i 

 

 



ii 

 

Copyright@2020 Ghana Statistical Service 

Prepared by: Francis Bright Mensah, John Foster Agyaho, Dr. Raymond Elikplim Kofinti, 

and Dr. Joshua Sebu  

 

Edited by: Dr. Ewura-Adwoa Ewusie  

 

 

Chief Editor: Prof. Samuel Kobina Annim 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 



iii 

 

PREFACE AND ACKNOWLEDGEMENT 

 

This report presents Ghana’s Multidimensional Poverty Index (MPI), which complements the 

monetary poverty by providing an assessment of deprivation of basic survival needs. The 

complementarity engenders the deployment of diverse and targeted social and monetary 

interventions to deprived populations, especially the poorest of the poor. The criticality of an MPI 

assessment of poverty is the pervasiveness of an unequal and varied level of lack of access to basic 

survival needs across different population groups and more importantly, the indispensability of 

public services notably on issues in the domain of health and education policy needs. The 

computational process draws on multiple national level datasets and benchmarks the analytical 

procedures with internationally recognized methods of accessing multidimensional poverty.  

The GSS wishes to acknowledge the invaluable contribution of Francis Bright Mensah, John 

Foster Agyaho, both from GSS, and Raymond Elikplim Kofinti and Joshua Sebu of the University 

of Cape Coast for engaging with the data, analysis and report writing. The technical support and 

dedication of Christian Oldiges, Corinne Mitchell and Davina Governance Osei (all from the 

Oxford Poverty and Human Development Initiative) in the process of conceptualization, analytical 

validation and report writing are very much appreciated. The Ghana MPI team is particularly 

grateful to the MPI National Steering Committee, especially, Mary Mpereh of the National 

Development Planning Commission, Paul Nkegbe (University of Development Studies), Jamil 

Seini (Ministry of Finance), Shirazu Inusah (Local Government Authority), Gertrude Elleamoh, 

Verena Goranko and Isabel Rodde (Agenda 2030, GIZ Ghana),  Kordzo Sedegah, Radhika Lal 

and Frederick Mugisha (United Nations Development Programme (UNDP), Ghana) and Abena 

Osei-Akoto (GSS), for their guidance and support. A special appreciation goes to UNDP Ghana 

and the German Federal Government through GIZ, for providing both financial and technical 

support.  

 

Prof. Samuel Kobina Annim 

(Government Statistician and National Project Director) 

  



iv 

 

FOREWORD 

 

Who is poor in Ghana? What does it mean to be poor, and how can we best combat poverty and 

inequality? 

The first Multi-dimensional Poverty Index (MPI) Report for Ghana provides in-depth insights to 

answer these crucial questions. By using multiple dimensions to measure poverty, it provides a 

better understanding of the various deprivations that the poor in the country battle with. Ghana has 

made impressive strides in its economic development. Yet, inequality is on the rise and large parts 

of the population are at risk of being left behind. The recent outbreak of COVID-19 has 

demonstrated once again that it is the most disadvantaged who pay the highest price in times of a 

crisis. To better protect them, not just in times of crises, high quality data on their living situation 

is urgently needed. However, too often, it is precisely them who remain uncounted and 

unaccounted for.  

The MPI Ghana constitutes an important milestone, as it provides disaggregated data that sheds 

light on the realities of the most vulnerable in the different regions. This information is key for 

identifying and tailoring effective interventions that reflect the development needs of all 

Ghanaians. The eradication of poverty and inequality in all its forms and dimensions, as addressed 

by the Sustainable Development Goals (SDGs), is an overarching goal of German Development 

Cooperation. GIZ Ghana´s engagement, in this respect, includes support of the Government of 

Ghana in improving the management of domestic revenues and expenditures to finance inclusive 

development.  

The Agenda 2030 Project is partnering with a variety of governmental and non-governmental 

actors to strengthen the data-ecosystem to better track Ghana’s progress in the implementation of 

the SDGs. The cooperation with Ghana Statistical Service (GSS), aiming at closing the existing 

data gaps for effective monitoring and planning, has been particularly fruitful. The MPI Ghana is 

yet another significant achievement to provide “better data for better decisions”.  

I thank GSS, the University of Cape Coast, the University of Development Studies, the Oxford 

Poverty and Human Development Initiative and all other partners for this pioneer work. Let´s all 

use this data to inform inclusive policies and ensure that no one will be left behind. 

 

Regina Bauerochse,  

Country Director GIZ Ghana 

 

 

 

 



v 

 

FOREWORD 

 

This report on Multi-Dimensional Poverty Index for Ghana comes at the time when the world is 

experiencing the coronavirus pandemic that is negatively impacting lives and livelihoods. The 

report tells an important success story and provides a baseline for us to understand the impact of 

COVID-19 once future estimates are computed to provide a basis for building back better.  

 

I want to thank the Ghana Statistical Service (GSS) and GIZ for their continued partnership with 

us at the United Nations Development Programme (UNDP), which again has resulted in this 

important report.  

 

It is welcoming news that for the past 7 years, between 2011 and 2018, according to the report, 

multidimensional poverty, its incidence and severity have reduced across the country, with 

significant improvements in electricity, cooking fuel and school attainment. What is even more 

heartening is that the former Northern region (present day Northern, Savannah, and North East) 

had the greatest improvement. However, the report reveals inequalities, particularly relating to 

rural/urban and geographical divides, with rural areas and the former Northern region having 

relatively higher levels of multidimensional poverty. 

 

While celebrating the success chalked in the report, we must keep our eyes on the Sustainable 

Development Goals (SDGs) to address the remaining challenges, especially given that we have 

only 10 years to the 2030 deadline. It is important to note that UNDP’s Human Development 

Report Office has warned that global human development – which can be measured as a 

combination of the world’s education, health and living standards – could decline this year for the 

first time since the concept was introduced in 1990, due to COVID-19. For the story to be different 

for Ghana, we must continue to work together to reach those being left behind.   

 

It is our hope that these results will help inform our response to the pandemic and policies for 

recovery post-COVID-19. We look forward to nurturing our partnerships with the GSS, GIZ and 

all stakeholders towards SDGs achievement. 

 

 

 

Gita Welch 

UNDP Resident Representative 

 

 

 



vi 

 

TABLE OF CONTENTS 

 

PREFACE AND ACKNOWLEDGEMENT ......................................................................... iii 
FOREWORD ........................................................................................................................... iv 
LIST OF TABLES ...................................................................................................................vii 
LIST OF FIGURES ............................................................................................................... viii 
LIST OF ABBREVIATIONS ................................................................................................. ix 
EXECUTIVE SUMMARY ........................................................................................................x 
CHAPTER ONE:  INTRODUCTION.................................................................................... 1 

1.0 Background ...................................................................................................................... 1 

1.1 Why Multidimensional Poverty? ..................................................................................... 1 

1.2 Purpose of Ghana’s MPI .................................................................................................. 2 
CHAPTER TWO:  METHODOLOGY AND DATA .............................................................. 3 

2.1 Alkire-Foster Method ....................................................................................................... 3 
2.2 Data .................................................................................................................................. 5 

2.3  Structure of the Measure .................................................................................................. 5 
CHAPTER THREE:  RESULTS AND DISCUSSIONS ....................................................... 10 

3.1 The Level of Multidimensional Poverty in Ghana ......................................................... 10 
3.2 MPI across Large Area Aggregates ............................................................................... 12 

3.3 Multidimensional Poverty by Region ............................................................................ 15 
3.4 MPI by Gender and Age of the Head of Household ...................................................... 18 

3.5 MPI by Age Decomposition ........................................................................................... 19 
3.6 Monetary Poverty vs Multidimensional Poverty ........................................................... 21 

CHAPTER FOUR:  REGIONAL ANALYSES ...................................................................... 25 

4.1 Western Region .............................................................................................................. 25 
4.2 Central Region................................................................................................................ 27 

4.3 Greater Accra Region ..................................................................................................... 28 
4.4 Volta Region .................................................................................................................. 30 
4.5 Eastern Region ............................................................................................................... 32 

4.6 Ashanti Region ............................................................................................................... 34 
4.7 Brong Ahafo Region ...................................................................................................... 35 

4.8 Northern Region ............................................................................................................. 37 
4.9 Upper East Region ......................................................................................................... 39 

4.10    Upper West Region ........................................................................................................ 41 
CHAPTER FIVE:  MULTIDIMENSIONAL POVERTY OVER TIME ............................. 44 

5.1 Introduction .................................................................................................................... 44 

5.2 National Censored Headcount Ratios-2011 to 2018 ...................................................... 45 
CHAPTER SIX:  SUMMARY AND POLICY IMPLICATIONS .......................................... 54 
APPENDIX ............................................................................................................................. 55 
 

  



vii 

 

LIST OF TABLES 

 

Table 2.1:  Ghana’s national MPI – indicators, deprivation cut-offs and weights ......................... 7 

