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FISHERIES AND ECONOMIC WELFARE:
Economic Evaluation of a Small-scale Inland Fisheries Project
from the Delta Region of Myanmar
Master Thesis
Submitted at the
Institute of Development Research and Development Policy (IEE),
Ruhr University of Bochum (RUB), Germany
In partial fulfillment of
M.A (Development Management)
By
Om, Ki
(Student ID – 108012254079)
Supervised by
Prof. Dr. Wilhelm Löwenstein
Bochum, Germany Date - February 10, 2014
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TABLE OF CONTENTS
Declaration .............................................................................................................................. iii
Acknowledgement .................................................................................................................. iv
List of Figures .......................................................................................................................... v
List of Tables .......................................................................................................................... vi
List of Photos .......................................................................................................................... vi
List of Abbreviations and Acronyms .................................................................................. vii
1. Introduction ....................................................................................................................... 1
1.1 Justification and Problem Statement ............................................................................. 2
1.2 Research Objective and General Research Question .................................................... 4
1.3 Relevance and Importance ........................................................................................... 6
1.4 Structure of the Master Dissertation ............................................................................. 7
2. Literature Review.............................................................................................................. 9
2.1 Global Trends and Issues of Fisheries .......................................................................... 9
2.2 Global and Regional Fisheries Institutions ................................................................. 10
2.3 The Role of Fisheries Governance and Co-management ............................................ 11
2.4 Relationship of Fisheries with Livelihoods and Food Security .................................. 12
2.5 Relationship of Fisheries with Economic Growth and Poverty Reduction ................ 13
3. Theoretical and Conceptual Framework ...................................................................... 14
3.1 Economic Evaluation of Public Interventions............................................................. 14
3.2 Cost-Benefit Analysis (CBA) ..................................................................................... 16
3.2.1 Main Steps of CBA ......................................................................................... 17
3.2.2 Attractions and Limitations of CBA ............................................................... 18
3.3 Conceptualizing IFGS Project Impacts using CBA and Productivity Method ........... 19
3.4 Productivity Method .................................................................................................. 20
3.4.1 Applications of Productivity Method .............................................................. 21
3.4.2 Limitations and Advantages of Productivity Method ..................................... 22
4. Research Methodology.................................................................................................... 24
4.1 Hypothesis Derivation and Research Design .............................................................. 24
4.2 Sample Selection ......................................................................................................... 25
4.3 Data Collection............................................................................................................ 28
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4.4 Limitations of Field Research ..................................................................................... 29
4.5 Data Entry, Processing and Analysis .......................................................................... 30
5. Research Findings and Discussions ............................................................................... 31
5.1 Productivity Method: Approach and Data ................................................................. 31
5.1.1 Dependent Variable of the Production Function ............................................. 33
5.1.2 Independent Variables of the Production Function ......................................... 34
5.1.2.1 Boat and Fishing Equipment ............................................................. 35
5.1.2.2 Intermediate Inputs ........................................................................... 39
5.1.2.3 Labor ................................................................................................. 41
5.1.2.4 Common Fishing Ground ................................................................. 43
5.1.2.5 Trainings/Workshops ........................................................................ 44
5.2 Predicted Total Fishing Value with the NGO-Intervention ........................................ 45
5.2.1 Calculation of Predicted Boat and Fishing Equipment ................................... 45
5.2.2 Calculation of Predicted Total Fishing Value ................................................. 46
5.3 Predicted Total Fishing Value without the NGO-Intervention ................................... 48
5.4 Calculation of the IFGS Project’s Impact .................................................................. 49
6. Conclusion and Recommendations ................................................................................ 52
6.1 Conclusion .................................................................................................................. 52
6.2 Recommendations ....................................................................................................... 54
Bibliography .......................................................................................................................... 58
Annexes .................................................................................................................................. 62
Annex 1: Standardized Pre-structured Household Questionnaire ..................................... 62
Annex 2: Field Research Timetable .................................................................................. 67
Annex 3: Gender of Respondents ..................................................................................... 68
Annex 4: Marital Status of Respondents ........................................................................... 69
Annex 5: Gender Vs Marital Status of Respondents ........................................................ 70
Annex 6: Household Earning Perceptions of Respondents............................................... 71
Annex 7: Education Level of Respondents ....................................................................... 72
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DECLARATION
I hereby declare that this Master thesis on “Fisheries and Economic Welfare: Economic
Evaluation of a Small-scale Inland Fisheries Project from the Delta Region of
Myanmar” is of my own work and that I have received no other assistance than stated
sources and citations.
Name : Om, Ki
Place : Bochum, Germany
Date : February 10, 2014
Signature : ……………………….…
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ACKNOWLEDGEMENT
First, I would like to extend my sincere appreciation to KAAD (Katholischer Akademischer
Ausländer Dienst) for awarding me full scholarship without which this postgraduate study
would have been impossible. My deepest thanks also go to the Institute of Development
Research and Development Policy (IEE) of Ruhr University Bochum (RUB) for providing
me with the excellent opportunity of studying in this unique international program despite
my academic background of Electronics Engineering.
Of utmost importance to me to express my heartfelt and foremost gratitude is Prof. Dr.
Wilhelm Löwenstein for his helpful and constructive comments, effective mentoring and
enthusiastic support which enabled me to accomplish this work before the deadline.
My sincere thanks are also due to Sayar Bobby, the chief executive officer of Network
Activities Group (NAG), for his permission to conduct my empirical field research in one
of NAG projects being implemented in the Ayeyarwady Delta Region of Myanmar. I am
also deeply grateful to U Hla Myint, the Project Manager of Improving Fisheries
Governance System (IFGS) Project, for his effective support and assistance in conducting
the field research in the project’s fishing villages of Pyapon and Daydaye townships.
Not to be missed to be deeply thanked is my mother, Daw Om Mang, who always
encourages and strengthens me by showing her trust in me and constantly supports me with
her daily prayers for my good health during my stay in Germany and South Africa as well
as for my successful completion of this MADM program.
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LIST OF FIGURES
Figure 1: The map showing the two IFGS project townships of field research ..................... 27
Figure 2: Graphical illustration of the production function with project ............................... 32
Figure 3: Boat ownership for the fishing activities ............................................................... 35
Figure 4: Remittance Receipt of households of respondents ................................................ 38
Figure 5: Engine possession for boat driving in the fishing activities .................................. 40
Figure 6: Proportion of individual license holders and non-holders ..................................... 40
Figure 7: Proportion of fishery license fee recipients ........................................................... 41
Figure 8: Proportion of respondents with hired labor and without hired labor ..................... 42
Figure 9: Frequency of family by household size ................................................................. 42
Figure 10: Number of households with different dependent members ................................... 43
Figure 11: Access to the common fishing ground .................................................................. 44
Figure 12: Attendance of trainings/workshops of respondents ............................................... 44
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LIST OF TABLES
Table 1: Composition of respondents from nine villages ...................................................... 26
Table 2: Descriptive Statistics of observed Total Fishing Value ........................................... 34
Table 3: Descriptive statistics of observed Boat and Fishing Equipment .............................. 37
Table 4: Descriptive statistics of NGO Credit ....................................................................... 38
Table 5: Descriptive statistics of License Fee ........................................................................ 41
Table 6: Descriptive statistics of Household Size of Respondents ........................................ 43
Table 7: Output of stage-1 regression with Project ................................................................ 46
Table 8: Output of stage-2 regression with Project ................................................................ 47
LIST OF PHOTOS
Photo 1: A child leaving to trap eels by using bamboo eel pots ............................................ 36
Photo 2: Some fishing gear used in the research villages ...................................................... 36
Photo 3: Nipa-palm trees and a house built of knitted Nipa-palm-leaves.............................. 39
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LIST OF ABBREVIATIONS AND ACRONYMS
ADB Asian Development Bank
ASEAN Association of Southeast Asian Nations
BFE Boat and Fishing Equipment
CBA Cost Benefit Analysis
CCRF Code of Conduct for Responsible Fisheries
CEA Cost Effective Analysis
CFG Common Fishing Ground
CSIS Center for Strategic and International Studies
DFID Department for International Development
DoF Department of Fisheries
DR Dependency Ratio
FAO Food and Agriculture Organization
FDC Fishers’ Development Committee
GDP Gross Domestic Product
HHS Household Size
HL Hired Labor
IFGS Improving Fisheries Governance System project
II Intermediate Inputs
IMF International Monetary Fund
IRR Internal Rate of Return
km kilometer
LIFT Livelihoods and Food Security Trust fund
MCA Multi-Criteria Analysis
MFF Myanmar Fisheries Federation
MMK Myanmar Kyat
NAG Network Activities Group
NGO Non-governmental Organization
NPV Net Present Value
OECD Organization for Economic Co-operation and Development
OGB Oxfam Great Britain
SEAFDEC Southeast Asian Fisheries Development Center
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SPSS Statistical Package for the Social Sciences
TCG Tripartite Core Group
TFV Total Fishing Value
TW Trainings and Workshops
UN United Nations
UNDP United Nations Development Program
USD United States of America Dollar
VDC Village Development Committee
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1 INTRODUCTION
During the past period of over six decades (1948-2010) as an independent nation, Myanmar
underwent from the most promising hope of Southeast Asia to its most prominent
embarrassment due to the three distinct periods of misguided governance.1 The country
practiced parliamentary democracy from 1948 to 1962, followed until 1988 by the rule of a
military General with a socialist path featuring nationalization, isolation and repression. As
a consequence of this, Myanmar has since 1987 been a member of least-developed
countries. From 1988 to 2010, the country was governed by the military regime which
restored the market-based economy and moved the nation along towards a seven-step
roadmap to democracy. The general multi-party election, held in 2010 pursuant to 2008
constitution, produced a new civilian government which has ended many of the repressive
policies of the past and has started to pursue sustainable and broad-based economic
growth.2 Emerging from half a century of isolation, the new government has been charting
a fresh course centered on domestic political reconciliation, international reengagement and
economic reforms.3
Currently, Myanmar stands at 149th
position among global nations, scoring 0.498 in Human
Development Index, and is categorized in the group of Low Human Development countries
according to Human Development Report 2013 of United Nations Development Program
(UNDP).4 In terms of corruption which has detrimental impacts on the overall development
of a nation and which is also an indicator for the quality of legal and political systems,
Myanmar rose to the position of 157 out of 177 countries in 20135 despite its standing at
172nd
position out of 176 countries in 20126 according to the Corruption Perceptions Index
reports of Transparency International headquartered in Berlin, Germany. As regards
flexibility for doing business, Myanmar is ranked 182nd
out of 189 economies on the Ease
of Doing Business Index 2014 developed by the World Bank and the International Finance
Corporation.7 When it comes to international competitiveness, Myanmar scores 3.23 out of
7.0, being ranked at 139th
position out of 148 economies in the World Economic Forum’s
1 Rieffel, R. (2013): The Myanmar Economy: Tough Choices p1.
2 Ibid p2.
3 IMF (2013): Staff-monitored Program p5.
4 UNDP (2013): Human Development Report p146.
5 Transparency International (2013): Corruption Perceptions Index 2013.
6 Transparency International (2012): Corruption Perceptions Index 2012.
7 The World Bank and International Finance Corporation (2013): Doing Business 2014 p11.
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Global Competitiveness Index, which is also an indicator for the quality of the economic
system.8
With the appropriate reforms, Myanmar has the opportunity to realize its rich economic
potential owing to its major advantages such as young labor force, abundant natural
resources including natural gas, copper, timber and gemstones as well as its geo-strategic
location at the crossroads of some of the most dynamic economies in the world – China,
India and Southeast Asia.9 Endowed with a 2,800-kilometer (km) coastline that provides
access to sea routes to the Indian Ocean and deep-sea ports, Myanmar also has the potential
to serve as a gateway between East Asia, South Asia, and Southeast Asia.10
If stability is
augmented by comprehensive political reforms and implementing of basic economic
reforms, Myanmar’s economy could experience rapid growth, contributing to millions of
new jobs to its citizens. Currently, weak political stability, weak transparency and
accountability, high corruption, poor infrastructure, ineffective education system and dearth
of trainings are the most important and unique hurdles to its growth.11
1.1 Justification and Problem Statement
Myanmar is an agro-based economy, and agriculture accounts for 36% of the country’s
gross domestic product (GDP), 60-70% of employment and 25-30% of exports by value in
2010.12
The government emphasizes agricultural development as one of the main drivers of
the economy and the foundation for broad-based development essential for the well-being
improvement of most of its population.13
As one of the productive sub-sectors of
agriculture, fisheries play a crucial role in the livelihoods and food security of the people as
Myanmar has a coastline of nearly 3000 km, a continental shelf of 228,000 km2
and an
Exclusive Economic Zone of 486,000 km2.14
Inland freshwater bodies cover 8.2 million
hectares of which 1.8 million hectares are permanent, and the remaining proportion is
seasonally inundated floodplains.15
In 2009-2010 fiscal year, 7.6% of GDP was contributed
8 World Economic Forum (2013): The Global Competitiveness Report 2013-2014 p15.
9 IMF (2013): Staff-monitored Program p4.
10 ADB (2012): Interim Country Partnership Strategy Myanmar 2012-2014 p1.
11 CSIS (2012): Southeast Asia Program: Myanmar Trip Report p5.
12 ADB (2012): Sector Assessment (Summary): Agriculture and Natural Resources p1.
13 Ibid p3.
14 FAO (2003): Myanmar Aquaculture and Inland Fisheries p1.
15 DoF, Myanmar (2011): Fisheries Statistics p59.
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by fisheries and livestock sector.16
Fish is also one of the most important staples for animal
proteins of Myanmar people, and the per capita consumption of fish for fiscal year 2010-
2011 is 48 kilogram, with the production of 4.14 million tons, of which 0.37 million tons
was exported, thereby earning USD 555.52 million.17
As the per capita fish consumption of
the world in 2009 was estimated at 18.4 kilogram18
, that of Myanmar is almost three times
higher, signaling the nutritional significance of fish in Myanmar people’s diet. Furthermore,
Myanmar is also the 9th
top aquaculture producer on earth in 2010, manufacturing 850,700
tons by means of aqua-farming of fish.19
Myanmar fisheries can be categorized into two main groups: the Marine fisheries (Onshore
fisheries and offshore fisheries) and the Inland or Freshwater fisheries (Leasable fisheries,
Open fisheries and Aquaculture fisheries). Of 3490 leasable fisheries which are still
exploitable, 1738 (52.3%) are located in the Ayeyarwady Delta region20
, highlighting the
significant role of inland fisheries in the livelihoods of delta inhabitants. Furthermore,
majority of open fisheries of Myanmar is also situated in this delta region due to a
multitude of brooks, streams and rivers criss-crossing the province.
