A STUDY OF THE EFFECTS OF INCREASING LOCAL RICE PRODUCTION ON 

GREEN HOUSE GAS EMISSIONS IN GHANA 

 

 
 
 
 

BY 
 

FORSTER KWAME BOATENG 

(IDENTIFICATION NUMBER: 10075412) 

 

 
THIS THESIS IS SUBMITTED TO THE UNIVERSITY OF GHANA, LEGON 

IN PARTIAL FULFILLMENT OF THE REQUIREMENT FOR THE AWARD OF 

DOCTOR OF PHILOSOPHY DEGREE IN APPLIED AGRICULTURAL 

ECONOMICS AND POLICY 

 

 

DEPARTMENT OF AGRICULTURAL ECONOMICS AND AGRIBUSINESS 

COLLEGE OF BASIC AND APPLIED SCIENCE 

 UNIVERSITY OF GHANA 

 
 

OCTOBER 2023 
 
 

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DEDICATION 

This dissertation is devoted to my wife, MRS. ALICE ABENAA ANSAA BOATENG, for her 

unwavering support throughout the four-year program. I am incredibly grateful to her. 

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

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DECLARATION 

 

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ACKNOWLEDGMENTS 
 

First and foremost, I would like to express my gratitude to the Almighty God for everything 

He has done for me throughout my life, including my PhD studies. 

Second, I want to thank my supervisory team made up of Professor Kwabena Asomanin 

Anaman, Major supervisor and the two Co-Supervisors: Professor Irene Susana Egyir and Dr. 

Yaw Bonsu Osei-Asare. I would like to express my heartfelt gratitude to Professor Anaman for 

his assistance in converting the 2018 Ghana Social Accounting Matrix to the equivalent 2018 

Ghana national input-output table. All three of my supervisors provided constructive feedback, 

comments, and suggestions, which improved the final thesis report. 

Third, I acknowledge with deep gratitude the assistance and support given to me by all my 

lecturers and supervisors at the University of Ghana over the four years of my PhD programme, 

which resulted in the development of my thesis report. Dr. Daniel Tutu Benefo, Deputy 

Director of the Ghana Environmental Protection Agency’s Climate Change Unit, provided me 

with the EPA Ghana Emission Data, 1990–2019, which I used in the input-output analysis in 

this study. 

Mr. Llewellyn Hille, former Executive Director of Self-Help International, Waverly-Iowa, 

USA, my boss and mentor, deserves special recognition for encouraging me to pursue a PhD 

program. Finally, and by no means least, I am grateful to the AGRA President and the United 

Nations Secretary General’s Special Envoy for the 2021 Food Systems Summit, Dr. Agnes 

Kalibata, for her encouragement and support. 

 
 
       ……………………………………… 

        Forster Kwame Boateng 

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ABSTRACT 
 
This research was motivated by the government of Ghana's (GoG) initiative to boost local rice 

production to achieve self-sufficiency by 2025, in line with the country's commitment to meet 

its Nationally Determined Contribution (NDC) of a 15% reduction of the growth of Ghana’s 

total greenhouse gas (GHG) emissions by 2030 relative to a Business as Usual (BAU) scenario. 

Rice production emits methane (CH4) and nitrous oxide (N2O), which have a relatively higher 

global warming potential (GWP) than carbon dioxide (CO2). Increasing local rice production 

to achieve self-sufficiency could increase GHG emissions, making Ghana's NDC pledge to 

reduce CO2, CH4, and N2O unachievable. The government’s policy of increasing local rice 

production brings about conflicting policy goals. GHG emissions resulting from paddy rice 

production are comprehensively discussed in many Sub-Saharan African studies, including in 

Ghana, but the emphasis has been on rice intensification to reduce food insecurity and poverty 

with little attention to environmental costs. The problem statement informed the four study 

objectives of this study. The first was to identify the macro drivers of GHG emissions in Ghana 

and the second objective was to identify the factors that contribute to the observed declining 

share of the total GHG emissions in Ghana attributed to the agricultural sector using time series 

regression analysis from 1990 to 2019. For the third objective, an environmentally extended 

input-output analysis was used to examine the direct and indirect GHG emissions arising from 

rice production and compare these emissions with the corresponding generation of incomes 

and employment. Using a random cross-sectional survey of farmers and qualitative research 

methods, the fourth objective dealt with the methods local rice farmers used to manage their 

production systems to deal with GHG emissions. 

 

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From the macro-level analysis in objectives one and two, it was determined that the total land 

area dedicated to rice production was a significant driver of total GHG emissions in the 

economy; a one percent increase in the land area dedicated to rice production would result in a 

0.35% increase in total emissions. The study further showed that while increasing rice 

production was a significant long-term macro driver of total emissions, this was not the case in 

the short-term period. Using an environmentally extended input-output analysis to deal with 

the third objective, it was established that rice production was the second biggest GHG-

impacting industry in the domestic economy, after the electricity generation industry, despite 

its relatively small share of total emissions, estimated at around two percent. The other three 

big GHG-impacting industries were transport, crude oil production, and all other agricultural 

industries (excluding rice production). Rice production generated broad-based income and 

employment impacts, both directly for the rice industry, and also indirectly for other industries 

in the economy. It was ascertained from the survey of rice producers that farmers had a modest 

understanding of climate change and GHG emissions. In response to climate change, rice 

producers were implementing agronomic practices such as soil fertility management, planting 

of early-maturing varieties, using improved seeds and drought-tolerant rice varieties, and 

employing no-till land preparation. However, their efforts to adapt to climate change were 

hampered by their limited understanding of the effects of GHG emissions, high labour costs, 

and low levels of extension officer contacts.  All three analyses confirm that rice production is 

a significant emitter of GHG emissions. However, its share of the national total GHG emissions 

is relatively small compared to all other agricultural industries (excluding rice production), 

transport, crude oil production, and electricity generation. 

 

         

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TABLE OF CONTENTS 

DEDICATION ........................................................................................................................ II 

DECLARATION .................................................................................................................. III 
ACKNOWLEDGMENTS .................................................................................................... IV 

ABSTRACT ............................................................................................................................. V 
TABLE OF CONTENTS .................................................................................................... VII 

LIST OF TABLES .................................................................................................................. X 
LIST OF FIGURES ........................................................................................................... XIII 

ABBREVIATIONS AND ACRONYMS .......................................................................... XIV 
CHAPTER ONE ...................................................................................................................... 1 

INTRODUCTION ................................................................................................................. 1 
1.1 Background to the Study ............................................................................................ 1 
1.2 Why the Focus on Rice? ............................................................................................. 2 
1.3 Problem Statement ..................................................................................................... 9 
1.4 Research Questions .................................................................................................. 10 
1.5 Objective of the Study .............................................................................................. 11 
1.6 Relevance of the Study ............................................................................................. 11 
1.7 Organization of the Thesis Report ........................................................................... 13 

CHAPTER TWO ................................................................................................................... 14 
LITERATURE REVIEW .................................................................................................... 14 

2.1 Introduction .............................................................................................................. 14 
2.2 Definition of Concepts ............................................................................................. 14 
2.3 Empirical Review ..................................................................................................... 17 
2.4 Methodological Approaches for Analysing GHG Emissions ................................... 32 
2.5 Summary of the Major Findings from the Review of the Literature ........................ 36 
2.6 Gaps in the Literature .............................................................................................. 38 

CHAPTER THREE ............................................................................................................... 40 
METHODOLOGY AND PROCEDURES USED FOR THE STUDY ................................ 40 

3.1 Introduction .............................................................................................................. 40 
3.2 Theoretical Framework ........................................................................................... 40 
3.3 Conceptual Framework ........................................................................................... 44 
3.5 Methodology for Analysing Macro Level Determinants of GHG Emissions in the 
Economy ........................................................................................................................... 48 
3.6 Data Sources and Methodology for Determining the Effect of Rice Production on 
Total National GHG Emissions ....................................................................................... 56 
3.7 Data Sources and Methodology for Analysing Farmers’ Understanding of Climate 
Change Issues and Management Responses in Reducing GHG Emissions ..................... 66 

CHAPTER FOUR .................................................................................................................. 72 
MACRO-LEVEL DETERMINANTS OF GREENHOUSE GAS EMISSIONS IN THE 
ECONOMY ......................................................................................................................... 72 
RESULTS AND DISCUSSION .......................................................................................... 72 

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4.1 Introduction .............................................................................................................. 72 
4.2 National GHG Emission Trends by Sector from 1990 to 2019 ............................... 72 
4.3 Results of the Regression Analysis on Macro-level determinants of Total GHG .... 78 
4.4 Drivers of the declining Agriculture Sector (AFOLU) share of the Total National 
GHG Emissions in the Economy ...................................................................................... 85 

CHAPTER FIVE ................................................................................................................... 90 
INPUT-OUTPUT ANALYSIS OF GREENHOUSE GAS EMISSIONS IN THE 
ECONOMY OF GHANA .................................................................................................... 90 
RESULTS AND DISCUSSION .......................................................................................... 90 

5.1 Introduction .............................................................................................................. 90 
5.2 GHG Emissions of the 20 Industries in the Domestic Economy .............................. 91 
5.3 Production Externalities in the Domestic Economy Based on a Unit Change in 
Final Demand .................................................................................................................. 93 
5.4 Comparative Performance of the 20 industries' Production Externalities and 
Value-Added Income Multipliers based on Unit Change in Final Demand .................... 97 
5.5 Comparative Performance of the 20 industries' Production Externalities and Total 
Employment Multipliers Based on Unit Change of Final Demand ............................... 101 
5.6 Chapter Summary .................................................................................................. 105 

CHAPTER SIX .................................................................................................................... 106 
FARMERS’ UNDERSTANDING OF CLIMATE CHANGE ISSUES AND THEIR 
MANAGEMENT RESPONSES IN REDUCING GREENHOUSE GAS EMISSIONS ... 106 
RESULTS AND DISCUSSION ........................................................................................ 106 