Table 3.1:  Incidence, intensity, and multidimensional poverty index (MPI), 2017 .................... 10 

Table 3.2:  Multidimensional poverty by rural/urban areas, 2017 ................................................ 12 

Table 3.3: Multidimensional poverty by ecological zones, 2017 ................................................. 14 

Table 3.4: Regional distribution of incidence of poverty and intensity ........................................ 16 

Table 3.5: Multidimensional poverty by gender, 2017 ................................................................. 18 

Table 4.1: MPI, headcount ratio and intensity - Western Region ................................................. 25 

Table 4.2: MPI, headcount ratio and intensity - Central Region .................................................. 27 

Table 4.3: MPI, headcount ratio and intensity - Greater Accra Region ....................................... 29 

Table 4.4: MPI, headcount ratio and intensity - Volta Region ..................................................... 31 

Table 4.5: MPI, headcount ratio and intensity - Eastern Region .................................................. 33 

Table 4.6: MPI, headcount ratio and intensity - Ashanti Region .................................................. 34 

Table 4.7: MPI, headcount ratio and intensity - Brong Ahafo Region ......................................... 36 

Table 4.8: MPI, headcount ratio and intensity - Northern Region ................................................ 38 

Table 4.9: MPI, headcount ratio and intensity - Upper East Region ............................................ 40 

Table 4.10: MPI, headcount ratio and intensity - Upper West Region ......................................... 42 

Table 5.1: Change in incidence, intensity and MPI, 2001 to 2018 ............................................... 44 

  



viii 

 

LIST OF FIGURES 

 

Figure 2.1:  National uncensored headcount ratios, 2017 ............................................................... 8 
Figure 3.1:  National censored headcount ratios, 2017 ................................................................. 11 
Figure 3.2:  Censored headcount ratios by urban and rural areas, 2017 ....................................... 12 
Figure 3.3:  Percentage contribution of each indicator to rural and urban MPI ........................... 13 
Figure 3.4: Censored headcount of indicators across ecological zones ........................................ 14 

Figure 3.5: Percentage contribution of each indicator to MPI for ecological zones, 2017 ........... 15 
Figure 3.6: Population share and composition of the poor per region .......................................... 16 
Figure 3.7: Spatial distribution of poverty incidence and poverty intensity by region ................. 17 
Figure 3.7a: Spatial distribution of MPI by region ....................................................................... 17 
Figure 3.8: Percentage contribution of each indicator to the regional MPI .................................. 18 

Figure 3.9: Censored headcount ratios by gender of the household head, 2017 .......................... 19 
Figure 3.10: Multidimensional poverty by age groups ................................................................. 20 

Figure 3.11:  Percentage contribution of indicators across age groups ........................................ 21 
Figure 3.12: Comparison between monetary and non-monetary poverty ..................................... 22 

Figure 3.13: MPI and monetary poverty across area aggregates .................................................. 22 
Figure 3.14: Multidimensional and monetary poverty across administrative regions .................. 23 

Figure 3.15: Distribution of double burden of poverty by region................................................. 24 
Figure 4.1: Percentage contribution by indicator - Western Region ............................................ 26 
Figure 4.2: Percentage contribution by indicator - Central Region .............................................. 28 

Figure 4.3: Percentage contribution by indicator - Greater Accra ................................................ 30 
Figure 4.4: Percentage contribution by indicator - Volta Region ................................................. 32 

Figure 4.5: Percentage contribution by indicator - Eastern Region .............................................. 33 

Figure 4.6: Percentage contribution by indicator - Ashanti Region ............................................. 35 

Figure 4.7: Percentage contribution by indicator - Brong Ahafo Region ..................................... 37 
Figure 4.8: Percentage contribution by indicator - Northern Region ........................................... 39 

Figure 4.9: Percentage contribution by indicator - Upper East Region ........................................ 41 
Figure 4.10: Percentage contribution by indicator - Upper West ................................................. 43 
Figure 5.1:  Multidimensional poverty in Ghana, 2011-2018 ...................................................... 45 

Figure 5.2: National headcount ratios, 2011-2018........................................................................ 46 
Figure 5.3: Absolute change in censored headcount ratios between 2011 and 2017 ................... 46 

Figure 5.4: National uncensored headcount ratios, 2011-2018 .................................................... 47 
Figure 5.5: Absolute change in uncensored headcount ratios 2011-2017 .................................... 48 
Figure 5.6a: Incidence of multidimensional poverty 2011-2017 .................................................. 49 
Figure 5.6b: Intensity of multidimensional poverty 2011-2017 ................................................... 50 

Figure 5.6c: Multidimensional poverty index 2011-2017 ............................................................ 50 
Figure 5.7: Absolute change across regional MPI, 2011-2017 ..................................................... 51 
Figure 5.8: Percentage change across regions, 2011-2017 ........................................................... 51 

Figure 5.9: Multidimensional poverty reduction across regions, 2011-2017 ............................... 52 
Figure 5.10: Absolute change in censored headcount ratios by region, 2011-2017 ..................... 53 
  



ix 

 

LIST OF ABBREVIATIONS 

 

AF   Alkire-Foster 

AR   Ashanti Region 

BAR   Brong-Ahafo Region 

BCG   Bacille Calmette Guerin 

CR   Central Region 

DPT   Doctor of Physical Therapy 

ER   Easter Region 

FAO   Ghana Food and Agricultural Organisation 

GAR   Greater Accra Region 

GIZ   German Agency for International Cooperation 

GLSS   Ghana Living Standards Survey 

GSM   Global System for Mobile Communication 

GSS   Ghana Statistical Service 

HDRO   Human Development Report Office 

ICT   Information and Communication Technology 

MICS   Multiple Indicator Cluster Surveys 

MPI   Multidimensional Poverty Index 

NDPC   National Development Planning Commission 

NR   Northern Region 

OPHI   Oxford Poverty and Human Development Index 

SDGs   Sustainable Development Goals 

SE   Standard Error 

TV   Television 

UER   Upper East Region 

UN   United Nations 

UNICEF  United Nations Children’s Fund 

UWR   Upper West Region 

VR   Volta Region 

WR   Wester Region 

  



x 

 

EXECUTIVE SUMMARY 

 

This report presents Ghana’s official national Multidimensional Poverty Index (MPI) using the 

seventh round of the Ghana Living Standards Survey conducted between 2016/2017 survey 

periods. The report also employed a strict harmonised dataset from the Ghana Multiple Indicator 

Cluster Surveys conducted in 2011 and 2018 for trend analyses. The Alkire-Foster methodology 

was used to measure the MPI for the country. Following the three broad dimensions of the global 

MPI in Health, Education and Living Standards, twelve (12) respective indicators were used to 

reflect national priorities in the MPI structure. 

Our results show that 45.6 percent of Ghana’s population are multidimensionally poor. The 

indicators that contribute most to multidimensional poverty in Ghana are lack of health insurance 

coverage, undernutrition, school lag and households with members without any educational 

qualification. The intensity of poverty is 51.7 percent, meaning that poor people experience, on 

average, more than half of the weighted deprivations. The MPI, which is the product of the 

incidence and intensity of poverty, is 0.236. 

Comparing the incidence of Ghana’s multidimensionally poor of 45.6 percent to the incidence of 

consumption expenditure poverty of 23.4 percent revealed a difference of 22.2 percentage points. 

A scrutiny of both estimates, however, revealed that 19.3 percent of the population are both 

multidimensionally and consumption expenditure poor; 4.1 percent are consumption expenditure 

poor but not MPI poor; and 26.3 percent are MPI poor but not consumption expenditure poor. The 

analysis, therefore, suggests that a majority, constituting approximately 82.3 percent of people 

who are monetary poor are also MPI poor. The reverse, however, is not true. A greater proportion 

of the MPI poor (26.3%) are not monetary poor and would thus be excluded from any poverty 

policy initiative based on the monetary measure. 

As expected, the rural-urban differences are evident, with 64.6 percent of the rural population and 

27.0 percent of the urban population being multidimensionally poor. Our computations indicate 

that Northern Region recorded the highest rate of multidimensional poverty - with every eight out 

of ten persons being multidimensionally poor (80.0%), followed by the Upper East Region- with 

close to seven out of every ten persons being multidimensionally poor (68.0%).    

From the trend analyses, we found substantial progress in multidimensional poverty reduction.  