Unfortunately, Cyclone Nargis, which struck this delta region mainly and another province
in May 2008, resulted in the tragic death toll of about 140,000 people, 2.4 million people
severely affected and over 7 million people affected, leading to the total damage and loss of
USD 4.057 billion.21
Many of the people affected suffered devastating losses of family
members and homes.22
Compounding the tragedy, the catastrophic disaster caused
widespread destruction to their livelihoods and critical infrastructure, including roads,
jetties, water and sanitation systems, fuel supplies and electricity.23
The fishing communities also suffered from heavy loss of their productive assets and
fishing gear such as boats, nets and traps24
, which pushed them into the trap of poverty and
debt. Many of them have now no access to formal credit, and are often charged the high
16
Ibid pVI. 17
Ibid p54. 18
FAO (2012): FAO Yearbook 2010: Fisheries and Aquaculture Statistics pXVII. 19
Ibid pXVI. 20
FAO (2003): Myanmar Aquaculture and Inland Fisheries p5. 21
TCG - UN, ASEAN and Myanmar (2010): Post-Nargis Periodic Review-III pIX. 22
TCG - UN, ASEAN and Myanmar (2008): Post-Nargis Periodic Review-I pI. 23
TCG - UN, ASEAN and Myanmar (2008): Post-Nargis Joint Assessment p1. 24
TCG - UN, ASEAN and Myanmar (2010): Post-Nargis Periodic Review-IV pXIV.
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monthly interest rate of 10-20% for loans from informal local money-lenders. To make
matters worse, they have limited access to government extension services and have little
information on fish markets. On top of that, small-scale fishers are also forced to buy the
fishing rights from local businessmen who have access to the rights through a transparency-
weak tender process, and then to sell their catch to the middlemen, leaving them with
virtually no profit.
Under these combined circumstances, a local non-governmental organization (NGO)
named Network Activities Group (NAG), partnering with Oxfam GB (OGB), was
encouraged to launch the “Improving Fisheries Governance System (IFGS) Project” which
targets small-scale and subsistence fishing folks in 45 villages of two townships (Pyapon
and Daydaye) of Ayeyarwady Delta region in a 3.5-year period of 2011-2014.
1.2 Research Objective and General Research Question
Since March 2011, the new civilian government of Myanmar has been undertaking a range
of unexpectedly constructive measures for political, social and economic reforms, thereby
creating a platform and space from which the general public, including the fishing folks,
can enjoy the right to strikes and protests, the right of association and the right of voicing
their rights. Though the inland fisheries were in the past managed by the Ministry of
Livestock and Fisheries of central government, they are now in the hands of the Ministry of
Agriculture and Livestock of local governments thanks to the new constitution which
allows a certain degree of decentralization and devolution.25
On March 23, 2012, the local
Parliament of Ayeyarwady Region26
has also passed a new Freshwater Fisheries Law27
which guarantees more fishing rights of small-scale fishers.28
Nevertheless, the detailed
rules, which are to be drafted by the respective ministry and approved by the parliament as
guidelines to implement and enforce this law, was unfortunately not available until October
25
Government of Myanmar (2008): Constitution of the Republic of the Union of Myanmar p181-194. 26
Myanmar is delineated and constituted by seven Regions, seven States and the Union Territories according
to Article 49 of 2008 Constitution of the Republic of the Union of Myanmar. Ayeyarwady Region is one of
those seven Regions. In fact, States and Regions are of the same level and meaning, and each of them has its
own parliament. Those provinces situated at the border areas are termed as States whereas those located more
inside the country are named as Regions. 27
Parliament of Ayeyarwady Region, Myanmar (2012): Freshwater Fisheries Law p1-14. 28
Though the fishing tender license must be granted by means of a competitive tender auction according to
the new law enacted in 2012, it was observed that they were granted by means of a Lucky Draw system in
2012. In 2013, the competitive auction was practiced again pursuant to the new law in the whole region.
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2013 of this field research period29
, and some conservative government fisheries officials
are not ready or still reluctant to adapt to this changing political atmosphere.30
Against this background, NAG has been implementing IFGS project which will strengthen
inland fisheries governance, being financed by Livelihood and Food Security Trust Fund
(LIFT Fund)31
which is managed by UNOPS Myanmar (United Nations Office for Project
Services).32
The total amount of the funding for this project is USD 721,38433
and the
proposed target population is 2500 men and women fishers.34
The specific focus of this
project is to engage directly with small-scale fishing communities by forming fishing
groups that are better able to represent their members in an extremely competitive industry.
The formation of these groups will enable fishers to request the common fishing grounds in
the proximity of their villages, bid for their collective own licenses, have access to credit in
order to purchase new and more effective equipment including boats and fishing nets, gain
sharper information about local fish markets, add values to their business by exposing to
new processing practices and gain skills from capacity building.35
Some activities of this
project include organizing and training of Fishers’ Development Committees (FDC),
Village Development Committees (VDC), Fishers groups, Income-generating Activities
29
During my empirical field research period of September-November 2013 in Pyapon and Daydaye towns, I
requested a copy of Fishery Rules when meeting with (1) U Win Myint, the parliamentarian of Pyapon
Constituency of Ayeyarwady Region Parliament (2) U Aung Htay Oo, a fishery expert of an FAO project (3)
the principal of Fishery Training School (Lower Myanmar), (4) a District governmental fishery officer and (5)
U Hla Myint, the project manager of IFGS project but it was not available until then. During an inclusive
Fishery Governance workshop held on October 12-13, 2013 in Pathein, the capital of Ayeyarwady Region
where the local government headquarters and attended by different fishery key stakeholders including over
ten law-makers of parliament, the same question was raised again to the panelists which included a very high
position holder from the Fishery Ministry of Local Government, but the same answer was repeated. 30
Upon my request of the list of fishery tender license winners of 2012 and 2013 of some townships together
with the basic prices, a fishery official denied providing them to me, giving the reason of being not allowed to
outsiders. When raising the same question whether this list is a state secret or not at the workshop, a very
high-ranking governmental official responded that I could take it at the main office of the Ayeyarwady Delta
Region if I wanted. To tell the truth, the common small-scale fishers have a strong desire to keep a hard copy
of the tender prices so that they can conduct a collective tender purchase in the following years, saving the
money collectively and taking preparatory measures in advance, but they have unfortunately no access to
them so far. 31
LIFT is a multi-donor trust fund constituting the World Bank, the European Union, the Australian Agency
for International Development (AusAID), Swedish International Development Cooperation Agency (Sida),
Department for International Development of United Kingdom (DFID) and others, and the fund Manager of
LIFT is UNOPS. 32
http://www.unops.org/english/whatwedo/Locations/Europe/Myanmar-Operations-Centre/Pages/Myanmar
OperationsCentre.aspx 33
This figure was confirmed with Mr. Yin Nyein, the Program Officer (IFGS project) of NAG head office on
January 29, 2014. 34
NAG (2010): Proposal for Improving Fisheries Governance System Project. 35
Ibid
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group, Processors groups and small-scale Aquaculture group, establishment of a revolving
fund at the community level, analysis of tender process, piloting aquaculture micro-projects
for aqua-farmers, advocacy meetings and workshops at the village and township level,
establishment of a resource center as well as regular publication and dissemination of
newsletters.36
Given this setting in the background, the overall objective of this research is to “assess the
impact of IFGS project on the economic welfare of local small-scale fishers”. That is why
the general research question is “Do the activities of IFGS project lead to a positive
change in the economic welfare of local small-scale fishers?”
1.3 Relevance and Importance
Myanmar has since 2011 launched an ambitious political transition led by the newly-
elected President, and brave moves in his first year include opening a political dialogue
with the opposition leader, suspending the construction of controversial Chinese-funded
Myitsone mega-dam project and changing an extremely-overvalued exchange rate into a
market-determined one. These bold and positive moves unleashed a swarm of visitors such
as presidents, ex-presidents, prime ministers, foreign ministers, chief executives of multi-
national corporations, heads of donor agencies and international NGOs and many others to
support the democratization process and make a difference.37
Every respectable aid agency
and international NGO on earth is now planning to start or extend its operations in
Myanmar with the purpose of supporting and smoothing the transition, and the best and the
brightest in these organizations are taking steps to be posted in Yangon and to become a
part of a success story in Myanmar.38
In truth, foreign aid is not always a blessing.39
What matters most is to ensure the
relevance, effectiveness, efficiency, positive impacts and sustainability of development
interventions which are being and are going to be implemented in Myanmar. In order to
achieve this, besides the practice-oriented evaluations of NGOs, the economic evaluation of
these public interventions is also of unique importance and value, and financial evaluation
36
Ibid 37
Rieffel, R. and J. Fox (2013): Too Much, Too Soon? The Dilemma of Foreign Aid to Myanmar/Burma p1. 38
Ibid p3. 39
Ibid p3.
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of them should also be undertaken in order to test their sustainability after the projects’ exit
whenever and wherever feasible.
Conducting the economic evaluation of the IFGS project in this sense will help examine
whether the activities of this project increase their economic welfare or not from the
perspectives of the affected small-scale fishers. Since the result of this field research will be
disseminated to the implementing organization (NAG), Oxfam GB, Department of
Fisheries (DoF), Myanmar Fisheries Federation (MFF) and local parliamentarians so that
lessons learnt can be taken into account for future projects, this Master dissertation is of
great relevance and importance to the highly-increasing current aid atmosphere of
Myanmar. Above all, as NAG and OGB are also planning to document this project as a
governance-focused project model for other NGOs in Myanmar, this research will be of
help to them since it is approached in a way different from the evaluation techniques being
utilized widely in the NGO field.
1.4 Structure of the Master Dissertation
This Master Thesis is structured as follows. Chapter 1, which has already been presented,
explains the general background context of the study, discusses about the justification and
problem statement, defines research objective and general research question to be
answered, highlights the relevance and importance of this study and presents the structure
of this Master Dissertation. Chapter 2 focuses on the global trends and issues of fisheries,
global and regional fisheries institutions, the role of fisheries governance and fisheries co-
management as well as the relationships of fisheries with economic growth, poverty
reduction, livelihoods and food security. Chapter 3 concentrates on the theoretical and
conceptual framework by stressing the importance of economic evaluation of public
interventions, explaining the Cost Benefit Analysis (CBA) theory and the productivity
method as well as conceptualizing the impacts of the case study of IFGS project by means
of CBA and the productivity method. Chapter 4 covers the research methodology, ranging
from hypothesis derivation, research design, sample selection and field research limitations
encountered to data collection, data entry, data processing and analysis. In Chapter 5,
research findings and analyses from the empirical field study are presented and discussed,
finally leading to the calculation of the overall impact of IFGS project on the economic
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welfare of the small-scale fishers. Finally, Chapter 6 covers the conclusion and the
recommendations to the implementation organization, to the small-scale fishers as well as
to DoF and the local government. In order to detect whether it holds true or not under the
field research limitations confronted and the findings presented in Chapter 5, the research
hypotheses are also assessed in the conclusion.
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2 LITERATURE REVIEW
2.1 Global Trends and Issues of Fisheries
The total global production of fish has continued to increase and reached 148.5 million tons
in 2010.40
Whilst capture production has remained around 90 million tons since 2001,
aquaculture production enjoys strong growth, increasing at an average annual growth rate
of 6.3% from 34.6 million tons in 2001 to 59.9 million tons with the estimated value of
USD 119.4 billion in 2010.41
About 86% of total fishery production (128.3 million tons in
2010) was used for direct human consumption and the remaining 14% for non-food
products. Globally, fish supplies about 2.9 billion people with almost 20% of their average
per capita intake of animal protein, and 4.2 billion people with 15% of such proteins.42
Currently, the top-5 fishing countries of the world are China, Indonesia, India, United
States of America and Peru in terms of quantity. As regards aquaculture, the top-5
producers in 2010 are China, India, Vietnam, Indonesia and Bangladesh, contributing
87.6% of world aquaculture production by quantity. Regarding the species of fish, the most
caught one at the global level is still the Anchoveta, followed by Alaska pollock, Skipjack
tuna, Atalantic herring and Chub mackerel, though its catches fell by 39% in 2010 when
compared to 2009.43
Relatively stable since 1998, the world fishing fleet has composed
about 4.4 million vessels in 2010, with 73% in Asia, followed by Africa, Latin America and
the Caribbean, North America and Europe. In total, 3.2 million vessels were forecast to
operate in marine waters and 1.1 million vessels in inland waters.44
In terms of international trade of fish, the major exporting countries are China, Norway,
Thailand and Vietnam in 2010 whereas the major importing nations are the European
Union, United States of America and Japan.45
The share of developing countries in total
fisheries export was over 50% by value and 60% by quantity in 2010, and their fishery net
exports have indicated a continued rising trend in the three most recent decades, growing
40
FAO (2012): FAO Yearbook 2010: Fisheries and Aquaculture Statistics pXVI. 41
Ibid pXVI. 42
Ibid pXVII 43
Ibid pXVI. 44
Ibid pXVI. 45
Ibid pXVII
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from USD 10.2 billion in 1990 to USD 18.3 billion in 2000 and to USD 28.3 billion in
2010.46
2.2 Global and Regional Fisheries Institutions
At the global level, the WorldFish is a non-profit fishery research organization
headquartered in Malaysia, and it is one of the fifteen members of Consultative Group on
International Agricultural Research (CGIAR) consortium, a global partnership which unites
national and regional organizations, civil society organizations, academia and private sector
engaged in research for a food-secure future. The WorldFish is committed to addressing
two main development challenges: (1) improving the livelihoods of those who are
especially poor and vulnerable in places where fisheries and aquaculture can make a
difference and (2) achieving large-scale and environmentally-sustainable increases in
supply and access to fish at affordable prices for poor consumers in developing countries.
