Cost benefit analysis of a mangrove restoration program as a climate change impact mitigation strategy in de gi lagoon, binh dinh province

MINISTRY OF EDUCATION AND TRAINING NHA TRANG UNIVERSITY __________________________ CHARLES NYANGA COST-BENEFIT ANALYSIS OF A MANGROVE RESTORATION PROGRAM AS A CLIMATE CHANGE IMPACT MIT

MINISTRY OF EDUCATION AND TRAINING

NHA TRANG UNIVERSITY

CHARLES NYANGA

COST-BENEFIT ANALYSIS OF A MANGROVE RESTORATION PROGRAM AS A CLIMATE CHANGE IMPACT MITIGATION STRATEGY IN DE GI LAGOON IN BINH DINH PROVINCE

MASTER THESIS

KHANH HOA – 2018

MINISTRY OF EDUCATION AND TRAINING

NHA TRANG UNIVERSITY

CHARLES NYANGA

COST-BENEFIT ANALYSIS OF A MANGROVE RESTORATION PROGRAM AS A CLIMATE CHANGE IMPACT MITIGATION STRATEGY IN DE GI LAGOON IN BINH DINH PROVINCE

MASTER THESIS

Management and Climate

Change Code

Topic Allocation Decision

Decision on establishing the

Committee

Defense Date

Supervisors:

1 Professor: Curtis Jolly

2 Professor: Kim Anh Nguyen Thi

Chairman of the Committee

Professor: Le Kim Long

Faculty of Graduate Studies

KHANH HOA – 2018

iii

UNDERTAKING

I undertake that the thesis entitled: “Cost Benefit Analysis of the Mangrove

Restoration Programme as a Climate Change Mitigation Strategy in De Gi Lagoon

in Binh Dinh Province”, is my own work The work has not been presented elsewhere

for assessment until the time this thesis is submitted

Khanh Hoa, 19th Jun, 2018

Charles Nyanga Author

ACKNOWLEDGEMENTS

I, Charles Nyanga, wish to acknowledge the financial support from the Norwegian Agency for Development Cooperation (NORAD) through the Norwegian Programme for Capacity Development in Higher Education and Research for Development (NORHED) for the International Master of Science in Marine Based Ecosystems Management and Climate Change (MEMACC)

I also wish to acknowledge funding from NORAD for the full scholarship which was granted to me to enable me to pursue the International MSc (MEMACC)

I also express my gratitude to the Ministry of Education and Training of the Socialist Republic of Viet Nam for the material and financial support through the Faculty of Graduate Studies of Nha Trang University and the Department of External Cooperation (DEC)

I, wish to acknowledge the Department for Agriculture and Rural Development of Binh Dinh Province for the assistance they rendered during the data collection exercise

Special thanks go to Professor Kim Anh Nguyen of Nha Trang University, Viet Nam and Professor Curtis Jolly of Auburn University, United States of America for their advice, patience, guidance, motivation and expert knowledge which enabled me to complete my research and write my thesis successfully Further, all my lecturers from Nha Trang University (Viet Nam), University of Tromso (Norway), University of Bergen (Norway), University of Ruhuna (Sri Lanka) and Bogo University (Indonesia) deserve to be acknowledged for the contributions in preparing me for the thesis work

I wish also to thank you my family, my parents, my brothers and sisters, my wife and my children for the spiritual support they have rendered to me throughout my study period Lastly my thanks go to my classmates for the encouragement and enthusiasm they have endowed into me My special thanks go to Loi To Thi Bich for allowing me to use her data for my report

Khanh Hoa, 19th Jun, 2018

Charles Nyanga Author

v

TABLE OF CONTENTS

UNDERTAKING iii

ACKNOWLEDGEMENTS iv

TABLE OF CONTENTS v

LIST OF SYMBOLS vii

LIST OF ABBREVIATIONS viii

LIST OF FIGURES x

LIST OF TABLES xi

LIST OF APPENDICES xii

ABSTRACT xiv

CHAPTER 1 INTRODUCTION 1

1.1 Background information 1

1.2 The Problem Statement 4

1.3 Objectives of the research study 5

CHAPTER 2 LITERATURE REVIEW 6

2.1 Ecosystems Goods and Services (EGS) - free goods and services from nature 6

2.2 The benefits of Natural Capital – the ecosystems goods and services 7

2.3 Drivers of changes in ecosystems 7

2.4 Historical trends in mangrove deforestation and restoration in Viet Nam – 1940s to 2015 10

2.5 Methods of Mangrove Ecosystems Valuation – a conceptual framework 13

2.6 Methods of carrying of out CBA 13

2.7 Procedure of carrying out CBA – an analytical framework 15

2.8 Examining Community Participation in Mangrove Restoration - an application of the Tobit Regression Model 15

2.9 National Mangrove Restoration Programs in Viet Nam 16

2.7 Mangrove Restoration, Development and Climate Change 19

CHAPTER 3 RESEARCH METHODS 20

3.1 Research approaches 20

3.2 Method of estimating willingness to pay (WTP) 20

3.3 Mathematical Models for Performing Cost Benefit Analysis (CBA) 21

3.4 Mathematical Models for performing discounted cash flow (DCF) 24

3.5 Tobit Regression Model – a theoretical background 24

3.6 The determination of sample size 26

3.7 The research process 27

3.8 The methods to attain the objectives 29

3.9 Research Tools Utilised to Attain the Objectives 30

3.10 Study Site 31

3.11 Data synthesis/analysis 33

CHAPTER 4 RESULTS AND DISCUSSIONS 34

4.1 Results from Focus Group Discussions 34

4.2 Results from Expert Opinion Interviews 35

4.3 Results from research data - Biographical information 35

4.4 Results from research data - Calculation of cost benefit analysis of aquaculture 39

4.5 Results from research data - Cost-benefit analysis of mangrove restoration programmes 42

4.6 Results from meta-analysis, synthesis of past research results and citations 50

4.7 Results from citations – providing evidence in support of mangrove restoration 53

4.8 Results from research data - Climate change awareness and understanding of implication of good mitigation practices in communities around De Gi Lagoon 54