Ghana reduced its incidence of multidimensional poverty by nine percentage points from 55 

percent in 2011 to 46 percent in 2017. The intensity of poverty also reduced (from 54.2% in 2011 

to 51.7% in 2017), showing that the improvement is ‘pro-poor’. The MPI reduced by 0.062 from 

0.298 in 2011 to 0.236 in 2017.  The differences observed in the incidence and intensity of 

multidimensional poverty are statistically significant, indicating substantial progress in 

multidimensional poverty reduction over time in the country. We also observed statistically 

significant progress being made across all of the 12 indicators of multidimensional poverty among 

the poor except inadequate housing and school attendance.   



xi 

 

Based on our results, it is paramount that resources are allocated to the Health Sector (health 

insurance coverage and nutrition) and efforts coordinated to increase school attainment among the 

populace and reduce the number of school-age children that are not in school and their counterparts 

who are two or more years behind in school. Complementary policies should also be adopted to 

reduce the co-occurrence of multidimensional and consumption expenditure poverty in the 

country. Going forward, the Ghana 2020 Population and Housing Census will engender MPI 

analyses at the district/municipal and locality levels to inform specific and efficient allocation of 

resources.  



 

 

1 

 

CHAPTER ONE 

INTRODUCTION 

 

1.0 Background 

This report presents for the first time the results of Ghana’s official National Multidimensional 

Poverty Index (MPI). The purpose of Ghana’s National MPI is to have a measure to complement 

monetary poverty, enabling a more comprehensive understanding of the simultaneous deprivations 

faced by the poor and providing evidence for more targeted and efficient poverty reduction 

policies. As an official national statistic, it is owned by the people of Ghana and is, in its final 

structure, the result of a process led by the Ghana Statistical Service (GSS) and the Steering 

Committee, with representation from the Deutsche Gesellschaft für Internationale 

Zusammenarbeit (GIZ), United Nations Development Programme (UNDP), University of Cape 

Coast, University of  Development Studies, Oxford Poverty and Human Development Initiative 

(OPHI), National Development Planning Commission (NDPC), Local Government Authority and 

Ministry of Finance. Ghana’s National MPI was computed using data from the Ghana Living 

Standards Survey (GLSS) 2016/2017, a nationally-owned survey with context-specific variables 

which permits the measurement of multidimensional poverty in Ghana. In order to assess trends 

in multidimensional poverty over time, the report also draws on the 2011 and 2018 Ghana Multiple 

Indicator Cluster Surveys (MICS).  

Given Ghana’s history and its trajectory of social indicators, instituting a multidimensional poverty 

measure represents a natural progression in thought, policy analysis, and statistical application. 

This chapter serves as an introduction to Ghana’s first official national Multidimensional Poverty 

Index (MPI). It has the following sections: 

- Why Multidimensional Poverty? 

- The Purpose of Ghana’s MPI 

 

1.1 Why Multidimensional Poverty? 

Multidimensional poverty considers the many overlapping deprivations that poor people 

experience. People living in poverty often refer to lack of education, poor health and nutrition, 

ramshackle housing, and unsafe water as examples of their disadvantages to a meaningful standard 

of. These deprivations reflect the lived experiences of many poor people and the obstacles they 

face in pursuing and achieving valuable capabilities. The presence and shared experiences of 

multiple deprivations, therefore, motivate the urgency to focus on the Sustainable Development 

Goals (SDGs), especially Goal 1, which calls for an end to poverty in all its forms everywhere. 



2 

 

A Multidimensional Poverty Index (MPI) makes visible the joint distribution of deprivations, 

starting with a profile of each person’s simultaneous challenges, in order to measure non-monetary 

poverty. Overall, MPIs provide not only a headline figure, but also an associated information 

platform on national and subnational conditions across population groups and joint deprivations 

in different dimensions of poverty. The Oxford Poverty and Human Development Initiative 

(OPHI) at the University of Oxford and the United Nations Development Programme’s Human 

Development Report Office (HDRO) jointly compute and publish a global MPI that compares 

acute multidimensional poverty across more than 100 countries. However, this measure is intended 

for international comparability and is not adapted for the specific circumstances of a given country. 

Thus, many countries have developed their own national MPIs, in much the same way that they 

use national monetary poverty lines as well as the $1.90/day measure. 

National MPIs are increasingly being adopted as official permanent poverty statistics, which 

provide a more detailed exposition of the various dimensions of people’s living standards to 

complement monetary poverty statistics. These MPIs are tailored to the particular contexts and 

priorities of the country and reflect national understandings of poverty. Updated regularly, national 

MPIs are used to shape and energize effective policy actions. They are also reported against SDG 

Indicator 1.2.2 – to reduce, by 2030, the proportion of men, women and children of all ages living 

in poverty in all its dimensions according to national definitions. 

In Ghana, poverty has been measured using a monetary metric up until now. For the first time, 

Ghana’s National MPI captures the overlapping deprivations experienced by poor people in the 

country, using 12 non-monetary indicators across the three dimensions - education, health, and 

living standards. Given the importance of other non-monetary dimensions in the understanding 

and alleviation of poverty, the Ghana National MPI is a powerful tool for both poverty analysts 

and policymakers. It allows social planners to target those who are most affected by multiple 

disadvantages simultaneously and enables concerted policy-efforts across sectors and departments. 

 

1.2 Purpose of Ghana’s MPI 

The purpose of Ghana’s National MPI is to monitor key simultaneous disadvantages that affect 

multidimensionally poor people. The indicators constituting Ghana’s MPI reflect national 

priorities. Ghana’s MPI will be used to monitor and evaluate progress across a set of interlinked 

and policy-responsive Sustainable Development Goals and targets that are of recognised national 

and global importance. Detailed MPI analysis, such as that presented in this report, will be used to 

support more effective integrated and multi-sectoral policies at both national and regional levels, 

including budget allocation and targeting. Analysis of MPI by region, age cohort, and other 

characteristics would help identify the poorest groups and specific areas of deprivation to ensure 

effective prioritisation and inclusion of all disadvantaged people. 

 



3 

 

CHAPTER TWO 

METHODOLOGY AND DATA 

 

This chapter presents how multidimensional measures are constructed, a description of the data 

used in this report, and an explanation of the structure of Ghana’s national MPI. It has three 

sections which are Alkire-Foster Method, Data and Structure of the Measure. 

 

2.1 Alkire-Foster Method 

The Ghana national MPI and all results presented in this report are calculated using the Alkire-

Foster (AF) method for multidimensional poverty measurement. The AF method allows for the 

construction of individual and household level deprivation profiles that can then be used to identify 

multidimensionally poor people. It first identifies who is poor, by summing up the deprivations 

each person experiences in a weighted deprivation score, and then aggregates this information into 

a headline and associated information platform for a given population. This methodology for 

multidimensional poverty measurement has come to be widely used because of its simple, yet 

specific approach. There are three key features for any MPI: 

• Incidence or headcount ratio (H) which is the proportion of the population who are 

multidimensionally poor. 

• Intensity (A) is the share of weighted indicators multidimensionally poor people are 

deprived in on average. 

• MPI or adjusted headcount ratio is the multidimensional poverty index, which is the 

product of incidence and intensity (MPI = H × A). 

The MPI can be equivalently computed as the weighted sum of censored headcount ratios – which 

shows the percentage of people who are identified as poor and are also deprived in an indicator. 

The MPI is always broken down by indicator to show the composition of multidimensional 

poverty. This feature of dimensional detail brings added policy relevance to the analysis. In 

addition, the MPI can be disaggregated by different population groups, such as, urban/rural areas, 

age groups, and subnational regions. 



4 

 

 
 

The AF method allows for the structure of an MPI - dimensions, indicators, weights, and cut offs 

to be adapted to the specific purposes and contexts. The structure of Ghana’s National MPI is 

presented below. 

HOW TO INTERPRET THE MPI 

IS THE MPI JUST ONE NUMBER? Sometimes people presume that the MPI is “just” an index – a 

single number – showing the level of poverty. However, the MPI is much more than that. It unfolds into an 

associated information platform of sub-indices. Below is an example of the information contained in the 

MPI and its information platform. 

 

INCIDENCE (WHO IS POOR): This is perhaps, the most familiar number: the percentage of people who 

are MPI poor? This is called the headcount ratio, incidence of poverty, or poverty rate. 

 

DISAGGREGATION: Additionally, the MPI is disaggregated – by age group, location (urban/rural), 

and (data permitting) by subnational regions or districts – to examine poverty variations within a society. 

 

INTENSITY (HOW POOR ARE THEY?): This is the average deprivation score among the poor or the 

average share of deprivations that poor people experience. 

 

Prevalence of deprivation (HOW THEY ARE POOR): The censored headcount ratio of an 

indicator is the percentage of the total population – or one of its subsets – who are MPI poor and deprived 

in that particular indicator. The MPI is the weighted sum of the censored headcount ratios. What this means 

is that a decrease in any deprivation of any poor person will decrease poverty as measured by the MPI. It is 

important to note that the censored headcount ratios only count a deprivation when the person who 

experiences it is also multidimensionally poor. The uncensored headcount ratio of an indicator is the 

percentage all people – poor and non-poor – who are deprived in that particular indicator. 

 

COMPOSITION OF POVERTY: The percentage contribution of an indicator shows how much 

it contributes to the overall MPI of a given population. It depends on both the censored headcount ratio 

and the weight of that indicator. Using this measure – often visualised as a striped bar – we can immediately 

compare the indicators that most contribute to the MPI for different population groups within the country. 