Its regional and country offices are situated in Asia (Bangladesh, Cambodia, Malaysia and
the Philippines), Africa (Egypt, Malawi and Zambia) and the Pacific (Solomon Islands).47
Starting with its first scoping visit to the Delta region of Myanmar in November 2012, the
WorldFish has also begun implementing the MYFish fisheries project in Myanmar,
coordinating with Department of Fisheries, Myanmar Fisheries Federation, Food Security
Working Group and the University of Yangon.48
At the regional level where Myanmar is situated, the Southeast Asian Fisheries
Development Center (SEAFDEC), established in 1967, is an autonomous
intergovernmental body, whose mandate is to develop and manage the fisheries potential of
the region by rational utilization of the resources for providing food security and safety to
the people and alleviating poverty through the transfer of new technologies, research and
information dissemination activities. SEAFDEC members consist of ten Southeast Asian
countries such as Myanmar, Brunei, Cambodia, Indonesia, Laos, Malaysia, Philippines,
Singapore, Thailand and Vietnam as well as Japan, and it operates through the Secretariat
located in Thailand.49
46
Ibid. 47
WorldFish: http://www.worldfishcenter.org/welcome-worldfish (Accessed on 05.08.2013) 48
DoF (2013): MYFish Newsletter. Issue 1, June 2013. p 10-17. 49
SEAFDEC: http://www.seafdec.org/index.php/about (Accessed on 05.08.2013)
11 | P a g e
2.3 The Role of Fisheries Governance and Co-management
The capture fisheries worldwide are generally perceived as being in crisis, and its most
visible indicator of crisis is the leveling off of the total world catch since 1990s. Though
aquaculture is frequently regarded as a panacea for the carrying incapacity of capture
fisheries to meet the increasing demand for fish products, the way to responsible
aquaculture is also strewn with various challenges and obstacles.50
As fisheries scores high
in terms of diversity, complexity and dynamics, the only means to cope with them is
through creating fisheries governance systems that are inclusive and adaptive through
learning, with a solid foundation of principles to help with navigation.51
Food and Agricultural Organization (FAO) defines fisheries governance as the sum of the
legal, social, economic and political arrangements used to manage fisheries. Moreover,
fisheries governance has international, national and local dimensions, and includes legally-
binding rules as well as customary social arrangements.52
According to the fishery experts
of Kooiman and his colleagues, fisheries governance is the whole of public as well as
private interactions undertaken to create societal opportunities and solve societal problems.
It also includes the formulation and application of principles guiding those interactions and
cares for the institutions that enable them.53
In reality, the establishment of institutions, policies and processes through which
management can be realized is of fundamental importance to the effective fisheries
governance. Over the past half a century of period, there have been significant changes in
the policy and governance context of fisheries, with implications for the roles of institutions
engaged in fisheries management.54
What can be observed clearly is a shift in objectives
from maximizing production and employment to sustaining stocks and taking into account
wider ecosystem aspects. Policies have shifted from the use of command-and-control
instruments to inter-sectoral policies, access rights and more participatory approaches. For
small-scale fisheries in particular, the failure of top-down and centralized arrangements
have led to increased interest in creating more devolved and locally-accountable
50
Bavinck, et al. (2005): Interactive Fishery Governance: A Guide to Better Practice p16. 51
Ibid p16-17. 52
FAO (2001): FIGIS Topics and Issues Fact Sheet: Fisheries Governance. Fisheries Policy and Planning
Division. 53
Kooiman, J. et al. (2005): Fish for Life: Interactive Governance for Fishery p17. 54
DFID (2006): Fisheries and Governance: Fishery Management Science Program. Policy Brief-5 p1-4.
12 | P a g e
management structures and developing fisheries co-management systems or community-
based management arrangements.55
2.4 Relationship of Fisheries with Livelihoods and Food Security
Fisheries, especially in the developing world, contribute to the livelihoods of people in a
number of ways: directly as food, as a source of income and through other social benefits
such as reduced vulnerability to poverty. Globally, 36 million people are employed in
fisheries, 90% of whom can be classified as small-scale fishers and 95% of whom are in the
developing countries.56
As the fishery-related livelihoods are often dynamic, complex and
adaptive, fishing may be engaged in full-time as part of a mixed farming-fishing-livestock
livelihood or in part-time as a seasonal fall-back. While the fishers are in general poor, the
cash income earned by selling fish can let them have access to the basic commodities and
services such as food, education, health and other assets.57
The important contributions of
small-scale fisheries to the livelihoods and employment opportunities of the fishers is also
acknowledged in the Code of Conduct for Responsible Fisheries (CCRF), developed in
1995 by the Food and Agriculture Organization.58
On the other hand, fisheries also provide the main source of animal protein for about one
billion people globally. Fish are especially important for poor people as they are often one
of the most accessible and cheapest sources of protein available. In particular, inland
fisheries are essential for the food security of the poor and the disadvantaged since most
inland fish production goes for subsistence or local consumption. Nonetheless, competing
demands for resources and access can lead to conflicts of interests and overexploitation of
fishers, resulting in negative repercussions on food security. Consequently, management of
fisheries that ensures their sustainability is essential to safeguard their contribution to food
security.59
55
DFID (2006): Fisheries and Governance: Fishery Management Science Program. Policy Brief-5 p1-4. 56
DFID (Unknown): Developing, Implementing and Evaluating Policies to support Fisheries Co-management
p3. 57
DFID (2006): Fisheries and Livelihoods: Fishery Management Science Program. Policy Brief-4 p1-4. 58
FAO (1995): Code of Conduct for Responsible Fisheries. 59
DFID (2006): Fisheries and Food Security: Fishery Management Science Program. Policy Brief-3 p1-4.
13 | P a g e
2.5 Relationship of Fisheries with Economic Growth and Poverty Reduction
Fisheries are potential sources of significant wealth and contribute to both economic growth
and poverty reduction, depending on their distribution and management. Although the
economic contribution of industrial-scale fisheries is easily visible as they include exports
and revenues from licensing, that of a small-scale fishery may be noticed only when it
collapses and the resulting costs of food substitution and unemployment are confronted.60
Consequently, developing countries face decisions about how best to realize the economic
potential of all their fisheries. Should they prioritize resource rent from industrial fisheries
or socio-economic benefits of small-scale fisheries? Should they develop their own fishing
industry or allow foreign fleets to exploit their fisheries resources? These tricky questions
need to be answered with great care.
Crucial to the role fisheries can play in poverty reduction, on the other hand, is the fact of
who enjoy the benefits from fisheries. Where industrial fisheries provide revenues to the
state, they can contribute to poverty alleviation if the distribution of that revenue promotes
pro-poor growth, is invested in infrastructure and public services for the poor or is re-
invested in the economy to promote general economic growth. Regarding small-scale
fisheries particularly, fishing rights should be allocated specifically to the poor and to those
dependent on fisheries in order to avoid capture and monopoly of use-rights by influential
individuals and businessmen.61
All in all, though there are many facets of fisheries governance to cope with its dynamic,
complex and diverse nature, this empirical field research study will only focus on
measuring the impacts of IFGS project on its beneficiaries as it is strongly believed that
measuring the economic welfare from the perspectives of affected fishers is also an
essential aspect of a good fisheries governance project.
60
DFID (2006): Fisheries and Economic Growth: Fishery Management Science Program. Policy Brief - 2.
p1-4. 61
DFID (2006): Fisheries and Poverty Reduction: Fishery Management Science Program. Policy Brief - 1.
p1-4.
14 | P a g e
3 THEORETICAL AND CONCEPTUAL FRAMEWORK
3.1 Economic Evaluation of Public Interventions
Every nation on this planet, in particular the developing ones, has been experiencing the
fundamental economic problem of allocating limited resources such as capital, labor and
land to a variety of uses such as investment in education, health, infrastructure, agriculture
and other sectors or production of consumer goods.62
If the allocation of these limited
resources is not efficient in a country, i.e. if imperfect competition occurs or if the price
systems are distorted or if there are no markets for some commodities, the public
interventions need to be initiated and implemented in order to change the provision with
public or private goods.
Economic evaluation gives us an answer to the question of whether such a public
intervention or an intervention of the state is economically desirable or not from the
perspective of the affected population.63
It looks at a project from the perspective of the
entire society and measures the effects of the project on the economy as a whole.64
If a
project utilizes resources from other activities that produce goods and services, the value of
what are forgone means the opportunity cost of the project to the society.65
The prices used
for the economic analysis of public interventions are based on these opportunity costs. In
situations where these public interventions are funded over a pre-determined period only
and should sustain themselves after the termination of the financing period, questions about
their profitability and associated liquidity effects arise. In such cases, it is necessary to
integrate the economic and financial analyses in order to look at the project from the
viewpoints of the society for identifying losers and winners, and ultimately to judge
whether a project can be sustainably or profitably implemented.66
If the economic analysis
indicates that a project is worthwhile for the society although the financial analysis shows
that it has no rentability, subsidization of the project makes sense to attract investors by
buffering them against the risks and uncertainties. On the other hand, a project should never
62
Squire, L., G. Herman and H.V.D. Tak (1995): Economic Analysis of Projects p8. 63
Mawire, B. (2008): Biofuels and Economic Welfare p19. 64
Belli, P. et al. (2001): Handbook on Economic Analysis of Investment Operations p26. 65
Ibid p26. 66
Ibid p27.
15 | P a g e
be implemented if its opportunity costs or economic costs are judged too high despite being
financially viable.67
The main purpose of economic evaluation is to design and choose projects which contribute
to the social welfare of a nation, and it is most useful when applied early in the project
cycle (ex- ante) to identify poor projects and poor project components.68
When employed at
the end of the cycle (ex post), it can only help in making decisions whether to proceed with
the project or not. It can serve only very limited objectives if used only for computing a
single summary measure such as net present value (NPV) or economic internal rate of
return (eIRR).69
Though there are three main economic evaluation tools (Cost Benefit Analysis - CBA, Cost
Effective Analysis - CEA and Multi-Criteria Analysis - MCA), CEA and MCA will be
presented just in brief here since CBA is selected as the most appropriate tool for this field
research of evaluating a public intervention, and it will be presented in more details later.
Cost-Effective Analysis (CEA): CEA is a policy-advice instrument conducted from the
perspective of the society or the financier, and it is an assessment of the costs of alternative
options which all achieve the same objective without restricting the costs to purely financial
ones. It should thus include non-cash opportunity costs such as the use of assets owned by the
spending body, which would otherwise be put to other uses. If there are alternative options to
achieve a specific objective but the objective itself cannot be valued, CEA can be used to assess
the minimum-cost method of achieving the objective.70 The underlying assumption is that
different alternatives are associated with different costs and different results, and thus the
society can utilize its resources most effectively by selecting those alternatives with the
minimum cost for a pre-determined outcome. Those resources saved through using more cost-
effective approaches can be allocated to expanding the projects or can be invested elsewhere.
CEA has been most commonly used in evaluating the projects in health sector by World Health
Organization (WHO) to examine the costs and health effects of specific interventions,71 and it
67
Mawire, B. (2008): Biofuels and Economic Welfare p20. 68
Belli, P. et al. (2001): Handbook on Economic Analysis of Investment Operations p3. 69
Ibid p3. 70
Department from Communities and Local Government (2000): DTLR Multi-criteria Analysis Manual p12. 71
Tan-Torres Edeger, T. et al (2003): Making choices in Health - WHO guide to cost-effectiveness analysis.
16 | P a g e
has been successfully applied in evaluating the cost-effectiveness of strategies used to combat
malaria in developing countries.72
Multi-Criteria Analysis (MCA): MCA is also an instrument used for the policy advice
from the perspective of experts but is more appropriate for a project rating by private investors
and widely applied for project ratings by development finance institutions. It establishes
preferences among alternatives with reference to a set of objectives that the decision-makers
have identified and for which it has set measurable criteria to assess the extent to which the
objectives have been achieved.73 Its key feature is its emphasis on the judgment of the decision-
making team in setting objectives and criteria, estimating relative important weights and
judging the contribution of each alternative to each performance criterion to some extent. What
can be a matter of concern in MCA is its subjectivity. In principle, its foundation is the decision
maker’s own selection of objectives, criteria, weights and assessments of achieving objectives
though objective data such as observed prices can be incorporated. Nevertheless, MCA brings a
degree of structure, analysis and openness to classes of decision lying beyond the practical
reach of CBA.74 A standard feature of MCA is the performance matrix where each column
shows the performance of alternatives against each criterion and each row mentions an
alternative.75
3.2 Cost -Benefit Analysis (CBA)
CBA is an effective instrument of policy advice conducted from the perspective of the
affected people, and it is now an established technique widely applied in both government
and international organizations.76
Though the underlying concepts of the technique, the
concept of consumer surplus developed by Dupuit and the concept of externality developed
by Pigou, originated from Europe in the 1840s, the use of CBA in environmental
economics is a relatively new occurrence.77
72
Morel, C. M. et al (2005): Achieving the Millennium Development Goals for Health – Cost-effectiveness
analysis of strategies to combat Malaria in Developing Countries. 73
Department from Communities and Local Government (2000): DTLR Multi-criteria Analysis Manual p17. 74
Ibid 75
Ibid 76
Mishan, E.J and E. Quah (2007): Cost Benefit Analysis p243. 77
Ibid
17 | P a g e
A concrete theoretical framework for CBA was established with the works of three
economists (Eckstein, 1958, Krutilla and Eckstein, 1958 and McKean, 1958) that
methodically applied neoclassical welfare economics in relation with CBA.78
Its use
became more institutionalized and widespread from 1960 onwards, and the academic
contributions of Mishan (1971) on CBA and normative economics (1981) added
significantly to the increasing literature. Besides being applied by the governments, CBA
was formally adopted by several multilateral organizations – the Organization for
Economic Cooperation and Development (OECD) in 1969, the United Nations (UN) in
1972 and the World Bank in 1975. Furthermore, agreement was also reached at the Earth
Summit in Rio de Janeiro in 1992 that country application of financial support for public
sector projects must be subject to passing the CBA test as much as possible.79
The main purpose of CBA is to locate and include all efficiency effects of a project,
expressing the unobservable change in welfare in observable monetary units. As the
operational measure for benefit, CBA typically uses consumer surplus which is the
maximum sum of money a consumer would be willing to pay for a given amount of the
good minus the amount he actually pays.80
CBA valuations are based on a well-developed
economic theory of valuations which depends on willingness-to-pay or willingness-to-
accept. This theory can serve as a guide to how valuations should be conducted, and act as
a referee in disputes on valuation.81
3.2.1 Main Steps in CBA
CBA can be undertaken in nine major steps as explained below.82
(1) The first step requires the analyst to specify a set of alternative projects.
