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Natural Resources Management
in Agriculture
Methods for Assessing Economic and
Environmental Impacts
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Prelims.indd 2 01 Nov 2004 5:16:02 AM
Natural Resources Management
in Agriculture
Methods for Assessing Economic and
Environmental Impacts
Edited by
B. Shiferaw, H.A. Freeman
ICRISAT, and ILRI, Nairobi, Kenya
and
S.M. Swinton
Michigan State University, East Lansing, Michigan, USA
CABI Publishing
Prelims.indd 3 01 Nov 2004 5:16:02 AM
CABI Publishing is a division of CAB International
CABI Publishing CABI Publishing
CAB International 875 Massachusetts Avenue
Wallingford 7th Floor
Oxfordshire OX10 8DE Cambridge, MA 02139
UK USA
Tel: +44 (0)1491 832111 Tel: +1 617 395 4056
Fax: +44 (0)1491 833508 Fax: +1 617 354 6875
E-mail: cabi@cabi.org E-mail: cabi-nao@cabi.org
Web site: www.cabi-publishing.org
Published in association with:
The International Crops Research Institute for the Semi-Arid Tropics (ICRISAT)
Patancheru 502 324
Andhra Pradesh, India
The International Crops Research Institute for the Semi-Arid Tropics (ICRISAT) is a non-profit,
non-political organisation for science-based agricultural development. ICRISAT conducts
research on sorghum, pearl millet, chickpea, pigeonpea and groundnut – crops that support
the livelihoods of the poorest of the poor in the semi-arid tropics, encompassing 48 countries.
ICRISAT also shares information and knowledge through capacity building, publications and
information communication technologies. Established in 1972, it is one of 15 centres supported
by the Consultative Group on International Agricultural Research (CGIAR).
©CAB International 2005. All rights reserved. No part of this publication may be reproduced in
any form or by any means, electronically, mechanically, by photocopying, recording or other-
wise, without the prior permission of the copyright owners.
A catalogue record for this book is available from the British Library, London, UK.
Library of Congress Cataloging-in-Publication Data
Natural Resource management in agriculture : methods for assessing economic and environ-
mental impacts / edited by B. Shiferaw, H.A. Freeman, and S.M. Swinton.
p.cm.
Includes bibliographical references and index.
ISBN 0-85199-828-3 (alk. paper)
1. Agriculture--Environmental aspects--Congresses. 2. Agriculture--Economic aspects--Congresses. 3.
Agricultural resources--Management-Congresses. I. Shiferaw Bekele. II. Freeman, H.A.
III. Swinton, Scott M. IV. Title
S589.75.N368 2005
338.1--dc22
200402093
ISBN 0 85199 828 3
Printed and bound in the UK by Biddles Ltd, Kings Lynn, from copy supplied by the editors
Prelims.indd 4 01 Nov 2004 5:16:03 AM
Contents
Preface vii
Foreword xi
Contributors xiii
Reviewers xv
Part I. Introduction
1. Assessing the Impacts of Natural Resource Management
Interventions in Agriculture: Concepts, Issues and Challenges 3
H.A. Freeman, B. Shiferaw and S.M. Swinton
Part II. Valuation of Ecosystem Services and Biophysical Indicators of NRM Impacts
2. Valuation Methods and Approaches for Assessing Natural Resource
Management Impacts 19
B. Shiferaw, H.A. Freeman and S. Navrud
3. Measurable Biophysical Indicators for Impact Assessment:
Changes in Soil Quality 53
P. Pathak, K.L. Sahrawat, T.J. Rego and S.P. Wani
4. Measurable Biophysical Indicators for Impact Assessment:
Changes in Water Availability and Quality 75
K.L. Sahrawat, K.V. Padmaja, P. Pathak and S.P. Wani
5. Biophysical Indicators of Agro-ecosystem Services and Methods for
Monitoring the Impacts of NRM Technologies at Different Scales 97
S.P. Wani, Piara Singh, R.S. Dwivedi, R.R. Navalgund and A. Ramakrishna
Part III. Methodological Advances for a Comprehensive Impact Assessment
6. Econometric Methods for Measuring Natural Resource Management
Impacts: Theoretical Issues and Illustrations from Uganda 127
J. Pender
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vi Contents
7. Assessing Economic Impacts of Natural Resource Management
Using Economic Surplus 155
S.M. Swinton
8. Bioeconomic Modelling for Natural Resource Management
Impact Assessment 175
S.T. Holden
Part IV. NRM Impact Assessment in Practice
9. Valuing Soil Fertility Change: Selected Methods and Case Studies 199
P. Drechsel, M. Giordano and T. Enters
10. Evaluating the Impacts of Watershed Management Projects:
A Practical Econometric Approach 223
J.M. Kerr and K.R. Chung
11. Assessing Economic and Environmental Impacts of NRM Technologies:
An Empirical Application Using the Economic Surplus Approach 245
M.C.S. Bantilan, K.V. Anupama and P.K. Joshi
12. Assessing the Economic and Environmental Impacts of Conservation
Technologies: A Farm-level Bioeconomic Modelling Approach 269
B. Shiferaw and S.T. Holden
13. Assessing the Impacts of Natural Resource Management Policy
Interventions with a Village General Equilibrium Model 295
S.T. Holden and H. Lofgren
Part V. Towards Improved Approaches for NRM Impact Assessment
14. The Concept of Integrated Natural Resource Management (INRM)
and its Implications for Developing Evaluation Methods 321
B. Douthwaite, J.M. Ekboir, S.J. Twomlow and J.D.H. Keatinge
15. NRM Impact Assessment in the CGIAR: Meeting the Challenge and
Implications for CGIAR Centres 341
T.G. Kelley and H.M. Gregersen
16. Towards Comprehensive Approaches in Assessing NRM Impacts:
What We Know and What We Need to Know 361
S.M. Swinton, B. Shiferaw and H.A. Freeman
Index 377
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vii
Preface
In response to increasing concerns about degradation of natural resources and
the sustainability of agricultural production potentials in many poor regions
of the world, many national and international organisations have initiated
research and development programmes for natural resource management
(NRM). Efforts in this direction include the design and development of
low-cost technological options for integrated management of soil and water
resources, the development of ecologically sound cropping systems, and
options for the conservation and management of agro-biodiversity and
forestry resources. Among others, the Consultative Group for International
Agricultural Research (CGIAR) has substantially increased its research
investments in the area of NRM. Development agencies in developing countries
also invest substantially in measures to sustain productivity and conserve both
the agricultural resource base and the environment. Donors, policy makers,
development agents, and researchers are all anxious to evaluate the potential
social benefits and environmental outcomes resulting from such investments
through the adoption of new resource conserving and/or productivity
enhancing technologies. Although methods for evaluating the impacts of crop
improvement technologies are well developed and widely applied, there is
a dearth of methods to evaluate the impacts of NRM interventions. This is
partly due to the methodological difficulties encountered in assessing the
impacts from NRM research, including those arising from inter-relationships
among natural resources, spatial and temporal dimensions of impact, and the
valuation of direct and indirect environmental benefits and costs.
Despite a handful of attempts to assess the impacts from NRM
research, until now researchers from a range of disciplines and institutional
backgrounds have not joined to critically address the challenges and develop
methods for NRM impact assessment. This book is an effort towards filling
this gap. Its objective is to examine methodological difficulties and present
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viii Preface
practical methods that can be used to assess the economic and environmental
impacts of NRM technology and policy interventions. It synthesises recent
methodological advances and results from frontier research in this field. The
methodological and conceptual chapters are enriched and illustrated with
case studies and examples. Several chapters bring together current thinking
and perspectives on NRM impact assessment and define directions for future
research, covering such important areas as economic valuation methods,
measurable performance indicators and applicable impact evaluation
approaches together with other special features in evaluating the impacts of
NRM interventions.