 

THE MPI (Adjusted Headcount Ratio): This is the product of incidence and intensity. It shows the 

share of possible deprivations that poor people experience. MPI ranges from zero to one, and a higher 

number signifies greater multidimensional poverty. 

 

HOW TO REDUCE THE MPI: Because the MPI is made up of two sub-indices – incidence and intensity 

– it goes down if either of these decreases. So, if a poor person becomes non-poor, the MPI will decline. 

And if a poor person becomes non-deprived in an indicator in which they were previously deprived, the 

MPI will also fall. Put simply, if any deprivation of any poor person is removed, then the MPI always reduces. 

The MPI thus tracks not just movement over the poverty line but also improvements among the poor, thus, 

providing an ideal reference point and an impetus for monitoring interventionist policies that target the 

poorest of the poor. 



5 

 

2.2 Data 

Ghana’s National MPI is designed to facilitate its computation from as many data sources as 

possible to enable regular (annual or biennial) updates that can be used for continuous policy 

evaluation and improvement. This report draws on data from the seventh round of the Ghana 

Living Standards Survey (GLSS), a household survey, representative at the national level and for 

each of Ghana’s ten subnational regions. The GLSS is one of the country’s most important tools 

to inform national policies on poverty reduction and for the country’s monetary poverty 

measurement.  

In addition to providing Ghana’s National MPI results for 2016/17, which are computed from the 

GLSS data, this report also presents results for trends in multidimensional poverty in Ghana. For 

intertemporal comparability, the trend analyses have been computed using data from the 2011 and 

2017/18 rounds of the Multiple Indicator Cluster Survey (MICS), an international household 

survey developed by UNICEF. Data from the 2011 and 2017/18 rounds of the Multiple Indicator 

Cluster Survey (MICS), an international household survey developed by UNICEF, were used for 

the trend analysis to enable an intertemporal comparison of multidimensional poverty. 

The fieldwork for the 2016/17 round of GLSS was conducted by the Ghana Statistical Service over 

a period of 12 months, from October 2016 to October 2017, and gathered information from 14,009 

households and 59,864 individuals. It was the first round of the GLSS to collect anthropometric 

data, though this exercise is expected to constitute a regular component of subsequent rounds. 

MICS 2011 and MICS 2017/18 were also carried out by the Ghana Statistical Service, from 

September-December 2011 and October 2017-January 2018, respectively. MICS 2011 

interviewed 11,925 households, 10,627 women aged 15-49; 7,550 children below the age of 5; and 

3,321 men aged 15-59; MICS 2017/18 interviewed 12,886 households; 14,374 women aged 15-

49; 8,870 children below the age of 5; 323 men aged 15-49, and 8,946 children aged 5-17.  

 

2.3  Structure of the Measure 

Ghana´s National MPI has three dimensions – health, education and living standards – and 12 

indicators. It uses the same dimensions as the global MPI produced by OPHI and UNDP but adjusts 

the indicators to better reflect the specific context and priorities of the country. 

 

2.3.1 Unit of Identification and Analysis 

The unit of identification refers to the entity that is identified as poor or non-poor – usually the 

individual or the household. In the case of Ghana’s MPI, the unit of identification is the household, 

which considers information of all household members. This acknowledges intra-household caring 

and sharing – for example, educated household members reading for other members or multiple 



6 

 

household members being affected by a child’s malnutrition. In addition, it allows the measure to 

include indicators that are specific to certain age groups (for instance, school attendance).  

The unit of analysis which refers to how the results are reported and analysed is the individual 

person. It forms the basis of the analysis and subsequently informs the reporting of results, as is 

customary for monetary poverty statistics. This means that, for instance, the headcount ratio is the 

percentage of people who are identified as poor. 

 

2.3.2  Dimensions, Indicators and Deprivation Cut-offs 

Ghana’s MPI employs the three dimensions of the global MPI. The choice of indicators reflects 

the country’s context within data constraints. The selection of dimensions, indicators, and cut-offs 

was determined through a consultative process of the Steering Committee, drawing on expertise 

from many different sectors and reflecting national plans and priorities.  The living standards 

indicators are largely similar to the global MPI, with the addition of an indicator on overcrowding.  

The overcrowding indicator captures households with a large number of people per sleeping room, 

following the UN-Habitat guidelines. The cooking fuel indicator is intended to highlight the type 

of fuel and cooking space used, which is linked to the quality of ventilation and respiratory health. 

The water indicator is based on SDG 6 and the global MPI indicator for drinking water. The assets 

indicator measures asset ownership, which is indicative of improvement in living standards. The 

deprivation cut-off (Table 2.1) is similar to that of the global MPI. The housing indicator measures 

the quality of materials used in the flooring and walls of the house. The cut-off is also similar to 

the global MPI except that it does not consider roofing materials, as these are not as relevant for 

identifying poverty in Ghana. The electricity indicator captures households without access to 

electricity. The sanitation indicator is similar to that of the global MPI and is intended to measure 

households with inadequate toilet facilities. 

The education dimension has three indicators: school attendance, school attainment, and school 

lag. School attendance measures households in which a school-age child is not attending school. 

School attainment captures households in which no member has received an educational 

qualification, equivalent to completing at least basic education. The school lag variable captures 

pupils who are two or more years behind the grade they should be in, based on their age. 

The health dimension has two indicators: nutrition and health insurance. The nutrition indicator 

measures children under 5 years old who are underweight or stunted. The health insurance 

indicator measures households in which any member is not covered by the national health 

insurance scheme. Members of the household may be registered with the health insurance scheme, 

but the indicator measures the coverage of the scheme. 

  



7 

 

Table 2.1:  Ghana’s national MPI – indicators, deprivation cut-offs and weights 

Dimension Indicator Deprivation cut-off definition  Weight 

Living 

Standards 

Cooking fuel Deprived if household uses solid fuels and cooking is 

not done outside the house or in the open/ or cooking is 

undertaken in enclosed spaces 

1/21 

Water Deprived if a household’s drinking water is from an 

unclean source (tanker supply/vendor provided; 

unprotected well; unprotected spring; river/stream; 

dugout/pond/lake/dam/canal; other) or a round trip 

distance to collect water takes 30 minutes or more 

1/21 

Assets Deprived if household does not have more than one 

small asset (radio, TV, telephone, bike, motorbike, 

refrigerator, or computer) and does not own a car 

1/21 

Housing Deprived if household uses inadequate flooring 

(earth/mud, other) or walls (earth/mud, palm 

leaves/thatch (grass/raffia), other) 

1/21 

Overcrowding Deprived if household has more than 3 people per 

sleeping room, on average 

1/21 

Electricity Deprived if household does not have electric power 1/21 

Sanitation Deprived if household has no toilet facilities, uses 

bucket/pan, public toilet, shared toilet outside the 

house, other 

1/21 

Education School 

attendance 

Deprived if any school-age child (4-15years) in the 

household is not attending school 

1/9 

School 

attainment 

Deprived if no household member has received an 

educational qualification 

1/9 

School lag Deprived if household has any member who is 2 or 

more years behind in school  

1/9 

Health Nutrition Deprived if household has any child under 5 who is 

undernourished (underweight or stunted) 

1/6 

Health 

insurance 

Deprived if anyone in the household is not covered by 

the national health insurance scheme 

1/6 

Note for Table 2.1: 

a. Children are considered malnourished if their z-score of weight-for-age is below minus two standard 

deviations from the median of the reference population. 

 

A household suffers in bearing the medical bills if a single member is not covered. The global MPI 

uses an indicator on child mortality, but this was not considered useful for the Ghana National MPI 



8 

 

because the GLSS has a shorter recall period, so only captures deaths in the twelve months prior 

to the interview.  

Although it remains a crucial issue for human development, child mortality rates have been 

declining in Ghana over the years. However, affordability is a crucial factor for accessing health 

care services and is vital for ensuring a higher probability of survival. Currently, ill or injured 

people are not consulting a doctor as in previous years and since 2005, there has been a continual 

decline in those who consulted a chemist or pharmacist (GSS, 2018). The foregoing justifies the 

essence of the ‘affordability factor’ and the implementation of a national health insurance scheme 

which ensures that people can access minimum health care services despite their economic 

background. Hence, the health insurance indicator is currently a critical measure of 

multidimensional poverty in Ghana. 

 

Figure 2.1:  National uncensored headcount ratios, 2017 

 
 

Figure 2.1 shows the level of deprivations in each of the twelve MPI indicators in 2016/17. The 

‘uncensored headcount ratio’ of each indicator represents the proportion of the total population of 

Ghana who are deprived in that particular indicator, irrespective of their poverty status. The highest 

deprivations are engendered by sanitation (with 86.8% of the population deprived in this indicator) 

and health insurance (64.6%), with moderate deprivations recorded for housing (36.6%), 

overcrowding (35.4%), cooking fuel (31.5%) and school lag (30.2%). Low levels of deprivations 

were recorded for school attendance (16.1%), and nutrition (17.5%). 