6.1 Introduction ............................................................................................................ 106 
6.2 Socio-economic Characteristics of the Respondents ............................................. 106 
6.3 Characteristics and Management of Farms of Respondents ................................. 111 
6.4 Respondents’ Perceived Causes of Climate Change ............................................. 118 
6.5 Farmers’ Responses in the Management and Reduction of GHG Emissions ........ 121 
6.6 Constraints Affecting Farmers’ Management of GHG emissions ......................... 125 
6.7 Chapter Summary .................................................................................................. 129 

CHAPTER SEVEN .............................................................................................................. 130 
CONCLUSIONS AND RECOMMENDATIONS ............................................................. 130 

7.1 Introduction ............................................................................................................ 130 
7.2 Summary of the Study ............................................................................................. 130 
7.3 Conclusions of the Study ........................................................................................ 135 
7.4 Policy Recommendations ....................................................................................... 138 
7.5 Limitations of the Study and Suggestions for Further Research ........................... 141 
7.6 Contribution to Knowledge .................................................................................... 142 

REFERENCES ..................................................................................................................... 143 

APPENDICES ...................................................................................................................... 160 
APPENDIX 1:  TECHNICAL COEFFICIENTS OF THE GHANAIAN ECONOMY, 2018
............................................................................................................................................ 160 
APPENDIX 2:  TOTAL REQUIREMENT TABLE (LEONTIEF INVERSE MATRIX)
........................................................................................ ERROR! BOOKMARK NOT DEFINED. 
APPENDIX 3: TOTAL GHG EMISSION MULTIPLIER TABLE ............................................... 161 

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APPENDIX 4: TOTAL VALUE ADDED MULTIPLIER TABLE ................................................ 162 
APPENDIX 5: TOTAL LABOUR INCOME MULTIPLIER TABLE ...................................... 163 
APPENDIX 6: TOTAL CAPITAL OWNERS’ INCOME MULTIPLIER TABLE ............................ 164 
APPENDIX 7: TOTAL EMPLOYMENT MULTIPLIER TABLE ................................................. 165 
APPENDIX 8: SURVEY QUESTIONNAIRE .................................................................. 166 
APPENDIX 9: EXPECT INTERVIEW ............................................................................. 187 

 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

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LIST OF TABLES 

Table 2. 1: The structure of an Input-Output Table ................................................................. 34 

 
Table 3. 1: Data sources and variables ..................................................................................... 51 

Table 3. 2: Illustration of Ghana 2018 Input-Output Table with 20 Industries ....................... 62 

 
Table 4. 1: The National Total Greenhouse Emissions Trends from 1990 to 2019 ................ 73 

Table 4. 2: Unit Root Tests of the Continuous Variables at the Levels and First Differences 79 

Table 4. 3: Results of the Estimated ARDL Cointegration Model of the production of GHG 

Emissions in Ghana, 1990 to 2019 based on the Optimal Lag Length of Two Years ............. 81 

Table 4. 4: Results of the Estimated Long Run Function Derived from the Optimal ARDL 

Cointegration Model of GHG Emissions in Ghana, 1990 to 2019 .......................................... 83 

Table 4. 5: Results of the Estimated Error Correction Function of the Production of Total GHG 

Emissions in Ghana over the period, 1990-2019 ..................................................................... 84 

Table 4. 6: Results of the Estimated ARDL Cointegration Model of the Share of the Total GHG 

Emissions Attributed to the Agricultural Sector from 1990 to 2019 Based on the Optimal Lag 

Length of Three Years ............................................................................................................. 86 

Table 4. 7: Results of the Estimated Long Run Function derived from the Optimal ARDL 

Cointegration Model of the share of Total GHG Attributed to the Agricultural Sector from 

1990 to 2019 ............................................................................................................................ 88 

Table 4. 8: Results of the Estimated Error Correction Function of the share of the Total GHG 

Attributed to the Agricultural Sector over the Period, 1990-2019 ........................................... 89 
 
Table 5. 1: GHG Emissions of the 20 industries in the Domestic Economy and their share of 

the Total GHG Emission in 2018 ............................................................................................. 92 

Table 5. 2: Backward Linkage Production Externalities based on One Ghana Cedi Change in 

Final Demand for 20 Industries in the Domestic Economy for 2018 ...................................... 95 

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Table 5. 3: Forward Linkage Production Externalities based on One Ghana Cedi Change in 

Final Demand for 20 Industries in the Domestic Economy for 2018 ...................................... 96 

Table 5. 4: Backward Linkage GHG Emissions and Value-Added Income Multipliers Based 

on One Cedi Change in Final Demand for 20 Industries in the Domestic Economy .............. 99 

Table 5. 5: Forward Linkage GHG Emissions and Value-Added Income Multipliers Based on 

One Cedi Change in Final Demand for 20 Industries in the Domestic Economy ................. 100 

Table 5. 6: Backward Linkage GHG Emissions Multipliers and the Number of Workers 

Employed Based on Unit Change in Final Demand for 20 Industries in the Domestic Economy

................................................................................................................................................ 103 

Table 5. 7: Forward Linkage GHG Emissions Multipliers and the Number of Workers 

Employed Based on Unit Change in Final Demand for 20 Industries in the Domestic Economy

................................................................................................................................................ 104 
 
Table 6. 1: Summary of Socio-Economic Characteristics of Rice Farmers Based on Frequency 

Analysis Using Percentages ................................................................................................... 109 

Table 6. 2: Summary of Socio-Economic Characteristics of Rice Farmers Based on Average, 

Standard Deviation and Range Figures .................................................................................. 110 

Table 6. 3: Frequency Analysis on Production and Input Use on Rice Production ............... 113 

Table 6. 4: Characteristics of Inputs Used in Rice Production, their Average Quantity and 

Average Prices in Years 2020 and 2021 ................................................................................ 114 

Table 6. 5: The Major Moveable Agricultural Assets Used in the 2021 Production Year .... 115 

Table 6. 6: Average Amount of Money Spent per Acre for Farm Operations in 2020 and 2021

................................................................................................................................................ 116 

Table 6. 7: Farmers’ Perceived Ability to Handle the Risks Associated with Various 

Components of Rice Production ............................................................................................ 117 

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Table 6. 8: Ranking of Respondents’ Perceptions of the Causes of Climate Change Through 

Greenhouse Gas Emissions .................................................................................................... 119 

Table 6. 9: Ranking of the Respondents’ Declared Factors Contributing to the Climate Change 

Specifically from Greenhouse Gases Released from Rice Production .................................. 120 

Table 6. 10: Ranking of the Adaptation Measures to Reduce Greenhouse Gas Emissions 

Emanating from Rice Production Used by Responding Farmers .......................................... 122 

Table 6. 11: Results of the Regression Analysis of Factors Influencing the Intensity of use of 

Adaptation Strategies by Respondents to combat the Release of GHGs in Rice Production 124 

Table 6. 12: Ranking of Constraints to Management of Greenhouse Gas Emissions Arising 

from Rice Production Declared by Responding Farmers ...................................................... 126 

Table 6. 13: Results of the Regression Analysis of Factors Influencing the Level of Constraints 

involved in the management of the Reduction of GHG in Rice ProductionError! Bookmark 

not defined. 

 

 
 
 
 
 
 
 
 
 
 

 

 

 

 

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LIST OF FIGURES 

 

Figure 1. 1: Rice production (milled) and consumption in Sub-Saharan Africa ....................... 4 

Figure 1. 2: Paddy & Milled Rice Production Quantities in Ghana, 2009 -2018 ...................... 6 

Figure 1. 3: Top Five Rice Production Regions in Ghana (Three Year Average, 2017-2019) . 7 

Figure 1. 4: Emissions from Rice Production in Sub-Saharan Africa ....................................... 8 
 
Figure 2. 1: Sustainability in Food Systems ............................................................................ 16 
 
Figure 3. 1: Negative Production Externalities ........................................................................ 42 

Figure 3. 2: Conceptual Depiction of the Use of the Natural Environment ............................ 44 

Figure 3. 3: Conceptual Framework of the Study .................................................................... 46 

Figure 3. 4: Flow chart of the methodological approach ......................................................... 50 

Figure 3. 5: Steps followed in estimating the multipliers used for the inter-industry analysis 59 

Figure 3. 6: Map showing the study districts of Volta Region ................................................ 67 
 
Figure 4. 1: Total National GHG Emissions Trend ................................................................. 74 

Figure 4. 2: Energy Sector Emissions Trend ........................................................................... 75 

Figure 4. 3: Agriculture Sector Emissions Trend .................................................................... 76 

Figure 4. 4: Trend of AFOLU Share of Total National Green House Emissions .................... 77 

 

 

 

 

 

 

 

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ABBREVIATIONS AND ACRONYMS 
 

ADF   Augmented Dickey-Fuller  
AFOLU    Agriculture, Forestry and Other Land Use  
AWD   Alternate Wetting and Drying  
BCE   Before the Common Era 
BAU   Business as Usual  
CF    Continuous Flooding 
CFCs   Chlorofluorocarbons  
CH4   Methane  
CO2   Carbon dioxide  
ECM   Error Correction Model 
EE I-O   Environmentally-Extended Input-Output  
EPA    Environmental Protection Agency  
FBO   Farmer-Based Organization  
FWI   Flooded and Wet Intermittent Irrigation  
GHG    Greenhouse Gas  
GNRDS   Ghana National Rice Development Strategy 
GoG   Government of Ghana 
GSS   Ghana Statistical Service  
GWP   Global Warming Potential  
HFC   Hydrofluorocarbons  
IFPRI    International Food Policy Research Institute 
INDC   Intended Nationally Determined Contribution 
I-O    Input-Output Analysis 
IPPU   Industrial Production and Product Use  
LM    Lagrange Multiplier test 
MMDAs    Metropolitan, Municipal, and District Assemblies  
MOFA    Ministry of Food and Agriculture  
MPB   Marginal Private Benefit  
MPC   Marginal Private Cost  
MSB   Marginal Social Benefit  
MSC   Marginal Social Cost  
N2O   Nitrous Oxide  
PP    Phillips-Perron 
MPC   Marginal Private Cost  
SSA   Sub-Sharan Africa 
SDGs    Sustainable Development Goals  
SAM    Social Accounting Matrix  
SFS   Sustainable Food System 

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MSC    Marginal Social Cost 
TOFP   Tropospheric Ozone Forming Potential  
UNFCCC    United Nations Framework Convention on Climate Change  
VAR   Vector Autoregressive model

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CHAPTER ONE 
 

INTRODUCTION 
 

1.1 Background to the Study  
 
 
This study is in the area of resource and environmental economics. The key underlying aspect 

of this discipline is that the production of commodities by human beings entails externalities or 

side effects, for example pollution. These externalities are often not captured or considered by 

producers and/or consumers of the commodities (Jopke & Schoneveld, 2018).  GHG emissions 

from rice production, a subject of this study, is a classic example of externalities.   