(2) The analyst must decide whose benefits and costs to be counted.
(3) The impacts of the alternatives must be catalogued as benefits or costs, and the
measurement unit of the impacts must be selected.
(4) The impacts must be predicted quantitatively over the lifespan of the project.
78
Ibid p244. 79
Ibid p244. 80
Mishan, E.J. (1982) Cost Benefit Analysis: An Informal Introduction p23. 81
Department for Communities and Local Government (2000): DTLR Multi-criteria Analysis Manual p13. 82
Boardman, A.E. et al. (2001): Cost Benefit Analysis: Concepts and Practice p7-17.
18 | P a g e
(5) All the impacts are monetized. Monetization means assigning value in dollars, euros
or local currency.
(6) Benefits and costs are discounted in order to obtain present values. Relative to
present benefits and costs, future benefits and costs are usually discounted with the
purpose of getting their present values. Because of most people’s preference to
consume now rather than later and because we usually give up the opportunity to
consume more in the future if we consume now, the need of discounting arises. It is
commonly assumed that the true rate of discount or interest is one which reflects
society’s rate of time preference.83
The methods commonly used include Market
Price method for actual preferences, Productivity method, Hedonic Pricing method
and Travel Cost method for revealed preferences and Contingent Valuation method
for stated preferences. If a public intervention changes the provision of private
goods, Market Method is used whereas Productivity Method, Travel Cost Method
and Hedonic Pricing Method are applied if such an intervention alters the provision
of public goods affecting the use of private goods. Nevertheless, Contingent
Valuation Method will be employed when a public project changes the provisions
of public goods which do not affect the use of private goods.
(7) The net present value of each alternative is computed.
(8) Sensitivity analysis must be conducted to deal with uncertainties and risks, by
varying the important parameters such as estimates of costs and benefits, discount
rate and the project lifespan.
(9) Finally, a recommendation is made based on the NPV and sensitivity analysis.
Negative NPV means that a project is not economically desirable whilst NPV value
of zero indicates an indifferent situation. Positive NPV implies that the project is
economically desirable, and in the case of multiple alternatives with positive NPVs,
the project with the highest NPV should be selected and implemented.
3.2.2 Attractions and Limitations of CBA
As a tool of guiding public policy, CBA has three attractions.84
First, it covers the welfare gains and losses to all members of the society on whose
behalf the CBA is conducted.
83
Mishan, E.J and E. Quah (2007): Cost Benefit Analysis p129. 84
Boardman, A. E. et al. (2001): Cost Benefit Analysis: Concepts and Practice p13.
19 | P a g e
Second, it values in terms of a single and familiar scale (monetary units) and can
thus clearly show that implementing an alternative is worthwhile or not.
Third, the money values applied to gauge the relative importance of different
impacts are based on people’s preference, using established method of
measurement.
Of equal importance to analysts is comprehension of the limitations of CBA. There are two
kinds of circumstances which make CBA an inappropriate decision rule for public policy.85
First, technical limitations can make it impossible to quantify and monetize all
relevant impacts as benefits and costs.
Second, goals other than “efficiency” are sometimes more relevant to the policy as
some policies are intended to affect the “equality” of outcomes or opportunities
rather than efficiency. Nevertheless, even when the net benefit criterion is not
suitable as a decision rule, CBA provides a useful yardstick in comparing
alternative policies in terms of efficiency.
Since CBA records only those project effects which have an effect on people and to which
the affected population attributes importance, it is perceived to be strictly anthropocentric.
Another criticism is that CBA does not generally take account of the interactions between
different impacts (e.g. environmental and social costs).86
More important is the fact that
while procedures such as stated preferences (Contingent Valuation) or Hedonic Pricing
give ways to establish monetary values of some non-marketed impacts, it is immediately
impracticable for others.87
Furthermore, CBA encounters some problems in the areas of
income distribution, intergenerational equity, risk and uncertainty, irreversibility, value of
biodiversity, value of human life and value of cultural, historical and aesthetic resources.
3.3 Conceptualizing IFGS Project Impacts Using CBA and Productivity
Method
Given the impacts of the IFGS project in accordance with the Cost Benefit Analysis, the
project effects which are judged positive by the small-scale fishers will be benefits and
85
Ibid p39. 86
Department for Communities and Local Government (2000): DTLR Multi-criteria Analysis Manual p14. 87
Ibid p14.
20 | P a g e
those judged as negative will be costs for them. As the total fishing value of small-scale
fishers can be affected by some activities of the project which are the public goods or
services used as inputs in producing a marketed good of fish, the productivity method is
chosen to be applied. In other words, IFGS project activities change the provisions of
public goods or services (NGO credit, Common Fishing Ground and Trainings/Workshops)
which affect the use of their private goods through the utilization of their total fishing
value. This IFGS project may have impacts on the total fishing value of the fishing folk in
the following ways:
(1) Having access to NGO credit may indirectly increase the total fishing value of
fishers by enabling them to purchase more effective fishing equipment and boat
which play an essential role in their fishing activities. In other words, NGO credit
may strengthen their financial capital needed for their small-scale fishing
industries.
(2) If they make use of the skills and knowledge acquired during the sessions of some
trainings/workshops such as fishery law workshops, processing/value-added
trainings, fishery-equipment trainings and aquaculture trainings, they may raise
their total fishing value in some productive ways, enhancing their human capital.
(3) The common fishing ground may also augment the total fishing value of small-
scale fishers by means of letting them have free and easy access to the fishing
ground and saving the license fee for fishing.
Hence, in constructing the production function according to the productivity method
presented in deeper details below, NGO credits, Trainings/Workshops and Access to
Common Fishing Ground will be included in the group of independent variables in order to
detect whether the dependent variable of total fishing value is influenced by them or not.
3.4 Productivity Method
As the economic evaluation of this field research deals with the revealed preferences of
small-scale fishers, the productivity method is chosen to be applied. Also known as the
income method or the derived value method or the net factor income method, the
productivity method is used to estimate the economic values of public goods or services
affecting the use of private goods or to estimate the economic values of ecosystem services
21 | P a g e
or products contributing to the production of commercially-marketed goods. It can also be
applied in cases where the products or services of an ecosystem (e.g. bee pollination) are
used as inputs, together with other inputs, in order to manufacture a marketed good (e.g.
sunflower seed production).88
If a natural resource or a public good/service is a factor of production, changes in the
quantity or quality of this natural resource or this public good/service will result in changes
in production costs and/or productivity of other inputs. In turn, this may affect the quantity
supplied and/or the price of the final good. In addition, it can also affect the economic
returns to other inputs. What may be important here are two types of benefits or costs. First,
if the price or quantity to the consumers of the final good changes, there will be changes in
consumer surplus. Second, if the production cost or the productivity changes, there will be
changes in producer surplus. Therefore, the economic benefits from improvements in the
resources or public goods/services can be estimated by measuring changes in the
observable market data.89
3.4.1 Applications of Productivity Method
Productivity method can be performed in three steps.
The first step is to specify the production function which is the functional
relationship between the output and the inputs.
The second step is to estimate how variation in the costs of the inputs changes the
output.
The third and final step is to estimate the economic benefits of public
goods/services or natural resources/ ecosystem goods or services.
In order to apply this method, data must be collected regarding how changes in the quantity
and quality of the natural resources or public goods/services affect (1) costs of production
for the final good, (2) supply and demand for the final good and (3) supply and demand for
other factors of production. This information is applied to link the effects of changes in the
88
King, D.M. and M. Mazzotta (2000): Ecosystem Valuation: Dollar-based Ecosystem Valuation Methods.
http://www.ecosystemvaluation.org/productivity.htm Accessed on 06.08.2013. 89
Ibid
22 | P a g e
quantity or quality of the resources or public goods/services with changes in consumer
surplus or/and producer surplus, and therefore to finally estimate the economic benefits.90
Moreover, this method can be most easily applied in two specific scenarios.91
The first scenario is in situations where the resource or public good/service in
question is a perfect substitute for other inputs. For instance, improved quality of
soil fertility resulting from agroforestry initiative means that reduced chemical
fertilizers will be necessary to supply crop nutrients. In this case, the benefits of
improved soil fertility can be directly measured by the reduced fertilizer costs.92
The second scenario is in cases where only producers of the final good benefit
from changes in the quantity or quality of the natural resources/ecosystem services
or public goods/services without affecting consumers.93
For example, increased
quality or quantity of bee pollination services resulting from an afforestation or
forest-preservation project may lead to higher productivity, producing more coffee
on the same area of land. If the market prices of the coffee do not change,
consumers are not affected, and benefits can be estimated from changes in producer
surplus resulting from increased income. In this scenario, the profits per acre of
coffee plantation will rise, and this increase can be applied to estimate the benefits
of increased quality or quantity of bee pollination or an ecosystem service.94
3.4.2 Limitations and Advantages of Productivity Method
There are three main limitations of productivity method.95
First, the method is limited to valuing those resources or public goods/services
which can be used as inputs in the manufacture of marketed goods.
Second, the information is necessary on the scientific relationships between actions
to improve quantity and quality of the natural resources and the actual outcomes of
90
Ibid 91
Ibid 92
Mawire, B. (2008): Biofuels and Economic Welfare p29. 93
King, D.M. and M. Mazzotta (2000): Ecosystem Valuation: Dollar-based Ecosystem Valuation Methods.
http://www.ecosystemvaluation.org/productivity.htm Accessed on 06.08.2013. 94
Olschewski, R. et al. (2006): Economic evaluation of Pollination Services Comparing Coffee Landscapes in
Ecuador and Indonesia p1-7. 95
King, D.M. and M. Mazzotta (2000): Ecosystem Valuation: Dollar-based Ecosystem Valuation Methods.
http://www.ecosystemvaluation.org/productivity.htm Accessed on 06.08.2013.
23 | P a g e
those actions. In some cases, these relationships may not be easily well-understood
or well-known.
Third, if the changes in the natural resources or public goods/services affect the
market price of the final good or the prices of any other production inputs, the
method becomes more complicated and difficult to apply.
On the other hand, two main advantages of productivity method can also be observed.96
First, the methodology is straightforward in general.
Second, data requirements are limited, and the relevant data can be readily available
so the method is relatively inexpensive to apply.
96
Ibid
24 | P a g e
4 RESEARCH METHODOLOGY
4.1 Hypothesis Derivation and Research Design
Literature Review presented in the Chapter TWO revealed that fisheries play a significant
role in the livelihoods and nutritional diet of the people, especially the poor and the
disadvantaged mainly dependent on fisheries. Theoretical and Conceptual Framework
outlined above in Chapter THREE can thus be applied to evaluate the impacts of IFGS
project activities for its targeted poor and disadvantaged fishing folk. Therefore, the main
research hypothesis of economic evaluation on the IFGS project, which has such target
beneficiaries, has been derived as follows:
“Provision of fisheries-related public goods or services of IFGS project has resulted in
a positive change in the economic welfare of the small-scale fishers.”
There is one dependent variable in this study which is the total fishing value of the small-
scale fishers. Though the total fishing value can be affected by seven independent variables
which can be in details observed in the following Chapter FIVE of Research Findings and
Discussions, there are only three independent variables which are related to IFGS project
activities: namely, NGO credit (Indirectly), trainings/workshops and access to the common
fishing ground. Hence, the following sub-hypotheses have been derived.
i. Provision of NGO credit leads to an improvement in the economic welfare of
small-scale fishers by increasing their total fishing value indirectly.
ii. Provision of trainings and workshops results in an increase in the economic
welfare of small-scale fishers by augmenting their total fishing value.
iii. Provision of technical assistance to have access to the common fishing ground
leads to a rise in the economic welfare of small-scale fishers by raising their
total fishing value.
In testing whether the provision of these public services or goods of IFGS project is
worthwhile or not, the “with and without” approach is applied, and a research design
based on the productivity method was created to analyze the economic welfare effects of
the project. For the “with situation”, the total fishing value of the small-scale fishers will be
calculated, taking into account the impacts of IFGS project activities such as NGO credit,
common fishing ground and trainings/workshops. For the “without situation”, the total
25 | P a g e
fishing value of each fishery beneficiary household will be computed, excluding the effects
of the above-mentioned three activities of NGO. The difference between the two figures of
predicted total fishing value of “with situation” and “without situation” will be attributed to
the IFGS project.
Utilized in this empirical field research was a standardized pre-structured household
questionnaire which mainly focuses on the quantitative data. The most important collected
data, which are associated with the IFGS project and the applied productivity method, are
data on the NGO credit, boat and fishing equipment, attendance of Trainings/Workshops
and access to the Common Fishing Ground as well as total fishing value (fish sales revenue
plus fish consumption value). Moreover, also collected are the data on family composition
with residents only (to calculate the household size and the dependency ratio), hired labor
in the fishing activities, intermediate inputs (fuel costs plus license fees) as well as
remittance and income from other sources.
4.2 Sample Selection
The empirical field research that examines the analysis of the impact of a public
intervention by means of the “with and without approach” needs a robust sampling and also
requires the integration of the different behaviors of the affected and non-affected people of
the project. The selected two groups for such integration of different behaviors should be
identical in socio-demographic aspects as much as possible, and their significant difference
is the existence of the public intervention in the project villages. Hence, in order to collect
data, ten villages were selected as follows:
One project-village for the pilot test,
Three project-villages that succeeded in applying for the common fishing ground
and two project-villages that were not successful in acquiring the common fishing
ground and
Four non-project villages.
In selecting these villages and respondents for pilot test and field research, the following
guiding criteria were applied.
All the villages must be of approximately same travelling distance and same
transportation from the town or project office.
26 | P a g e
All the villages must have identical socio-demographics as much as possible
(primary school, rural clinic etc.)
All the respondents must be small-scale fishers.