 

 

 

19.8 22.4

36.6

18.1

35.4
31.5

86.8

16.1

28.0 30.2

17.5

64.6

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2.3.3 Weights and Deprivation Scores 

The weighting system adopted for Ghana’s MPI is the ‘nested weights’ approach, implying that 

each of the three dimensions is equally weighted—one-third of the total weight is assigned to 

education, health, and living standards—and each component indicator is equally weighted within 

its dimension. For each dimension, there is a possible variation in the number of indicators. 

Subsequently, indicators in the health dimension receive a weight of 1/6, each education indicator 

has a weight of 1/9, and the living standards indicators are given a weight of 1/21. Overall, the 

weights add up to 100 percent. The deprivation score is the sum of the weights of the indicators in 

which the person is deprived and shows the percentage of total possible deprivations that the 

person experiences. 

 

 2.3.4 Poverty Cut-off 

For Ghana’s MPI the cut-off is specified at one-third of the indicators; that is, a person whose 

deprivation constitute at least 33 percent of the weighted indicators is identified as 

multidimensionally poor. The chosen cut-off reflects the global MPI, which suggests that a person 

must be deprived in at least one full dimension’s worth of indicators to be considered 

multidimensionally poor. A person deprived in 20-33.3 percent of the weighted indicators is 

considered ‘vulnerable to poverty’ and a person deprived in at least 50 percent of the weighted 

indicators is identified as being in severe poverty.  

  



10 

 

CHAPTER THREE 

RESULTS AND DISCUSSIONS 

 

This chapter provides a detailed analysis of the national MPI results for Ghana using the seventh 

round of the Ghana Living Standards Survey conducted between 2016/2017. The chapter 

specifically presents results on the three main statistics of the MPI; namely, the headcount (H), 

intensity (A) and the adjusted headcount ratio (MPI). The results are presented nationally and 

across three main group variables; geographical groupings (residence, ecological zone and 

administrative regions), age groups and gender of household head. The percentage contributions 

of each indicator to MPI are also discussed. Finally, the incidence of multidimensional poverty is 

compared with the conventional money-metric consumption-based poverty. 

3.1 The Level of Multidimensional Poverty in Ghana 

Table 3.1 shows Ghana’s National MPI for 2017, as well as its partial indices: the incidence of 

poverty (the proportion of people identified as multidimensionally poor –H) and the intensity of 

poverty (the average proportion of weighted indicators in which the poor are deprived – A). The 

incidence of multidimensional poverty is 45.6 percent. This means that at least two out of every 

five Ghanaians are identified as multidimensionally poor. Based on the 95 percent confidence 

interval, the true multidimensional poverty headcount ratio is between 43.7 percent and 47.5 

percent of the population. 

The intensity of poverty, which reflects the share of deprivations each poor person experiences on 

average, is 51.7 percent. That is, each poor person is, on average, deprived in about 52 per-cent of 

the weighted indicators–implying that a multidimensionally poor person is deprived in six of the 

12 weighted indicators, on average. For example, a person may be deprived in two of the five 

education and health indicators, in addition to four living standards indicators. The National MPI, 

which is the product of the incidence and intensity of poverty, has a value of 0.236. This means 

that multidimensionally poor people in Ghana experience about 24 percent of the weighted 

deprivations out of the total possible deprivations that could be experienced.  

Table 3.1:  Incidence, intensity and multidimensional poverty Index (MPI), 2017 

Poverty cut-off (k) Index Value         95% Confidence interval  

 MPI 0.236 0.224 0.2485 

k-value=33% Headcount ratio (H, %) 45.6 43.7 47.5 

 Intensity (A, %) 51.7 51 52.5 

k=20% to 33.3% 
Percentage of population 

vulnerable to poverty  31.0 29.3 32.6 

k = 50% 
Percentage of population in 

severe poverty  21.4 19.7 23.0 

 



11 

 

The percentage of the population that are vulnerable to multidimensional poverty is 31 percent and 

21.4 percent of the population are considered to be in severe poverty.  

As previously discussed, the MPI is a composite index.  Hence, to determine the specific indicators 

contributing the most to deprivation, the index is examined at a disaggregated level. Figure 3.1 

presents the censored headcount ratio of each indicator used in the composite index. Each bar 

represents the share of the population that is multidimensionally poor and also deprived in that 

indicator. This implies that the MPI can also be calculated as the summation of the weighted 

censored headcount ratios. Figure 3.1 shows the contribution of individual indicators to 

multidimensional poverty. For policy purposes, it clearly depicts the indicators which engender 

the largest deprivation for poor people in Ghana and any effort -to reduce deprivation in the 

affected areas will lead to a fall in the MPI.  

Figure 3.1:  National censored headcount ratios, 2017 

 
 

The largest censored headcount ratio is found in the sanitation indicator (44.1%). About 40 percent 

of the population are multidimensionally poor and are not covered by any form of health insurance. 

Additionally, 27.5 percent are both multidimensionally poor and deprived in modern housing 

features (flooring and wall). However, it is evident that few people are multidimensionally poor 

and deprived in the ownership of small assets (13.2%). This share of the population does not have 

more than one small asset (radio, TV, telephone, bike, motorbike, refrigerator, or computer) and 

do not own a car. 

 

16.8 17.8

27.5

13.2

23.1

19.8

44.1

14.1

21.9
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15.5

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Electricity Water Housing Assets

Overcrowding Cooking fuel Sanitation School attendance

School Aattainment School lag Nutriction Health Insurance



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3.2 MPI across Large Area Aggregates 

To appreciate the disparities in the distribution of multidimensional poverty across Ghana, the 

profile disaggregated the levels of poverty by rural and urban areas, the three ecological zones, 

and the administrative regions of the country (Table 3.2). The incidence of multidimensional 

poverty in the rural area (64.6%) is more than twice that of the urban areas (27.0%) and accounts 

for 49.6 percent of the incidence and intensity of poverty of the population.  

Table 3.2:  Multidimensional poverty by rural/urban areas, 2017 

 

Figure 3.2 presents the levels of deprivation suggested by indicators depicting multidimensional 

poverty in rural and urban areas. From the figure, the largest differences are observed in the 

housing (42 percentage points), sanitation (37 percentage points) and health insurance (31 

percentage points) indicators. 

Figure 3.2:  Censored headcount ratios by urban and rural areas, 2017 

 

 

 

5.5 3.9
6.8 6.2

15.6

7.3

25.8

7.2
10.0

12.8
9.8

24.7
28.2

31.8

48.5

20.3

30.7 32.5

62.8

21.1

33.9 34.4

21.3

55.7

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Urban Rural

Area Population 

share (%) 

 

Value 

     MPI 

Confidence interval 

 

Value  

Incidence (%) 

Confidence interval 

 

Value 

Intensity (%) 

Confidence interval 

Rural 49.59 0.349 0.331 0.366 64.6 61.9 67.2 54.1 53.1 55.1 

Urban 50.41 0.124 0.113 0.136 27.0 24.7 29.2 46.3 45.4 47.1 

National 100 0.236 0.220 0.246 45.6 43.7 47.5 51.7 50.9 52.5 



13 

 

The percentage contribution of each indicator to the MPI within rural and urban areas is shown in 

Figure 3.3. The results suggest some minor differences in each indicator’s contribution to the MPI 

in these specific localities. For example, the indicators with the highest contribution to MPI in rural 

areas are health insurance (26.6%), school lag (10.9%), school attainment (10.8%) and nutrition 

(10.2%). In the urban areas, health insurance (33.0%) contributes the highest deprivation to the 

MPI, followed by nutrition (13.1%) and school lag (11.4%).  

Figure 3.3:  Percentage contribution of each indicator to rural and urban MPI 

 

Comparing the dimension of living standards between rural and urban areas, water contributes 1.5 

percent to MPI of urban areas and contributes more than a double (4.3%) to the MPI in the rural 

areas. A similar trend is observed with the contribution of the housing indicator.  

Table 3.3 shows the estimates for the National MPI, incidence of poverty, and intensity of poverty 

by ecological zone. The distribution suggests that the savannah zone has the highest level of MPI 

(0.403), incidence of poverty (70.9%) and intensity (56.8%), whiles the coastal zone registers the 

lowest levels of MPI (0.154), incidence (32.0%) and intensity (47.9%) of poverty. In all estimates, 

the analysis suggests an increasing trend in the distribution of the MPI, incidence and intensity of 

multidimensional poverty from the coastal to the savannah zones. The differences between 

ecological zones are statistically significant.  