 

Food is an essential need for the functioning and sustenance of human society. Consequently, 

the development of food systems has occurred in parallel with the advancement of human 

civilisation. Approximately 200,000 years in the past, people engaged in the activities of 

foraging, hunting, and scavenging as means of sustenance (Headrick, 2020). The cultivation of 

teff in the highlands of Ethiopia from about 9,000 BCE signified a shift from a subsistence 

strategy of hunting and gathering to one centred on agricultural practices for food and nutrition 

(Kreike, 2018).  In Mexico, China, and the Middle East, societies changed as people tried to find 

new ways to feed themselves (Huntington, 2020). The food supply chain has undergone 

significant transformations due to population increase and commerce (Hobbs, 2021).  

 

Many food production operations produce greenhouse gas emissions, aerosols, and albedo shifts 

that contribute to global warming and climate change, which have crippled agricultural 

communities (Smil, 2020). Climate change, biodiversity loss, and other environmental changes 

also threaten future generations health and wealth (Williams et al., 2021). To feed the 8.6 billion 

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people expected in 2030, sustainable food production is essential (WHO, 2020). From the farm 

to the global food supply chain, food production systems must use less land, water, and inputs 

to produce more food sustainably and more resilient to changes and shocks (Queiroz et al., 2021).  

 
Farmers and value chain actors underestimate the agriculture sector's contribution to global and 

national greenhouse gas emissions (Castro-Nunez et al., 2020; Ahmed et al., 2020). Land 

clearing, biomass burning, fertilizer application management, enteric fermentation, and rice 

cultivation produce a lot of CO2, CH4, and N2O (Ahmed et al., 2020). 

 

Developing nations account for three-quarters of direct greenhouse gas (GHG) emissions and 

will be the most rapidly expanding sources in the future (IPCC, 2014). Despite this, agricultural 

land use in these nations has a relatively high potential for mitigating climate change. In addition, 

a larger proportion of individuals have targeted agriculture to reduce their carbon footprints 

(CGIAR, 2015). 

 

1.2 Why the Focus on Rice? 
 
During the period from 2013 to 2019, agriculture accounted for an average of 20% of GDP in 

Ghana, while industrial and service sectors account for 22% and 48% respectively (GSS, 2020).  

Despite Ghana's vast agricultural potential, both basic and cash crop yields are among the lowest 

in the world. Ghana is a net importer of food, with an annual import bill of more than $2 billion, 

which is equal to the anticipated annual revenue from cocoa exports (World Bank, 2018).   

 

Rice is a very important cereal grain cultivated globally, with its cultivation extending to many 

regions including Africa (Zenna et al., 2017). A significant number of individuals from the 

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African continent, especially the population of Ghana, depend on rice as a primary source of 

sustenance and nutritional intake. Based on statistics provided by the United States Department 

of Agriculture (USDA), it can be shown from Figure 1.1 that rice consumption in sub-Saharan 

Africa (SSA) is experiencing exponential growth, surpassing production levels. In the West 

African region, around 56% of Africa's overall rice output is grown across a landmass spanning 

3.7 million hectares (Soullier et al., 2020). However, despite this significant cultivation, the sub-

region relies on Asia for approximately 50% of its imports in order to satisfy local consumption 

needs (d’Amour & Anderson, 2020). 

 

 

 

 

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Figure 1. 1: Rice production (milled) and consumption in Sub-Saharan Africa 
Source: USDA Production, Supply Distribution Online at https://apps.fas.usda.gov/psdonline/app/index.html#/app/home 

 

Ghana grows rice for food and cash. Population growth, urbanization, and consumer habits 

increase rice consumption. According to MoFA-SRID (2020), paddy rice production ranged 

from 302,000 to 987,000metric tonnes (181,000 to 622,000 metric tonnes of milled rice) with 

large annual fluctuations as shown in Figure 1.2. In 2020, rice consumption in Ghana reached 

1,450,000 metric tonnes at 45.0 kg per capita in comparison to the 2016 per capita consumption 

of 36.0kg. Ghana imports rice to make up for domestic shortages. As annual per capita 

consumption of rice has grown rapidly over time as a result of population growth, urbanization, 

and the fact that rice has a much longer shelf-life than other cereals, Government of Ghana 

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(GoG), as a policy, envisages rice self-sufficiency for Ghana through local cultivation to achieve 

greater food security. To ensure the sustainability and the comprehensive development of the 

rice crop, the Ministry of Food and Agriculture has facilitated the revision of the National Rice 

Development Strategy (NRDS) with a goal to achieve self-sufficiency. The government has in 

2018 launched the rice chapter of its flagship project of Planting for Food and Jobs (PFJ) as a 

policy to boost local rice production to achieve self-sufficiency by 2025 for food security, import 

substitution, and foreign exchange savings. Since 2018, rice yield has steadily increased while 

other rice-producing regions in Ghana are expanding land area (IFPRI, 2020).  

 

 

 

 

 

 

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Figure 1. 2: Paddy & Milled Rice Production Quantities in Ghana, 2009 -2018 
Source: MOFA-SRID (2020) 
 

 

Rice cultivation is undertaken in all 16 regions of Ghana. On average, the Volta Region of Ghana 

is responsible for the production of around 40% of the country's paddy rice. According to Figure 

1.3, it is evident that the top five areas responsible for rice production together accounted for 

87% of the total output, so underscoring their significant contribution in this domain. In Ghana, 

rice producers are categorized based on their agro-ecological systems, which include irrigated, 

rain-fed lowland, and rain-fed upland cultivation methods. The distribution of agricultural land 

may be categorized into three main types: lowland rainfed systems, irrigated systems, and upland 

systems. On average, lowland rainfed systems occupy around 78% of the total arable land, while 

0

100

200

300

400

500

600

700

800

900

2009 2010 2011 2012 2013 2014 2015 2016 2017 2018

Rice (paddy)'000' Mt Rice (milled) '000'MtYear  

Q
ua

nt
ity

 (i
n 

10
00

 m
et

ri
c 

to
ns

)  
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irrigated systems cover approximately 16%. Upland systems, on the other hand, account for 

approximately 6% of the arable land. According to the Ministry of Food and Agriculture-

Statistics, Research and Information Directorate (MOFA-SRID), in 2018, an annual average of 

118,000 hectares of land was used for rice cultivation.  

 

 

 
Figure 1. 3: Top Five Rice Production Regions in Ghana (Three Year Average, 2017-
2019) 
Source: MOFA-SRID (2018) 
 

According to a study conducted by Li et al. (2021), the cultivation of paddy rice is responsible 

for around 3% of world greenhouse gas emissions. The primary gases that contribute to the 

phenomenon are carbon dioxide (CO2), methane (CH4), and nitrous oxide (N2O). Rice farming 

is responsible for around 60% of global methane (CH4) emissions and 15% of global nitrous 

oxide (N2O) emissions. Methane (CH4) and nitrous oxide (N2O) have global warming potentials 

 -

 50,000.00

 100,000.00

 150,000.00

 200,000.00

 250,000.00

 300,000.00

 350,000.00

VOLTA NORTHERN UPPER EAST ASHANTI WESTERN

305,439

174,535

115,448

53,305 52,056

Q
U

AN
TI

TY
 (M

T)

REGION

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(GWPs) that surpass carbon dioxide (CO2) by factors of 84 and 268, respectively (Gorh & 

Baruah, 2019). According to Boateng et al. (2017), the region of West Africa is responsible for 

about 66% of the overall greenhouse gas (GHG) emissions generated by paddy rice cultivation 

in sub-Saharan Africa (SSA). Figure 1.4 illustrates the yearly emissions resulting from rice 

cultivation in the Sub-Saharan Africa region. 

 

Figure 1. 4: Emissions from Rice Production in Sub-Saharan Africa 
Source: (Boateng et al., 2017) 

 

According to several scholarly sources, including Behnassi et al. (2022), Gholipour et al. (2021), 

Khan and Ullah (2019), Wang et al. (2019), Cassia et al. (2018), and Wolf et al. (2017), it is 

widely accepted among environmental experts that greenhouse gas (GHG) emissions are a 

significant contributor to the phenomenon of global warming and subsequent climate change. If 

0

2000

4000

6000

8000

10000

12000

14000

16000

18000

2010 2011 2012 2013 2014 2015 2016

E
m

is
si

on
s(

G
gC

O
2e

)

Yearly Emissions

East Africa

Central Africa

Southern Africa

West Africa

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greenhouse gas (GHG) emissions are not promptly mitigated, the adverse impacts of global 

warming and climate change on economies will become more apparent. Hence, it is vital to note 

that all member states of the United Nations have made a commitment to mitigate greenhouse 

gas (GHG) emissions, encompassing carbon dioxide (CO2), methane (CH4), and nitrous oxide 

(N2O), by means of their nationally determined contributions (NDC) as outlined by the United 

Nations Framework Convention on Climate Change (UNFCCC) in 2021.  

 

1.3  Problem Statement  
 
Increasing local rice production to achieve self-sufficiency in Ghana will increase GHG 

emissions, making the country’s NDC pledge to reduce CO2, CH4, and N2O unachievable. The 

Ghanaian government’s policy of increasing local rice production brings about conflicting goals. 