Table 1: Composition of Respondents from nine villages
Sr. Village Name Village Tract Name Township
Name
Project or
Non-project
No. of
Respondents
Pilot Thae-eain-kyaung-su Thae-eain-kyaung-su Pyapon Project (10)
1 Ahsi-ka-lay Ahsi-ka-lay Pyapon Project 17
2 Tha-htay-gone Thae-eain-kyaung-su Pyapon Project 24
3 Shwe-taung-su Thae-eain-kyaung-su Pyapon Project 11
4 Pho-shan-gyi Kan-seik Daydaye Project 35
5 Tha-gya-hin-oo Kan-seik Daydaye Project 31
6 Thauk-gya-ywa-ma Thauk-gya Daydaye Non-project 27
7 Hnegt-chaung Thauk-gya Daydaye Non-project 8
8 Ta-man-su Thauk-gya Daydaye Non-project 19
9 Ma-ngay-lay Da-none-kone Daydaye Non-project 10
Total (Excluding pilot test) 182
Source: Questionnaire, Question No. 3
As such, sampling was undertaken as follows:
In selecting a project village for the pilot test of questionnaire feasibility, the
suggestion of the project manager and field team leader was acquired.
For choosing the 5 project villages, a meeting was organized with the project
manager, field team leader and other personnel at the project field office.
In selecting 4 non-project villages, expert suggestion was conducted with a fishery
expert of an FAO project who has thorough knowledge on delta fishing villages.
Furthermore, the suggestions and recommendations of project field office staff were
also taken into account as some of them are delta inhabitants.
Of the ten villages chosen, 9 villages are accessible by boat only and it takes at least
2 hours to reach these villages from the project office.
In the selection of respondents, only members of fishers group were chosen by
means of random sampling in the project villages because they are the main target
of IFGS project despite the four categories of project beneficiaries, namely (1)
Fishers Group, (2) Aquaculture Group, (3) Fish Collector Group and (4) Processing
or Income-generating Group. For the purpose of random sampling, the list of fishers
27 | P a g e
group was obtained at the project office, and lucky draw system was used to choose
the respondents in the village.
In the non-project villages also, random sampling was applied but the main criterion
is that they had to be small-scale fishers.
In total, 64 respondents were interviewed in 4 non-project villages and 118
respondents in the two sub-categories of the project villages, leading to a total
household survey of 182. The composition of respondents from nine villages of two
townships can be observed in details in the table above.
In addition, the map of the Ayeyarwady Delta Region showing the two townships of IFGS
project is also presented below in Figure 1 for the sake of visualization.
Figure 1: The Map showing the two IFGS project townships of field research
Source: Myanmar Information Management Unit (Modified by the author)
Ayeyarwady Delta Region
Daydaye
Pyapon
28 | P a g e
4.3 Data Collection
The empirical field research consisted of two main steps. The first step was secondary data
collection with regards to fisheries, conducted by means of a study of several
documentations from the Resource Center of IFGS Project, Myanmar Information
Management Unit, internet and others. Some more documents were also received from the
Fisheries Training School (Lower Myanmar). Of help to acquiring useful information and
documents on delta fisheries was also my personal familiarity with the principal of the
Fishery Training School and a fisheries expert of an FAO project, which is also being
launched in the delta region. Secondary data from the project proposal, project reports, and
IFGS newsletters, coupled with informal discussions and interviews with the employees of
NAG field office staff and fisheries experts, were verified during the field work in the
villages, serving as guiding points for the collection of primary data.
For the primary data sources, as described before, a standardized pre-structured
questionnaire was utilized in household surveys after translating it into Myanmar language
from English as local fishers or respondents cannot understand English. As the fishing
license period was fixed according to the Fiscal Year of Myanmar Government, the period
for which data collection was undertaken was also decided to be from April 2012 (Tagu
1374 of Myanmar Era) to March 2013 (Tabaung 1374 of Myanmar Era).97
The pilot test of
the questionnaire was conducted in one project village before the actual field survey began
so that the feasibility and appropriateness of drafted questions could be assessed. Drawing
on the experience and information gained during the pre-test of household survey,
amendments of questionnaire were made wherever needed. The amended survey
questionnaire was then emailed to the supervising professor to be confirmed and remarked
on its suitability and applicability after cross-checking. Through the use of the household
questionnaire finalized in accordance with the mentor’s conclusive remarks and
recommendations, 182 respondents of target population from nine villages were
interviewed. In order to ensure the consistency and fulfillment of important data
requirements, all the 182 interviews were undertaken by the author of this book only.
97
The detailed comparison of Gregorian Calendar months and Myanmar Lunar Calendar months can be
observed at Question No.24 of household questionnaire which is also appended as Annex I.
29 | P a g e
4.4 Limitations of Field Research
In conducting the empirical field research, a variety of difficulties and hardships was
encountered as forecast in advance.
First, there is limited public transportation from the project office to the project and
non-project villages. As presented above, nine villages can be accessible only by
boats since there is a multitude of streams and rivers criss-crossing the delta
province, and only one village is accessible by motorcycle. Under such
circumstances, boats and motorbikes had to be privately hired to go to the field
research villages.
Second, to make matters worse, the period of field research coincided unfortunately
with the rainy season of Myanmar. If there are heavy rains, it is risky and
impossible to go to the villages or go around in the villages. Such situations forced
the researcher to remain stayed in the village for two or three days until almost
every household interview was administered in that village. To cap it all, in some
villages such as Pho-shan-gyi and Tha-gya-hin-oo of Daydaye township, visiting
one house after another for the interviews is possible by boat only since the village’s
main road is so muddy and slippery because of constant heavy rain that it cannot be
used in the rainy season. Compounding the problem encountered, these villages are
built on both sides of a stream.
Third, though planned in advance to conduct 30 household surveys in each village,
it became unrealistic due to the absence of some beneficiaries in the project villages,
resulting from their participation in the celebration of religious/cultural festivals,
travelling, visiting their relatives or moving to other cities for better employment.
Fourth, as majority of interviewees are subsistence fishers, they were busy with
their fishing activities in this rainy season. Only when they were free, especially at
night, could the survey be conducted with the battery or candle lighting as
electricity or generator lighting is scarce.
Last but not least, most of the small-scale fishers interviewed are not educated and
consequently weak in record keeping. It took the enumerator patience, a calculator
and more time and posed some difficulties to ask them numerical and financial
figures, especially in questionnaire number 24 of estimated monthly fish sale
30 | P a g e
revenue and fish consumption value, questionnaire number 26 of income from other
sources as well as questionnaire number 17 of total fishing gear expenditures.
4.4 Data Entry, Processing and Analysis
Data entry was carried out upon completion of the household surveys in all villages because
it was quite impossible to perform so in the villages owing to electricity scarcity. A total of
182 completed household questionnaires was entered into the Microsoft Excel software and
then imported into the Statistical Package for the Social Sciences (SPSS) software of
Windows Version 20.0. For the purpose of identifying mismatches and omissions, data
verification and cleaning was also undertaken.
In analyzing the information collected in the field survey, not only descriptive statistical
methods such as graphical description of data (Pie Chart and Bar Graph), tabular
description of data (frequencies and aggregates) and numerical measures (Measures of
Central Tendency and Measures of Dispersion) but also the two-stage multiple regression
was also performed so that the impact of IFGS project activities on the economic welfare of
fishing community members can be investigated. The graphs and tables are created in
Microsoft Word and Microsoft Excel as those outputted by SPSS are not of reporting
quality for visualization. Analyzed data were presented in the form of graphs, tables and
numerical measures, and these outputs were applied in the interpretations and drawing of
conclusions.
31 | P a g e
5 RESEARCH FINDINGS AND DISCUSSIONS
This Chapter presents the approach and data of the productivity method with detailed
discussions about the dependent variable and all the independent variables of the
production function established and explains the step-by-step computation of predicted total
fishing value under “with and without project” circumstances by means of the two-stage
regression model, finally ending with the calculation of the overall impact of IFGS project
on the economic welfare change of small-scale fishers.
5.1 Productivity Method: Approach and Data
According to the Productivity Method of Cost Benefit Analysis theory, the production
function is necessary to be established in order to check whether or not the provision of
fisheries-related public goods or services of IFGS project leads to a positive change in the
economic welfare (Total Fishing Value) of affected fishery beneficiaries. Before
developing the equation of this production function from the figure illustrated below, the
logic of the production function will also be briefly discussed here. In economics, the
production function specifies the amount of the output that can be produced by combining
the factors of production for a given level of technology. In other words, the production
function of a firm or an industry explains the size of output flow in relation to the size of
the corresponding flow of productive inputs which are necessary to manufacture it.
According to Thompson, comprehension of the production function plays an important role
as it can be of help to answering the below-mentioned questions.98
To what extent will the total output of the production alter if the quantity of some
inputs is increased?
To what degree will the total output of the production change if some or all of the
inputs are increased in equal or unequal proportions?
To what extent will the total output of the production alter if the quantity of the
input decreases by one unit while the quantity of other inputs is increased
simultaneously?
98
Thompson, A. (1977): Economics of the Firm, Theory and Practice.
32 | P a g e
Fig 2: Graphical illustration of the production function with Project
Source: Creation by the author99
Now, the following production function is developed using the graphical illustration of the
case study as the change in the total fishing value is required to know when the inputs of
NGO credit, common fishing ground and trainings/workshops alter.
TFV = f (BFE, II, Labor, CFG, TW)
= f (BFE, II, HL, HHS, DR, CFG, TW)
Where TFV = Total Fishing Value (Fish sales revenue plus Fish consumption value)
BFE = Boat and Fishing Equipment (NGO Credit, Remittance and Income from
Other Sources) 99
The activities of IFGS project, which will be empirically tested, are shaded in green color. Though hired
labor, household sized and dependency ratio cannot be treated as one independent variable due to their
different units, they are grouped as “labor” for easier visualization.
Total Fishing
Value
Predicted Boat and
Fishing Equipment
NGO Credit
Remittance
Income from other
sources
Intermediate Inputs
Fuel Cost
License Fee
Labor
Hired Labor
Household Size
Dependency Ratio
Common Fishing
Ground
Trainings/
Workshops
33 | P a g e
II = Intermediate Inputs (Fuel Cost plus License Fee),
Labor = Hired Labor (HL), Household Size (HHS) and Dependency Ratio (DR)
CFG = Common Fishing Ground (Dummy Variable) and
TW = Trainings/Workshops (Dummy Variable).
If this production function is again related to the sub-hypotheses presented in the previous
chapter, the following questions will be answered.
To what extent will the total fishing value change if the NGO credit, which in turn
affects the capital stock for purchasing boat and fishing equipment, is increased?
To what extent will the total fishing value alter if the accessibility to the common
fishing ground is changed?
To what extent will the total fishing value change if trainings/workshops attendance
changes?
5.1.1 Dependent Variable of the Production Function
The production function’s dependent variable of Total Fishing Value (TFV) consists of
total fish sales revenue and total fish consumption value. As the field research was
undertaken from September to November 2013, the respondents could make good
estimations although the fixed period for collecting data is from April 1, 2012 to March
31, 2013.100
(From now onwards, this period will be referred as one year). Despite the weak
record-keeping of interviewees, it was observed that majority of them had a clear idea of
the fishing pattern which is of help to their calculation of total fishing value. For the sake of
data consistency and cross-checking, two steps of questioning were applied. First, they
were asked to estimate their total fishing income in one year. Second, they were questioned
to give the estimated fishing revenue for each month of that year. If the total fishing
revenue of 12 months is not consistent with the previous estimated figure of the whole year
upon quick cross-checking with a calculator, the fishing income of each month was again
adjusted with respondents in order to obtain the most reasonable fishery revenue figure.
In addition, the total value of fish consumption is also included in this dependent variable
of Total Fishing Value since almost all the beneficiaries are small-scale subsistence fishers,
100
Myanmar fiscal year begins on April 1 of each year and ends on March 31 of the following year. This is
also the case for granting the fishing license by the union/federal government or local government.
34 | P a g e
depending mainly on fish for their nutritional consumption of animal protein. After asking
the market price of the average one-day consumption of fish which is multiplied by the
number of days on which they consumed fish, the monthly amount of fish consumption
value is available. Finally, the total fishing value of dependable variable is obtained by the
addition of total fishing income of 12 months and total fish consumption value of the same
period. Mathematically, it can be expressed as shown below.
Total Fishing Value for 12 months = Total fish sales revenue for 12 months +
Total fish consumption value for 12 months
As elaborated in Table 2 below, the highest frequency of households interviewed gained
300000 MMK101
of total fishing value while the mean value of 717418 MMK, the median
value of 527500 MMK and the standard deviation value of 926,555 MMK are observed.
The minimum TFV is 30000 MMK whereas the maximum TFV is 10710000 MMK.
Table 2: Descriptive statistics of observed total fishing value
N Mean Median Mode Standard Deviation Minimum Maximum
182 717418 527500 300000 926555 30000 10710000
Source: Questionnaire, Question No. 24
5.1.2 Independent Variables of the Production Function
As can be noticed in the equation of the production function presented above, there are 7
independent variables102
which can influence the total fishing income of the fish-workers,
and they will in more details be discussed below in the context of the empirical field
research. Since no single fisher of respondent was observed to make use of modern
technology in his fishing industry in the villages where the survey was conducted, the
variable of technology or total factor productivity is excluded in the production function
and in running the multivariate regression.
101
MMK is the acronym of the currency unit used in Myanmar, meaning that Myanmar Kyat. 102
Labor consists of three independent variables: Hired Labor, Household Size and Dependency Ratio. That
is why there are 7 independent variables together with Boat and Fishing Equipment, Intermediate Inputs,
Common Fishing Ground and Trainings/Workshops.
35 | P a g e
5.1.2.1 Boat and Fishing Equipment (BFE): As boat and fishing gear play the
most important role in the fishing industry of small-scale fishers, their quantities and prices
are also collected for the sake of regression. Though over one-third of participating
beneficiaries of this research possessed no boat as illustrated in Figure 3, they could still be
engaged in the fishing activities as fishing can be done so from the shores, in the gardens
and on the paddy fields.
Figure 3: Boat ownership for the Fishing Activities
Source: Questionnaire, Question No. 15
It is also advisable here to take notice of the following definition of fish in the Freshwater
Fisheries law of Myanmar enacted in 1991 which is still in effect in the whole country as it
has not yet repealed so far despite the enactment of new freshwater fisheries laws in the
respective local parliaments.
“Fish means all aquatic organisms living the whole or a part of their life cycles in the waters, their
spawns, larvae, frys and seeds. This expression also includes aquatic plants, their seedlings and
seeds.”103
Therefore, those who search for eels in the gardens and those who catch crabs on the paddy
fields are also included as fishery beneficiaries by the IFGS project. What can be noticed in
the following photo is a child who is going to trap the eels by making use of the bamboo
Eel Traps/Pots on the paddy fields and in the gardens.