The book brings together a number of peer-reviewed papers many of
which were originally presented and discussed at the international workshop
on ‘Methods for Assessing the Impact of Natural Resource Management
Research’ held at the International Crops Research Institute for the Semi-
Arid Tropics (ICRISAT), 6–7 December 2002. The workshop aimed: a. to
deliberate the special features and methodological difficulties of NRM impact
assessment, b. to examine the strengths and weaknesses of alternative impact
assessment methodologies and suggest options for pilot testing, and c. to
identify data requirements for developing impact indicators. The book was
conceived and inspired by the issues discussed during the workshop.
Given the multi-faceted and complex nature of NRM impacts, contributions
come from a multidisciplinary team that included economists, agro-ecologists,
and soil and water management scientists, from a range of institutions
covering the CGIAR, universities and research institutions. The main theme
of the book is rooted in agricultural and resource economics as applied to
the evaluation of multi-dimensional outcomes from NRM interventions.
The book contains 16 chapters organised into five parts. The methodological
sections are rigorous but well exposed and should be readable to impact
assessment practitioners and graduates in applied economics. The applied
sections are treated carefully to make them available to general practitioners,
development agents, and advisors interested in evaluating the impacts of
interventions that affect NRM.
The volume can serve as a valuable reference for economists, impact
assessment practitioners, agronomists, resource management specialists,
rural development advisors, and researchers and academics interested in
the impacts of NRM interventions. The key recommendations and policy
findings may also be of interest to policy advisors, planners, development
agencies, and research managers, both in national and international
agricultural research systems. We hope that the book will add usefully to
the scant literature on evaluation of NRM impacts for all those interested
in understanding the social benefits of such investments and developing
suitable evaluation skills.
The editors would like to thank ICRISAT for providing the necessary
funds for the background workshop and for publication of the book. We wish
to express our sincere gratitude to the external reviewers for their comments
and suggestions that were instrumental in excluding some of the initially
suggested chapters and in improving the quality of those that finally appear.
Prelims.indd 8 01 Nov 2004 5:16:03 AM
Preface ix
A list of all reviewers is given after the list of contributors. We are very grateful
to the authors and co-authors of all the chapters for their contributions and
for their efforts in responding to reviewer and editorial comments.
The editors also express thanks for the support and efforts of ICRISAT
and CAB International staff in the production of this book. Sincere thanks are
due to Tim Hardwick and Rachel Robinson for their patience and support.
Special thanks are due to Sue Hainsworth, our technical editor, and her
assistants T.N.G. Sharma and Deanna Hash, for their tireless and remarkable
efforts to enhance the presentation and readability of the manuscripts, and
to P.N. Jayakumar for his editorial and scientific support from the book’s
inception.
Bekele Shiferaw, H. Ade Freeman and Scott M. Swinton
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Foreword
In many poor regions of the world, lack of technological progress and
increasing population pressure are taking a heavy toll on the productive
resource base. Water scarcity, soil degradation and productivity loss are
becoming global challenges to the eradication of poverty, especially in
many less-favoured areas where there is a strong nexus between poverty
and environmental degradation. Depletion of the resource base diminishes
the capabilities of poor people and increases their vulnerabilities to drought
and other natural disasters. Sustainable productivity growth and natural
resource management are indeed inextricably linked, and strategies aiming to
enhance livelihood security should identify ways to enhance the productivity
of the natural resource assets of the poor. Semiarid tropical agriculture
is characterised by high risks from drought, pest and disease incidence
and pervasive poverty. It is here that knowledge-based agro-ecosystem
management holds the key to sustainability and livelihood security.
Attainment of the Millennium Development Goals will simply not be
possible without sufficient technological progress and improved policies to
address the global challenges that face the resource-poor regions of the world.
Coupled with efforts to increase agricultural productivity in such regions,
natural resource management (NRM) has become one of the cornerstones
of research and development efforts within the national, sub-regional
and international agricultural research systems. The Consultative Group
on International Agricultural Research (CGIAR) has devoted significant
resources into this area of research. Development investors, policy makers
and researchers alike are keen to assess and evaluate investments in NRM.
In the past, progress has been limited by the lack of scientifically valid ways
to evaluate the complex economic and environmental outcomes associated
with these interventions that need new methods and techniques to enhance
their effectiveness.
xi
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xii Foreword
This book focuses on these felt needs and synthesises recent methodo-
logical advances in the evaluation of the impacts of integrated genetic and
natural resource management interventions. The overlapping problems
of poverty, resource degradation, and the threats of climate change and
desertification are real concerns for the future of semiarid tropical agriculture,
on which the livelihoods for millions of poor families depend. Methods
that enhance the effectiveness of interventions to address such challenges
worldwide are urgently needed. The diverse topics covered in this book,
contributed by leading researchers, will make a significant contribution
to enhancing the impact of resource management interventions in many
regions. The authors and editors are to be commended for making positive
progress in this difficult area. This work will provide a sound basis for further
refinement and future research.
William D. Dar
Director General
International Crops Research Institute for the Semi-Arid Tropics
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Contributors
K.V. Anupama, Scientific Officer (Economics), International Crops Research Institute for the Semi-
Arid Tropics, Patancheru 502 324, Andhra Pradesh, India, sepp@cgiar.org
M.C.S. Bantilan, Principal Scientist (Economics) and Theme Leader (SAT Futures), International
Crops Research Institute for the Semi-Arid Tropics, Patancheru 502 324, Andhra Pradesh, India,
c.bantilan@cgiar.org
Kimberly R. Chung, Assistant Professor, Department of Community, Agriculture, Recreation and
Resource Studies, 323 Natural Resources Building, Michigan State University, East Lansing, Michigan
48823, USA, kchung@msu.edu
Boru Douthwaite, Technology Policy Analyst, Centro Internacional de Agricultura Tropical, AA
6713, Cali, Colombia, b.douthwaite@cgiar.org
Pay Drechsel, Senior Researcher, Head, West Africa Office, International Water Management Institute,
PMB CT 112, Cantonments, Accra, Ghana, p.drechsel@cgiar.org
R.S. Dwivedi, Head, Sustainable Agriculture Division, National Remote Sensing Agency, Department
of Space, Government of India, Balanagar, Hyderabad 500 037, Andhra Pradesh, India, dwivedi_rs@nrsa.
