surveyed population
Purulia TotalGrand Total
Working population engaged inDistrict Block Name of
villageNo. of
Households
Bankura Saltora
Purulia Santuri
Bankura Total
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APPENDIX-II
PRICE LIST OF CPRs The price list of the common property resources in the study area is shown in Table
A2.1 below:
TABLE A2.1
Sl No. Unit Market Price(Rs) GrassShrubDry leaves
2 per kg 2.50 3 per kg 5.00
Kalmegh (leaf) per kg 2.00 Neem (leaf) per kg 15.00 Basak (leaf) per kg 2.00 Bamboo per piece 20.00 Sal (leaf) per 1000 plates 50.00 Kend (leaf) per jhuri 30.00
6 per log 1,200.00 Bel (fruit) per kg 2.50 Amla (fruit) per kg 3.50 Tal (fruit) per piece 3.00 Mango (fruit) per kg 25.00 Kend (fruit) per kg 12.00 Jamun (fruit) per kg 10.00 Mahua (flower) per kg 5.00 Honey per kg 25.00 Meat per kg 80.00 Snail per kg 40.00 Shak (leafy vegetable) per kg 5.00 Kachu per kg 30.00 Oal (Tuber root) per kg 30.00
10 per kg 60.00 11 per piece 5.00
Source : Field Survey 2011Broom
Vegetables9
Fish
Timber
Cow dung (dung cake)
4 Herbal medicine
Fuelwood
5 Bamboo / Sal & other leaves
Hunded birds / animals /snails8
7 Fruits / Flowers / Honey
Price List of Common Property Resources in the Surveyed Villages
Common Property Resource
1 Fodder per kg 2.00
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APPENDIX-III
SUMMARY STATISTICS
Based on our primary data, we present the summary statistics in Table A3.1 & A3.2
below:
TABLE A3.1 Descriptive Statistics of Quantitative and Dummy variables for Bankura District
BANKURA PURULIA TOTAL1 No. of Households 150 150 3002 Total area of lease in land (Hectare) 28.47 7.09 35.563 Total area of lease out land (Hectare) 0.28 0.27 0.554 Total area of ownland (Hectare) 14.48 35.49 49.975 Total area of operated land (Hectare) 42.66 42.31 84.98
Source: Field Survey, 2011
TABLE A4.1Land Ownership Pattern
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216
From Table A4.2 above, we can infer that 44 percent of the surveyed households in
the district of Bankura who have no ‘own land’. It can also be observed that 90.7
percent of the surveyed households in the district of Bankura belong to landless and
marginal size own land holders (0-0.25 hectare) and they cater to 68 percent of the
total own land. It is further observed that 9.4 percent of the surveyed households
belong to small and medium land owners (0.25-0.75 hectare) having 32.1 percent of
the total ‘own land’. There are no large size (>1 hectare) own land holders. This
implies that majority of the households have almost equally very small area of own
land which indicates that households are extremely poor and have fragmented land.
The Gini coefficient which shows the degree of inequality in the distribution of ‘own
land’ holding is 0.52. Thus there is high degree of inequality in the ownership
distribution of land owners.
In the case of the surveyed villages in the district of Purulia, it is observed that 6.7
percent of the households are without any own land. Survey results show that 93.3
percent of the surveyed households in the district of Purulia have ‘own land’ in the
range of 0-0.50 hectare which account for 78 percent of the total own land, whereas
only 1.3 percent of the surveyed households belong to large size group (> 1 hectare)
having 6 percent of the total own land. Here the Gini coefficient is 0.33.
APPENDIX-V PROPERTY RIGHTS AND ‘THE TRAGEDY OF THE COMMON’ The concept of over exploitation of the natural resources in the ‘Commons’ was first
published by Garett Hardin (1968) in his highly debatable article ‘The Tragedy of the
Commons’. The ‘Tragedy of commons’ is a dilemma arising from the situation in
which several individuals, acting independently and rationally consulting their own
self-interest, will ultimately deplete a shared limited resource, even when they are
fully aware that it is not in anyone’s long-term interest for it to happen. The article
highlighted two important aspects about the natural resource, usually referred to as a
common-pool resource to which a large number of people have full access:
i) There is huge demand on the natural resources due to high growth in
human population and therefore there is increased usage of the resources.
ii) Excessive demand of the natural resources leads to unlimited usage by
many users, resulting in over exploitation.
The concept has been used to explain the reason for overgrazing in pastures,
overexploitation of fisheries, air and water pollution, depletion of fuel wood and
ground water, decline in wild life, etc. (Stevenson, 1991). The article describes the
situation in a common pasture where there is no restriction to entry for the herdsmen.
In primitive times, overpopulation of the pasture by herds did not occur because of
natural attrition. However, in modern times, it is not so and the balance will be tipped
as adding one more animal to the grazing land will cause it to be overpopulated. In
spite of this, each rational herdsman wants to maximize his gains by adding one more
animal to the herd. The marginal utility of adding one more animal to the herd has one
positive and one negative component. The positive component is a function of the
increment of one animal. Now that the herdsman receives all the benefits from the
sale of the additional animal, the positive component can be considered to be almost
equal to +1. The negative component is the function of the additional overgrazing
which resulted due to addition of one more animal to the herd. In this particular case it
may be noted that the effect of over grazing due to addition of one more animal to the
herd by a herdsman is shared equally by all the herdsmen. Hence the negative utility
for a herdsman is a fraction of -1. Thus the rational herdsman concludes that it is
Appendices
219
logical to add one more animal to the herd since it maximizes his gain while the cost
is distributed equally amongst all the herdsmen. Since all the herdsmen reach the
same calculation, overgrazing is inevitable. Each herdsman will continue to impose
costs on all of the others, until the pasture is depleted, which is detrimental to all.