The policy maker is confronted with two conflicting goals to be managed to meet the food needs 

of the growing population (Saray, et al., 2022; Pereira et al., 2020). In the Ghanaian case, the 

two goals are: production maximization to improve economic welfare related to food security, 

jobs, and incomes; and GHG emissions growth minimization to achieve a 15 percent reduction 

in the growth of total national GHG emissions by 2030, based on business-as-usual scenario. 

GHG emissions resulting from paddy rice production are discussed in many Sub-Saharan 

African studies, including Ghanaian works, but the emphasis has been on rice intensification to 

reduce food insecurity and poverty with little attention to environmental costs.  

 

Environmental issues are often analyzed based on the three natural environmental media: air, 

land and water. Air pollution includes particulate matter, sulphur dioxide and greenhouse gases 

(GHGs).  Water pollution is the contamination of water sources through causes such as poisoning 

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with cyanide used in illegal mining.  Land pollution relates more to soil erosion, and 

environmental sanitation. For this study, the focus is on air pollution (GHG emissions). 

 

According to Hisschemöller & Hoppe (2018) when policy conflicts arise in policymaking, a 

conflict analysis is required. The policymaker requires hard empirical evidence in order to select 

the optimal combination of policy instruments for evidence-based decision making. This is 

precisely what this study aims to address. 

 

1.4  Research Questions  
 
The study aimed to investigate relevant questions that emerged from the Ghanaian government's 

policy of enhancing domestic rice production. This policy is designed to promote economic well-

being, enhance food security, generate employment opportunities, raise incomes, and mitigate 

environmental pollution in alignment with the country's NDC related to the reduction of the 

growth of GHGs. The overarching research question is, what are the effects of increasing local 

rice production on total greenhouse gas (GHG) emissions in the economy and how can these 

emissions be managed? Specifically, the study sought to respond to the following questions: 

1.  What factors drive the production of GHG emissions in the overall economy of Ghana? 

2. What factors contribute to the observed declining share of the total GHG emissions 

attributed to the Agricultural Sector? 

3. How would increasing local rice production affect the total GHG emissions in terms of 

both direct and indirect effects based on the linkages between the rice industry and all other 

industries in the economy? 

4. How do local rice producers manage their production systems to deal with GHG emissions? 

 

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1.5 Objective of the Study  
 
The main objective of this study was to ascertain the influence of increasing local rice production 

on total GHG emissions in the economy through the effects on other industries and economic 

sectors. 

The specific objectives were:  

1. To identify the macro drivers of GHG emissions in Ghana. 

2. To identify the factors that contribute to the observed declining share of the total GHG 

emissions attributed to the agricultural sector. 

3. To examine the direct and indirect GHG emissions arising from rice production based 

on the linkages between the rice industry and all other industries in the economy. 

4. To assess how local rice farmers manage their production systems to deal with GHG 

emissions.  

 

1.6  Relevance of the Study 
 
The policy continuum is an essential component of any public policy, consisting of the policy 

problem, policy objectives, and a set of instruments to achieve the policy objectives. In light of 

the foregoing, policymakers are faced with an optimization challenge: maximizing welfare in 

terms of food security, job creation, and income growth by increasing local rice production while 

minimizing production externalities. When such conflicts arise in policymaking, a conflict 

analysis is required. Examining paired policy scenarios and informing policymakers of potential 

policy conflicts is what policy conflict analysis entails. The policymaker requires credible 

empirical evidence in order to select the optimal combination of policy instruments for evidence-

based decision making (Hisschemöller & Hoppe 2018). However, there is a scarcity of 

information on how policymakers might resolve the policy dilemma.  

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In order to forecast the results of a policy experiment, as per the Lucas critique, it is necessary 

to construct a model that incorporates the "deep parameters" including preferences, technologies, 

and resource limitations, which are posited to influence individual behaviour (Caldwell, 2019). 

Consequently, an analysis was conducted on both macroeconomic and microeconomic 

interdependencies. Hence, the primary value of this work is in its comprehensive analysis of 

policy conflicts across several levels, including macro, meso, and micro. 

 

First, the study examined Ghana's macro level GHG emission drivers and identified the most 

important ones for policy consideration.  Using environmentally extended input-output (EE I-O) 

methods, based on the 2018 Ghana Social Accounting Matrix (GSS & IFPRI, 2020), the effects 

of increasing local rice production on other industries' GHG emissions were examined. The EE 

I-O analysis emphasizes the industry effects of the externality and potential policy trade-offs. 

Adaptation is essential to combating climate change. Volta Region, the leading producer of 

paddy rice among Ghana's top five regions, was used as a case study to assess smallholders' 

management strategies for reducing GHG emissions in rice production at the micro level. The 

data from the field survey can be incorporated into Ghana's policy on climate change adaptation.  

 

Last but not least, the author compiled Ghana's first enhanced total GHG emissions panel data 

for various industries and economic sectors, from a secondary source, developed by the 

Environmental Protection Agency of Ghana, which were originally classified into five sectors: 

agriculture, forestry and other land use (AFOLU), energy, industrial production and product use 

(IPPU), and waste. This ground-breaking information may inform future research.  

 

 

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1.7 Organization of the Thesis Report  
 
This thesis is organised in seven chapters. The first chapter is the introductory chapter and 

discusses the background of the study, problem statement, objectives, relevance of the study as 

well as the organization of the study report. The second chapter is a review of the literature 

focusing on definition of key concepts relevant to the research objectives, findings of empirical 

research on AFOLU sector and GHG emissions, rice production at the global, regional and 

national level and GHG emissions, how farmers across the globe and Africa in particular are 

adapting and /or mitigating GHG emissions in rice fields. Further, the review identifies several 

gaps in the literature which also drive the objectives of the current study and important 

information on the methodological approaches used in determining macroeconomic drivers of 

GHG emissions, and analysing the inter-relationship between environmental pollution and 

economic activities.  The third chapter is a presentation of the theoretical and conceptual 

framework used for the study, the data collection and sampling procedures and model 

specifications utilized for the analysis of the data, linked to the specific objectives of the study. 

The fourth chapter is devoted to the presentation of the results and discussions of the study 

undertaken to identify the macroeconomic determinants of GHG emissions in Ghana involving 

the use of time series macroeconomic data from 1990 to 2019. The results and discussion of the 

input-output analysis of GHG emission in the economy of Ghana are presented in chapter five. 

The sixth chapter focusses on the results and discussion of the analysis of rice farmers’ 

understanding of climate change issues and their management responses in reducing GHG 

emissions.  The final chapter of the main text of the thesis report, chapter seven, provides a 

summary, conclusions and policy recommendations arising out of the study. The references cited 

in the text and appendices follow. 

 

  

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CHAPTER TWO 
 

LITERATURE REVIEW 
 
 

2.1 Introduction 
 
This literature review is organized under six main sections. The second section after the 

introduction defines a few concepts relevant to the research objectives. The third section 

summarizes empirical research on agriculture, forestry and other land use (AFOLU) sector and 

greenhouse emissions.  The fourth section is devoted to rice production at the global, regional 

and national level and GHG emissions. The fifth section is devoted to how rice farmers across 

the world and in Africa are mitigating greenhouse gas emissions. The sixth section is focused on 

review of the methodological approaches used in determining macroeconomic drivers of GHG 

emissions, and analysing the inter-relationship between environmental pollution and economic 

activities. The seventh and final section, summarizes the findings of the literature review and the 

gaps that exist in the literature. 

2.2 Definition of Concepts  
 
 Environmental quality  

The term "environmental quality" refers to how clean or dirty the air, water, and land are. 

Environmental quality refers to how free land, air, and water are from human-produced  

pollutants and deterioration (Chu & Karr, 2017; Zhang et al., 2022). Environmental quality is 

further defined in this research study as the amount of greenhouse gas (GHG) emissions 

produced and released into the atmosphere. Existing literature (e.g., Zhang et al., 2022; Khan 

and Ullah, 2019) demonstrates that greenhouse gas (GHG) emissions generally contribute to 

global warming and climate change. 

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Global warming potential (GWP) 

For policy discussion and target setting, greenhouse gases are measured by global warming 

potential (GWP), a measure of how much energy one tonne of gas emissions will absorb during 

a given period relative to one tonne of carbon dioxide emissions. GWP is calculated for a 100-

year period. 

 

 Public goods 

Public goods are non-excludable and non-rivalrous in nature. An additional use of a public good 

has no marginal cost. These items cannot be denied for non-payment. Also, one person's use of 

a resource does not limit others' access to it (Chen, 2021). Multiple people can use the goods 

simultaneously without a reduction in their quality and quantity. 

 

Externality  

Arthur Pigou, a prominent economist during the 1920s, is credited with the conceptualization 

and development of the economic concept known as externality. An externality refers to the 

indirect costs or benefits experienced by a third party as a result of the actions of another party 

(Ekici et al., 2022). Pollutants may be seen as externalities in the context of environmental 

economics. An illustrative instance may be seen in the context of motorized transportation, 

where manufacturers and customers of such vehicles do not bear the costs associated with the 

air pollution produced from the vehicles. This phenomenon has detrimental effects on society, 

as it fails to incentivize responsible behaviour, thereby exemplifying a typical manifestation of 

negative externality. A positive externality is said to occur when a positive advantage is 

experienced by a party other than those directly involved in a transaction or activity. The 

promotion of positive externalities may be facilitated by the government through the provision 

of subsidies for products and services that provide spill-over benefits. Conversely, the mitigation 

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of negative externalities can be achieved by imposing Pigouvian tax on goods and services that 

result in spill-over costs (Lauer et al., 2023).  

 

Agri-food systems  

FAO (2018) defines a food system as a complex web of activities involving the production, 

aggregation, processing, distribution, consumption, and disposal of food products derived from 

agriculture, forestry, or fisheries, as well as components of the broader economic, social, and 

natural environment, as illustrated in Figure 2.1. Food systems produce food and affect 

everything else, including food security, nutrition, social equity, and sustainability. Human-made 

food systems affect the environment.  However, sustainable food system generates net additional 

income for people, financial returns for investors, government revenue, and consumer benefits 

and also benefit other non-human animal species (Adhikari et al., 2021). 