gov.in
Javier M. Ekboir, Consultant Economist – at time of meeting – Centro Internacional de Mejoramiento
de Maíz y Trigo, AP 6-641 06600 Mexico, D.F. Mexico, jekboir@prodigy.net.mx
Thomas Enters, National Forest Programme Facilitator, Food and Agriculture Organization of the
United Nations, Regional Office for Asia and the Pacific, Maliwan Mansion, 39 Phra Atit Road, Bangkok
10200, Thailand, thomas.enters@fao.org
H. Ade Freeman, Director, Targeting Opportunities Theme, International Livestock Research Institute,
PO Box 30709, Nairobi, Kenya, h.a.freeman@cgiar.org
Mark Giordano, Senior Researcher (Resource Policy), International Water Management Institute, PO
Box 2075, Colombo, Sri Lanka, mark.giordano@cgiar.org
H.M. Gregersen, Chair, Standing Panel on Impact Assessment, Science Council, CGIAR, PO Box
498, Solvang, California 93464, USA, h.gregersen@cgiar.org
Stein T. Holden, Professor, Department of Economics and Resource Management, Agricultural
University of Norway, PO Box 5033, N-1432 Ås, Norway, stein.holden@ior.nlh.no
xiii
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xiv Contributors
P.K. Joshi, Research Fellow and South Asia Coordinator, Markets, Trade and Institutions Division,
International Food Policy Research Institute, Pusa Campus, CG Center Block, NASC Complex, Deva
Prakash Sastri Marg, New Delhi 110 012, India, p.joshi@cgiar.org
J.D.H. Keatinge, Deputy Director General (Research), International Crops Research Institute for the
Semi-Arid Tropics, Patancheru 502 324, Andhra Pradesh, India, d.keatinge@cgiar.org
T.G. Kelley, Senior Officer, CGIAR Science Council Secretariat, Sustainable Development Division,
Food and Agriculture Organization of the United Nations (FAO), vialle Terme di Caracalla, Rome, Italy
00100, timothy.kelley@fao.org
John M. Kerr, Assistant Professor, Department of Community, Agriculture, Recreation and Resource
Studies, 323 Natural Resources Building, Michigan State University, East Lansing, Michigan 48823,
USA, jkerr@msu.edu
H. Lofgren, Senior Research Fellow, Development Strategy and Governance Division, International Food
Policy Research Institute, 2033 K Street, NW, Washington, DC, 20006-1002, USA, h.lofgren@cgiar.
org
R.R. Navalgund, Director, National Remote Sensing Agency, Department of Space, Government of
India, Balanagar, Hyderabad 500 037, Andhra Pradesh, India, rangnath@nrsa.gov.in
S. Navrud, Associate Professor, Department of Economics and Resource Management, Agricultural
University of Norway, PO Box 5033, N-1432 Ås, Norway, stale.navrud@ior.nlh.no
K.V. Padmaja, Visiting Scientist (Environmental Sciences), International Crops Research Institute for
the Semi-Arid Tropics, Patancheru 502 324, Andhra Pradesh, India, k.padmaja@cgiar.org
P. Pathak, Principal Scientist (Soil and Water Management), International Crops Research Institute
for the Semi-Arid Tropics, Patancheru 502 324, Andhra Pradesh, India, p.pathak@cgiar.org
John Pender, Senior Research Fellow, Environment and Production Technology Division, International
Food Policy Research Institute, 2033 K Street, NW, Washington, DC, 20006-1002, USA, j.pender@cgiar.
org
A. Ramakrishna, Senior Scientist (Agronomy), International Crops Research Institute for the Semi-
Arid Tropics, Patancheru 502 324, Andhra Pradesh, India, a.ramakrishna@cgiar.org
T.J. Rego, Principal Scientist (Soil Science), International Crops Research Institute for the Semi-Arid
Tropics, Patancheru 502 324, Andhra Pradesh, India, t.rego@cgiar.org
K.L. Sahrawat, Visiting Scientist (Soil Chemistry), International Crops Research Institute for the
Semi-Arid Tropics, Patancheru 502 324, Andhra Pradesh, India, k.sahrawat@cgiar.org
Bekele Shiferaw, Senior Scientist (Resource and Development Economics), International Crops Research
Institute for the Semi-Arid Tropics, PO Box 39063, Nairobi, Kenya (formerly at ICRISAT, Patancheru
502 324, Andhra Pradesh, India), b.shiferaw@cgiar.org
Piara Singh, Principal Scientist (Soil Science), International Crops Research Institute for the Semi-Arid
Tropics, Patancheru 502 324, Andhra Pradesh, India, p.singh@cgiar.org
Scott M. Swinton, Professor, Department of Agricultural Economics, 304 Agriculture Hall, Michigan
State University, East Lansing, Michigan 48824-1039, USA, swintons@msu.edu
Steve Twomlow, Principal Scientist (Soil Science) and Theme Leader (Agro-ecosystem Development),
International Crops Research Institute for the Semi-Arid Tropics, PO Box 776, Bulawayo, Zimbabwe,
s.twomlow@cgiar.org
S.P. Wani, Principal Scientist (Watersheds) and Regional Theme Coordinator (Agro-ecosystem
Development), International Crops Research Institute for the Semi-Arid Tropics, Patancheru 502 324,
Andhra Pradesh, India, s.wani@cgiar.org
Prelims.indd 14 01 Nov 2004 5:16:04 AM
Reviewers
Tony Addison, World Institute for Development Economics Research, Finland
Jeffrey Apland, University of Minnesota, USA
Samuel Benin, International Food Policy Research Institute (IFPRI), Uganda
Marrit van den Berg, Wageningen University and Research Centre, The Netherlands
Bruce Campbell, Centre for International Forestry Research (CIFOR), Bogor, Indonesia
Peter Cooper, International Development Research Centre (IDRC), Canada
Robert Delve, Centro Internacional de Agricultura Tropical (CIAT), Uganda
John Dixon, Food and Agriculture Organization of the United Nations (FAO), Italy
Simeon Ehui, The World Bank, USA
Thomas Enters, Food and Agriculture Organization of the United Nations (FAO), Thailand
Robert Evenson, Department of Economics, Yale University, USA
Berhanu Gebremedhin, International Livestock Research Institute (ILRI), Ethiopia
Francis Gichuki, International Water Management Institute (IWMI), Sri Lanka
Meredith Giordano, International Water Management Institute (IWMI), Sri Lanka
Solveig Glomsråd, Central Bureau of Statistics, Norway
Douglas Gollin, Williams College, USA
Fitsum Hagos, Mekelle University, Ethiopia
Andy Hall, United Nations University – Institute for New Technologies (UNU–INTECH), The
Netherlands
Stein Holden, Agricultural University of Norway, Norway
Nancy Johnson, Centro Internacional de Agricultura Tropical (CIAT), Colombia
John M. Kerr, Michigan State University, USA
Gideon Kruseman, Wageningen University and Research Centre, The Netherlands
Mywish Maredia, Michigan State University, USA
Kelly F. Millenbaugh, Michigan State University, USA
Michael Morris, Centro Internacional de Mejoramiento de Maíz y Trigo (CIMMYT), Mexico
xv
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xvi Reviewers
George Norton, Virginia Polytechnic Institute and State University, USA
Suresh Pal, National Centre for Agricultural Economics and Policy Research (NCAP), India
Julian Park, The University of Reading, UK
John Pender, International Food Policy Research Institute (IFPRI), USA
Frank Place, World Agroforestry Centre (ICRAF), Kenya
Roberto Quiroz, Centro Internacional de la Papa (CIP), Peru
David Rohrbach, International Crops Research Institute for the Semi-Arid Tropics (ICRISAT),
Zimbabwe
Eirik Romstad, Agricultural University of Norway, Norway
Ruerd Ruben, Wageningen University and Research Centre, The Netherlands
John Sanders, Department of Agricultural Economics, Purdue University, USA
Nteranya Sanginga, Tropical Soil Biology and Fertility Institute (TSBF)–Centro Internacional de
Agricultura Tropical (CIAT), Kenya
Christopher Scott, International Water Management Institute (IWMI), India
Keith Shepherd, World Agroforestry Centre (ICRAF), Kenya
Katar Singh, India Natural Resource Economics and Management Foundation, India
S. Subrahmanyam, Centre for Economic and Social Studies, India
Aysen Tanyeri-Abur, Food and Agriculture Organization of the United Nations (FAO), Italy
Hermann Waibel, Universität Hannover, Germany
Roger White, International Centre for Integrated Mountain Development (ICIMOD), Nepal
Ada Wossink, North Carolina State University, USA
T.J. Wyatt, United States Environmental Protection Agency, USA
Prelims.indd 16 01 Nov 2004 5:16:04 AM
Part I.