CHAPTER 5 :CONCLUSIONS AND RECOMMENDATIONS 56

5.1 Conclusions 56

5.2 Recommendations 57

5.3 Future of research work in De Gi lagoon mangrove restoration as a climate change mitigation strategy 58

REFERENCES 59

APPENDICES 67

𝝱j parametric estimate of the jth variable

C0 initial cash outlay

CFi Cash flow occurring at the end of the period i

N Total number of households

pH potential of Hydrogen (acidity or basicity)

q number of variables or regressors

r cost of capital used as a discount rate NaCl Sodium Chloride

t life of the project US$ United States dollar

Xi a vector of independent variables, the regressors

Yi the dependent variable, the regressand

Yi* the latent variable

the sum from i=1 to the tth value

LIST OF ABBREVIATIONS

ACCCRN Asian Cities Climate Change Resilience Network

ASEAN Association of South East Asian Nations

BAU Business as Usual

BCR Benefit Cost Ratio

BFT Benefit transfer

BMZ The Germany Federal Ministry for Economic Cooperation and Development

CBA Cost-Benefit Analysis

CICES Common International Classification of Ecosystems Services

CIEM Central Institute for Economic Management

CIT Citation

CP Change in production

CVM Contingent Valuation Method

DERG Development Economics Research Group

DESA-SD Department of Economic and Social Affairs – Statistics Department

EGS Ecosystems Goods and Services

EVC Economic Value Coefficients

FAO Food and Agriculture Organization

FCR Feed Conversion Ratio

GHG Green House Gases

GoV Government of Viet Nam

GRETL GNU Regression, Enometrics, Time-series Library

GSO General Statistical Office of Viet Nam

IUCN International Union for the Conservation of Nature

IRR Internal Rate of Return

MA Meta-Analysis

MARD Ministry of Agriculture and Rural Development

MEA Millennium Ecosystem Assessment

MEMACC Marine Based Ecosystems Management and Climate Change

ix

MFF Mangrove for the Future

MONRE Ministry of Natural Resources and Environment

MV Market value

NGO Non-Governmental Organization

NMV – SP Non-Market Valuation method

NORAD Norwegian Agency for Development Cooperation

NORHED Norwegian Programme for Capacity Development in Higher Education

and Research for Development

NPV Net Present value

NTU Nha Trang University

PES Payment for Ecosystems Services

ProEcoServ Project for Ecosystems Services

PVB Present value of benefits

SDGs Sustainable Development Goals

SEA Southeast Asia

SES Synthesis of existing studies

TEV Total Economic Value

USD United States Dollar

VND Viet Nam Dong

WRI World Resources Institute

WTP Willingness to pay

WWF World Wide Fund for Nature

xi

LIST OF TABLES

Table 1.1: Mangrove species replanted in Viet Nam 2

Table 1.2: Mangrove forest losses in Southeast Asian Countries during periods measured (1960 – 1997) 3

Table 2.1: Ecosystems Goods and Services 6

Table 2.2: Percentage of the total deforested mangroves (2000-2012) converted to different land uses 9

Table 2.3: Showing summary of some of the various mangrove restoration intervention programmes in Viet Nam 18

Table 3.1: Tobit model variable description and possible signs of factors 26

Table 4.1 : Total cost-analysis of 1 ha of aquaculture per ha per year in Thi Nai Lagoon (2012 prices) 40

Table 4.2: Total cost-analysis of 1 ha of aquaculture per ha per year in De Gi Lagoon (adjusted for inflation to 2017 prices) 40

Table 4.3: Variation in total cost for sensitivity analysis 41

Table 4.4: Summary of CBA and sensitivity analysis for aquaculture 42

Table 4.5: Total benefit of mangrove restoration estimated with non- parametric method at 2012 prices 44

Table 4.6: Total benefit of mangrove restoration estimated with non- parametric method at 2017 prices 45

Table 4.7: Sensitivity analysis for mangrove restoration 46

Table 4.8 ARR Calculation results 46

Table 4.9: PBP calculation 46

Table 4.10 Determination of IBCR 47

Table 4.11: Comparison of between mangrove restoration and aquaculture development (mangrove conversion and destruction) 48

Table 4.12: Results of the Tobit regression model run using Gretl software 49

Table 4.13 Summary of meta-analysis with no regression of restoration programs 51

Table 4.14: Mangrove contribution to fisheries at different locations in the world 52

LIST OF APPENDICES

2 Calculations and Statistical Results 39

2.5 Computation of Number of Households in De Gi

Lagoon and Population Adjusted to 2017 figures

4 Sensitivity analysis for aquaculture development 38, 53

5 Sensitivity analysis for mangrove restoration 53

6 Total costs and benefits of mangrove restoration 41, 53

8 Results from meta-analyisis continued 45

9 Impacts of Climate on Aquaculture (2010 – 2020)

– Mekong River Delta, Viet Nam

31

9.1 Possible Impacts of Climate Change on Pangasius

Production Costs

45

xiii

9.2 Possible Impacts of Climate Change on Shrimp

10.1 Monthly Rainfall in Quy Nhon City 31

10.2 Average of Sea Level Rise in Quy Nhon City 31

10.3 Mean Air Temperature in Quy Nhon 31

10.4 Production of Aquaculture in Binh Province 31

14 FGD & Expert Interview Consent Form 30, 31

ABSTRACT

Mangrove forests occupy approximately not more than 1% of the world forested land, according to experts These important ecosystems are currently being lost at an alarming rate Aquaculture, urban development, agriculture, and industrial development have been observed to be the major causes of these mangrove losses The mangroves are an important source of ecosystems goods and services (EGS) amongst which are carbon sequestration, providing breeding and nursery grounds for several species of flora and fauna, materials, medicines, and climate change impact protection This study investigated the cost benefit analysis of a mangrove restoration programme, particularly in De Gi lagoon of Binh Dinh province of Viet Nam The methodology involved data collection from both secondary and primary sources such as Focus Group Discussions (FGDs), Expert Opinion interviews, survey questionnaire administration and synthesis of previous research results Thereafter an analysis was carried out to calculate the benefit-cost ratio (BCR), net present value (NPV), internal rate of return (IRR, for mangrove restoration only), average rate of return (ARR), payback period (PBP), and incremental benefit cost ratio (IBCR) The results showed that mangrove restoration and conservation appear to be a better option as opposed to mangrove conversion and destruction for aquaculture development without mangrove forests This was supported by results from other studies around the world which showed that mangroves were very valuable as a source of EGS such as aquaculture production and fisheries support, climate change impact mitigation as well as adaptation to name, but a few