 
 
 

 

Figure 2. 1: Sustainability in Food Systems 
    Source: Adapted from FAO, 2018  
 
 

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2.3 Empirical Review  
 

Air pollution is an environmental concern. Heinrich et al. (2020) assert that air pollutants consist 

of greenhouse gases (GHG), acidification contributing pollutants (ACID), and tropospheric 

ozone forming potential (TOFP). ACID and TOFP have less of an effect on climate change than 

GHG, according to Wang et al. (2021). A rise in greenhouse gas concentration causes climate 

change. 

 

Gases help regulate Earth's temperature. By absorbing solar radiation, these gases regulate 

Earth's temperature (Kweku et al., 2018). Human activities like fossil fuel consumption, solid 

waste disposal, wood and coal production, and agricultural and industrial processes, like cement 

manufacturing, emit greenhouse gases (Hussain et al., 2019). Human-produced greenhouse 

gases include carbon dioxide (CO2), methane (CH4), nitrous oxide (N2O), chlorofluorocarbons 

(CFCs), hydrofluorocarbons (HFCs), hydrochlorofluorocarbons (HCFCs), perfluorocarbons 

(PFCs), and sulphur hexafluoride (SF6).  CFCs, HFCs, HCFCs, PFCs, SF6, methane, and nitrous 

oxide have a higher GWP than CO2, forcing temperature increases over time (Delevingne et al., 

2020). Excess greenhouse gas emissions cause global warming. High-GWP gases trap more heat 

per unit of mass than CO2.  

 

Despite the fact that greenhouse gases help keep the planet warm enough for humans’ survival, 

too much greenhouse gas in the atmosphere depletes Earth's resources. Nonetheless, human 

activity has increased greenhouse gas concentrations since 1750 (Yoro & Daramola, 2020). 

According to Woolf et al. (2021) some greenhouse gases can last in the atmosphere for 100 years. 

Policymakers and researchers are therefore concerned about rising GHG emissions, since they 

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cause global warming resulting in climate change (Islam et al., 2022). GHG emissions harm 

agriculture, health, and energy security. 

 

Climate change has caused rising sea levels, ocean acidification, floods, droughts, land 

degradation, and the extinction of millions of plant and animal species (Talukder et al., 2021). 

Climate change and biodiversity loss may be more costly than COVID-19 (McElwee et al., 

2020). Thus, many studies have examined greenhouse gas effects on crop yield, particularly 

climatic change (Agba et al., 2017). Kukal & Irmak (2018) state that climate change will harm 

the world's food supply. Greenhouse gases harm food and health. Its regional impact varies, like 

food production. Climate change caused by GHG emissions increases crop and animal pests and 

diseases. These measures fit a specific climate. Weather changes may affect pest resistance. 

Increased GHG emissions therefore endanger humans. Climate change in Africa and Asia causes 

malaria, cholera, and heat stress (Watts et al., 2018). 

 

Some studies have presented findings that demonstrate a positive relationship between greater 

greenhouse gas (GHG) emissions and certain outcomes, which contradicts the prevailing body 

of research indicating that such emissions contribute to global warming, reduced crop yields, 

diminished availability of arable land, and increased prevalence of animal diseases. On the 

contrary, Harris et al. (2017) found that elevated levels of greenhouse gases (GHGs) in the 

atmosphere have a positive impact on agricultural productivity, result in decreased heating 

expenses in temperate regions, and contribute to a reduction in mortality rates associated with 

cold weather. 

a large portion 

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Agriculture, forestry, and other land use change (AFOLU) is essential to the global economy, 

food security, and sustainable development in all nations, but particularly in developing nations 

(Mbow et al., 2017).  Increased AFOLU-related activities have resulted from population growth 

and rising food demand. The world population is projected to reach 9.7 billion by 2050 (Gu & 

Dupre, 2021). The anticipated increase in the global population might potentially lead to a 

substantial rise in the demand for food.  The AFOLU sector is responsible for between 20% to 

27% of global greenhouse gas emissions, making it the second largest emitter (Xu et al., 2021; 

Ahmed & Almeida, 2020).  AFOLU is both a major climate change contributor and carbon sink. 

AFOLU activities release CO2 and non-CO2 emissions, such as CH4 and N2O, which have higher 

atmospheric forcing and longer life cycles (Allen et al., 2022). 

 

Land use emits greenhouse gases and stores carbon in forests and the atmosphere. Clearing plants 

and soil contributes to climate change (Fearnside, 2019). Clearing tropical forests for farm 

development (in Africa, Asia, and Europe) and intensive animal farming (in South America) 

accounted for between 12-25 percent of total GHG emissions. Changes to the earth's surface 

affect climate, food security, and sustainable development (Rogers, 2021). Total net agriculture, 

forestry, and other land use (AFOLU) emissions increased from 7,497 million tons of CO2 

equivalent in the 1990s to 8,103 million in the 2000s due to agricultural operations (50%), 

woodland conversion (38%), peat degradation (11%), and biomass fires (1%). Stavert et al. 

(2022) report that livestock, rice production, and biomass burning produce 80% of agricultural 

methane emissions. Fertilizer application causes 80% of global agricultural N2O emissions 

(Zhou et al., 2017). The agricultural sector feeds the world. As population and food needs 

increased, more land was farmed (Ahmed & Almeida, 2020).  

 

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Agriculture's GHG emissions have been studied extensively. There have been studies on cattle 

(Wang et al., 2017; FAO, 2019). Tillage and irrigation, however, are the most important sources 

of CO2 emissions because they rely on fossil fuels and are now widely employed globally as 

recommended management methods to boost yields (Jaiswal & Agrawal, 2020).   

 

2.3.1 Rice production and GHG emission at the global level 

 
Every day, millions of individuals in low-income and developing nations consume rice for food 

and nutrition (Biswas et al., 2020). As the importance of rice in human diets grows, producing 

countries regard it as a cash crop (Chirinda et al., 2018). Asia produces 90% of the world's rice, 

while Africa produces only 2%. Rice yields have increased in tandem with farmland and 

population growth (FAO, 2018). An estimated 47.6 million tonnes of rice were to be exported in 

2017 (FAO, 2018). Rice yields are increasing as a result of high-yielding, short-duration rice 

varieties and irrigation (Acharjee et al., 2019).  

 

The phenomenon of global warming, which is caused by the release of greenhouse gases 

(GHGs), has been extensively studied and recorded in scientific literature. It has been observed 

that the severity and frequency of global warming events have been on the rise due to the 

escalating concentrations of GHGs resulting from human activities (Baker, 2022). The 

agricultural sector is well recognized as a significant contributor to greenhouse gas (GHG) 

emissions among various human activities (Gao et al., 2022). It is estimated that the agricultural 

sector accounts for around 11% of the overall GHG emissions (Masson-Delmotte et al., 2021). 

The current emphasis in the field of agriculture is on maintaining food production levels while 

also reducing greenhouse gas (GHG) emissions (Sun et al., 2020).  

 

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Many nations are experiencing energy shortages and environmental damage from extractive 

agricultural production (Baruah et al., 2004; Nagothu, 2018; Naz et al., 2019). Thus, 

environmental disasters, land degradation, and global food insecurity alarm policy makers and 

researchers worldwide (Gathala, 2020). In Asia, heavy tillage, uneven fertilizer usage, excessive 

irrigation, and energy consumption may raise greenhouse gas (GHG) emissions by 37% by 2050 

(Frank et al., 2019). 

 

As a major source of the greenhouse gas methane, rice farming both contributes to global 

warming and is affected by it.  Methane emissions from rice fields are estimated to be around 

12%, with wetlands and flooded rice fields contributing the most (Wang et al., 2023). There is 

evidence that rice contributes far more to global warming than wheat and maize, both of which 

are widely consumed staples (Elbasiouny & Elbehiry, 2020). Nonetheless, rice is a major staple 

for millions of people around the world, and as food demand rises, more rice production is 

needed to feed the world. Several countries, particularly in Asia and Africa, have already tried 

to increase rice output. 

 

Rice production emits greenhouse gases. Rice cultivation relies on a human-dominated or, in 

some cases, human-induced environment that uses natural wetland controls and good agronomic 

techniques like irrigation and fertilizer use (Cohen & Teytelboym, 2019). Most farmers choose 

flooded terrain for rice farming because of the high soil fertility and nutrients requirements for 

rice production. The presence of water on the soil reduces oxygen and carbon dioxide, causing 

anaerobic fermentation thereby emitting methane and nitrous oxide into the atmosphere 

(Emmerling & Junk, 2020).  The rate and pattern of organic/chemical fertilizer input and 

degradation in the soil also affects methane and nitrous oxide production rates. Methane is 

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emitted into the atmosphere immediately after the floodwater recedes on paddy rice farms (Saha 

et al., 2022).  

 

Irrigated rice fields emit more methane than rice wetlands. Consistent water supply and soil 

preparation produce high yields in rice fields (Pal & Debanshi, 2022). Farming rice on flooded 

lands is sustainable and has fewer environmental impacts than dry land or elevated rice farming 

(Tran et al., 2021).  In the context of upland rice cultivation, it has been reported that there is a 

decrease in methane emissions. However, it is important to note that this reduction in methane 

emissions is accompanied by an increase in nitrous oxide emissions (Ali & Amin, 2019). This 

phenomenon, known as "emission swapping," leads to a situation where greenhouse gas 

emissions are not effectively reduced. For every kilogram of paddy rice produced from dryland, 

Yodkhum et al. (2017) reported that 0.58kg of carbon dioxide is emitted. In comparison, rice 

exhibits relatively modest greenhouse gas (GHG) emissions. Nevertheless, it is important to note 

that the global warming potentials (GWPs) of methane (CH4) and nitrous oxide (N2O) are 

projected to be 34 and 298 times more than that of carbon dioxide, respectively (Gupta et al., 

2021).   