Introduction
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Pg1_16 Chap1.indd 2 01 Nov 2004 5:17:26 AM
Assessing the Impacts of
Natural Resource Management
Interventions in Agriculture:
Concepts, Issues and Challenges
H.A. Freeman1, B. Shiferaw2 and S.M. Swinton3
1 International Livestock Research Institute (ILRI), Nairobi, Kenya
2 International Crops Research Institute for the Semi-Arid Tropics (ICRISAT),
Nairobi, Kenya
3 Michigan State University, East Lansing, Michigan, USA
Introduction
One of the greatest development challenges facing the world in the 21st century
is meeting the rising demand for food while maintaining the sustainability of
the natural resource base. Increases in per capita income, population growth
and urbanisation are expected to double global food demand in the next
40–50 years. The demand for cereals is estimated to increase from 1.9 billion
tonnes (t) in 1997 to 2.5 billion t by 2020 and for meat from 209 million t to 327
million t (Rosegrant et al., 2001). These trends in food demand have important
implications for natural resources that provide essential support to life and
economic processes.
Natural resource management (NRM) aims for the efficient and
sustainable utilisation of renewable and non-renewable natural resources. In
the context of this book, NRM in agriculture refers to human administration
and sustainable utilisation of biophysical resources for the production of
food, feed, fibre and fuel. Production in this sense entails direct husbandry,
including such activities as aquaculture and planted forests, but does not
include hunting, fishing and gathering of uncultivated species. Natural
resources of interest include all those affected by the production process
(e.g. soil, water, biodiversity, fish and forests). Accordingly, depending on
the resource and environmental service flows affected, impact assessment
of NRM in agriculture includes the associated changes in the environmental
impacts of agricultural production.
Well-managed natural resources generate flows of benefits that provide
the basis for maintaining and improving livelihoods, improve the quality
©CAB International 2005. Natural Resource Management in Agriculture:
Methods for Assessing Economic and Environmental Impacts
(eds B. Shiferaw, H.A. Freeman and S.M. Swinton) 3
Pg1_16 Chap1.indd 3 01 Nov 2004 5:17:26 AM
4 H.A. Freeman et al.
of life, and contribute to sustainable growth. Agricultural production
worldwide mostly depends on soil, providing the most important source of
livelihoods for the majority of rural people in the developing world. Water is
essential for sustaining human populations and, indeed, all species. It is also
a key input in agricultural and industrial production and processing as well
as an important sink for discharging waste. Fish are an important biological
resource that account for 20% of the animal-derived protein consumption in
low-income countries and about 13% in the developed countries (Delgado et
al., 2003). With increasing intensification of food production, aquaculture is
becoming an important source of income and livelihoods in many parts of the
world. Forests and forest resources, including agroforestry and tree crops,
provide a source of livelihoods for over 1.6 billion people worldwide. Forests
also contain at least 80% of the remaining global biodiversity, they help to
protect water resources, and they are a significant carbon sink mitigating
climate change (World Bank, 2001). Biodiversity enables animal and crop
improvement programmes that maintain and increase productivity. Properly
managed natural resources provide an essential foundation for reducing
poverty and promoting sustainable growth.
However, the combined effects of population growth, higher levels of
economic activity per capita, and mismanagement are putting increasing
pressure on the natural resource base. There is abundant evidence of natural
resources degradation worldwide. Over the past 45 years an estimated 1.2
billion ha has been degraded as a result of human activity. This affects more
than 900 million people in 100 countries. Erosion, salinisation, compaction,
and other forms of degradation afflict 30% of the world’s irrigated lands, 40%
of rainfed agricultural lands, and 70% of rangelands. Every year an additional
12–15 million ha of forests are lost to deforestation. The world is facing a
systemic water crisis resulting from the unsustainable use and management
of water resources. New threats and challenges to water supplies arise from
urbanisation, over-extraction of surface and ground water, pollution, and
loss of aquatic biodiversity (World Bank, 2001).
Degradation of natural resources has real economic, social, and human
costs with substantial impacts on national economies. It also directly
threatens the long-term growth of agricultural productivity, food security,
and the quality of life, particularly in developing countries. Investments in
agricultural research have resulted in dramatic increases in food production
generated from higher-yielding crop varieties with improved resistance to
pests and diseases, mostly in areas of high agricultural potential in developing
countries. The dramatic increase in production of rice, maize and wheat,
referred to as the Green Revolution – was credited with averting widespread
per capita food shortages and starvation in the later half of the 20th century,
particularly in Asia and Latin America. The short-term crop productivity gains
of the Green Revolution are however associated with long-term degradation
of soils, water, biodiversity, and marginal lands. Pingali and Rosegrant
(1998) provided empirical evidence linking the intensification of rice–wheat
systems in the Indo-Gangetic plains of South Asia to the build up of salinity
and waterlogging, depletion of groundwater resources, formation of hard
Pg1_16 Chap1.indd 4 01 Nov 2004 5:17:26 AM
Assessing the Impacts of NRM Interventions in Agriculture 5
pans, soil nutrient deficiencies, and increased incidence of soil toxicity. Thus,
while improving agricultural productivity is an essential component in many
poverty-reduction and growth strategies, degradation of natural resources
can threaten the achievement of this objective.
Natural resource degradation is particularly costly for the poor. Poor
people often depend directly on natural resources for their livelihoods,
making them especially vulnerable when natural resources lose their
productive potential. There is growing awareness that sustainable use of
natural resources can contribute to poverty alleviation and improvements
in human welfare. Project, programme, or policy interventions that improve
the management of natural resources can lead to significant economic gains
that directly benefit poor people, resulting in substantial improvements in
their welfare.
The linkages between sustainable management of natural resources and
improvements in the well being of the poor have contributed to a resurgence
in development lending and research investments on environment and
NRM over the past two decades. The World Bank, for example, is increasing
lending for environment and NRM issues after a period of decline over the
last few years. In 2003 US$1.1 billion was allocated for environmental and
NRM issues, representing 6% of overall lending, an increase from 4.7% in
2002 (World Bank, 2003). Similarly, international organisations focusing on
sustainable increase in agricultural productivity and improvement in rural
livelihoods such as the Consultative Group on International Agricultural
Research (CGIAR), have increased the share of NRM research in their overall
research portfolio (Kelley and Gregersen, Chapter 15, this volume). Between
1994 and 2001, CGIAR research investments in protecting the environment
rose from 15 to 19% of total resource allocation, while investment on
biodiversity almost doubled from 6 to 11% (Barrett, 2003). These trends in
resource allocation generally reflect the growing consensus that the objectives
of poverty alleviation, food security, and sustainable management of natural
resources are highly interdependent.
This chapter identifies key issues involved in assessing the impacts
of NRM interventions. Such interventions include adoption of changed
NRM practices arising from investments in research and outreach that are
implemented through NRM projects, programmes, and policies. The focus is
on impact analysis of NRM interventions, not on conducting NRM projects
per se. The next sections discuss the purposes of impact assessment, followed
by the underlying concepts and techniques for conducting impact assessment.