103
State Law and Order Restoration Council (1991): Freshwater Fisheries Law. Article 2(f). p2. Yangon,
Myanmar.
65 (35.7%) 117 (64.3%)
Did you have a boat? (N=182)
Had no boat
Had a boat
36 | P a g e
Photo 1: A child leaving to trap the eels by using bamboo Eel Pots
Source: A photo taken by the author during the empirical field research
Regarding the fishing gear or equipment, the most widely used in the fishing villages of
research area are Fence Net (Pike-bawun), Trammel Net (Nga-tha-lauk-pike), Stow Net
(Kya-pa-zark-pike), Push Net (Yin-toon), Set-gill net (Kwin-tar-pike or Sein-pike),
Portable Cast Net (Let-pyit-kon), Drift Net (Hmyaw-pike), Collapsible Crab Trap (Ka-nan-
hmyone), Prawn Trap (Pazun-hmyone), Eel Pot/Trap (Nga-shint-hmyone), Bottom-set
long-line (Nga-hmyar-tann), Fishing Stick (Kaing-htauk-tan) and others.104
Four widely-
used fishing gear are illustrated for visualization in the following pictures.
Photo 2: Some fishing gear used in the research villages
104
FAO and DoF (2012): Field Guide on Common Fishing Gear. Environmentally Sustainable Food Security
Program (ESFSP) which is also being implemented in the delta region. This guide book is referenced for
fishing equipment terminology and some photographs.
37 | P a g e
Source: Field guide on common fishing gear (FAO and DoF)
When computing the total investment of each household interviewed in the purchase of the
boat and fishing equipment, the mean cost of 268,351 MMK, the median cost of 109,700
MMK and the standard deviation value of 366,911 MMK are observed. While the
minimum investment in the fishing equipment is found out to be 1,800 MMK, the
maximum one is 3,400,000 MMK.
Table 3: Descriptive statistics of observed Boat and Fishing Equipment
N Mean Median Mode Standard Deviation Minimum Maximum
182 268351 109700 35000 366912 1800 3400000
Source: Questionnaire, Question No. 17
NGO Credit: NGO credit is one of the main IFGS project activities to be tested whether
it leads to a positive change in the economic welfare of the fishing folks by means of its
contribution to their purchase of the boat and fishing equipment. This NGO credit is
available to all 117 respondents of project villages with the exception of one interviewee
who did not take it. Table 5 gives more details of NGO credit, showing the mean value of
86,132 MMK, the mode value of 30,000 MMK, the medium value of 65,000 MMK with
the standard deviation of 100,011 MMK.
It was also observed that some households enjoyed two channels of credit as the husband
joined the fishers group and his wife participated in Income Generating Group. Though
different Fishers Development Committees (FDCs) of project villages have different rules
and regulations for and periods of repayments, the total amount of credit taken for each
household was computed for the regression.
38 | P a g e
Table 4: Descriptive statistics of NGO Credit
N Mean Median Mode Minimum Maximum Standard Deviation
182 86,132 65,000 0 0 540,000 100,012
Source: Questionnaire, Question No. 12
Remittance: As the remittance can also be expended for purchasing the boat and fishing
equipment such as different kinds of nets and traps, it will also be tested whether the impact
it has on the purchase of fishing gear is statistically significant or not. As depicted in Figure
4, only about one-tenth of the total respondents had some channels of remittance and over
90% of interviewees obtained no remittance in 2012-2013 fishing license period.
Figure 4: Remittance Receipt of households of Respondents
Source: Questionnaire, Question No. 27
Income from Other Sources: Income from other sources, which consists of Income
from Livestock and Own Land, Income from Wage Labor, Income from Salaried
Employment and others, will also become one of the three independent variables of the
first-stage regression of calculating predicted BFE. Collecting this information was also
time-consuming as counter-checking had to be undertaken so that the most reasonable
figures could be obtained for each category.
In terms of livestock, most respondents are observed to raise pigs, chickens and ducks. In
order to earn wage, majority worked on the paddy fields from the season of
0
20
40
60
80
100
120
140
160
180
Received no Remittance Received Remittance
166(91.2%)
16(8.8%)
Situation of Remittance Receipt of Respondents (N=182)
39 | P a g e
growing/ploughing to the season of harvesting twice in a year as double-cropping is widely
practiced there. Some people also got seasonal employment as a fishery worker in the
fishing ships that go to the nearby Andaman Sea. Some also earned income by means of
Nipa-palm-leave cutting and knitting which is widely and mainly used for roofing and
walling the houses in this Delta Region. The following photograph depicts the Nipa-palm
trees growing on the bank of a stream and a home which is walled and roofed by the use of
dry knitted Nipa-palm-leaves.
Photo 3: Nipa-palm trees and a house built of knitted Nipa-palm-leaves
Source: A photo taken by the author during the field research
5.1.2.2 Intermediate Inputs (II): As the intermediate inputs consist of fuel costs and
license fees in this production function, they will be separately presented in more details
below. As they have the same unit of currency (in MMK), they were added together to
obtain one figure and treated as one explanatory variable in the second-step regression of
computing predicted TFV.
Fuel Cost: Though some households owned a small boat, they had to rely on hand-
rowing by the use of oars for their fishing activities as they could not afford to buy an
engine and fuel cost. Nearly a quarter of total respondents could purchase the engine, and
consequently they had to expend some amount of capital for purchasing the intermediate
input of fuel.
40 | P a g e
Figure 5: Engine possession for boat driving in the fishing activities
Source: Questionnaire, Question No. 16
License Fee: With regard to the individual license as illustrated in Figure 6, only about
two-fifth (39.6%) of interviewees reported that they have purchased a license, which in turn
suggests that majority of beneficiaries relied on the common fishing ground or they fished
in the gardens or on the farms where no license is necessary. When questioned to whom
they paid their license fee again, nearly half of 72 respondents was found to be sub-granted
by the tender license holders whilst over one-third paid to the Department of Fisheries.
Interestingly, it is found out that 15.3 % of all license fee payers were noticed to give the
fee to both DoF and tender license holders as elaborated in Figure 7.
Figure 6: Proportion of individual license holders and non-holders
Source: Questionnaire: Question No. 19
142 (78%) 40 (22%)
Did you have an engine for boat? (N=182)
Had no engine
Had an engine
0
20
40
60
80
100
120
Had individual license Had no individual license
72 (39.6%)
110 (60.4%)
Did you have individual license? (N=182)
41 | P a g e
Figure 7: Proportion of fishery license fee recipients
Source: Questionnaire: Question No. 20
When asked about the amount of the license fee, the minimum fee is 5000 MMK whilst the
maximum fee is 7000000 MMK. The highest frequency of license holders paid 8000 MMK
whilst the mean fee is 1084257 MMK and the median fee is 45000 MMK.
Table 5: Descriptive statistics of license fee
N Mean Median Mode Minimum Maximum
72 1084257 45000 8000 5000 7000000
Source: Questionnaire: Question No. 19
5.1.2.3 Labor: As regarding the labor which is included in the production function, it is
discussed based on the hired labor, household size and dependency ratio whose
explanations will be followed below.
Hired Labor: Hired labor is also one of the explanatory variables which can affect the
total fishing value of beneficiaries. Figure 8 illustrates that only about one-sixth could
afford to hire the labor while the remaining respondents were involved in the fishing
activities with family members only.
27 (37.5%) 34 (47.2%)
11 (15.3%)
To whom did you pay your license fee? (N=72)
To Department of
Fisheries
To Tender license holders
To Both
42 | P a g e
Figure 8: Proportions of respondents with hired labor and without hired labor
Source: Questionnaire, Question No. 22
Household Size: Under the circumstances where there is no hired labor, the household
size can be also an influencing factor on the total fishing income as the households with
higher family number have greater possibilities of more people engaged in fishing. As
illustrated in Figure 9 below, over a quarter of the respondents’ families have 4 members
whereas the remaining proportion of three-quarters consists of interviewees with family
members of 2, 3, 5, 6, 7, 8 and 9. Interestingly, there is a respondent who has 10 family
members and a respondent with no family member, living alone. The medium and the mode
of household size are 4, having the mean value of 4.49 and standard deviation of 1.54.
Figure 9: Frequency of Family by Household Size
Source: Questionnaire, Question No. 9
0
20
40
60
80
100
120
140
160
Had hired labor Had no hired labor
29 (15.9%)
153 (84.1%)
Did you have hired labor? (N=182)
1
12
39
49
37
28
10
3 2 1 0
10
20
30
40
50
60
Frequency of family with different HH Size (N=182)
43 | P a g e
Table 6: Descriptive statistics of Household Size of Respondents
N Mean Median Mode Standard Deviation Minimum Maximum
182 4.49 4 4 1.54 1 10
Source: Questionnaire, Question No. 9
Dependency Ratio: Since the higher or lower proportion of dependency ratio of a
household can impact the engagement of its family members in the fishing activities, it is
also calculated as one of the explanatory variables. In order to compute the dependency
ratio with the age group of 14 and under as well as the age group of 65 and above by means
of the below-mentioned formula, the age and the name of every member of the
participating households were collected. The following figure will illustrate the number of
dependent members in 182 families interviewed.
( )
× 100
Figure 10: Number of households with different dependent members
Source: Questionnaire, Question No. 9
5.1.2.4 Common Fishing Ground (CFG): Though the IFGS project provided
technical assistance to the project villages in applying for the common fishing ground, only
three villages were successful for 2012-2013 fishing license period. As illustrated in Figure
11, only over a quarter of respondents had access to the common fishing ground while
38 (20.9%)
59 (32.4%)
43 (23.6%)
26 (14.3%)
11 (6.0%)
3 (1.7%) 2 (1.1%)
0
10
20
30
40
50
60
70
0 Dependent
Member
1 Dependent
Members
2 Dependent
Members
3 Dependent
Members
4 Dependent
Members
5 Dependent
Members
6 Dependent
Members
Number of households with different dependent members (N=182)
44 | P a g e
some respondents from the project villages had no access to it like those in non-project
villages. It will be treated as an independent dummy variable in the multiple regression
analysis.
Figure 11: Access to Common Fishing Ground
Source: Questionnaire, Question No. 18
5.1.2.5 Trainings/Workshops (TW): By participating in the workshops/trainings
conducted by IFGS project such as the fisheries law workshop, value-added training and
fishing equipment-making training, the beneficiaries may also have the possibility of
raising their total fishing value, empowering their human capital.
Figure 12: Attendance of Trainings/Workshops of respondents
Source: Questionnaire, Question No. 13
52 (28.6%) 130 (71.4%)
Access to common fishing ground (N=182)
Had Common Fishing
Ground
Had no Common
Fishing Ground
28 (15.4%)
154 (84.6%)
0
20
40
60
80
100
120
140
160
180
Attended Trainings /Workshops Attended no Trainings/Workshops
Attendance of Trainings /Workshops (N=182)
45 | P a g e
Figure 12 indicates that almost 85% had not participated in the trainings/workshops
whereas the remaining 15% had the opportunity of joining them, signaling that majority of
respondents from the project villages had no chance of participation. Trainings/workshops
will also be applied as an independent dummy variable like the common fishing ground, so
as to check whether it has a statistically significant association with the total fishing value
of fishery beneficiaries.
5.2 Predicted Total Fishing Value with the NGO-Intervention
As it, before running the multivariate regression of the whole production function presented
above, is necessary to know whether or not the capital stock of purchasing boat and fishing
equipment comes from NGO credit, Remittance and Income from Other Sources, a two-
stage regression model will be applied. Especially, it is of importance to know whether
NGO credit was spent on purchasing boat and fishing gear, which in turn will impact the
total fishing value of small-scale fishers.
5.2.1 Calculation of Predicted Boat and Fishing Equipment
The intercept, the coefficient of NGO credit, the coefficient of Remittance and the
coefficient of Income from Other Sources will be provided by the following function which
utilizes Observed BFE, thereby enabling us to compute Predicted BFE (the predicted
capital stock for purchasing boat and fishing equipment).
Observed BFE = f (NGO Credit, Remittance, Income from Other Sources)
= θ0 + θ1 * NGO Credit + θ2 * Remittance + θ3 * Income from Other
Sources + εi
where εi = the error terms.
Using the constant and coefficients of the three independent variables gained by
means of running the first-step linear regression, the following equation can be
developed in order to calculate the predicted BFE of each household interviewed.
Predicted BFE = θ0 + θ1 NGO Credit + θ2 Remittance + θ3 Income from Other
Sources + εi
46 | P a g e
= 80229.033 + 1.438*NGO Credit + 0.052*Remittance + 0.119* Income
From Other Sources + εi
Table 7: Output of Stage-1 Regression with Project
Dependent Variable: BFE Coefficients t-value Sig.
Constant 80229.033 1.791 0.075
Remittance 0.052 0.532 0.595
Income from other sources 0.119 2.000 0.047
NGO Credit 1.438 5.590 0.000
N 182 α 0.050
R 0.425 R-squared 0.181
F-value 13.101 Sig. for F-value 0.000
Source: Questionnaire and SPSS output
Upon having a look at the table outputted by the SPSS after running the first-stage
regression, it can be clearly noticed that NGO credit is the most significant independent
variable (t-value = 5.59 and p-value = 0.0001) on the dependent variable of predicted BFE
for purchasing boat and fishing gear. Specifically speaking, if there is 1MMK increase in
NGO credit, the predicted BFE also goes up 1.438 MMK, holding remittance and income
from other sources constant. Similarly, Income from Other Sources is statistically
significant with t-value of 2.000 and p-value of 0.047, suggesting that if it goes up by 1
MMK, the predicted BFE also increases by 0.119 MMK while keeping the remaining two
explanatory variables fixed. Nevertheless, it was found out that remittance is not
statistically significant, having the t-value of 0.532 and p-value of 0.595.
On the other hand, the R value of 0.425 means that there is a rather strong relationship
between the predicted BFE and the three explanatory variables of remittance, income from
other sources and NGO credit. Although the R2 value of 0.181 implies that about 18.1% of
total variability in the dependent variable is explained by the above 3 independent
variables, the F-value of 13.101 with p-value of 0.0001 indicates that this is a significant
association.