  

2.1 3.9 3.4
1.5

4.3 3.62.6

6.6
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2.8
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6.0

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Table 3.3: Multidimensional poverty by ecological zones, 2017 

   MPI Incidence (H) (%) Intensity (A) (%) 

Ecological 

zone  

Population 

share (%) Value Conf. interval Value Conf. interval Value Conf. interval 

Coastal 29.5 0.154 0.138 0.169 32.0 29.1 35.0 47.9 46.8 49.0 

Forest  46.7 0.203 0.188 0.217 41.3 38.5 44.0 49.2 48.3 50.0 

Savannah  23.8 0.403 0.377 0.429 70.9 67.5 74.4 56.8 55.4 58.3 

National 100 0.240 0.220 0.250 45.6 43.7 47.5 51.7 50.9 52.5 

 

The levels of deprivation of all indicators are higher in the savannah compared to the remaining 

two ecological zones. However, deprivations are lower in almost all the indicators in the coastal 

zone except for school lag which is lowest in the forest zone. It can be deduced from Figure 3.4 

that the levels of deprivation in the coastal and forest zones are similar (no statistically significant 

differences), except in housing, water, electricity, cooking fuel, and sanitation. This is not the case 

when a comparison from the two zones are carried out with the savannah zone: statistically 

significant differences exists in all the indicators except for asset and overcrowding indicator.  

Figure 3.4: Censored headcount of indicators across ecological zones  

 

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The percentage contributions of each indicator to the MPI for each of the ecological zones (Figure 

3.5) reveal that health insurance, nutrition, and school lag are the indicators that contribute the 

most to the MPI in each of the zones. In the case of the coastal zone, the percentage contribution 

of water is the lowest, whereas the asset indicator provides the lowest contribution to the MPI in 

the forest and the savannah zones. 

Figure 3.5: Percentage contribution of each indicator to MPI for ecological zones, 2017 

 

3.3 Multidimensional Poverty by Region 

The regional distribution of incidence and intensity of poverty are presented in Table 3.4 and 

Figure 3.8. The incidence of multidimensional poverty is highest in the Northern region (80.8%). 

The broad pattern suggests that the Northern, Upper East and Upper West Regions have the highest 

levels of MPI and incidence and intensity of poverty. For these regions, the MPI is (0.491, 0.359 

and 0.348, respectively, while the Greater Accra and the Ashanti Regions registered the lowest 

levels of poverty (MPI of 0.102 and 0.147 respectively).  

2.1 3.3 4.12.0
3.2

4.82.6

5.2
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2.7

3.2

2.2

6.1

5.5
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9.4 8.2
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9.4

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11.6
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32.6 30.8
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Table 3.4: Regional distribution of incidence of poverty and intensity 

Region MPI 
Confidence 

Interval 

Headcount 

(%) 

Confidence 

Interval 

Intensity 

(%) 

Confidence 

Interval 

Western 0.235 0.203 0.267 47.6 42.2 53.1 49.4 47.7 51.1 

Central 0.239 0.211 0.267 47.6 42.5 52.7 50.1 48.8 51.5 

Greater Accra  0.102 0.083 0.121 22.5 18.5 26.4 45.5 43.9 47.1 

Volta 0.306 0.253 0.360 58.2 50.6 65.8 52.7 49.7 55.7 

Eastern 0.217 0.191 0.242 44.0 39.1 48.9 49.3 47.5 51.1 

Ashanti 0.147 0.125 0.170 31.1 26.5 35.6 47.5 46.1 48.9 

Brong Ahafo 0.255 0.222 0.288 49.4 44.1 54.7 51.6 49.7 53.5 

Northern 0.491 0.454 0.527 80.8 76.9 84.7 60.7 58.3 63.2 

Upper East  0.359 0.327 0.391 68.0 62.6 73.4 52.8 51.3 54.3 

Upper West 0.348 0.307 0.389 65.5 59.9 71.1 53.1 50.6 55.7 

 

Figure 3.6 presents the regional share of the population and the corresponding percentage of the 

poor in each region. With a population share of 18.5 percent, the Ashanti Region has 13 percent 

of the multidimensionally poor people in Ghana. The Northern Region has the largest proportion 

(17%) of the poor and has a population share of 9.3 percent. The lowest proportion of the poor 

lives in the Upper West region and the regions has a population share of 2.9 percent. 

 

Figure 3.6: Population share and composition of the poor per region 

 

 



17 

 

Figure 3.7: Spatial distribution of poverty incidence and poverty intensity by region 

 

Figure 3.7a: Spatial distribution of MPI by region 

 



18 

 

The distribution of percentage contribution of each indicator to the regional MPI reveals a similar 

pattern across all the ten regions. The pattern generally indicates that health insurance, nutrition, 

school attainment, school lag and sanitation are the indicators that contribute most to MPI in each 

of the ten regions. Alternatively, assets, electricity and water contribute less to the MPI across all 

the ten administrative regions.  

Figure 3.8: Percentage contribution of each indicator to the regional MPI 

 

3.4 MPI by Gender and Age of the Head of Household 

In Table 3.5, the MPI, incidence and intensity of poverty are shown for male and female headed 

households. The male headed households’ headcount ratio is about 7 percentage points higher than 

that of the female headed households. Similarly, the distribution shows clear evidence of male 

headed households being more multidimensionally poor than their female counterparts. However, 

it is worth noting that almost 71 percent of households in Ghana are headed by males.  

Table 3.5: Multidimensional poverty by gender, 2017 
 

Male Female 

Index Population 

share (%) 

 

Value 

Confidence 

Interval (95%) 

Population 

share (%) 

 

Value 

Confidence 

Interval (95%) 

MPI 
 

0.251 0.237 0.265 
 

0.199 0.186 0.212 

Incidence (H) 71% 47.7% 45.4% 49.9% 29% 40.6% 38.1% 43.2% 

Intensity (A) 
 

52.7% 51.7% 53.7% 
 

49.0% 48.2% 49.8% 

 

Figure 3.9 presents the MPI distribution for each indicator across the male and female headed 

households. For the female distribution, the sanitation indicator contributes the most to 

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deprivation, followed by health insurance. However, for the male distribution, there is no clear-cut 

difference between sanitation and insurance due to their overlapping confidence intervals.  

Figure 3.9: Censored headcount ratios by gender of the household head, 2017 

 

 

School attainment is equal for both gendered headed households, while female headed households 

seem to be less deprived in all other indicators, except for assets where male headed households 

are extremely less deprived than their female counterparts. 

 

3.5 MPI by Age Decomposition 

This section presents analysis of multidimensional poverty across age categories. As suggested by 

Figure 3.10, multidimensional poverty is prevalent among children under 15 years, with an MPI 

of 0.307. The outcome may appear contrary to the belief that the risk of poverty is prevalent among 

the elderly. The results suggest that households without a child are likely to be less poor.  

0

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Figure 3.10: Multidimensional poverty by age groups 

 
 

The elderly (persons aged 65+) are the least poor with an MPI of 0.158 while the working age 

category (persons aged 35-64 years) also have a relatively low MPI of 0.189. Undoubtedly, the 

result shows that children are mostly affected by multidimensional poverty. 

It is very useful to have the MPI broken down across indicators for policy intervention. This 

disaggregation shows that children are deprived most in access to health insurance (27.1%), 

Nutrition (12.4%), School lag (10.8%) and school attainment (10.5%). As indicated by Figure 

3.11, children additionally experience more deprivation in overcrowding (5.1%) compared to the 

youth (15-34 years), the adult (35-64 years) and the aged (65+ years). The three upper categories 

have a deprivation rate of 4.4 percent, 4.3 percent and 2.5 percent respectively. Access to health 

insurance remains the most deprived indicator across all the age categories. The aged are the most 

deprived in sanitation facility (9.6%). There is the need to review the type of sanitation facilities 

available to the aged.  

0.307

0.204
0.189

0.158

M
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0-14  15-34  35-64  65+



21 

 

Figure 3.11:  Percentage contribution of indicators across age groups 

  
 

3.6 Monetary Poverty vs Multidimensional Poverty  

Given that monetary poverty assessment using consumption expenditure has been the conventional 

measure of poverty in Ghana, it is crucial to compare the two measures in this contextual analysis. 

This section presents the comparisons of the distributions and patterns of the MPI with 

consumption expenditure poverty estimates at different levels of disaggregation. The analyses are 

conducted at two levels. First, the national overview indicates how the two measures intersect. The 

second focuses on the broader area aggregates (rural, urban, ecological zones), and the 

administrative regions of the country. Figure 3.12 indicates that the national incidence of 

multidimensional poverty of 45.6 percent is almost twice the national incidence of consumption 

expenditure poverty of 23.4 percent. It is interesting to note from Figure 3.13 that 19.3 percent of 

Ghanaians are concurrently poor in both measures of poverty. Figure 3.14 compares the levels of 

multidimensional and monetary poverty across large area aggregates of the country. The figure 

shows substantial differences in the levels of the two measures of poverty. As indicated by the 

error bars, the differences are statistically significant across all the areas. 