This is followed by a discussion of the special challenges that complicate
impact assessment of NRM interventions. The chapter ends by providing
an overview of the conceptual and empirical approaches for NRM impact
assessment.
Pg1_16 Chap1.indd 5 01 Nov 2004 5:17:26 AM
6 H.A. Freeman et al.
Why Assess NRM Impacts?
Impact assessment should enhance the understanding of the extent to which
project, programme, and policy interventions affect the target population
and the magnitude of these intervention effects on the welfare of the intended
beneficiaries. Resources are limited and managers in research and development
institutions are under pressure to allocate available resources efficiently and
effectively.
Impact assessment, whether it is backward-looking, evaluating the
impact of past research and development (R&D) investments (ex post impact
assessment) or forward-looking, evaluating the impact of current and future
R&D investments (ex ante impact assessment) should help in setting priorities
over competing interventions and inform policy decisions on efficient
allocation of scarce resources.
Impact assessment can be used to measure the outcomes and impact
of development interventions, aiming to discern intervention effects from
the influence of other external factors. As noted above, this is particularly
challenging with NRM interventions.
Donors, policy makers, and development managers need information to
monitor progress in achieving outputs and outcomes, providing a basis to
demonstrate results, and strengthening accountability for results that may
justify continued funding. Often, broad indicators of impact such as aggregate
rates of returns to investments and benefit–cost ratios are used as indicators to
provide evidence of the effectiveness of past and future interventions. These
indicators are used to make decisions on whether to expand, adjust, or drop
project, programme, or policy interventions. Ex post evaluation also provides
lessons that could be used to improve the design and management of service
delivery and other future interventions. Comprehensive impact assessment
that includes both productivity and environmental and sustainability
impacts provides an objective basis for comparing the effectiveness of
alternative interventions in achieving the stated welfare and sustainability
objectives. Such information is useful for planning, setting priorities, and
allocating resources to alternative interventions. However, evaluating the
actual livelihood and poverty impacts of agricultural and NRM interventions
would require analysis of distributional and equity impacts in addition
to computation of such simple efficiency indicators as net present values,
benefit–cost ratios, and internal rates of return. New methods and approaches
are needed to extend traditional impact assessments to address such policy-
relevant concerns.
R&D organisations are increasingly interested in assessing a broad range of
impacts from NRM interventions. This, however, requires examining a range
of multi-dimensional impacts that may include impacts on the quality of the
resource base as well as the flow of ecosystem services that provide basic life
support functions in agro-ecosystems. These non-market benefit objectives
imply that conventional economic impact analyses are fundamentally
incompatible with measuring the benefits that NRM projects seek to obtain.
Methodological development in the approaches and techniques for valuation
Pg1_16 Chap1.indd 6 01 Nov 2004 5:17:27 AM
Assessing the Impacts of NRM Interventions in Agriculture 7
of ecosystem and environmental goods and services is enabling assessment
of environmental impacts associated with NRM interventions that have been
largely neglected in past impact assessment studies.
Nevertheless, methods for assessing the multi-faceted impacts from NRM
interventions are far less developed than methods for assessing impact for
crop improvement research (Izac, 1998; Shiferaw and Freeman, 2003). This
explains, in part, the dearth of credible quantitative evidence, ex ante or ex post,
that assesses the impact of NRM research compared to the evidence on the
effects of crop improvement research. For example, of the 1886 rates of return
on research investment reviewed by Alston et al. (2000) over 50% were for
crops research, while NRM research accounted for less than 5%. The limited
number of studies on NRM impact assessment, despite the increased interest
on sustainability issues, suggests that tracing the practical linkages between
NRM interventions with changes in the resource base, the environment, and
human welfare is fraught with complexities (Nelson and Maredia, 1999). The
specific challenges and empirical difficulties that impact evaluators face in
undertaking valid and plausible assessment of NRM impacts are discussed
below.
Impact Assessment: Concepts and Processes
In the literature, the term ‘impact assessment’ is used interchangeably with
‘impact evaluation’. Impact assessment determines the welfare changes from
a given intervention on individuals, households and institutions and whether
those changes are attributable to the project, programme, or policy intervention
(Baker, 2000; World Bank, 2002).
Impact assessments are often undertaken ex ante, evaluating the impact
of current and future interventions, or ex post, evaluating the impact of past
intervention. Impact assessment can also be made concurrently within the
project cycle. Ex ante assessment intends to inform policy decisions as to
whether a proposed project or programme intervention should be carried
out at all. Such evaluations gather information on the likely economic and
environmental impacts and how the flow of costs and benefits is distributed
across the affected populations. The distributional impacts and identification
of winners and losers are critical elements in evaluating the social impacts
of proposed interventions. The ex ante assessment compares the expected
benefits and costs over time along with the anticipated social impacts. Such
information is often used to prioritise interventions and inform policy choice
as to whether the expected social benefits would outweigh the costs – to
justify implementation of proposed interventions. Ex post impact assessments
gener-ally intend to measure realised benefits and costs of programme
interventions to see whether stated objectives have been met and whether
the realised benefits indeed outweigh the direct and indirect costs incurred.
Ex post assessment also attempts to understand the pathway through which
observed impacts have occurred and why interventions fail or succeed in
attaining stated objectives. Hence, ex post assessments can inform policy
Pg1_16 Chap1.indd 7 01 Nov 2004 5:17:27 AM
8 H.A. Freeman et al.
choices as to whether related planned programme interventions should be
discontinued, modified, improved or sustained in the future.
An important aspect of impact assessment is to understand how
interventions affect the beneficiaries or affected populations and whether
any outcomes and improvements are a direct result of the intervention. An
intervention will not enhance economic efficiency unless the realised or
anticipated benefits exceed the overall costs. In cases where the desired impact
is not being achieved, the evaluation can also provide useful information on
how the programme design could be improved.
Measuring project outcomes alone is not sufficient to assess impacts. In
many cases, there may be other factors or events that affect outcomes other than
the project itself. For example, if an agroforestry outreach project is initiated
and shortly thereafter the national government ceases to subsidise imported
fertiliser, farmers may begin to rely upon agroforestry methods to meet crop
nutritional needs. In order to measure the real impact of the agroforestry
outreach intervention, it is important to control for other confounding factors
such as the subsidy termination, and to net out those outcomes that can be
attributed only to the intervention itself. This means that impact assessment
must estimate the counterfactual, i.e. what would have happened had the
intervention never taken place.
Determining the counterfactual is at the core of evaluation design
(Baker, 2000). Three broad quantitative methods can be used to identify an
appropriate counterfactual (Heckman and Robb, 1985; Heckman and Smith,
1995), including estimation methods used with randomised experimental
design, non-randomised quasi-experimental methods, and non-experimental
designs.
In the experimental design approach, groups are selected randomly from
the same population as the programme participants, while the control group
is randomly assigned among those who do not receive the programme. The
control group should resemble the treatment group in every sense, with
the only difference between the two being the presence of the programme
intervention in the treatment group. The main benefit of this technique is the
simplicity in interpreting the results – intervention impact can be estimated
by the mean difference between the treatment and control groups. While
the experimental design is considered the ideal and most robust approach
to estimating intervention impacts, it has several disadvantages. Firstly,
randomisation, which involves denial of benefits for a certain group of
people, may not be ethically acceptable for many interventions. Secondly,
randomisation may not be politically acceptable. Thirdly, the proposed
project, programme or policy may have economy-wide effects that make
randomisation unfeasible. Fourthly, experimental designs may be technically
impossible (e.g. due to mobile populations) or expensive and tedious to
implement.1 These difficulties often limit the practical usefulness of the
experimental design approach for establishing a valid counterfactual.