5.2.2 Calculation of Predicted Total Fishing Value
In this second stage of two-stage regression, NGO Credit, remittance and Income from
other sources will also be indirectly used as predicted BFE which is derived in the first
47 | P a g e
stage regression. As the Common Fishing Ground and Trainings/Workshops are categorical
variables, they were coded into dummy variables so that they can be included in the
multiple regression. As the three categories of Labor cannot be combined together because
of their different units, they will stand separately with different coefficients of γ3, γ4 and γ5
in the equation.
Predicted TFV = f (Predicted BFE, II, Labor, CFG, TW)
= f (Predicted BFE, II, HL, HHS, DR, CFG, TW)
Predicted TFV = γ0 + γ1 Predicted BFE + γ2 II + γ3 HL + γ4 HHS+ γ5 DR + γ6 CFG +
γ7 TW + εi (where εi is the error terms)
= 50404.863 + 1.325*Predicted BFE + 0.001*II + 3.351*HL+
46376.738*HHS – 829.537*DR – 109916.427*CFG + 159526.495*TW
Table 8: Output of stage-2 regression with Project
Dependent Variable: TFV Coefficients t-value Sig.
Constant 50404.863 0.510 0.611
Predicted BFE 1.325 4.740 0.000
Intermediate Inputs (II) 0.001 0.060 0.952
Hired Labor (HL) 3.351 9.133 0.000
Household Size (HHS) 46376.738 2.123 0.035
Dependency Ratio (DR) -829.537 -1.624 0.106
Common Fishing Ground (CFG) -109916.427 -1.216 0.226
Trainings/Workshops (TW) 159526.495 1.744 0.083
N 182 α 0.050
R 0.907 R-squared 0.823
F-value 115.209 Sig. for F-value 0.000
Source: Questionnaire and SPSS Multiple Regression Output
Since the R value equals 0.907 as shown in table 8, there is a very strong positive
relationship between the dependent variable of predicted TFV of small-scale fishers and the
group of selected independent variables. The R2
value of 0.823 indicates that 82.3% of
variation in total fishing value is explained by the variation in the given independent
variables, which is really a high degree of explanation, implying that the model fits the data
48 | P a g e
well. This statistical significance is also confirmed by the F-value of 115.209 and p-value
of 0.0005.
Returning to the independent variables associated with the IFGS project activities, t = 4.740
and p = 0.0001 of predicted BFE suggests that it has a significant relationship with
predicted total fishing value. Specifically speaking, if the predicted BFE (in which the
NGO credit is the most significant) goes up by 1 MMK, the total fishing value of the
fishers also rises by 1.325 MMK, keeping all the remaining dependent variables constant.
Nevertheless, the p-vale of 0.083 and t-value of 1.744 suggest that Trainings/Workshops
attendance has no statistically significant association with the dependent variable of
predicted TFV. Similarly, the p-value of 0.226 and t-value of -1.216 also imply that the
Common Fishing Ground is also not statistically significant. The possible causes of such
insignificant impacts of common fishing ground as well as trainings/workshops will be
discussed more in the final chapter of Conclusion and Recommendations.
When it comes to the remaining four explanatory variables which are not related to the
project, Intermediate Inputs of fuel cost and license fee has no significant relationship
with total fishing value as it has p-value of 0.952 and t-value of 0.60. Returning to the
association of the Labor with predicted TFV, hired labor (p-value = 0.0001 and t-value =
9.133) and household size (p-value = 0.035 and t-value = 2.123) are statistically significant
whereas dependency ratio (p-value = 0.106 and t-value = -1.624) is not statistically
significant. Finally, the derived equation from this stage-2 regression will be used to
compute the predicted total fishing value of each household “with project intervention” so
that it can be compared with “without project intervention”.
5.3 Predicted Total Fishing Value without the NGO-Intervention
In order to know the impact of IFGS project activities on the fisheries beneficiaries, it is
necessary to obtain the difference between the predicted TFV with project and the predicted
TFV without project. For the purpose of getting the predicted total fishing value without
project, the coefficients of the two-stage regression acquired before will be applied again.
After kicking out NGO credit in the equation of the first-stage regression developed above,
the predicted BFE without project can be calculated as shown below.
Predicted BFE = f (Remittance, Income from other sources)
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= θ0 + θ1 * Remittance + θ2 * Income from Other Sources + εi
= 80229.033 + 0.052*Remittance + 0.119* Income from Other Sources
Afterwards, by using the predicted BFE without project of each households interviewed in
the equation of second-stage regression established before as well as excluding Common
Fishing Ground and Trainings/Workshops, the following equation will be obtained to be
able to calculate the predicted TFV of each survey household in the context of “without
project”.
Predicted TFV = f (Predicted BFE without project, II, HL, HHS, DR)
= α0 + α1 Predicted BFE + α2 II + α3 HL + α4 HHS + α5 DR + εi
= 50404.863 + 1.325 * Predicted BFE + 0.001 * II + 3.351 * HL +
46376.738 * HHS - 829.537 * DR + εi
This equation of predicted TFV without project will be also utilized below in order to
compute the overall impact of the NGO-intervention.
5.5 Calculation of the IFGS Project’s Impact
With the purpose of measuring the impact of the IFGS project on the small-scale fishers,
the predicted total fishing value of every household surveyed will be calculated under two
conditions of “with project” and “without project”, making use of the two derived equations
developed above.
TFV (With Project) = 50404.863 + 1.325 * Predicted BFE + 0.001* II + 3.351*HL +
46376.738*HHS–829.537*DR–109916.427*CFG + 159526.495*TW
TFV (Without Project) = 50404.863 + 1.325 * Predicted BFE + 0.001 * II + 3.351*HL +
46376.738*HHS – 829.537*DR
Economic welfare change of each household = TFV (With Project) – TFV (Without Project)
Total economic welfare change of the sample =∑ ( TFV (With Project)-TFV(Without Project))
= 130,572,696 – 101,953,342
= 28,619,354 MMK
50 | P a g e
After calculating the impact of the IFGS project activities on each household interviewed
resulting from NGO credit, Common Fishing Ground and Trainings/Workshops, the total
economic welfare impact of the IFGS project on the beneficiary respondents (118 out of
182 respondents) will be available by adding the impact each household acquired together.
Average economic welfare change of sample =
=
= 242,537 MMK
After that, the figure of total economic welfare change of the sample will be divided by the
number of interviewees from project villages in order to know the average economic
welfare change of the sample, which will be applied to calculate the overall impact of the
project generalizing from the sample size to the population. According to the calculation
presented above, each household of fishery beneficiary has obtained an economic welfare
increase of 242,537 MMK in 2012-2013 fishing license period.
Total economic welfare change of the project = 242,537 * Total No. of beneficiaries
= 242,537 * (1598)105
= 387,574,126 MMK
= 392,679 USD106
As random sampling is applied in the field research and the cross-sectional data is assumed
to be homoscedastic in data analysis and linear multiple regression, the overall economic
welfare change of the IFGS project can be calculated by the multiplication of economic
welfare increment of each beneficiary by the total beneficiary number of the project.
Though it is computed that the overall economic welfare change of the project over 2012-
2013 fishing license period is 387,574,126 MMK (392,679 USD), it should be noted that
the IFGS project can bring more increment in the economic welfare of small-scale fishers if
105
Though the number of targeted beneficiary households is 2500 according to the IFGS project proposal, the
realized one is 1598 in total. It is also wise to take notice that these 1598 beneficiaries enjoyed the benefits of
the IFGS project in different years over 2011-2014 period. (Confirmed with the finance officer of IFGS
project on January 29, 2014 and re-confirmed with Mr. Yin Nyein, the program officer of IFGS project on
February 07, 2014.) However, it is assumed that they obtained the benefits of the project activities in the same
year as the project inputs are almost the same in all villages. 106 http://forex.cbm.gov.mm/index.php/fxrate (1 USD = 987 MMK) Accessed on January 30, 2014.
51 | P a g e
the NGO credit can be effectively and efficiently managed by FDC leaders since it will be
kept in their hands as the revolving fund after the exit of the project at the end of 2014.
52 | P a g e
6 CONCLUSION AND RECOMMENDATIONS
6.1 Conclusion
The fundamental objective of this field research is to test empirically whether the IFGS
project intervention leads to an improvement in the economic welfare of rural small-scale
fishers. As the IFGS project activities include public goods/services (NGO credit,
Trainings/Workshops and Common Fishing Ground) affecting the use of private goods of
these fishers through the utilization of their total fishing value, the productivity method of
Cost Benefit Analysis theory was selected to be applied. According to this productivity
method, the production function was established to specify the functional relationship
between the output (Total Fishing Value) and the inputs (Boat and Fishing Equipment,
Intermediate Inputs, Hired Labor, Household Size, Dependency Ratio,
Trainings/Workshops and Common Fishing Ground).
In identifying the welfare changes experienced by the small-scale fishers resulting from the
NGO intervention, the two-stage multiple regression was utilized as it is necessary to know
whether or not the fishers invested the NGO credit they gained in purchasing boat and
fishing equipment in the first stage regression, leading to the computation of the predicted
BFE which has to be used in the second-stage regression. For the calculation of predicted
BFE, Remittance and Income from Other Sources are also used in the regression in addition
to NGO credit. From the observation of the coefficients, it is noticeable that NGO Credit is
the most significant (t-value = 5.59 and p-value = 0.0001) among the three explanatory
variables. Specifically interpreting, if the NGO credit rises by 1 MMK, the predicted BFE
also goes up by 1.438 MMK, holding remittance and income from other sources fixed.
In the second-stage regression, together with other four inputs mentioned above, the impact
of the predicted BFE, the common fishing ground and trainings/workshops on the total
fishing value is measured to know the economic welfare changes of small-scale fishers
resulting from the IFGS project activities. It should also be remembered here that the two
categorical variables of common fishing ground and trainings/workshops were treated as
dummy variables so that they can be included in the multiple regression. In this second-
stage of multivariate regression, it is observed that if the predicted BFE increases by 1
MMK, the predicted TFV of the small-scale fishers rises by 1.325 MMK (t-value = 4.74
and p-value = 0.0001), revealing that the provision of NGO credit results in an indirect
53 | P a g e
improvement in the economic welfare of fishers. Interestingly, it is also noticed that having
access to the common fishing ground and attendance of trainings/workshops are not
statistically significant. As regards the remaining four explanatory variables, it is found out
that Hired Labor and Household Size have statistically significant relationships with the
predicted TFV whilst Dependency Ratio and Intermediate Inputs are not statistically
significant. Finally, the predicted TFV is calculated for all households interviewed, using
the equation of second-stage regression established.
On the other hand, with the purpose of measuring the difference between “with and
without condition” of the IFGS project, the predicted BFE is also calculated again under
“without project” circumstance after kicking out NGO credit in the equation of the first-
step regression. After that, using this predicted BFE and excluding Common Fishing
Ground and Trainings/Workshops from the equation of second-stage regression, the
predicted TFV is computed again. Eventually, by subtracting predicted TFV (Without
project situation) from predicted TFV (With project situation), the total impact of the IFGS
project on the sample (118 beneficiaries)107
is available, which is divided by 118 again to
know the average economic welfare increase of each project household surveyed. When the
increment in the economic welfare of a fisher (242,537 MMK) is multiplied by the number
of total beneficiaries (1598), the overall impact of the IFGS project becomes 387,574,126
MMK (392,679 USD).
Based on the aforementioned results and empirical findings, it can be summarized that the
NGO credit has an indirectly-positive impact on the total fishing value of fishers despite the
insignificant influence of Trainings/Workshops and Common Fishing Ground, and
therefore the main hypothesis holds true that IFGS project activities lead to an increase in
the economic welfare of small-scale fishers. Regarding the three sub-hypotheses, the first
one associated with NGO credit holds true whilst the second and third ones related to the
Trainings/Workshops and Common Fishing Ground do not hold true as they are not
statistically significant. Nevertheless, it is of importance to acknowledge that the empirical
research encountered some limitations. First and most importantly, majority of the
respondents are subsistence fishers who are not educated, and consequently, they are very
weak in record keeping, leading to the estimated figures in terms of fish sales revenue,
107
Sixty-four respondents are from non-project villages so they are excluded.
54 | P a g e
income from other sources and expenditures on fishing equipment. Second, as the field
research period unfortunately coincided with the rainy season, the fishers were heavily
loaded with their fishing activities, resulting sometimes in difficulty in drawing their full
attention and active participation.
6.2 Recommendations
The empirical field study of the impacts of IFGS project activities on the economic welfare
of small-scale fishers revealed a number of recommendations for the project-implementing
organization (NAG), the small-scale fishers as well as the DoF and the local government of
the Ayeyarwady Region. The most important recommendations are outlined as follows:
Recommendations to the Project implementing organization (NAG): First,
IFGS project should pay special attention to NGO credit management since the empirical
findings indicate that this credit leads to an indirect positive change in the economic
welfare of the local fishers, playing a statistically significant role in purchasing their boat
and fishing equipment which in turn contributes to the augmentation of their total fishing
value. Hence, the leaders of FDCs and VDCs should be in advance well-trained and well-
equipped with context-friendly coping mechanisms so that they have the capability of
solving any problem they might encounter in the future and of maintaining the positive
effects of the revolving fund108
after the exit of the IFGS project at the end of 2014. In
some villages such as Tha-gya-hin-oo, the leadership of FDC chairman and one of its
members is so effective coupled with good record-keeping that the revolving fund is well-
managed and still well-functioning. However, in some villages such as Ahsi-ka-lay, the
management of the revolving fund is observed to be weak, encountering some problems.
Before the exit of the project, the IFGS staff should more extensively and frequently
monitor the performance of VDC and FDC leaders over their revolving funds, and financial
management trainings should as necessary be provided again so that it can bring continued
welfare increment in the future in the absence of the project.
108
After one-year implementation of the project in each village, the NGO credit was transferred to FDCs and
VDCs as the revolving fund. That is why the first-year 15 villages and the second-year 15 villages have
already obtained the revolving fund, and their FDCs and VDCs are responsible for the management of this
fund.
55 | P a g e
Second, the root causes of the insignificant impact of the Common Fishing Ground on the
total fishing value of small-scale fishers should be systematically investigated. If it is
because of scarce quantity of fish in the common fishing grounds as reported by some
respondents during the field research, more advocacy measures need to be launched to
convince the DoF officials or fishery authorities to provide the rural fishers with access to
the common fishing ground teeming with higher quantity of fish. On the other hand, it
should also be detected that it is whether or not due to the shortcomings and weak capacity
of respective FDC in implementing fishery co-management as some respondents mentioned
the use of more powerful fishing gear which is not legally allowed in the common fishing
ground. As DoF is now providing a few common fishing grounds and keeping a constant
watch on the functionability of fishery co-management mechanism, such a condition can
lead to discouraging DoF. That is why some feasible and workable coping mechanisms
should be explored, established and implemented as quickly as possible in this regard.