In this study, it has been strongly recommended that the government of Viet Nam (GoV) should come up with programmes aimed at both informing the fishing and aquaculture communities of the importance of mangrove restoration, encouraging community-based ecosystems management and conservation for the benefit of the present and future generations

Key words: Mangrove forests, ecosystems, aquaculture, climate change, mitigation,

conservation

CHAPTER 1 INTRODUCTION

1.1 Background information

The term mangrove (Rhizophoraceae) refers to various plant species (trees and

shrubs) which are tolerant to salty waters and normally grow in the intertidal zones of coastlines belonging to tropical and subtropical sheltered coastlines (UN Environment, 2014).The term is applied to both individual plants and entire ecosystems occupied by mangroves The area covered by mangroves is referred to as the mangal Mangroves cover less than 1% of tropical forests worldwide (UN Environment, 2014) The mangroves are a well-adapted plant species that grow in fresh, brackish and salty water wetlands They occur dominantly in brackish and salty water wetlands since this tends to eliminate competition from plants and shrubs which are adapted to fresh water wetlands The mangroves’ adaptation mechanisms include salt coping mechanisms which enable them to filter out more than 90% of the salt in sea water; water hoarding mechanism which enables them to hoard water in thick succulent leaves; and breathing in a variety

of ways using snorkel like parts(American Museum of Natural History, 1999)

The mangrove forests are confined to regions 300 North and 300 South of the equator The total area occupied by mangrove forests in the world is 18.1 million ha South and Southeast Asia has a total of 7.5173 million ha of mangrove forest area This is equal to 41.5% of the world total mangrove forest area (Spalding, Blasco, & Field, 1997)

Vietnam with a population of 95.541 million and population density of 308.1 persons per km2 (DESA-SD, 2017), is mostly a coastal country with a coastline of 3,260 km long and occupies a land mass of 33.1 million ha The country is located at

140 3’ 29.96” N and 1080 16’ 37.91” E (GPS-coordinates, 2018) This country had about 408,500 ha of natural and dense mangrove forests before the wars, in 1943 , and

by 2001 the mangrove forests had been reduced to 156, 608 ha of which 32,402 ha (21%) were natural mangrove forests and 122, 892 (79%) were planted mangrove forests according to 2001 statistics (Hong & Dao, 2005; Vietnam Environmental Protection Agency, 2005) Spalding et al (1997) The World Mangroves Atlas reports that in Viet Nam some of the losses of mangrove forests came about due to the use of herbicides and napalm during the war, from 1955 to 1975 They also state that in

1997 Viet Nam had 272, 300 ha of mangrove forests and two protected areas with mangroves, and also informs that the Vietnamese government had re-planted more than 53, 000 ha of mangrove forests since 1990 (Spalding et al., 1997) These values are much higher than those reported by other researchers like Hong and Dao (2005) Napalm which was used to destroy the mangrove forests is a thickener of gasoline used for flame warfare purposes Napalm is mainly an aluminium disoap of mixed oleic coconut, and naphthenic acids also containing minor proportions of uncombined fatty acids, unsaponifiables, inorganic impurities and moisture (Mysels, 1949) This chemical is dangerous and apparently burnt most of mangrove forests in Viet Nam

(a) Mangrove species replanted in Viet Nam

The world has more than 73 species of mangroves growing in more than 123 countries Viet Nam has more than 31 species and some effort was made at replanting the mangrove to replace some of the previous losses of species which were lost during the wars and after the wars due to various development activities Some of the species which were re-planted as reported by Spalding et al (1997) are shown in the table 1.1 (Spalding et al., 1997)

Table 1.1: Mangrove species replanted in Viet Nam

Classification (Genus)

Common name

1 R mucronate Rhizophoraceae Rhizophora Red mangrove

2 R apiculota Rhizophoraceae Rhizophora Tall stilted mangrove

3 R stylosa Rhizophoraceae Rhizophora Spotted mangrove

4 K candela Rhizophoraceae Kandelia Oriental mangrove

5 Avicennia alba Acanthaceae Avicennia Api api

6 C decandra Rhizophoraceae Ceriops Flat leaved spurred

mangrove

7 S caseolaris Lythraceae Sonneratia Mangrove apple

Source: Compiled by the student for this report, 2017 based on data from (Field, 1990)

However, despite the replacement of several species, the losses experienced are quite heavy Spalding et al (1997), informs that SEA had experienced some of the greatest losses in mangroves The loss of mangrove forests in South and Southeast Asia experienced by four countries which are very active in mangrove restoration are shown

in table 1.2 below These losses amount to 4% of the total area of world mangroves and it can be seen that Viet Nam had suffered the largest amount of losses among the four countries during this period (Spalding et al., 1997)

(b) Mangrove loss in four of the most active countries in mangrove restoration in Asia Table 1.2: Mangrove forest losses in Southeast Asian Countries during periods measured (1960 – 1997)

Country Original Area of

Mangroves (ha)

Area of loss (ha)

* This period is estimated based on the activities in the region

These mangroves play a very important role in supporting coastal community livelihoods in Vietnam The mangroves provide resources like fire wood, charcoal, food, medicines, tannin, and construction materials Mangrove ecosystems provide

support for biodiversity as habitats for diverse species of amphibians (Amphibia), reptiles (Reptilia), mammals (Mammalia) and birds (Aves) They provide aquatic

resources by supporting marine life and provide an important link in the marine food web by making available detritus to create biotope for marine creatures The

mangroves also provide habitats and breeding grounds for shrimps (Caridea), fish

(Ichthyoid), snails (Achatinoidea), crabs (Brachyura), frogs (Rana Temporaria) and

their juveniles; mangroves act as giant kidneys filtering solid waste; mangroves act as green walls sheltering the coastal areas from salt intrusion and providing storm protection hence forming natural dykes (Hong & Dao, 2005)

1.2 The Problem Statement

The problem lies in over-exploitation and double-destruction from conversion of mangrove forests for other uses like shrimp aquaculture, urban and industrial development on one hand and the herbicides and napalm used during the wars (1955 to 1975) on the other hand (Spalding et al., 1997) These activities have led to loss of the natural giant kidneys for the filtration of solid waste materials, loss of natural dykes, as well as loss of habitats and breeding grounds for marine and other creatures The government of Viet Nam (GoV) with support from Non-Governmental Organisations (NGOs), the World Bank, other international organizations and regional economic bodies like Association of South East Asian Nations (ASEAN) and the Asian Cities Climate Change Resilience Network (ACCCRN) has been making efforts to replant the mangroves, as noted earlier According to World Resources Institute (WRI), from