Quasi-experimental designs such as matching, reflexive comparison, and
double difference methods, and non-experimental designs, such as instrumental
variables methods, can be used when it is not possible to construct
Pg1_16 Chap1.indd 8 01 Nov 2004 5:17:27 AM
Assessing the Impacts of NRM Interventions in Agriculture 9
treatment and comparison groups through experimental design. Matching
involves identifying non-programme participants comparable in essential
characteristics to programme participants to be matched on the basis of
common characteristics that are believed to influence programme outcomes.
The propensity score matching approach that is based on the predicted
probability of participation given observed characteristics is the most
commonly used approach for matching. The reflexive comparison method
compares programme participants before and after the programme. The
double difference method compares both programme participants and non-
participants before and after the programme. Instrumental variables consist
of using ‘instruments’ that matter to participation but not to outcomes given
participation, allowing identification of exogenous variation in outcomes
attributable to the programme, while recognising that its placement may not
be random but purposive. Instrumental variables are first used to predict
programme participation; then the programme impact is estimated using
predicted values from the first equation (Baker, 2000).
Selection bias is a major challenge to measuring programme impacts in
non-experimental settings. Selection bias occurs when pre-existing conditions
skew outcomes in a way that is not truly attributable to the programme
intervention. For example, if farmers with the best land adopt a practice
of soil conservation faster than farmers with poor land, the yield gain they
achieve may exceed what other farmers could expect, due to their higher
land quality. When bias exists, the assessment may provide inaccurate results
that could lead to erroneous inferences and conclusion about the impacts of
the intervention (Friedlander and Robins, 1995). Randomised experiments
avoid selection bias through random selection. The quasi-experimental and
non-experimental designs must rely upon statistical methods to minimise
bias due to non-random data. Certain statistical methods allow comparison
of programme participants and non-participants while controlling for the
process of selection (Pender, Chapter 6, this volume; Greene, 1997; Baker,
2000). However, these methods tend to be less robust statistically than ones
that use experimental data. Moreover, the statistical methods for correcting
selection bias can be quite complex (e.g. Kerr, 2001), and it is often difficult to
fully correct for it in practice (Baker, 2000).
Qualitative methods are also used for impact assessment. Such methods
seek to determine impacts by relying on methods other than the counterfactual
(Mohr, 1995). Qualitative approaches involve understanding the processes,
behaviours and conditions surrounding NRM interventions. Often qualitative
methods are participatory, relying upon the perceptions of the individuals or
groups being studied (Valadez and Bamberger, 1994). Qualitative approaches
tend to use open-ended designs for data collection, including focus group
discussions, key informant surveys, and participatory appraisals. Examples
can be found in Chapters 11 (Bantilan et al.) and 14 (Douthwaite et al.) in this
volume. Commonly used analytical tools include stakeholder analysis and
beneficiary assessment. Qualitative approaches provide insights into the way
in which households and communities perceive a project and how they feel
affected by it. Qualitative methods can be simple, quick, flexible, and tailored
Pg1_16 Chap1.indd 9 01 Nov 2004 5:17:27 AM
10 H.A. Freeman et al.
to specific socio-economic conditions. However the subjectivity involved in
data collection, the lack of a counterfactual and limited statistical rigour make
the results less conclusive and more difficult to generalise than quantitative
assessments.
Qualitative approaches are increasingly used in conjunction with
quantitative approaches (Baker, 2000), and such combinations can enhance
the validity and reliability of impact evaluations (Bamberger, 2000). While
quantitative approaches allow statistical tests for causality and isolation
of programme effects from other confounding influences, qualitative
methods allow in-depth study of selected issues and help the evaluator find
explanations for the results obtained in the quantitative analysis. In short,
quantitative methods excel at answering impact assessment questions about
‘what’ and ‘how much’, whereas qualitative methods are preferred for
exploring questions of ‘how’ and ‘why’. A mix of quantitative and qualitative
approaches is ideal because it provides the quantifiable impacts of the
intervention as well as an explanation of the processes and relationships that
yielded such outcomes.
The evaluation design chosen for NRM impact assessment needs to capture
the special features, complexities and multiple outcomes associated with such
interventions. For example, assessing the impacts of NRM technology and
policy interventions requires accounting for both the tangible and the less-
tangible and diffuse productivity and environmental impacts. The process of
tracking these relationships and impact pathways may involve several steps.
Nelson and Maredia (1999) discussed five steps in assessing environmental
costs and benefits in NRM projects. These steps involve:
• Understanding the causes and impact of changes in the use of natural re-
sources such as declining soil fertility, land degradation, water pollution,
deforestation, loss of biodiversity, etc.
• Identifying the main types of economic costs and benefits. Economic costs
could include depletion of the stock of natural resources and species loss-
es. An important consideration is to identify the distribution of the burden
of these costs over time and space and across affected communities
• Determining whether or not there is a means to measure costs and benefits
in monetary terms
• Assessing the extent of changes in the use of natural resources and the
environmental consequences resulting from these changes. This includes
collecting data to estimate the impact of environmental effects on such
indicators as productivity, income, and human health
• Using economic techniques to place values on environmental changes.
Key biophysical processes and related indicators of NRM status are
explored in this volume with foci on the soil (Pathak et al., Chapter 3), water
resources (Sahrawat et al., Chapter 4), and ecosystem services (Wani et al.,
Chapter 5). Shiferaw et al. (Chapter 2), discuss several methods for placing
economic values on non-market ecosystems services, while Drechsel et al.
(Chapter 9) provide examples of applying some of the commonly used
valuation methods to valuing changes in soil fertility.
Pg1_16 Chap1.indd 10 01 Nov 2004 5:17:27 AM
Assessing the Impacts of NRM Interventions in Agriculture 11
Challenges in NRM Impact Assessment
Apart from the general challenges of attribution and selection bias in impact
analysis, there are special conceptual and methodological challenges that
arise from several unique features of natural resource management. NRM
impact assessment needs to address important challenges of attribution,
measurement, spatial and temporal scales, multidimensional outcomes, and
valuation. The cross-commodity and integrated nature of NRM interventions
makes it very challenging to attribute impact to any particular one among
them. In crop genetic improvement where the research outputs are embodied
in an improved seed, it is less difficult to attribute yield improvements to
the investment in research. Changes in NRM frequently involve observable
research products adopted by farmers as well as qualitative information
about recommended management practices. Knowledge about such
improved management practices may be transmitted through formal and
informal outreach activities and by the self-experimentation and indigenous
knowledge of the farmers themselves. In many cases, for such knowledge
and information-based changes in NRM practices, it is difficult to identify the
impacts attributable to the intervention. Also, it is not uncommon for different
agencies to be involved in the development and promotion of new NRM
technologies, making it hard to separate the impacts attributable to specific
programmes. For example, in the evaluation of watershed programmes in
India, it was difficult to attribute improvements in resource conditions and
farm incomes to specific interventions, since increased participation and
collaboration among a range of R&D partners was identified as a significant
determinant of success (Kerr, 2001). The fact that most agricultural NRM
interventions are information-based but not embodied in an easily measured
package vastly complicates the attribution of observed impacts.