What can become a negotiating platform for such problems is the inclusive Fisheries
Governance workshops of IFGS project, like the one organized in October 2013 in the
capital of Ayeyarwady Region and attended by a variety of key stakeholders including the
local parliamentarians, the ministers, high-ranking government officials, different NGOs,
several civil society organizations, members of local fishery associations and fisheries-
related businessmen.
Third, since the trainings/workshops also have an insignificant impact on the economic
welfare of small-scale fishers, some exploratory measures should be performed with respect
to their effectiveness. It should be ensured that those who attended the trainings/workshops
make use of what they have learnt during the sessions, contributing to the enhancement of
their human capital. Some respondents reported that they stopped the application of fishery-
related trainings (e.g. fish cracker production) as they could not make profit, highlighting
that more village-context-friendly trainings and techniques are in need of being organized.
Among 118 project-respondents interviewed, nobody expressed the income earned from
making fishing equipment although there are some trainings associated with fishing-
equipment production.
Recommendations to the small-scale Fishers: First, the leaders of FDCs and
VDCs, if possible the fishers themselves, need to deepen and broaden their scope of
56 | P a g e
knowledge associated with the fishery laws, rules and regulations with the help of NGOs
and civil society organizations so that they can readily and systematically request what they
deserve from DoF whenever feasible since some respondents reported their lack of
knowledge and information in this case. Especially when it comes to the common fishing
ground, the members of FDCs should be in active coordination with NGOs and DoF in
setting up the context-friendly mechanisms in order to ensure the long-term sustainability
of fishery resources and prove the applicability of fisheries co-management, winning the
trust of DoF government officials. In one project village which enjoys the opportunity of
having access to the common fishing ground, some respondents reported the use of
prohibited fishing gear of some fishermen. Such illegal actions should be well-monitored
and well-controlled by FDCs and VDCs in order to contribute to the perpetuation of the
right of common fishing ground.
Second, the fishers should also lend a helping hand to DoF in identifying those who break
the fishery laws and rules, especially
catching fish with explosive substance, poisons and chemicals,
catching fish with a prohibited method and fishing implement,
catching fish of a prohibited species and size and
catching fish during a prohibited period and at a prohibited place since some
examples of such violation are also reported by some respondents.
Such cooperation will contribute highly to the successful implementation of the fishery co-
management system in their villages and in the whole Ayeyarwady Delta Region of
Myanmar.
Recommendations to the DoF and the local Government: First, as presented
in the Literature Review of Chapter TWO, the failure of top-down and centralized
arrangements in the small-scale fisheries all over the world has resulted in the
establishment of more-devolved and locally-accountable management mechanism and
development of fishery co-management arrangements. In the research villages also, the
respondents reported their significant desire of having common fishing ground or
community-based fisheries management system. That is why DoF should also strengthen
and scale up its coordination and cooperation with NGOs, MFF, SEADEFC and WorldFish
57 | P a g e
in order to successfully implement and administer fishery co-management structures in the
Ayeyarwady Delta Region.
Second, the enforcement mechanism of fishery law and rules should be practically set up
and implemented for the sustainability and conservation of fishery resources as some
interviewees pointed out the usage of fishing nets with illegal mesh size and others. The
current common fishing grounds should also be monitored regularly in coordination with
FDCs and village authorities. In doing so, higher degree of transparency, accountability and
responsiveness should be practiced to win the trust of small-scale fishers and other fishery-
related stakeholders.
Third, though the high volume of revenue for the local government can be generated by
auctioning the fishing grounds, it is reported that they consequently become inaccessible to
poor small-scale fishers, leading to the gradually-increasing unemployment and poverty
trap of fishers in these fishing villages. That is why it should be noted that inland fisheries
can contribute to the poverty alleviation only when the distribution of fisheries revenue
promotes pro-poor growth or is re-invested in the infrastructure and public services for the
poor and the marginalized from these fishing villages.
Recommendation for further Research on IFGS Project: In conclusion, as
some governance-oriented IFGS activities such as the publication and dissemination of the
regular newsletter, the establishment of the resource center and the arrangement of
fishworkers’ official visits to DoF office are beyond the scope of this quantitative field
research, they will be open for another qualitative research to test whether they are of actual
benefit to the fishery beneficiaries or not.
58 | P a g e
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ANNEXES
Annex 1: Standardized pre-structured household questionnaire
Ruhr University of Bochum, Germany (Sep-Nov, 2013)
Household Questionnaire for the Economic Evaluation of
Improving Fisheries Governance System (IFGS) Project, Pyapon, Myanmar
Mingalarbar (Guten Tag)! My name is Om Ki, and I am a Master’s student from the
Institute of Development Research and Development Policy, Ruhr University of Bochum,
Germany. For my Master’s thesis, I am currently conducting an academic research,
assessing the impacts of IFGS project of NAG on the economic welfare of the affected
small-scale fishers.
It is an anonymous and voluntary questionnaire, and the information given by you will be
kept strictly confidential and used for academic purposes only. Most people need roughly
30 minutes to finish this household survey. Would you like to participate? Thank you very
much.
Enumerator’s name: ……………… Interview No. (Household ID): ………………………
Date: ……………………………… Township: …………………………………………….
Section A: Personal Information and Household Composition
1. Name of Household Head: ……………………………………………
2. Person interviewed (If other than household head): ………………….
3. What is the name of your village and municipality? ….………………/………………….
4. Gender (Observe):
Female (1) Male (2)
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5. What is your marital status?
Married (1) Single (2) Widow (3) Divorced (4)
6. What is your year of birth?
19………….. (Gregorian Calendar) or 13……….… (Myanmar Calendar)
7. What is your education level?
No Education (0) Primary (1) Secondary (2) Tertiary (3)
8. How would you in general categorize your household earnings?
Very Low (1) Low (2) Medium (3) High (4)
9. Household Composition (Resident household members only)
No. Name Gender (Male=M & Female=F) Age
1
2
3
4
5
6
7
8
Section B: Project-related Information
10. Was your household a beneficiary of IFGS project?
Yes (1) No (0) If no, go directly to Section - C.
11. In which group(s) of IFGS project did your household participate?
Fishers Group (1) Aquaculture Group (2)
Fish Collector Group (3) Processing /Income-generating Activities Group (4)
12. Did you receive credit from IFGS project from April 2012 to March 2013?
Yes (1) No (0) If no, go to 13. If yes, go to table.
NGO Credit Duration (Month) Interest Rate/Month Interest rate from other sources/Month
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13. Did your household members attend IFGS project workshops and trainings?
Yes (1) No (0) If yes, go to table.
No. Name of Training or Workshop Duration (No. of Days) Perceived as beneficial/
useful (Yes or No)
14. What is the prevailing wage rate in the village or region? (Cross-check with other
Sources)
Female (1)………………..Kyats Male (2)………………..Kyats
Section C: Information on Capital and Labor in Fishing Activities
15. Did you have a boat in 2012-2013 fishing license period?
Yes (1) No (0) If yes, current market price ………………..Kyats
16. Did you have engine for boat?
Yes (1) No (0) If yes, current market price ……………….....Kyats
If yes, please estimate average monthly expenses on fuel for boat. ….…….…...Kyats
17. Did you have fishing nets or gear?
Yes (1) No (0) If yes, go to table.
No Name of Fishing Gear/ Nets Quantity Current Market Price Total Price
1
2
3
4
5
6
7
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18. Did you have access to the common fishing ground in 2012-2013 fishing period?
Yes (1) No (0) If yes, license fee …………………..Kyats
19. Did you have individual (Implement) fishing license in 2012-2013 fishing period?
Yes (1) No (0) If yes, license fee …………………..Kyats
20. To whom did you pay license fee?
Department of Fisheries (1) Tender license holder and others (2)
21. Did you have small-scale aquaculture farming (Fish, Crab, Eel)?
Yes (1) No (0)
If yes, how much did you invest in it? …………………Kyats
22. Labor in Fishing Activities (April 2012 – March 2013)
Labor Type Labor No. Labor Wage (Monthly) Working Months/ Year Total Cost
Family member
Hired labor
Section D: Information on Fishing Production
23. Was your household able to sell any fish on market in 2012-13 fishing license period?
Yes (1) No, exclusively producing for subsistence purposes (0)
24. Please estimate monthly total fishing value in 2012-13 fishing license period.
No. Month Estimated Fish
Sale Income
Estimated Fish
Consumption Value Total
1 Apr -12 (Tagu,1374)
2 May -12 (Kason,1374)
3 Jun -12 (Nayone,1374)
4 Jul -12 (Waso,1374)
5 Aug -12 (Wakaung,1374)
6 Sep -12 (Tawtalin,1374)
7 Oct -12 (Thadingyut,1374)
8 Nov-12(Tasaungmon,1374)
9 Dec -12 (Nataw,1374)
10 Jan -13 (Pyatho,1374)
11 Feb -13 (Tabotwe,1374)
12 Mar -13 (Tabaung,1374)
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Section E: Information on Household Income
25. Did your household have any cash income in the 2012-2013 fishing license period?
Yes (1) Average monthly income in the period: ……..……………. Kyats
No (0)
26. Please estimate the shares of the different income sources that have contributed to your
household’s cash income in the 2012-2013 fishing license period?
No Income Sources Particulars (Specify) Amount
1 Income from Fishing activities Sales of fish
2 Income from Livestock & own land Sales of Livestock, fruits & crops
3 Income from Wage labor
4 Income from Salaried employment
5 Income from Remittance
6 Income from Other sources
27. Did any member of your household live outside the village who financially supported
your household (i.e. providing remittance income) in 2012-2013 fishing license period?
Yes (1) => Add income under “remittance” above. No (0)
28. Is there anything else you would like to share with us about how IFGS project has
changed the life of your household and fishing community? (For project villages only)
Many thanks for your cooperation!
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Annex 2: Field Research Timetable
Week No. Period Tasks Accomplished
Week - 1 19.08.2013 - 25.08.2013 Flight to Myanmar & Family Gathering at Home
Week - 2 26.08.2013 - 01.09.2013 Going to NAG field office, Meetings with IFGS Project
Manager, Field Team Leader and staff as well as experts
Week - 3 02.09.2013 - 08.09.2013 Pilot Test, Revising Questionnaire & Confirmation by
Supervising Professor
Week - 4 09.09.2013 - 15.09.2013 Village 1, 2 and 3 of Non-Project Villages
Week - 5 16.09.2013 - 22.09.2013 Village 1 and 2 of Project Villages
Week - 6 23.09.2013 - 29.09.2013 Village 3, 4 and 5 of Project Villages
Week - 7 30.09.2013 - 06.10.2013 Village 4 of Non-Project Villages
Week - 8 07.10.2013 - 13.10.2013 Attended the Fishery Governance workshop organized by
NAG and Oxfam GB in Pathein, Ayeyarwady Region
Week - 9 14.10.2013 - 20.10.2013 Break
Week - 10 21.10.2013 - 27.10.2013 Data Entry & Going to IFGS Project Office
Week - 11 28.10.2013 - 03.11.2013 Data Entry & Meeting with CEO of NAG
Week - 12 04.11.2013 - 10.11.2013 Data Entry
Week - 13 11.11.2013 - 20.11.2013 Family Gathering & Flight back to Germany
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Annex 3: Gender of Respondents
Of 182 respondents interviewed in the household survey, gender balance can be observed
despite the use of random sampling as females outnumber males just by 6. Men consist of
48 percent of the total respondents whereas 52 percent of total interviews are women.
Figure: Gender of Respondents
Source: Questionnaire, Question No. 4
94 (52%) 88 (48%)
Gender of Respondent (N=182)
Female
Male
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Annex 4: Marital Status of Respondents
As regards the marital status of respondents, 92.9% of respondents are married while only
1.1% of divorced people can be observed. While 2.7% are single, widow/widower consists
of 3.3% of total interviewees.
Figure: Marital Status of Respondents
Source: Questionnaire, Question No. 5
0
20
40
60
80
100
120
140
160
180
Married Single Widow Divorced
169 (92.9%)
5 (2.7%) 6 (3.3%) 2 (1.1%)
Marital Status of Respondents (N=182)
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Annex 5: Gender Vs Marital Status of Respondents
As can be observed in the table below, among the 169 married interviewees, 51.5 % are
females and 48.5% are males. Of 5 single respondents, 3 are women and 2 are men. While
widow group of 6 consists equally of 50% of men and 50% of women, divorced group of 2
also indicates the same percentage.
Table: Gender by Marital Status of Respondents
Gender of
Respondent
Marital Status of Respondents Total
Single Married Divorced Widow
Male Count 3 87 1 3 94
% with marital status 60% 51.50% 50% 50% 51.60%
Female Count 2 82 1 3 88
% with marital status 40% 48.50% 50% 50% 48.40%
Total Count 5 169 2 6 182
% with marital status 100% 100% 100% 100% 100%
Source: Questionnaire, Question No. 3 and 4
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Annex 6: Education Level of Respondents
When it comes to the education level of interviewees, over four-fifth (81.3%) of total
respondents received primary education while there are 7.2% of no education and 11% of
secondary education recipients. Exceptionally, there is only one person who reached the
tertiary education.
Figure: Education level of Respondents
Source: Questionnaire, Question No. 7
13 (7.2%)
148 (81.3%)
20 (11%)
1 (0.5%)
0 50 100 150 200
No Education
Primary Education
Secondary Education
Tertiary Eduation
Education level of Respondents (N=182)
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Annex 7: Household Earning Perceptions of Respondents
Regarding the perceptions of their household earnings, almost one-sixth of household
interviewed perceived themselves as very low income earners whereas low and medium
income level is assumed to be received by about 42%. Only one respondent (0.5%) regards
himself as a high income recipient. This question was asked to be answered, in comparison
to other households in their village level.
Figure: Perception of Household earnings
Source: Questionnaire, Question No. 8
29 (15.9%)
76 (41.8%)
76 (41.8%)
1(0.5%)
Perception of Household Earnings (N=182)
Very Low
Low
Medium
High