1978 to date over 18,000 ha have been replanted bringing the total to 172,000 ha from approximately 150,000 ha (Org, Buckingham, & Hanson, 2015)

What exacerbates the problem then? Healthy mangrove forests have three core functions According to Food and Agriculture Organisation (FAO ,2007), these three core functions are: (1) Direct productivity functions, namely providing high quality construction timber and poles, fuel wood, pulpwood, folders for domestic animals, non-timber-forest products (i.e tannin, medicines, adhesives etc.) The problem here is that mangroves provide an estimated value of products of between USD 1.0 billion and about USD 6.0 billion per year in ecosystems services Thus, conserving the mangroves will tend to contribute to the attainment of several Sustainable Development Goals (SDGs), namely: SDG 1 (end poverty and hunger), SDG 2 (foster decent work) and SDG 3 (foster economic development) (2) Ecological functions, namely spawning and nursery grounds

for fish (Ichthyoid) and crustaceans (Crustacea), maintaining delta building processes

(land forming), soil conservation (along rivers and creek banks), habitat for wildlife (birds

(Aves), otter (Lutrinae), crocodiles (Crocodylinae) etc.) The problem here is that 10% of

all known fish species make use of mangroves Therefore, conservation of mangroves adds notably to SDG 15 (halt biodiversity loss) (3) Protective and sequestration functions namely: storm protection (hydraulic resistance against storm surge), shelter and shoreline protection as well as CO2 sequestration The problem here is that mangroves are able to sequester 3 to 5 times more CO than the terrestrial forest trees Therefore, conserving

mangroves will tend to contribute to the attainment of SDG 13 (climate change adaptation and mitigation) (FAO, 2007; WWF, IUCN, & BMZ, 2017) All these benefits which are obtained from these functions will disappear if mangroves are not restored and attainment

of many SDGs may not be achieved Further, the problem is worsened since Vietnamese coastal areas are under extreme high pressure from natural stressors like climate change temperature rise and storms Over-exploitation for agriculture, fisheries and aquaculture have also added stress on mangrove forests (Field, 1990)

A study by Tinh et al (2013) in Thi Nai Lagoon showed that the benefits of mangrove restoration and conservation were apparently higher than the benefits of mangrove forest conversion for aquaculture purposes (Tinh, Toan, & Tuan, 2013) The study area for this current research project was De Gi Lagoon in Phu My and Phu Cat Districts in Binh Dinh Province There have not been any studies on the costs and benefits

of mangrove restoration in this lagoon The study will probe two possible scenarios, namely: (1) Convert mangrove forests for aquaculture; (2) Restore the mangrove forests and introduce ecosystem and environmental management procedures

After completion and conclusion, this study will contribute to the availability of literature on the Cost-Benefit Analysis of mangrove restoration and aquaculture development options in the face of climate change in De Gi Lagoon for consideration

by policy makers, for use by professional lecturers, researchers and students alike

1.3 Objectives of the research study

The main objective of this research project is to carry out a cost-benefit analysis (CBA) of a mangrove restoration programme as a climate change mitigation strategy

in De Gi Lagoon in Binh Dinh Province

To achieve the above main objective, the research will attempt to:

(1) Determine the costs and benefits of aquaculture development versus mangrove restoration of the De Gi Lagoon communities

(2) Examine the individual willingness to participate in a mangrove restoration program as a climate change mitigation strategy using a Tobit regression model

CHAPTER 2 LITERATURE REVIEW

2.1 Ecosystems Goods and Services (EGS) - free goods and services from nature

Ecosystems goods and services (EGS), which we take for granted as free goods and services from nature, have been categorized in a number of different ways namely: (i) functional groupings, like regulation, carrier, habitat, production and information services; (ii) organizational groupings, like services that are associated with particular species, that regulate certain exogenous input or which have a particular relationship to the organization of biotic services; (iii) descriptive groupings, like renewable resource groups, physical structure services, biotic services, information services, social and cultural services (MEA, 2003) All these are provided for free

The Millennium Ecosystems Assessment (MEA, 2015) gives a categorization of EGS

as shown in table 2.1 below, based on functions:

Table 2.1: Ecosystems Goods and Services

Ecosystems Goods and Services

 Recreational

Source: The Millennium Ecosystems Assessment (MEA, 2003)

2.2 The benefits of Natural Capital – the ecosystems goods and services

The International Union for Conservation of Nature (IUCN, 2015) states that the degradation of the natural environment by our actions as humans has considerable costs associated with it For instance, in the EU region alone, it is estimated that pollination is worth more than €14 billion per year and wetlands also provide approximately €6 billion in ecosystems goods and services (EGS) per year All these, that is pollination and the EGS like soil, water, air, biodiversity, landscape, pollination from natural capital, are free (IUCN, 2015)

The IUCN (2015) goes further to state that one quarter of species in the EU, for example, are currently under threat of going into extinction due to habitat loss, urban expansion, agriculture, industrial development and climate change There is a clear acceleration of this state of affairs The IUCN further reveals that, in Berlin alone, for example, a city of 3.5 million inhabitants was serviced by 23,000 ha of green protected areas which were able to supply enough clean water to all the inhabitants This service,

if carried-out using water supply infrastructure would cost more than €16.7 million per year The green areas are protected by Natura 2000 Managing Natura 2000 networks requires €5.8 billion per year but generates € 200 billion to € 300 billion per year of economic benefits (IUCN, 2015) Clearly there appears to be more benefits than costs

2.3 Drivers of changes in ecosystems

The MEA (2003) identifies two main categories of drivers of ecosystems change They are: (i) exogenous drivers and (ii) endogenous drivers Indirect exogenous drivers of change are institutions, prices and markets, and technology development Whilst direct exogenous drivers are the effects of environmental change such as increased mean temperature from carbon dioxide (CO2) concentrations or lower mean temperatures from volcanic pollution Indirect endogenous drivers are technology

adaptation like fish (Ichthyoid) location technology Whilst direct endogenous drivers

which directly affect ecosystems are, land use change, land cover change, species input and removal (MEA, 2003) The mangroves plays a very big role as carbon sequesters of exogenous effects from carbon dioxide among many others

(a) Pressure on mangrove ecosystems

Mangroves have pressures exerted from several sources as indicated above by the drivers of change Figure 2.1, under here, show a concept of the pressures on mangroves and the results On the left are the drivers and on the right are the results from the pressures

Figure 2.1: Pressures on mangroves forests

Source: Compiled by the student for this report (2017)

(b) Drivers of changes in mangrove ecosystems in Southeast Asia (SEA) 1950 - 2015

Richards and Friess (2016) in their report state that the major drivers of mangrove deforestation in Southeast Asia has been aquaculture And over the past 30 years, aquaculture has grown while mangrove forests have been shrinking in this region of the world (Richards & Friess, 2016b) Between 2000-2012 aquaculture accounted for almost 30% of all conversions of mangrove forests (see table 2.2)

Table 2.2: Percentage of the total deforested mangroves (2000-2012) converted to different land uses

palm

Mangrove forest

Countries are ordered by total mangrove lost Percentages may not add up to 100 owing to rounding

 The small amount of mangrove deforestation in Timor- Leste is due mainly to shoreline erosion.