Thus the ‘free riding’ leads to the Tragedy. Hardin had recommended that the tragedy
of the commons could be prevented by strict regulation by the government. He also
felt that privatization of the common property could solve the problem.
The term ‘common property’ as described by Hardin (1968) has been highly debated
as he failed to distinguish between ‘common property’ and ‘open access’ resource.
Common Property represents private property for the group (since all others are
excluded from use and decision making), and that individuals have rights (and duties)
in a common property regime (Ciriacy-Wantrup and Bishop, 1975). Open access is a
situation in which there is no property. Since there is no property rights in an open
access situation, “everyone‘s property is nobody’s property”. It can only be said that
“everybody’s access is nobody’s property” (Bromley, 1999). Thus the critics argue
that Hardin’s article is more apt for open access resource instead of common property
resource. Elinor Ostrom (2000) emphasized that the tragedy of the commons may not
be as prevalent or as difficult to solve as Hardin implies, since locals have often come
up with solutions to the commons problem themselves. Contrary to Hardin’s view on
the Tragedies of the commons, the pastures were well looked after for many centuries
before they depleted for reasons unrelated to any flaw in the commons (Cox, 1985).
To avert the tragedy of the commons, different solutions have been put forth by
several Economists. One view is that the overexploitation and the degradation of the
common property resource can be creating and enforcing private property rights
(Demsetz 1967). Private property helps to incorporate the externalities generated from
over exploitation of the common property resource. Another view to overcome the
overexploitation is to entrust the commons to the state regime which would have full
authority over it (Hardin 1968). Of late, a large number of scholars have advocated
that the best solution to overcome the ‘Tragedy of the commons’ is for the users to
form a decentralized collective management of the CPRs. This theory of the use of
Appendices
220
Collective management of the CPRs has been favoured by Jodha (1986), Chopra
et.al., (1989), Berks 1989, Ostrom (1990).
The influencing article of the ‘Tragedy of the Commons’ by Hardin (1968) could also
be described as a dilemma arising from a situation wherein several users act
independently and rationally in their own self-interest, ultimately depleting the shared
limited resource although they are very well aware that it would lead to long term
adverse situation for all. This theory is explained with the help of Figure A5.11 as
shown below:
FIGURE A5.1
Relationship among effort, cost and revenue
*q 0q
Source: Ostrom, E, et.al.(2002); The Drama of the Commons
As per the illustration in Figure A5.1 above, on the X-axis we have depicted the effort
required in extraction of the common property resource (q) and on the Y- axis we
have depicted the Total Cost (TC) / Total Revenue (TR) associated with the
extraction. The effort in extraction of the resource ranges from *q , the social optimum
achieved under private maximization i.e. MR MC= to 0q , the level of extraction
Appendices
221
under open access with AR AC= and profit ( ) 0π = . In order to achieve *q , there has
to be cooperation amongst all the members of the community and they must all agree
to exercise restraint in their effort to extract from the resource. Here the q is above *q in the case of CPR without cooperation, since each member tries to impose on
others a negative externality in extracting from the resource that he does not take into
account. This in turn leads to depletion of the resources.
The dilemma associated with the herdsmen whether to act independently at one’s
own interest or to cooperate and act collectively looking into the long term interest of
the CPRs can be best compared with the Prisoner’s Dilemma (PD). The Prisoner’s
Dilemma is a problem in game theory that demonstrates as to why two people or
group of people will not cooperate even if it is in both their best interest to do so. The
Prisoner’s Dilemma (PD) is the theoretical foundation to explain the tragedy of the
commons or the non-cooperative use of a CPR (Baland and Platteau, 1996).
A classic example of the prisoner's dilemma (PD) is presented as follows:
In an example of forest management, if the forest department and the village
community agree to participate, then both the forest department and village
community may share the forest produce equally at Rs 3 lakhs each. If the village
community alone participates and not the forest department, then the forest
department may collect all the forest produce and auction it and earn a forest revenue
to a tune of Rs 5 lakh (and not a total of 6 lakh) , but the village community gets
nothing and will be the net loser. If the village community does not participate, it may
indulge in illegal cutting of some timber and get its market price worth Rs 5 lakhs and
the forest department gets nothing and is the net loser. Finally, if both the forest
department and the village community do not participate in the forest management,
then the forest department may collect some timber and other forest produce and the
village community may collect some forest produce illegally, thereby each gaining
revenue equal to just Rs 1 lakh (Table A5.1).
Appendices
222
TABLE A5.1
Prisoner’s Dilemma
(Rs Lakhs)
Village
Community
Forest Department
Participate Do not participate
Participate 3 ; 3 0 ; 5
Do not participate 5 ; 0 1 ; 1
In the classic form of this game, cooperating is strictly dominated by defecting, so that
the only possible equilibrium for the game is for all players to defect. No matter what
the other player does, one player will always gain a greater payoff by playing defect.
Since in any situation playing defect is more beneficial than cooperating, all rational
players will play defect, all things being equal. In the above example, both the village
community and the forest department do not participate in the forest management and
settle for a pay-off of Rs 1 lakh each. However the best set of pay-offs could have
been each getting Rs 3 lakhs.
According to Amartya Sen, all it takes to make cooperation individually optimal is
‘assurance’ that others will cooperate. Hence, this is an assurance problem. (Sen
1967). It may be possible to overcome the prisoner’s dilemma by converting the
dilemma into an assurance problem by changing either incentives or personal