3.2 3.3 3.8 5.1
3.4 3.6 3.8 4.95.4 5.5 5.8

7.02.5 2.7 2.8
4.4

5.1 4.4 4.3
2.53.8 4.2 4.3
4.48.6 9.2 9.2
9.6

7.3 5.8 6.2
5.9

10.5 9.4 10.5

13.7
10.8 11.2

11.5

11.6
12.4

10.4
9.1

6.3

27.1 30.4 28.9
24.8

0-14 15-34 35-64 65+

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Electricity Water Housing Assets

Overcrowding Cooking fuel Sanitation School Attendance

School Attainment School Lag Nutrition Health insurance



22 

 

Figure 3.12: Comparison between monetary and non-monetary poverty 

 

 

Figure 3.13: MPI and monetary poverty across area aggregates  

 

 

The comparison of the two measures of poverty across administrative regions depicts broader 

similarities in the general pattern of poverty, albeit with some notable differences. For instance, 

both poverty measures suggest that Northern, Upper East and Upper West Regions have the 

19. 27 %4.1%

26.34 %

Monetary (23.38 %) MPI (45.61 %)

Total Population

Non-Poor=50.29 %

64.6

26.9
32.1

41.3

70.9

45.6

39.6

7.4 9.8
15.4

55.9

23.4

Rural Urban Coastal Forest Savannah National

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23 

 

highest poverty levels, followed by the Volta and Brong-Ahafo Regions. Greater Accra and 

Ashanti Regions also registered the least poverty levels using the two approaches. However, using 

the MPI, the Northern region is the poorest, while by monetary poverty, the poorest region is the 

Upper West. Additionally, while the income-based measure illustrates that the Central Region has 

a lower level of poverty compared to the Western Region, the MPI index suggests that the two 

regions have the same levels of multidimensional poverty. Overall, the monetary and non-

monetary measures indicate that there are substantial differences in the regional levels of poverty 

with multidimensional poverty being generally higher than the income measure. The error bars 

indicate statistically significant differences among eight regions of the country except for Upper 

East and Upper West Regions. 

The spatial distribution of the population that experience conjoined poverty are also shown in 

Figure 3.15. As expected, regions with higher incidence of both measures of poverty recorded 

higher incidence of the double burden of monetary and multidimensional poverty.  

The Northern Region has the highest proportion of population that are jointly poor (57.7%) and 

followed by the Upper East Region (54.3%). 

 

Figure 3.14: Multidimensional and monetary poverty across administrative regions 

 

 

 

 

0

10

20

30

40

50

60

70

80

90

100

Western Central Greater
Accra

Volta Eastern Ashanti Brong
Ahafo

Northern Upper
East

Upper
West

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Figure 3.15: Distribution of double burden of poverty by region 

 

 

  



25 

 

CHAPTER FOUR 

REGIONAL ANALYSES 

 

This chapter examines the regional distribution of multidimensional poverty in Ghana.  

4.1 Western Region 

Western Region has an MPI of 0.235 which is almost the national MPI of 0.236. and approximately 

48 percent of the population are multidimensionally poor. However, the incidence of 

multidimensional poverty is 2.0 percentage points more than the national value. The intensity of 

poverty in the region is about 49.4 percent implying that the population identified to be 

multidimensionally poor is deprived, on average, in 49.4 percent of the weighted indicators. This 

is about 2.3 percent lower than the national percentage. The Western region is the fourth most 

populated region in the country with 10.3 percent of the population, following the Ashanti (18.5%), 

Greater Accra (16.5%), and Eastern (10.8%) regions. Approximately 1.51 million MPI poor people 

reside in the region. This represents 10.7 percent of all MPI poor people in Ghana. 

Table 4.1: MPI, headcount ratio and intensity - Western Region 

Region MPI Incidence (%) Intensity (%) 

National 0.236 45.6 51.7 

Western 0.235 47.6 49.4 

Central 0.239 47.6 50.1 

Greater Accra  0.102 22.5 45.5 

Volta 0.306 58.2 52.7 

Eastern 0.217 44.0 49.3 

Ashanti 0.147 31.1 47.5 

Brong Ahafo 0.255 49.4 51.6 

Northern 0.491 80.8 60.7 

Upper East  0.359 68.1 52.8 

Upper West 0.348 65.5 53.1 

 

The insurance indicator (31.4%) contributes the most to multidimensional poverty in the Western 

Region. Although health insurance is the largest contributor to deprivation at the national level, it 

contributes more to poverty in the Western Region. The indicator is weighted at 1/6 of the measure 

but is responsible for about 31percent of the total MPI for the region, which is almost twice its 

weight. Other indicators with high contributions to poverty in the region include school lag (11%), 

school attainment (9.2%), sanitation (9.1%) and nutrition (7.9%). Electricity contributes the least 

to the MPI in the Western Region with 2.7 percent. This is followed by assets (2.9%) and water 

(3.4%). From a descending order, school lag, nutrition, school attendance, housing, water and 

electricity contribute more to the national MPI compared to their corresponding contribution to the 

region’s MPI.  



26 

 

Between 2011 and 2017, the proportion of MPI poor people in the Western Region reduced by 

11.2 percentage points, from 58.8 percent in 2011 to 47.6 percent in 2017. This reduction is 

statistically significant at 1 percent level. Using 2020 projected regional population figure, the 

decline represents an exit from poverty for nearly a third of a million people from the Western 

Region. There is also a statistically significant decrease in the MPI, as well as a statistically 

significant fall in the intensity of poverty. 

Figure 4.1: Percentage contribution by indicator - Western Region 

  

There was a statistically significant improvement in indicators such as electricity, water, cooking 

fuel, sanitation, school attainment, school lag, nutrition and health insurance between 2011 and 

2017. The greatest improvement was in electricity, which suggests that the percentage of poor 

people who lacked electricity reduced by more than 24 percentage points. However, the same 

period recorded a worsening of deprivation in housing, with the percentage of people who were 

deprived increasing by almost 3 percentage points, although not significant. Despite the general 

improvement in the reduction in multidimensional poverty in the Western Region, more needs to 

be done to reduce further, the millions of people in the region who are MPI poor.  

 

 

2.7 3.4
3.4 3.6
5.2 5.5
2.9 2.7
5.0 4.7

6.3 4.0

9.1
8.9

5.8 6.6

9.2 10.3

11.0 11.1

7.9 11.0

31.4 28.3

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

Western National

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4.2 Central Region 

Similar to the Western region, the MPI for the Central Region is also close to that of the National 

MPI. The headcount ratio of multidimensional poverty, however, is just 0.01percent less than that 

of the Western Region but 2 percent more than the national rate. With a headcount ratio of 47.6 

percent, the Central Region has approximately 48 percent of its population being 

multidimensionally poor. The intensity of poverty (50.14%) in the region is slightly less than the 

national level (51.74%) and exceeds that of the Western Region (49.4%) by just 0.74 percent. The 

intensity implies that those who are multidimensionally poor in the Central Region are deprived, 

on average, in 49.4 percent of the weighted indicators. The population share of the Central Region 

to the total population is 8.9 percent. According to the headcount ratio, about 1.24 million MPI 

poor people reside in the region. This represents about 8.8 percent of all the MPI poor people in 

Ghana. 

In the Central Region, insurance (30.9%) contributes the most to the MPI. This is close to thrice 

the contribution of the next most deprived indicator, nutrition. Nutrition contributes 11.8 percent 

to MPI in the region, closely followed by school lag (11.5%). Other indicators that contribute 

moderately to MPI include sanitation (9.0%), school attainment (8.7%), overcrowding (6.2%) and 

school attendance (5.3%). Similar to the Western Region, electricity (2.2%) contributes the least 

to the region’s MPI. This is followed by access to potable water (2.4%) and assets (3.0%). 

Compared to the national figures, insurance, nutrition, school lag, overcrowding, cooking fuel and 

assets have relatively higher contributions to the Central Region’s MPI than to the national MPI.  

Between 2011 and 2017, the proportion of MPI poor people in the Central Region reduced by 9.3 

percentage points, from 56.9 percent in 2011 to 47.6 percent in 2017. This reduction is statistically 

significant at 1 percent level. Using 2020 projected regional population figure, approximately a 

quarter of a million people escaped poverty in the region.  

Table 4.2: MPI, headcount ratio and intensity - Central Region 

Region MPI Incidence (%) Intensity (%) 

National 0.236 45.6 51.7 

Western 0.235 47.6 49.4 

Central 0.239 47.6 50.1 

Greater Accra  0.102 22.5 45.5 

Volta 0.306 58.2 52.7 

Eastern 0.217 44.0 49.3 

Ashanti 0.147 31.1 47.5 

Brong Ahafo 0.255 49.4 51.6 

Northern 0.491 80.8 60.7 

Upper East  0.359 68.1 52.8 

Upper West 0.348 65.5 53.1 

 



28 

 

There was a statistically significant decrease in the MPI by 5.1 percentage points while the 

intensity of poverty fell by 0.8 percentage points. The decline, however, was not statistically 

significant. A number of indicators suggest some statistically significant improvement over the 

period. These include: electricity, water, assets, cooking fuel, sanitation, school attainment, school 

lag and health insurance. The cooking fuel indicator had the highest significant decrease by almost 

16 percentage points. This is followed by electricity and water which have 14.5 and 13.1 

percentage points decrease in deprivation. Housing, school attendance and nutrition, had an 

increase in the number of people who were deprived in these indicators. However, only housing 

was statistically significant with a 10.6 percentage points increase in deprivation.  