Source: Adapted from (Richards & Friess, 2016b) page 346

mangrove forests have been converted to aquaculture in SEA They further reported that aquaculture is the largest single most cause of mangrove deforestation around the world and in SEA region countries in particular They have shown a typical example

of the Philippines’ situation in Figure 2.2 shown below The graph shows clearly aquaculture overtaking the mangrove forests in area (Giensen, Wulffraat, Zieren, &

(c) Drivers of changes in the mangrove ecosystems in Viet Nam

According to ProEcoServ (2015), Viet Nam’s Mekong River Delta ecosystem is second only to the Amazon in fish biodiversity with more than 1,100 species of fresh water fish However, the natural mangrove forest wetlands as well as other wetlands have been reduced by more than 180,000 ha during the 20-year period to 2003, while aquaculture areas had increased to 1.1 million ha during the same period of time These changes in ecosystems and land use pattern were mostly driven by conversion

of mangrove wetlands to aquaculture, tourism facilities and planted forests (ProEcoServ, 2015)

Richards and Friess (2016), carried out a study and determined that on the overall the rate of mangrove deforestation across Southeast Asia between 2000 and 2012 stood at 0.18% and they singled out aquaculture as the largest contributor to this deforestation of mangroves accounting for about 30% of this deforestation They further pointed out that about 16% of the world’s mangrove forest species are about to

go into extinction (Richards & Friess, 2016a) In addition to these studies, Cowles (2015) reports that mangrove forests are the most frequently converted type of forests with a conversion rate standing at 3-5 times more than the average rates of ordinary forest loss and this has led to over 40% of mangroves being lost since 1950 Cowles (2015) goes on to point out that most of these conversions go to aquaculture pond development, agriculture, infrastructure and other urban projects (Cowles, 2015)

2.4 Historical trends in mangrove deforestation and restoration in Viet Nam – 1940s to 2015

As mentioned and cited earlier, Viet Nam had been facing a decline in mangrove forest area since the 1940s Buckingham and Hanson (2015) in a report of a case study for the World Resources Institute(WRI) have informed that since 1978 more than 18,000 ha of mangrove forests have been restored bringing the total area of mangroves

to more than 170,000 ha by 2008 (Buckingham & Hanson, 2015) Further, from figure 2.3 below, it can be noted that the decline in mangrove forests was very rapid between

1943 and 1999 There was a stagnation in 1999 but a reversal in 2001 During 2001 and

2007 there was a marked increase but during 2007 to 2008 there was a slight decline

Figure2.3: Mangrove cover trends in Viet Nam between 1943 and 2008

Source: Adapted from (Buckingham & Hanson, 2015), page 3 (modified)

(a) In-action and its costs

The EU (2009) warns that failure to act, in stopping this continued trend of mangrove forest conversion, on the part of governments, policy makers and communities will lead to governments paying a heavy price The EU (2009), goes on

to warn that the world will be losing an equivalent of €50 billion annually in ecosystems services Further, if governments take the business as usual (BAU) pathway, the loss would be equivalent to 7% of world GDP by 2050 (EU, 2009)

(b) Importance of climate mitigation

The importance of climate mitigation through the use of natural means, such as the establishment of mangrove forests, has been studied by several authors (Powell & Osbeck, n.d.; Tinh et al., 2013; WWF et al., 2017) However, the determination of the value of the natural resources like mangrove forests as a means for climate mitigation and improvement of livelihoods has never been studied in De Gi Lagoon Tuan and Tinh (2013) carried out a classical study on CBA in Thi Nai Lagoon in Binh Dinh Province They determined the cost-benefit of aquaculture development option by using revealed preference methods that are based on market-pricing approaches They determined the cost-benefit of restoration of mangroves using the data from Asian Cities Climate Change Resilience Network (ACCCRN)-supported projects and benefits were calculated using non-use values of the mangrove forests The approaches

utilized WTP which is a contingent valuation method (CVM) and the valuation of use values utilized market-pricing approaches However, this study was carried out in Thi Nai Lagoon Tinh et al (2013) found out that restoring 1450 ha of mangroves would produce an estimated VND 21 million whilst aquaculture activities carried out on the same area would produce only VND 10 million over a period of 22 years (Tinh et al., 2013) The study concluded that the benefits of mangrove restoration out-weighed the costs There is a need of replicating the study to De Gi Lagoon This is required to provide policy makers with details of the situation in De Gi Lagoon regarding a program like mangrove restoration The study would also play the role of advocacy with both the community members and stakeholders alike Moreover, Thi Nai Lagoon and De Gi lagoon are separated by a distance of approximately 60 km This makes them belong to the same locality The flora and fauna is almost the same as no far reaching disparities have been observed The flaw with the study could be that it concentrated on two methods of computing BCA only Other methods like Average Rate of Return (ARR), Payback Period (PBP) and Incremental BCR could have also been considered to validate the results further

Nguyen et al (2000) carried out a study to value the mangrove ecosystems in Can Gio They based their analysis of value on the Total Economic Value (TEV) framework that states:

TEV = (Direct-use value) + (Indirect-use value) + (Optional value) + (Existence value) (2.1) They used the cost benefit ratio and concluded that activities like cost of planting, cost of protection and cost of thinning were far less than the direct benefits obtained from extractable marketable products And they also noted that the city administration had introduced a regulation banning thinning (Tri et al., 2000) However, this study does not include Binh Dinh Province and De Gi Lagoon These studies have concentrated on the Mekong River Delta or areas near this delta The other weakness is they do not bring the secondary values in VND’s to current prices when applying secondary data to their studies, for example, Tuan and Tinh (2013) However, they exhibit some strengths in that most of them depend on other studies, either for secondary data or for the results and this helps to valid the findings