 

 Islam et al. (2022) suggest agriculture's GHG emissions contribute to global warming and 

climate change. Thus, field tests at the Bangladesh Rice Research Institute Farm Research 

Institute in Gazipur, Bangladesh, were needed to determine rice production GHG emissions 

reduction measures. The project focused on nitrogen fertilizer efficiency and water-saving 

alternate wetting and drying (AWD). Four fertilizer treatments—control (no N), prilled urea 

(PU), urea deep placement (UDP), and the integrated plant nutrient system (IPNS), a 

combination of poultry manure and PU, in combination with two irrigation systems—AWD and 

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continuous flooding—were tested during the dry seasons of 2018, 2019, and 2020. The study 

found that AWD irrigation with enhanced fertilizer application techniques reduced pollution, 

including GHG emissions, compared to continuous flooding (CF) irrigation. 

 

Vo et al. (2023) performed research which revealed that rice cultivation in Vietnam contributes 

to around 15% of the country's total greenhouse gas (GHG) emissions. The objective of this 

study was to explore strategies for mitigating greenhouse gas emissions associated with rice 

cultivation. The research centred its attention on the modification of agricultural techniques and 

the use of alternative rice cultivars as means to mitigate emissions stemming from rice 

cultivation. The study was conducted in the Mekong Delta (VMD) in Vietnam to evaluate the 

performance of 20 rice varieties under two irrigation methods: continuous flooding (CF) and 

alternating wetting and drying (AWD). The study spanned a duration of two years and used the 

closed chamber technique to measure greenhouse gas (GHG) emissions. The findings of the 

study provided confirmation that the most significant source of variance in methane (CH4) 

emissions under conventional farming practices was due to differences in crop varieties. In the 

context of various types, methane (CH4) emissions shown greater significance compared to 

nitrous oxide (N2O) emissions. The impact of different rice types on greenhouse gas levels was 

shown to be influenced by water management practices. Therefore, it is essential to consider the 

appropriate choice of variety when implementing mitigation strategies. This consideration may 

either be included as an extra step to optimize the impact of alternate wetting and drying (AWD) 

during periods of low rainfall, or as an independent mitigation option in situations when AWD 

is not feasible. 

 

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A four-year (2012–15) field experiment by Yadav et al. (2020) examined the energy use  pattern, 

carbon footprint (CF), and economic viability/feasibility of tillage and mulches on direct-seeded 

upland rice cultivation at the India Council of Agricultural Research for the Northeastern Hill 

Region, Lembucherra, Tripura, India. Compared to conventional tillage, no-till (NT) reduced 

energy usage by 48.50%, specific energy by 49.63%, CF by 16.48%, and cost of cultivation by 

35%. It also improved energy use efficiency and benefit-to-cost ratio. Mulching improved energy 

consumption efficiency, economic productivity, net returns, and benefit-to-cost ratio over no 

mulch. The findings showed that NT with mulch is an ecologically clean production technique 

that improves energy efficiency and reduces CF in direct-seeded upland rice production in the 

Eastern Himalayas and other ecoregions. The research found that no-till-based direct-seeded rice 

used 48.5% less energy and 16.5% less CO2-e than traditional tillage without affecting yield. 

No-till had 35% lower production expenses and 12.8 times higher net return than conventional 

till. No-till improved energy efficiency, decreased continuous flow, and boosted direct-seed rice 

output and profitability.  

According to Singh, et al. (2021) pollution from rice farming is also caused by open-field rice 

straw burning. As much as 7300 kg CO2-eq/ha−1 of GHGs and pollutants from straw burning 

may harm soil, biodiversity, and human health. Global rice straw production is 731 million tons 

(MT), of which India contributed 126.6 MT. An estimated 60 percent of rice straw is burnt in 

the field. Stopping open burning reduces CH4 and N2O and helps the environment.  

 

2.3.2 Rice production in Africa and greenhouse gas emissions  

 
Rice has been farmed in Africa for over 3000 years and feeds millions (Rodenburg et al., 2006; 

Zenna et al., 2017). Africa produces 2.6% to 4.6% of the world's rice (Ibrahim & Wopereis, 

2021). Over 50 percent of Africa’s rice growers are smallholders.  Africa produced around 24 

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million metric tons of rice in the 2017/2018 trade year. However, domestic rice production meets 

60% of local demand (Zenna et al., 2017).   Akpoti et al. (2022) conducted a study which revealed 

that the majority of rice cultivation in Africa occurs in upland drylands (38%), rain-fed wetlands 

(33%), irrigated land (20%), and deep-water and mangrove swamps (9%).   

 

West African countries import almost a third of the world's rice each year (Nasrin et al., 2015; 

Norman and Kebbe, 2015). To meet expanding rice demand, governments have explored 

different wetlands for rice cultivation, bred high-yielding cultivars for Africa, and trained 

growers in rice production. (Makihara et al., 2018). Rice is the fastest-growing cereal in Africa 

(Makokha et al., 2017).  However, agriculture, especially rice farming, will increase Africa's 

GHG emissions (Ntinyari & Gweyi-Onyango, 2021). 

 

Farag et al. (2013) estimated the carbon footprints of Egyptian paddy rice using life cycle 

analysis and IPCC recommendations. They evaluated rice field emissions by analysing emissions 

from rice cultivation, mechanical operations such as irrigation, tillage, and harvesting, nitrogen 

fixation, and rice straw combustion. The findings revealed that rice farming was responsible for 

approximately 53% of total methane emissions, rice straw burning for approximately 35%, 

nitrogen fertilizer application for approximately 1%, and mechanical operations for 

approximately 1%. However, the contribution of rice production to Africa's total GHG emissions 

has not been studied in depth. Concerns about climate change, the intensification and expansion 

of rice production, and methods for increasing rice production are common themes in academic 

research on rice. 

 

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Nyamadzawo et al. (2013) examined Zimbabwe's intermittently flooded rice fields' emissions. 

The study sampled conventional tillage, no tillage, tied ridges, tied fallows, and mulched fields. 

No tillage, mulched fields, and tied ridges had the highest nitrous oxide (N2O), methane (CH4), 

and carbon dioxide (CO2) emissions, respectively. Rice fields release CO2, CH4, and N2O during 

cropping season. Osabohien et al., (2019) examined West African food production and GHG 

emissions. Their study found that GHG emissions decreased crop yields. Thus, social protection 

programs should compensate farmers for GHG-related crop losses and other risks. Their study 

focused on food crop production rather than paddy rice cultivation, which emits large amounts 

of GHGs directly and indirectly and is affected by them (climate change). 

 

GHG emissions in rice and maize production affected food security in Ghana, Senegal, Benin, 

and Côte d'Ivoire, according to Ba (2016)'s value chain analysis and greenhouse model. Nitrogen 

fertilizers increased maize cultivation's GHG emissions. Rice production emits more methane in 

flooded systems. 

 

By 2025, African governments plan to increase food production, particularly rice, which will 

increase fertilizer use and agricultural GHG emissions (Adegbeye et al., 2020). Van Loon et al. 

(2019) examined how rice intensification affects GHG emissions in ten countries using different 

management techniques. Regardless of cereal output, all countries studied will increase GHG 

emissions by 2025. GHG emissions rise when countries turn forests and grasslands into cereal 

farms.  

 

 

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2.3.3 Rice production and GHG emissions in Ghana 

 
 The government has focused on rice production in Ghana in recent years due to the high cost of 

importing rice to meet the 70% deficit from local production (Boateng et al., 2017). If Ghana's 

rice cultivation methods are used to increase rice production, they may negatively impact climate 

change mitigation. The research done by Narh et al. (2020) revealed that the use of inorganic 

fertilizer during rice production in northern Ghana is associated with the largest share of 

greenhouse gas emissions, at 72% of the overall emissions. The results support a previous, 

comparable research carried out by Eshun et al (2013). According to the study, the transportation 

of paddy by vehicle emerges as the second most significant contributor (10%) to greenhouse gas 

emissions within the rice-producing industry. In the southern part of Ghana, where a significant 

number of farmers transport their paddies to milling facilities, there is a possibility for this share 

to increase. 

 

Oladele et al. (2019) investigated Ghanaian lowland rice farmers' adoption of alternate wet and 

dry (AWD) methods. They surveyed 120 rice producers in Tema. They gathered information 

regarding the socioeconomic status, AWD usage, and climate-smart agriculture knowledge of 

producers. The majority of producers in the study were unaware of AWD and did not employ it. 

AWD adoption was also found to be influenced by contact with agricultural extension officers, 

farm size, rice cultivation experience, and production technique. Although this study did not 

measure greenhouse gas emissions from farms, it identified this as an area for future research.  

 

 

 

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2.3.4  Rice trade and GHG emissions  

 
Individuals and countries obtain their needs via commerce. As the population of a country grows, 

it becomes more dependent on other nations to satisfy its requirements that cannot be satisfied 

or created domestically. Countries spend extensively in industrialisation to create and sell more 

goods than they consume. The international commerce operations of producing and transporting 

goods and services result in the discharge of greenhouse gases into the environment (Cristea et 

al., 2013). The previous section of this review examined rice production and greenhouse gas 

emissions. This portion of the literature study will concentrate on the worldwide rice trade and 

its greenhouse gas (GHG) footprints.  

 

Trade is one of the means through which an economy expands, but it is also related with an 

increase in greenhouse gas emissions (Lee & Erickson, 2017). Lee & Erickson (2017) discovered 

that while global economic production has grown since 1990, this trend has been accompanied 

by a rise in greenhouse gas emissions. Emissions of greenhouse gases effect commerce in the 

same way that increases in GHG emissions impact trade. Loss of arable land due to rising sea 

levels has a negative impact on agricultural productivity (Zhang & Cai, 2011). Increased GHG 

emissions influence commerce: they impact agriculture, labour productivity, the supply chain, 

and transportation systems, such as the impacts of severe weather and rising sea levels on 

shipping, which accounts for around 80% of world trade (Dellink et al., 2017). Agriculture and 

public health are impacted by increased greenhouse gas emissions, which has an effect on 

commerce. These resources (such as land and labor) are exploited to produce commodities that 

are traded on both local and international marketplaces.  