Identifying an appropriate counterfactual in NRM interventions is
particularly challenging because quantifying the biophysical impacts of
interventions on natural resources can be costly, imprecise, and slow. For
NRM interventions that aim to halt resource degradation, the counterfactual
may be a significant productivity decline. Hence, a properly measured
counterfactual may reveal that achieving non-declining productivity represents
a major gain over what would otherwise have occurred.
Identifying appropriate spatial boundaries for assessing NRM impact is
often fraught with difficulty (Campbell et al., 2001; Sayer and Campbell, 2001).
Agricultural NRM typically involves different spatial scales, from farmers’
fields to entire watershed catchments, implying that many levels of interaction
may need to be considered in assessing the impacts of research interventions.
Multiple scales of interaction create upstream and downstream effects that
complicate impact assessment. For example, assessing the impact of land
use interventions in a watershed may need to take into account multiple
interactions on different scales because erosion and runoffs in the upper
watershed may not have the same impact on water quality downstream. It
is also likely that interventions could have different effects, which in some
cases can generate opposite impacts on different spatial scales. For example,
Pg1_16 Chap1.indd 11 01 Nov 2004 5:17:27 AM
12 H.A. Freeman et al.
soil and water conservation interventions can have a positive impact on
crop yields upstream but negative impacts by reducing water availability
downstream when water is a limiting factor for production, or positive
impacts by reducing sedimentation, runoff and flooding when water is not
a limiting factor.
In the temporal dimension, methodological challenges for NRM impact
assessment arise from slow-changing variables and substantial lags in the
distribution of costs and the benefits. For example, soil loss, exhaustion of
soil fertility, and depletion of groundwater resources take place gradually
and over a long period of time. In some cases it may be difficult to perceive
the costs or the benefits of interventions to reverse these problems. In other
cases, assessing the full range of the impacts of investments related to
these slow-changing variables in a holistic manner may involve intensive
monitoring of multiple biophysical indicators on different spatial scales over
long periods of time. These factors make impact monitoring and assessment
of NRM interventions a relatively slow and expensive process. Differences
in time scale for the flow of costs and benefits are translated into lags in the
distribution of costs and benefits that complicate impact assessment. Typically,
costs are incurred up-front while delayed benefits accrue in incremental
quantities over a long period of time (Pagiola, 1996; Shiferaw and Holden,
2001). For example, the benefits from the biodiversity that is used in genetic
improvement of crop and animal varieties accrue in the long term but costs
of in situ and ex situ conservation are incurred in the short term. The timing
of an intervention can also affect its impact. This is, for example, the case for
improved crop management practices that require optimising sowing date,
fertiliser application, weeding and harvesting.
When outcomes are delayed and tend to vary according to local
biophysical conditions, simulation models can facilitate the ex ante evaluation
of NRM technology options that fit micro-climatic and agro-ecological niches.
Biophysical process models are mainly used to explore the biophysical and
productivity impacts of changes in agricultural and NRM practices (Wani et
al., Chapter 5, this volume). Bioeconomic models, on the other hand, interlink
economic and biophysical information to simulate optimal resource use
and investment behaviour (Holden, Chapter 8, this volume; Shiferaw and
Holden, Chapter 12, this volume). Both kinds of models require biophysical
and experimental agronomic data to calibrate and validate them to local
conditions.
NRM interventions may generate multidimensional biophysical
outcomes across resource, environmental and ecosystem services. These
might include changes in the quality and movement of soil, quantity and
quality of water, sustainability of natural resources, and conservation of
biodiversity. Appropriate indicators are needed to monitor the impacts of
NRM interventions on the biophysical conditions of the soil (Pathak et al.,
Chapter 3, this volume), water resources (Sahrawat et al., Chapter 4, this
volume), and the flow of ecosystem services that support agro-ecosystems
(Wani et al., Chapter 5, this volume). The multidimensionality of outcomes
from NRM interventions means that impact assessment often faces difficult
Pg1_16 Chap1.indd 12 01 Nov 2004 5:17:27 AM
Assessing the Impacts of NRM Interventions in Agriculture 13
measurement challenges, including very different measurement units and
potentially the integration of very different natural resource outputs into
some kind of uniform aggregate yardstick (Byerlee and Murgai, 2001).
The multidimensionality of NRM outcomes extends to those directly
or indirectly affecting human beings. NRM interventions can generate
environmental and health benefits whose values might not be reflected in
current markets, but on which society places a value for multiple reasons. For
example, water and water-based ecosystems provide not only direct values
in consumptive uses (e.g. fishing, irrigation) and non-consumptive uses (e.g.
aesthetic value), but also indirect use values such as ecosystem functions and
services, option values for possible future uses and applications and non-
use values for intrinsic significance (existence and heritage value). Empirical
valuation of non-market benefits is explored by Shiferaw et al. (Chapter 2,
this volume). But depending on how NRM ideas are conveyed, the human
outcomes may extend even further. Integrated NRM projects engage in
participatory activities that may empower individuals and communities in
ways that extend far beyond the realm of agricultural NRM, as discussed by
Douthwaite et al. (Chapter 14, this volume).
Approaches for Assessing NRM Impacts
Impact assessment for NRM interventions ultimately needs to show the social
costs and benefits associated with the research, promotion, and adaptation of
these interventions. Given the complexities and challenges associated with
measuring, monitoring and valuing such changes, more innovative assessment
methods are required. An important factor that needs to be considered in
the selection of appropriate methods is the capacity to account for non-
monetary impacts that NRM interventions generate in terms of changes in
the flow of resource and environmental services that affect sustainability and
ecosystem health. As discussed earlier, a mix of quantitative and qualitative
methods may be the optimal approach for capturing on-site and off-site
monetary and non-monetary impacts. The economic surplus approach is the
commonly used method for evaluating the impacts of agricultural research
investments, particularly for crop improvement technologies. This approach
estimates benefits as changes in `economic surplus’ (the aggregate value that
consumers are willing to pay above and beyond what it costs producers to
supply the good or service in question). The cumulative benefits are then
compared to cumulative R&D costs over time. Specifics and the challenges
of incorporating non-marketed on-site effects and off-site externalities are
discussed by Swinton (Chapter 7, this volume), with Bantilan et al. (Chapter
11, this volume) providing an empirical application.
Promising analytical methods that can be used to quantify economic
changes due to NRM interventions include econometrics (Alston et al.,
1995) and bioeconomic optimisation modelling. For example, econometric
methods can be used in empirically estimating the demand for marketed
or certain non-marketed goods and services, providing elasticities for
Pg1_16 Chap1.indd 13 01 Nov 2004 5:17:27 AM
14 H.A. Freeman et al.
calculations of economic surplus. Econometric methods can also be used to
link a time-series of measures of output, costs and profits directly to past
R&D investments (Alston et al., 1995). Likewise, they can be used to establish
statistical relationships between changes in NRM practices and measured
performance indicators, such as land productivity, total factor productivity,
production costs, net farm income, or income volatility. Pender (Chapter 6,
this volume) discusses the conceptual and empirical issues while Kerr and
Chung (Chapter 10, this volume) provide an empirical application of this
method.
Bioeconomic modelling nests essential biophysical processes within
economic behavioural models. Their constrained optimisation perspective
allows evaluating how technological and/or policy changes would affect
economic welfare, sustainability, and environmental conditions over time.