2.5 Methods of Mangrove Ecosystems Valuation – a conceptual framework

The mangroves ecosystem are wetlands Therefore, the methods for valuing wetlands will be discussed The services provided by the mangroves ecosystems will

be identified using the classification outlined by the Common International Classification of Ecosystem Services (CICES) for purposes of valuation The CICES follows the functional classification and classifies ecosystems services and goods as follows: (1) Provisioning, namely, the cultivated crops and plant-based resources; (2) Regulating and Maintenance, namely, the global climate regulation by reduction of Green House Gases (GHGs) concentrations, and mass stabilization and control of erosion rates as well as maintenance of nursey populations and habitats; (3) Cultural, namely, physical and experiential interactions

Vegh et al (2014) identifies the following categories of wetland valuation methods: (1) Market-based Valuation (MV) methods which are (a) Market value, used for wetland ecosystem products and services which are traded at a market; (b) Change in productivity (CP), used for ecosystem services that contribute to marketed products e.g the fish nursey function, (c) Avoided Costs (AC), used to value damages; (2) Non-market valuation - Stated Preference (NMV-SP), mainly Contingent Valuation Method (CVM) used to value virtually any wetland ecosystem; (3) Synthesis of existing studies (SES), these methods are: (a) Meta-analysis (MA), combines results from several studies and produces robust results and validated results; (b) Citation (CIT) , directly cites results from other studies; (c) Benefit Transfer (BFT), transfers benefits from studies in one area to another location; (d) Ecosystems Value Coefficients (EVC), uses standard coefficients to multiply by the area of land use, each land use pattern has a specific coefficient (Vegh, Jungwiwattanaporn, Pendleton, & Murray, 2014) To produce the most well validated results this study shall utilize CIT, SES and NMV-SP procedures to determine the values of various ecosystems services and products

2.6 Methods of carrying of out CBA

The Contingent Valuation Method (CVM) is used in the determination of the value of virtually any wetland ecosystem The CVM value would be used to complete the determination of the non-use values of the mangrove ecosystmems to complete the total benefits The research analysis which is adopted to complete the CBA is the multiple methodological appraoch According to Wikipedia (2018), in multiple approach design

(MAD), improves the construct vadality and provides a more complete view of the CBA of the projects at hand (Wikipedia, 2018) This would tend to suit all parties interested in the project, namely the community members, students and academic researchers amongst many others The methods adopted in this multiple approach are:

(a) Benefit cost analysis (BCR)

This is fully defined later The BCR does not provide a result of the future values or projections of total gains or losses of one project compared to another

(b) Incremental benefit cost ratio (IBCR)

This fully defined later It is a prodedure which is able to give future projections of the total gains or losses of one project compared to another Therefore it gives the margin in monetary terms by which one project is more beneficial or costly than the other

(c) Net present value (NPV)

NPV method is described fully later The NPV method considers the difference between the total discounted benefits and total discounted costs This method does not provide the future projections or the margins by which one project is more beneficial than the other

(d) Pay back period (PBP)

PBP is described later as well It gives the time period for which the total discounted project costs will be surpassed by the total discounted project project benefits This is useful in that it provides an idea of how long it will take to start making profits and therefore this would be useful in case the project funds were borrowed PBP is used as a screening tool although it not appropriate for sophiscated projects It is simple to use as

well (Pan American Health Organisation, 2018)

It is important that a wide range of methods are adopted since, as we have seen, each method emphasizes a particular aspect of the project financial management And as we all know, project managers come in various styles Some will be spurred into action if they see the PBP, some if they see the NPV, some if they see the IBCR amongst many arguments As we have seen earlier, our key objective is to carry out a CBA of mangrove restoration versus aquaculture development It is thgrefore important that we explore all these methods to get the various results which are expected to be all in support of mangrove restoration

2.7 Procedure of carrying out CBA – an analytical framework

The figure below is a concept of the analytical steps of the process of carrying out CBA

Figure 2.4 Methodological steps in performing CBA

Source: Compiled by the student for this report (2018)

This framework presented in Figure 2.4, shows the steps for determing CBA based on NPV To determine CBA for the other procedures, namely, IBCR, ARR, PBP and IRR The appropriate monetary values should be carefully ascertained from these steps and input in the appropriate formula shown in the methods section

2.8 Examining Community Participation in Mangrove Restoration - an

application of the Tobit Regression Model

Many studies have been carried out on commnuty involvement in ecosystems conservation and care Abdullah et al (2014), studied community based mangrove management and conservation in Malaysia Abdullah et al (2014) proposes three theoretical frameworks for studying factors affecting communities’ participation in

Calculate the PVs of costs and benefits

Calculate the NPVs of costs and benefits

Calculate total costs &

benefits

Quantify costs and benefits in monetary terms

Value costs and Benefits

in monettary terms Identify costs and benefits

community based management of ecosystems These three theoretical frameworks are: (1) psychological and social framework factors which include attitudes, knowledge level, behavior, perception and awareness, costs, benefits; (2) institutional framework factors which include monitoring and evaluation, rules and policies, political status amomngst many others; (3) ecological framework factors which quality of flaura and fauna and biological data amongst many others Abdullah et al concluded that willingness to participate (WTP) had strong correlation with social factors such as Gender, Race and Educational levels (Abdullah, Said, & Omar, 2014) Halkos and Galani (2012) in their article on WTP show that the Tobit Model is a regression model which is popular amongst researchers to determine the factor affecting WTP in community based conservation projects Haikos and Galani (2012) show that out of twelve studies analyised at least four used the Tobit Regression Model ((Halkos & Galani, 2012) We see that the Tobit Model is well selected to show the effect of various factors on WTP as shown from the literature reviewed

One of the issues of which is raised in the use of the Tobit Regression Model is the model’s inability to explain the sources of particular decisions For example in this study, it is used to show the sources of influence of the decision to “Participate in a restoration programme” This gives rise to qualitative variables which in turn are assignmed dummy variables For example, thes sources of the Yes or No answer in relation to Gender as to how many “Nos” and how many “Yes” are coming from female

or the male counterparts To answer such a question a “Double Hurdle Regression Model” (DHRM) is required as explained in (Rossini, Vicentin, & Depetris, 2015) The choice of factors is shown in table 3.1 for this study