 

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As mentioned, Asia produces more than two thirds of the world's rice, a staple. Rice consumption 

has increased worldwide, especially in Africa, where most urban residents eat rice as their main 

food (Hegde & Hegde, 2013). Despite the high demand for rice, only 7% of all rice produced is 

traded internationally, mostly because most of it is eaten in the country of production and Asian 

countries, the largest producers, have policies to ensure national food security and protect 

farmers' incomes (FAO, 2006). Thailand, Vietnam, Pakistan, USA, India, Italy, Uruguay, China, 

UAE, Benin, Argentina, and Brazil export 90% of rice worldwide (Tubiello et al., 2014). Many 

developing countries like Ghana import large amounts of rice to meet their food and dietary 

needs. Due to comparative advantage, South American and East Asian countries are more likely 

to produce more food and export, while the Middle East, Africa, and South Asia are more likely 

to become net food importers (Schmitz et al., 2011). 

 

The transportation of rice plays a vital role in facilitating its distribution, including both intra-

national movements within producing nations and inter-national movements between producers 

and importing nations. When considering the whole supply chain, including the journey from 

the farm gate to factories, markets, and consumers, it becomes evident that transportation of 

agricultural products has the potential to emerge as a significant contributor to greenhouse gas 

(GHG) emissions. The predominant emphasis of contemporary research on greenhouse gas 

(GHG) emissions and international trade revolves on the examination of emissions stemming 

from the production of commodities, as well as the analysis of how trade activities contribute to 

the dispersion of carbon footprints across participating nations. (Tian et al., 2022).  

 

 

 

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2.3.5 Rice Farmers’ adaptation options to reduce GHG emissions.  

 
Rice cultivation releases methane and other greenhouse gases. Understanding the adaptation 

strategies of rice farmers to reduce greenhouse gas emissions is crucial for national 

policymaking. This review's objective is to evaluate farmers' adaptation strategies using case 

studies from Africa and Asia.  

  

Hussain et al. (2020) found that rice field greenhouse gas emissions can be reduced by alternating 

wetting and drying, intercropping with short-term vegetation, limiting chemical fertilizers by 

precise farming, using rice cultivars with low methane emissions, improved tillage, recycling 

farm waste into organic fertilizers, and developing integrated rice farming systems. Boateng et 

al. (2017) classified rice emission reduction adaptation strategies in Ghana as fertilizer 

application, water and soil management, and drought-resistant rice cultivars.  According to 

Esiobu et al. (2020) rice farmers in Nigeria use alternate wetting and drying (AWD) to mitigate 

greenhouse gas emissions.  Similarly, Arunrat et al. (2018) recommended that some of the most 

effective strategies for reducing greenhouse gas emissions for Thai rice farmers include the use 

of zero-tillage systems, ammonium sulfate rather than urea, mid-season drainage, and site-

specific nutrient management. 

 

Opoku Mensah (2023) found that smallholders' main strategies for minimizing climate change's 

impact on yield were changing planting date, planting early maturity varieties, and applying 

organic fertilizer. Hasan (2013) also found that Egyptian smallholders adapted by using short-

duration rice varieties and good water and fertilizer management. Hussain et al. (2022) found 

that many Singaporean rice farmers used fertilizer combinations and the integrated management 

system to reduce greenhouse gas emissions and increase yield potential by changing tillage, 

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nitrogen fertilization, irrigation, and organic and fertilizer inputs. Win et al. (2021) suggested 

resistant rice varieties, organic manure, and water management to reduce rice field greenhouse 

gas emissions. Islam et al. (2021) reported that most Bangladeshi rice farmers use water-saving 

irrigation. In non-tilled paddy fields in the central lowlands of China, Xu et al. (2015) reported 

water-saving irrigation and drought-resistant rice varieties. 

 

Human capital is essential for all industries including rice farming (Kim et al., 2018). The 

efficiency of the workforce on any given farm can increase the output of the agriculture industry. 

A study conducted by Almoussawi et al. (2022) highlighted among the findings, the importance 

of human capital's influence on agricultural productivity for Iraq's sustained economic growth. 

In a country-specific study, Zhang et al. (2021) investigated how natural resources, human 

capital, and economic growth affected environmental degradation in Pakistan from 1985 to 2018 

using the autoregressive distributed lag method (ARDL).  The analysis results show that human 

capital and natural resources negatively impact CO2 in the long run. They concluded that 

adopting new production processes via using new technology by human intellectual capital plays 

a critical role in resource utilization, resulting in the mitigation of environmental degradation.  

Similarly, Pata & Caglar (2021) reported that anthropogenic production and consumption 

activities pollute the air, soil, and water, endangering human health and long-term development. 

Hence, countries have implemented various measures and technologies to reduce and control 

GHG emissions, especially CO2 emissions. They revealed that human capital is crucial in 

reducing environmental degradation in China using annual time series data from 1980 to 2016. 

 

The aforementioned findings provide support for the human capital theory of economic growth 

proposed by Theodore Schultz (1961). This theory posits three key components: firstly, nations 

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lacking sufficient human capital face challenges in effectively utilizing physical capital; 

secondly, economic growth can only be achieved when both physical capital and human capital 

experience simultaneous growth; and thirdly, human capital is the primary factor that tends to 

impose limitations on growth. The ability of rice farmers to mitigate greenhouse gas (GHG) 

emissions through adaptation measures is contingent upon their human capital, including factors 

such as education, training, and experience.  

 

2.4  Methodological Approaches for Analysing GHG Emissions  
 

Several academics used econometric analysis to examine greenhouse gas emissions and their 

causes. Khan & Ullah, (2019) and Boateng, (2020) all estimated overall economy, sector, and 

industry GHG emissions using the production function. The selection of analytical procedures 

and instruments is determined by the subject area (environmental economics or biology), study 

objective and the availability of specific data types. The econometric approach only estimates 

coefficients that are direct. The approach is incapable of capturing interdependencies across 

sectors and industries; hence, projections based on these estimations may be misleading and 

inaccurate. Environmental economists calculate the economic and environmental impacts of 

GHG emissions using various methods, according to the literature. Most approaches use input-

output (IO) analysis, computable general equilibrium models, or a combination of I-O analysis 

and linear programming (Ribeiro et al., 2018; Nguyen et al., 2019; Moon et al., 2020). 

 

IO analysis was used to identify sustainable Korean industries based on CO2 emissions and to 

examine indirect CO2 emissions in China's construction industry, GHG missions, and Brazil's 

livestock industry (Moon et al., 2020). In recent years, the international community's focus on 

environmental issues has led to the measurement of the flows and changes in a country or region's 

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resources, energy, and emissions using the I-O framework (Cai et al., 2020). GSS-IFPRI (2020) 

examined COVID-19's effects on Ghana's agriculture, industry, and services using the I-O 

framework. 

Leontief's assumption of the constant input coefficient of production and the constant returns of 

scale and technology restricts input-output analysis when it is used for forecasting beyond five 

years. A stationary economy presupposes continual returns to scale, but a stationary technology 

assumes a constant technique of production. The model is based on difficult-to-find equations. 

Identify the mathematical pattern first, then the enormous data. Equations need significant 

mathematics and difficult-to-locate data. The input-output paradigm gets convoluted and 

abstract, which is why some researchers avoid using it. 

Leontief's (1986) input-output (I-O) analysis is used to analyse economic structure, global and 

local trade, energy, and environmental issues. The IO Inter-industry environmental impact 

analysis examines international trade and consumption (Daly 1968; Ayres and Kneese 1969; 

Chang and Lin 1998; Proops et al., 1999). Total output equals intermediate consumption plus 

final consumption (Leontief, 1985). Primary and intermediate texts discuss input-output analysis 

methods (Miller & Blair, 2009; Zhang et al., 2011; Ten Raa, 2017; Leontief, 2018; Ribeiro et 

al., 2018; Moon et al., 2020).  

The I-O table is an exhaustive statistics table that illustrates the inter-industry trade ties of all 

products and services generated in a particular year. An I-O table comprises a link between the 

main input factor sector and industry as well as the number of transactions between the final 

output sector and each industry (Miller and Blair 2009). This demand table contains demand for 

intermediate commodities—inputs such as labor, earnings, and taxes—as well as demand for 

final products, including consumer goods and services and exports (Moon et al., 2020) 

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Table 2. 1: The structure of an Input-Output Table 
Producing 
Sector  

Intermediate Goods and Services  Total 
Intermediate 
Demand  

Total Final 
Demand 

Total Output 

 R1 R2 R3 R4 …
.. 

Rn    

R1 X11 X12 X13 X14 …
.. 

X1n RX1n D1 X1 

R2 X21 X22 X23 X24 …
. 

X2n RX2n D2 X2 

R3 X31 X32 X33 X34 …
. 

X3n RX3n D3 X3 

R4 X41 X42 X43 X44 …
.. 

X4n RX4n D4 X4 

…..  
Quadrant I 

               …… Quadrant II 
….. 

Rn Xn1 Xn2 Xn3 Xn4 …
. 

Xnn RXnn Dn Xn 

 Total Purchase    
         Value Added      
                Total Input       

Source: Moon et al. (2020) 
 

In Quadrant I, goods are transferred from one sector of manufacturing to another. Rows R1 

through Rn in Quadrant I show the different industrial sectors that contribute to economic 

production. The sum of each column indicates the overall number of intermediate resources 

accessible to a particular sector. In contrast, the industries in the columns use the outputs of the 

manufacturers in the rows as inputs for their own goods. Total intermediate demand for each 

industry is the sum of the sectors in their respective columns. In the second quadrant, is the 

ultimate demand, which comprises of purchases made by consumers, governments, and export 

enterprises, but not the manufacturing sector. The output of an industry is the total of all its 

inputs, from raw materials to completed products. Three factors make up value added: wages 

and salaries, taxes on production and imports less subsidies, and gross operating surplus. Total 

industrial input equals intermediate demand plus output with added value.  