The integrated framework captures biophysical process evolution along with
rational human management responses. Holden offers a conceptual treatment
of bioeconomic modelling (Chapter 8, this volume), while Shiferaw and
Holden provide an empirical application for a farm household (Chapter 12,
this volume) and Holden and Lofgren demonstrate the use of an economy-
wide computable general equilibrium model for evaluating NRM technology
and policy impacts (Chapter 13, this volume).
As a response to the complexities that impact assessment practitioners
face in evaluating the multi-faceted impacts of NRM, there is an increasing
interest in developing more holistic and ‘softer’ assessment methods.
Integrated natural resource management (INRM) calls for participatory
NRM interventions at multiple scales with frequent adaptive feedback and
multiple stakeholders (who often hold contrasting objectives) (Campbell
et al., 2001; Sayer and Campbell, 2001). Douthwaite et al. (Chapter 14, this
volume) explore the conceptual underpinning of the INRM framework and
its implications for evaluating NRM impacts.
Organisation of the Book
The chapters in this book address the conceptual framework, methodological
challenges and selected empirical experiences of NRM impact assessment. In
so doing, they explore many of the complexities identified in this introductory
overview. The book’s 16 chapters are organised into five parts. Following this
initial part that introduces the challenges and approaches to NRM impact
assessment, Part II includes four chapters that deal with the valuation
of ecosystem services and the measurement of biophysical indicators of
NRM impacts. Part III introduces advances in methods used to evaluate
the economic and environmental impacts of NRM technology and policy
interventions. Part IV deals with NRM impact assessment in practice. Five
case studies illustrate the methodological advances discussed in Part III. The
final part of the book (Part V) highlights some of the existing controversies
and outlines best practices, research issues, and recommendations for NRM
impact assessment into the future.
Pg1_16 Chap1.indd 14 01 Nov 2004 5:17:27 AM
Assessing the Impacts of NRM Interventions in Agriculture 15
Endnote
1 One way to enhance ethical and political acceptability of randomisation is to phase the intervention
such that some groups gain access to programme benefits at a later stage. In this way the random
selection determines when a given group gains access to the benefit, not if they receive it.
References
Alston, M.J., Norton, W.G. and Pardey, P.G. (1995) Science Under Scarcity. Principles and
Practice for Agricultural Research Evaluation and Priority Setting. Cornell University
Press, Ithaca, New York, USA, and London, UK, 585 pp.
Alston, M.J., Chan-Kang, C., Marra, M.C., Pardey, P.G. and Wyatt, T.J. (2000) A meta-
analysis of rates of return to agricultural R&D: exe pede herculem? Research
Report 113. International Food Policy Research Institute (IFPRI), Washington,
DC, 159 pp.
Baker, J.L. (2000) Evaluating the Impacts of Development Projects on Poverty. A Handbook
for Practitioners. World Bank, Washington, DC, 230 pp.
Bamberger, M. (2000) Integrating Quantitative and Qualitative Methods in Development
Research. World Bank, Washington, DC, 189 pp.
Barrett, C.B. (2003) Natural Resources Management Research in the CGIAR: A Meta-
Evaluation in The CGIAR at 31: An Independent Meta-Evaluation of the Consultative
Group on International Agricultural Research. World Bank, Washington, DC, 217
pp.
Byerlee, D. and Murgai, R. (2001) Sense and sustainability revisited: the limits of total
factor productivity measures of sustainable agricultural systems. Agricultural
Economics 26(3), 227–236.
Campbell, B., Sayer, J.A., Frost, P., Vermeulen, S., Ruiz-Perez, M., Cunningham,
A. and Ravi, P. (2001) Assessing the performance of natural resource systems.
Conservation Ecology 5(2), 32. [online] http://www.ecologyandsociety.org/vol5/
iss2/art22/index.html
Delgado, C.L., Wada, N., Rosegrant, M.W., Meijer, S. and Ahmed, M. (2003) Outlook
for Fish to 2020. Meeting the Global Demand. International Food Policy Research
Institute, Washington, DC, 28 pp.
Friedlander, D. and Robins, P.K. (1995) Evaluating program evaluations: New
evidence on commonly used non-experimental methods. American Economic
Review 85, 923–937.
Greene, W.H. (1997) Econometric Analysis, 3rd edn. Prentice Hall, Upper Saddle River,
NJ, 1075 pp.
Heckman, J. and Robb, R. (1985) Alternative methods of evaluating the impact of
interventions: An overview. Journal of Econometrics 30, 239–267.
Heckman, J. and Smith, J.A. (1995) Assessing the case for social experiments. Journal
of Economic Perspectives 9(2), 85–110.
Izac, A.N. (1998) Assessing the Impact of Research in Natural Resources Management. The
World Agroforestry Centre (ICRAF), Nairobi, Kenya, 38 pp.
Kerr, J. (2001) Watershed project performance in India: conservation, productivity
and equity. American Journal of Agricultural Economics 83, 1223–1230.
Mohr, L.B. (1995) Impact Analysis for Program Evaluation, 2nd edn. Sage Publications,
Thousand Oaks, California, 336 pp.
Pg1_16 Chap1.indd 15 01 Nov 2004 5:17:28 AM
16 H.A. Freeman et al.
Nelson, M. and Maredia, M. (1999) Environmental Impacts of the CGIAR: An Initial
Assessment. Paper presented at the International Centers Week, October 25–
29, 1999, Washington, DC. Standing Panel for Impact Assessment, Food and
Agriculture Organization of the United Nations, Rome, Italy, 71 pp. [online]
http://www.sciencecouncil.cgiar.org/publications/pdf/envimp.pdf
Pagiola, S. (1996) Price policy and returns to soil conservation in semi-arid Kenya.
Environmental and Resource Economics 8, 251–271.
Pingali, P. and Rosegrant, M. (1998) Supplying wheat for Asia’s increasingly
westernized diets. American Journal of Agricultural Economics 80(5), 954–959.
Rosegrant, M., Paisner, M.S., Meijer, S. and Witcover, J. (2001) Global Food Projections
to 2020: Emerging Trends and Alternative Futures. IFPRI 2020 Vision. International
Food Policy Research Institute (IFPRI), Washington, DC, 206 pp.
Sayer, J.A. and Campbell, B. (2001) Research to integrate productivity enhancement,
environmental protection and human development. Conservation Ecology 5(2), 32.
[online] http://www.ecologyandsociety.org/vol5/iss2/art32/index.html.
Shiferaw, B. and Holden, S.T. (2001) Farm-level benefits to investments for mitigating
land degradation: empirical evidence from Ethiopia. Environment and Development
Economics 6, 335–358.
Shiferaw, B. and Freeman, H.A. (eds) (2003) Methods for Assessing the Impacts of Natural
Resource Management Research. A Summary of the Proceedings of an International
Workshop, 6–7 December 2002, International Crops Research Institute for the Semi-Arid
Tropics (ICRISAT), Patancheru, India, 136 pp.
Valadez, J. and Bamberger, M. (eds) (1994) Monitoring and Evaluating Social Programmes
in Developing Countries. The World Bank, Washington, DC, 536 pp.
World Bank (2001) Making Sustainable Commitments: An Environment Strategy for the
World Bank. World Bank, Washington, DC, 280 pp.
World Bank (2002) Understanding Impact Evaluation. World Bank, Washington, DC.
[online] http://www.worldbank.org/poverty/impact/index.htm
World Bank (2003) Environment Matters: Annual Review, July 2002 – June 2003. World
Bank, Washington DC. [online] http://lnweb18.worldbank.org/ESSD/envext.
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