2.9 National Mangrove Restoration Programs in Viet Nam

The government of Viet Nam (GoV) has recognized that mangroves have more value standing than cut, and due to its stance the GoV has been one of the most active governments in mangrove restoration in the world Viet Nam is a country whose mangrove forests have been subjected to the worst destruction in the world, as earlier reported, at the same time this is where the greatest afforestation has been made without foreign support in the form of funding and technical support (Kogo, 1997) Several studies and reports have been written on these interventions Table 2.3 below is a summary of the key interventions in mangrove forest restoration among

other restoration activities too numerous to list It should be noted that the interventions so reported were taking effect between 2004 and 2018 The total amount involved is not well known but it should be noted that at least more than 33 ha

of mangroves during the stated period have been replanted and the amount of fund pledges during this same period is more than VND 2.4 billion

In all these reports on mangrove restoration interventions by the government of Viet Nam (see table 2.3), it has been observed that De Gi Lagoon is more or less not featured as a prominent or favorable area of project implementation It is, therefore, felt that more studies like this one should be undertaken specially to include De Gi Lagoon as an area with great future potential in the development of mangrove ecosystems benefits

Table 2.3: Showing summary of some of the various mangrove restoration intervention programmes in Viet Nam

PROGRAMME

ORGANISATIONS SPEARHEADING

HA

AMOUNT VND INPUT

DURATION

1 Restoration of Destroyed

Mangrove in Mid-East

Vietnam

(Thi Nai Lagoon)

33 Ha Not specified 2012-2015

2 Mangrove for the Future

Phases I, II & III

Not specified More than

for Mangrove Forests

MONRE Various projects in

Viet Nam

Not specified Not specified 2004 – 2010

Sources: Compiled by the student for this report based on data from (MFF Viet Nam, 2011, 2015; MONRE, 2004; Tuyen & Tyler, 2017)

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2.7 Mangrove Restoration, Development and Climate Change

Mangroves have in recent years taken center stage in what has become to be known as the “green technologies” The Global Mangrove Alliance (Global Mangrove Alliance, 2016) informs that mangroves are amongst the most productive wetland ecosystems It is estimated that these ecosystems provide an estimated USD 33 – 57 thousand per ha per year to the national economies of developing countries that have mangrove forests These ecsosytems have been shown by science recently to provide very good carbon sinks in the trees themselves but more so in the soils below these forests.The climate change mitigation potential of the mangrove forests is astounding since they are more efficient as carbon sinks than the terrestrial forests Therefore, every policy and decision maker must invest in “coastal blue carbon” This is one reason why conserving mangroves is vital to climate change mitigation (IUCN, 2017)

However, despite this, these important ecosystems are amongst the most threatened A study carried out in Kuantan in Malaysia reveals that mangroves are amongst the most affected ecosystems by coatal development The study concluded

that coastal development was a major threat to mangroves (Saad, Ahmad, Yunus, & Chowdhury, 2009) It is due to the mentioned threats that the recent years have seen

various efforts at mangrove restoration some of which have been gargantuan covering many thousands of hectares One of the techniques which is being utilized in green technologies involving mangrove restoration is Ecological Mangrove Restoration (EMS) This method involves engaging the community members and considering

social, economical and ecological factors before restoration (Roy & Ben, 2014)

Restoration involving commuties is seen as important and sustainable and this will confirm the importance of communities participating in a restoration program

CHAPTER 3 RESEARCH METHODS

3.1 Research approaches

The research method utilized both the qualitative and quantitative methods, or triangulation approach Triangulation is a research method which involves the use of more than one method to collect data on the same topic This ensures the validity of the research through the use of a variety of methods This serves to facilitate deeper understanding of the phenomenon under investigation (Cohen & Crabtree, 2009; Kulkarni, 2013) The sampling method which was proposed to be used is snow-ball sampling method In the application of snowball sampling, sampling units point out to the researcher other sampling units who suit the research requirements This is because the researcher may have difficulties in identifying which community members undertake their economic activities in the mangrove forest areas Purposive sampling was used to select the first ten sampling units Purposive sampling is a sampling technique where the researcher uses his judgement to select suitable data units (Research Methodology.net, 2016) The data collection tools were semi-structured questionnaires for community households Face-to-face interview questions for key informants from government departments and Focus Group Discussions (FGDs) for leaders and selected government officials

3.2 Method of estimating willingness to pay (WTP)

The method which was used to measure the WTP was the statistical calculation

of the Arithemetic Mean (AM) The WTP was measured using a multiple choice type

of question with the respondents given choices of: 1 to 50,000 VND, 50,000 to 100,000 VND, upto 500,000 VND and more in steps of 50,000 VND The WTP was therefore calculated as:

Average WTP = Sum of (Mid-points of ranges of choices X Number of corresponding choices) / (Total number of respondents) This method was adapted from (Research Gate, 2016)

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3.3 Mathematical Models for Performing Cost Benefit Analysis (CBA)

An important aspect of this study is CBA This was accomplished by calculating the Net Present Value (NPV), Benefit Cost Ratio (BCR), Internal Rate of Return (IRR), and Sensitivity Analysis Also, the other less common methods which were used are: Average Rate of Return (ARR), Payback Period (PBP), and Incremental BCR (IBCR) to validate the results The multiple methodological approach ensure that the results are validated as the approaches validate each other A wide section of readers/users will be catered for as each method emphasizes a particular aspect of project financial analysis

(a) Net Present Value (NPV)

According to Goyal (2012), Net Present Value (NPV) is the present value of all cash flows which are associated with a particular project The NPV is computed using equation (3.1) Therefore:

(3.1) Where:

NPV = Net Present Value

CFi = Cash flow occurring at the end of the period i

C0 = initial cash outlay

t = life of the project

r = cost of capital used as a discount rate

The NPV takes 3 states: NPV = 0, NPV < 0, NPV > 0 Goyal (2012), further advises about the decision rules based on NPV calculation as follows:

If NPV = 0, only the initial cash outlay may be recovered This signifies a break – even point If NPV > 0, accept the project as viable If NPV < 0, reject the project as not viable (Goyal, 2012)

The NPV method considers the difference

(b) Benefit-Cost Ratio (BCR)