 
 
Miller and Blair (2009) calculated each sector's output as X = (I-A)-1 Y. A is the technology 

matrix showing how much input each sector needs to make one product in Ri. Technical 

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coefficients are calculated by dividing each I-O table entry by its column total (aij = xij/Xj). The 

identity matrix is I, and the inverse Leontief matrix is (I-A)-1. External demand is Y, and sector 

output is X. When sector j as a buyer and seller increases, so does its production. I-O analysis 

divides linkages into backward and forward effects. 

 

Forward and backward linkage measure a sector's relationship to the sectors from which it buys 

inputs and sells output, respectively (Rasmussen, 1956; Miller and Blair 2009; Moon et al., 

2020). Leontief inverse (I-A)-1 measures economic sector links. Choe et al., 2023, Quan et al., 

2020, and Moon et al. (2020) define the backward linkage effect as power of dispersion (POD) 

and the forward as sensitivity (SOD). 

 

Rasmussen (1956) calculated POD and SOD index formulae. Quan et al. (2020) calculated the 

inter-sectoral and effects-induced effects of final demand on output, value-added, and GHG 

emissions in Korea and Vietnam using IO analysis. The POD and SOD are defined below. 

  

Power of Dispersion (POD) =     ∑ ∪!"=
!
"
∑ $#$#

!
"%
∑ $#$#$

!   

 

Sensitivity of Dispersion (SOD) =      ∑ ∪!"=
!
"
∑ $#$$

!
"%
∑ $#$#$

"  

                                                                                                                                                               

where n is the number of industries and Bij is the sum of the Leontief inverse matrix  

B= (I-A)-1 column elements. To meet a one-unit increase in final demand for industry products, 

the entire system of industries must increase output.  The back link increases demand for inputs 

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from other sectors, and the forward link changes output sensitivity to other sectors, according to 

Guo and Hewings (2001). 

 

2.5  Summary of the Major Findings from the Review of the Literature 
 
 
This literature review was conducted to find out the contribution of rice production to GHG 

emissions and how production systems are being managed to deal with GHG emissions.  Among 

the key findings are: 

1) The contribution of the agricultural sector to greenhouse gas (GHG) emissions is well 

acknowledged, however its comprehension remains limited. It is a fact that approximately 

one quarter of global greenhouse gas (GHG) emissions are attributed to the sectors of 

agriculture, forestry, and land-use change. Furthermore, as the global population grows 

and the need for food increases, these emissions are projected to rise if nothing is done 

about them. 

2) Several researchers have conducted empirical research on this topic, with results 

indicating the net increase in production from the sector (Tubiello et al., 2014), sources 

of GHG emissions within the AFOLU sector (Foley et al., 2005; Houghton, 2003; 

Mammadova et al., 2020), forms of GHGs released by the sector (Lambin et al., 2003; 

Foley et al., 2005), and the effects of land use change. 

 

3) The sources of GHG in agriculture can be divided into three categories: crop production, 

transportation and processing, and farm equipment purchases (Gifford, 1984; Lal et 

al.,2004; Farag, 2013). Several studies on cereal production and GHG emissions have 

been conducted. These studies usually focus on maize, wheat, and rice. 

 

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4) Global rice production has increased, which affects methane and nitrous oxide emissions. 

The literature review found that most empirical rice studies are from Asia. Also, many of 

these studies focused on GHG emissions and cropping systems (Bouman et al., 2017; Cai 

et al., 2020; Linquist et al., 2012; Zhou et al., 2017) 

 

5) A significant number of studies also evaluated water management systems, while others 

analyzed both water management systems and fertilizer application (see for instance, 

Linquist et al., 2015; Xu et al., 2015). Some studies also focused on the use of fertilizer 

on rice fields and greenhouse gas emissions (Zhong et al., 2016; Snyder et al., 2009).   

 

6) From the review, it was determined that, despite the fact that some studies on rice 

production and GHG emissions have been conducted on the African continent, the 

proportion of studies conducted in Africa relative to the rest of the world is extremely 

low. Moreover, research on the continent examined cropping systems and water 

management systems (Farag et al., 2013; van Loon et al., 2019; Osabohien et al., 2019). 

 

7) Similarly, Ghanaian research has focused on cropping systems (Boateng et al., 2017), 

water management (Oladele et al., 2019), and GHG emissions in the rice production chain 

(Boateng et al., 2017; Oladele et al., 2019), and (Eshun et al., 2013). Although Eshun et 

al. (2013) examined transportation and greenhouse gas (GHG) emissions in rice 

production, their focus was on transportation from mills to the market. 

 

8) In Asia, environmental impact studies focused on inter-industry analysis to examine how 

changes in final demand affect economic production and the environment (Ha, 2021; 

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Firdaus & Wijayanto, 2020; Moon et al., 2020; Ha & Trinh, 2018; Temursho, 2016). In 

lieu of regression analysis, they utilized an environmentally-extended input-output (EE I-

O) technique to examine indirect greenhouse gas emissions, specifically carbon dioxide, 

in their respective industries. EE I-O builds on I-O in order to determine the hidden, 

indirect, or embodied environmental and/or social effects of an upstream economic event 

(Kitzes, 2013). 

2.6  Gaps in the Literature  
 
Among the gaps identified in literature are: 

1) The literature on the negative production externalities such GHG emissions associated 

with paddy rice production in Africa has received little attention. In research studies, the 

emphasis has been on rice intensification to reduce food insecurity. 

2) Studies on the impacts of rice production in Africa tend to focus on the direct effects of 

GHG emissions, ignoring the indirect effects of these emissions caused by industry 

interdependence. This emphasis is primarily due to the use of regression analysis, which 

is inadequate to explain industry interdependence. 

3) In the allocation of total GHG emissions in an economy, outputs of industries as a 

proportion of total economic output are frequently used to calculate total GHG emissions 

produced by each industry (Ha, 2021; Firdaus & Wijayanto, 2020; Moon et al., 2020; Ha 

and Trinh, 2018; Ribeiro et al., 2018; Temursho, 2016). Even though this method is 

simple, it could be misleading and give wrong estimates of the emission coefficients for 

different industries. 

4) The literature on drivers of GHG emissions frequently uses total trade as a measure of 

openness without distinguishing between imports and exports, which could have 

opposing effects on GHG emissions. 

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5) Input-output analysis studies frequently employ total output and total value-added 

multipliers and effects and do not distinguish between labour income and capital owner 

income effects. These studies tend to ignore income inequality issues, which are pertinent 

to political economy discourse, particularly in countries like Ghana where income 

inequality among the population is increasing. The causes and effects of GHG emissions, 

as perceived by policymakers and elites, and as indicated by farmers are not 

simultaneously addressed in studies of these emissions. 

This study aims to identify the direct, hidden, indirect, embodied environmental, and economic 

and social benefits of Ghana's policy of increasing local rice production. This study will also 

examine the macro drivers of GHG emissions and the externalities in terms of GHG emissions 

produced in the domestic economy based on inter-industry interactions to determine which 

industries in the economy generate higher total value-added multipliers at relatively low levels 

of pollution in response to a unit increase in final demand. In addition, the study will disaggregate 

the total value-added multipliers into labour income and capital owner income effects in order 

to identify the policy's winners and losers. Overall, the study will generate evidence for 

policymakers to make informed decisions about increasing local rice production to achieve self-

sufficiency while meeting the country's GHG mitigation commitments in accordance with its 

declared NDC linked to the reduction in the growth of GHG emissions. 

 

 

 

 

 

 

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CHAPTER THREE 
 

METHODOLOGY AND PROCEDURES USED FOR THE STUDY 
 

3.1 Introduction  
 
This chapter describes in details the theoretical underpinnings and the conceptual framework of 

the study. It also discusses the methodology and procedures of the study under the three different 

objectives.  

3.2 Theoretical Framework 
 
The theory underpinning this research is externality theory based on economics of negative 

production externalities. Externalities cause market failure if the price mechanism does not take 

account of social costs and benefits of production and consumption.   Market failure leads to an 

inefficient allocation of resources and dead weight loss of economic welfare. For this typology 

of externalities, a firm’s production reduces the well-being of others who are not compensated 

by the firm. In this case, marginal social cost (MSC) is greater than marginal private cost (MPC) 

due to marginal damage cost (MDC). Marginal damage cost (MDC) is the additional cost 

associated with the production of the good that are imposed on others but that producers do not 

pay. The social marginal cost (MSC) is therefore comprised of the marginal private cost (MPC) 

to producers plus marginal damage cost (MSC=MPC+MDC). 

MSB – Marginal Social Benefit  

MPB – Marginal Private Benefit 

 

3.2.1 Theory of externality (firm and industry) 

In an economy that operates on market principles or exchange mechanisms, the production of a 

particular item, such as rice, is undertaken by a distinct entity referred to as the producer. 

Subsequently, the consumption of this commodity is carried out by a separate entity known as 

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the consumer. The process of producing a commodity gives rise to externalities, which are 

unintended consequences in economic terminology. Neither the producer nor the consumer 

internalizes or captures these externalities. The use of the social cost of production concept is 

often necessary in the management of externalities.  

 

Figure 3.1 depicts a competitive rice production industry characterized by a multitude of 

producers and consumers. The producers are represented by an individual supply curve denoted 

as S1, while the overall demand for rice in the industry is represented by the aggregate demand 

curve, D. At the point of equilibrium quantity Q1, individual rice farmers optimize their profits. 

At this point of equilibrium quantity, the marginal private benefit (MPB) is equal to the marginal 

private cost (MPC). If environmental factors are taken into account, the supply curve S1 

experiences a leftward shift. The introduction of the new supply curve, denoted as S2, results in 

the establishment of a new equilibrium quantity, represented as Q2. The equilibrium level of 

output, when externalities are included, is lower compared to the scenario when externalities are 

not taken into consideration, as shown in Figure 3.1 

 

 

 

 

 

 

 

 

 

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 S2 
                 

 

                                           

Unit 
Benefit/                                     Deadweight loss                                      External Cost                                                                         
Cost 
                                                                                                                                  S1 

                                                                   

         P2 

                                                                                                                      

           P1                                

                                                                            

                                                                                                           D=MPB = MR 

                                                                                                                          D