According to Goyal (2012), Benefit-Cost Ratio (BCR) is sometimes referred to as the profitability index (PI) BCR may be defined as benefit per unit VND of costs The mathematical model for BCR is shown in equation (3.2) Therefore:

(3.2) Where:

BCR = Benefit-cost Ratio

PVB = Present value of benefits

I = Initial investment or NPV of cash outflows

The BCR takes 3 states: BCR = 1, BCR < 1, BCR > 1 Goyal (2012), further advises about the decision rules based on BCR calculation as:

If BCR = 1, then the project is indifferent If BCR > 1, accept the project as viable

If BCR < 1, reject the project as not viable

(c) Internal Rate of Return (IRR)

Goyal (2012) defines the Internal Rate of Return (IRR) as the discount rate or cost of capital which makes the NPV = 0 Therefore, if equation (3.3) above is equal to zero then r is the IRR, thus if:

(3.3) then r = IRR of the project Goyal (2012), further advises about the decision rule based

on IRR calculation as: select the project with largest value of IRR (Goyal, 2012)

(d) Sensitivity Analysis

Sensitivity Analysis is discussed later under section 4.4 (b)

(e) Problems with IRR and NPV

Goyal (2012) further points out that sometimes problems may arise when using NPV and IRR These problems might be due to: (i) Size disparities – which occurs when projects have different investment levels Size disparity might be dealt with by depending on NPV results This also might be resolved by altering IRR and computing IRR based on the incremental outlay, that is, the difference of the cash outlays and

23

select the project with incremental IRR greater than the cost of capital (ii) Time disparity – this occurs when timings and sometimes cash flows as well are different This might be solved by carrying out sensitivity analysis and any discounting rates before NPV of one project is equal to NPV of the other project would appear to support the other project (iii) Life disparity – this occurs when the projects have different life spans Life disparity may be dealt with by making the projects have equal time periods by repetition (Goyal, 2012)

(f) Average Rate of Return (ARR)

The ARR measures how much an investment made over the investment’s life (McBride, 2010) The model which is used to determine the ARR is expressed by:

(h) Incremental Benefit Cost Ratio (IBCR)

The incremental BCR is a strategy for comparing two or more investment project alternatives (Quintus, Mallela, Bonaquist, Schwartz, & Carvalho, 2012) It is defined

by the mathematical model given here (equation 3.7):

(3.7) Where: ΔB = Difference in benefits of project 1 and 2

ΔC = Difference between costs of projects 1 and 2

B1 = Benefits of project 1

B2 = Benefits of project 2

C1 = Costs of project 1

C2 = Costs of project 2

This model is adapted from (Quintus et al., 2012)

3.4 Mathematical Models for performing discounted cash flow (DCF)

Yet another aspect of this study is to perform Discounted Cash Flow (DCF) for CBA to be completed

DCF is defined as an investment analysis model that calculates the value of an investment based on the present value of its future income (My Accounting Course, 2018) The mathematical model which is used to run DCF in MS-excel is:

Present value = amount received in future/(1 + discount interest rate)number of years (3.8)Using mathematical symbols:

PV = FV/ (1 + r)t (3.9) Where:

PV = Present value

FV = Future value

r = discount factor

t = number of years This equation is adapted from (Alan, 2006)

3.5 Tobit Regression Model – a theoretical background

(a) Mathematical model

The research will focus on examining the impact of socioeconomic and other factors on the individuals willingness to participate in a restoration program This analysis, has hidden variables which one cannot observe Therefore one of the models which is used in such situations is the Tobit model The Tobit model was proposed first by an economist, John Tobin in 1958 The model became known as “Tobin’s probit” and later was given the name obtained by replacing the “n” by the “t” in Tobin’s name Hence, it became known as the Tobit model The model is used to explain the range of dependent variables (that is how regressors or independent variables would affect the dependent variable or the regressand) A typical application

of the Tobit model is in the analysis of lower threshold censored (left-censored) data or upper threshold censored (right-censored) data or both (Xu, Kouhpanejade, & Šarić, 2013) and (K A T Nguyen, Jolly, Bui, & Le, 2016; K A T Nguyen, Jolly, &

the dependent variable, the regressand

Xi = a vector of independent variables, the regressors

𝝱 = a vector

ɛi = a normally distributed error term

These model expressions are adapted from (Xu et al., 2013) and (K A T

Nguyen et al., 2016, 2018) In the study the latent variable would be the WTP (in

VND) which might not be actually mentioned in the model.Tobit model was run to

examine the individual willingness to participate in a restoration program The

statistical software, Gretl, was used to run the Tobit model which is shown below (see

table 4.9):

(Willingness to participate) = 𝝱o +𝝱1(X1) +𝝱2 (X2)+𝝱3 (X3)+𝝱4 (X5) +𝝱5 (X5)+𝝱6(X6)

Table 3.1 displays the variables used in the Tobit model, their descriptions and

possible signs of factors The possible factors as explained are socio-economical

factors that apparently would affect the individuals willingness to participate in a

restoration program These socio-economic factors are age, gender, number of

dependents in the household, annual income, amongst many others Other factors are

factors of opinion which are also considered together with the socio-economic factors

For input in the Tobit model the variables which are categorical are coded (with

1 or 0; 1,2,or 3 depending on available choices) and are referred to as dummy

variables The codes depend on the number of choices presented to the respondents

The numerical variables are input without coding All this, as we can see is shown in

the table 3.1, below

Table 3.1: Tobit model variable description and possible signs of factors

biodiversity , =2 if not, =3 otherwise

+/⎯

is beneficial to biodiversity , =2 if not,

=3 otherwise

+/⎯

(b) Issues with the Tobit model

The Tobit model is very useful for examining “Limited dependent variables” The main critique of this model is that it does not differentiate the set of variables used

to explain the sign of Y from the set of variables used to explain the sign of Y conditional on being positive strictly Moreover, the Tobit model becomes inconsistent when the error term is not normally distributed and when the variance of the error term does not have a constant value (Gale, 2008)

Despite these critiques, the Tobit model, has one big advantage over the linear regression model in that it yields unbiased estimates of the coefficients of the x-variable while the linear regression model does not (Gale, 2008)

3.6 The determination of sample size

The sample size was determined using formula (3.12) due to (Tinh, Toan, & Tuan, 2008):

(3.12) Where n = sample size

N = total number of households

e = margin of error

Taking e = 8%, N = 13,230 (calculated in Appendix 2.4)

Therefore