Figure 4.2: Percentage contribution by indicator - Central Region 

  

4.3 Greater Accra Region 

With an MPI of 0.102, 10.2 percent the regional capital of Ghana has the lowest MPI of all the 

regions in Ghana. The figure is also much lower than the national MPI of 0.236. The headcount 

ratio of multidimensional poverty in the Greater Accra Region is 22.5 percent implying that about 

23 percent of the region’s population is multidimensionally poor. This is also well below the 

national headcount ratio of 45.6 percent and lower than all other regions. The intensity of poverty 

in the region is 45.5 percent, meaning that those who have been identified as multidimensionally 

poor are deprived, on average, in 45.5 percent of the weighted indicators. The region’s intensity 

of poverty is the lowest among all regions and also lower than the national figure. The Greater 

Accra region has the second largest population share (16.5%) after the Ashanti region (18.5%). It 

2.2 3.4
2.3 3.64.5

5.53.31
2.666.1
4.7

4.2 4.0

9.0 8.9

5.3 6.6

8.7
10.3

11.5
11.1

11.8
11.0

30.9 28.3

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30%

40%

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80%

90%

100%

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is estimated that more than 1.14 million MPI poor people live in the Greater Accra region, which 

represents about 8 percent of all MPI poor people in Ghana. 

Similar to its high contribution to deprivations in the previous regions, insurance continues to be 

the indicator that contributes most to the MPI in the Greater Accra Region (35.5%). This 

contribution is much greater than the national estimate of 28.3 percent. Nutrition (16.4%) 

constitutes a little under half of the contribution by the insurance indicator. The nutritional 

deprivation of the region is also greater than its national contribution. Other moderate contributors 

to the region’s MPI include sanitation (9.7%), school lag (9.3%), school attainment (8.2%), school 

attendance (7.9%) and overcrowding (7%). Housing (0.6%) contributes the least to the region’s 

MPI followed by access to potable water (0.8%).  

Table 4.3: MPI, headcount ratio and intensity - Greater Accra Region 

Region MPI Incidence (%) Intensity (%) 

National 0.236 45.6 51.7 

Western 0.235 47.6 49.4 

Central 0.239 47.6 50.1 

Greater Accra  0.102 22.5 45.5 

Volta 0.306 58.2 52.7 

Eastern 0.217 44.0 49.3 

Ashanti 0.147 31.1 47.5 

Brong Ahafo 0.255 49.4 51.6 

Northern 0.491 80.8 60.7 

Upper East  0.359 68.1 52.8 

Upper West 0.348 65.5 53.1 

 

The Greater Accra region experienced 4.7 percentage points fall in MPI poor people from 27.2 

percent to 22.5 percent between 2011 and 2017. However, the decline was statistically 

insignificant. This 4.7 percentage points fall represents about 238,000 people in the region who 

have been lifted out of poverty. The MPI also decreased by just 2.2 percentage points while the 

intensity of poverty also decreased by 0.3 percentage points. These were however statistically 

insignificant. 

Over the six-year period (2011-2017), there has been a statistically significant improvement in 

deprivation indicators such as electricity, assets, cooking fuel, school attainment, and school lag 

in the Greater Accra region.  Of these, the cooking fuel indicator recorded the highest improvement 

with the percentage of poor people who use solid fuels in enclosed spaces reducing by 8.2 

percentage points. School attendance is the only indicator which suggests a statistically significant 

increase. Thus, between 2011 and 2017 school attendance worsened by close to 3.6 percentage 

points. 



30 

 

Figure 4.3: Percentage contribution by indicator - Greater Accra 

  

 

4.4 Volta Region 

The Volta Region is one of the four regions with an MPI greater than the national MPI. The MPI 

for the region is 0.306 which is about 0.07 percent above the national MPI. The headcount ratio of 

multidimensional poverty in the Volta Region is 58.2 percent. This implies that 58.2 percent of the 

region’s population is multidimensionally poor.  The figure exceeds the national and Greater Accra 

rates by about 12.6 percent and 35.7 percent respectively. The intensity of poverty in the region is 

52.7 percent, which means that those who were identified to be multidimensionally poor are 

deprived, on average, in six of the 12 weighted indicators. With a population share of 8.9 percent, 

there are about 1.6 million inhabitants who are multidimensionally poor. This represents about 11 

percent of all MPI poor people in Ghana.  

The indicator with the highest contribution to the region’s MPI is health insurance (27.8%). Other 

indicators contributing significantly to the region’s MPI include nutrition (11.5%), school lag 

(11.2%), school attainment (9.2%), sanitation (8.9%) and school attendance (7.1%). The least 

contributing indicator is assets (2.7%). Electricity (3.3%), cooking fuel (3.7%) and overcrowding 

(3.7%) also contribute relatively little to the regions MPI. The contribution of health insurance to 

1.6 3.40.8
3.6

0.6 5.51.9

2.7

7.0

4.7

1.1

4.0
9.7

8.97.9

6.68.2

10.39.3

11.116.4

11.0

35.5
28.3

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50%

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the region’s MPI (27.7%) is relatively lower than its contribution to the national MPI (28.3%), 

although, only less than a percentage (0.54%) difference. Other indicators that contribute less to 

the region’s MPI than to the national MPI include school attainment (9.2%), cooking fuel (3.7%), 

overcrowding (3.73%) and electricity (3.3%)  

Although not statistically significant, the proportion of MPI poor people in the Volta Region 

reduced by 6.8 percentage points, from 65 percent in 2011 to 58.2 percent in 2017. This represents 

an escape from poverty for about 183,000 people in the Volta region. The MPI and intensity of 

poverty fell by 4.0 and 0.6 percentage points respectively and these were however statistically 

insignificant. 

Table 4.4: MPI, headcount ratio and intensity - Volta Region 

Region MPI Incidence (%) Intensity (%) 

National 0.236 45.6 51.7 

Western 0.235 47.6 49.4 

Central 0.239 47.6 50.1 

Greater Accra  0.102 22.5 45.5 

Volta 0.306 58.2 52.7 

Eastern 0.217 44.0 49.3 

Ashanti 0.147 31.1 47.5 

Brong Ahafo 0.255 49.4 51.6 

Northern 0.491 80.8 60.7 

Upper East  0.359 68.1 52.8 

Upper West 0.348 65.5 53.1 

 

Similar to other regions, not all indicators saw an improvement in deprivation. The indicators that 

improved and were also statistically significant included electricity, water, assets, cooking fuel and 

school attainment. The greatest improvement was in electricity in which the percentage of poor 

people who lack electricity was reduced by about 20.6 percentage points. School attainment and 

cooking fuel also had reductions of 14.7 and 14.1 percentage points respectively. Indicators such 

as housing, school attendance and nutrition worsened, thus increasing the percentage of poor 

people in these indicators in the Volta Region. However, these were not significant. 



32 

 

Figure 4.4: Percentage contribution by indicator - Volta Region 

  

 

4.5 Eastern Region 

The Eastern Region has an MPI estimate of 0.217 which is about 0.019 points below the National 

MPI. The headcount ratio of multidimensional poverty is almost 44 percent in the region, meaning 

that at least two out of five people in the Eastern Region are multidimensionally poor. This is also 

a little below the national headcount ratio of multidimensional poverty of 45.6 percent. The 

intensity of poverty in the region is about 49.3 percent. This implies that among those who have 

been identified as multidimensionally poor in the region are deprived, on average, in 49.3 percent 

of the weighted indicators. This is also below the national rate of 51.7 percent. As the third 

populous region in the country, the Eastern Region has a population share of 10.8 percent. It is 

estimated that close to 1.46 million MPI poor people live in the region, which represents about 

10.3 percent of the multidimensionally poor in Ghana. 

Similar to other regions and following the national trend, insurance remains the indicator with the 

most contribution to the region’s MPI. It contributes approximately 29.2 percent to the region’s 

MPI. Other indicators that contribute relatively more to the region’s MPI include school lag 

(11.6%), school attainment (9.2%), nutrition (8.3%), housing (5.4%) and overcrowding (5.3%). 

However, assets contributed the least to the region’s MPI with a value close to 3.4 percent.  

3.27 3.38
4.3 3.6

6.7 5.5

2.7 2.7
3.7 4.7
3.7 4.0

8.9 8.9

7.1 6.6

9.2 10.3

11.2 11.1

11.5 11.0

27.8 28.3

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Volta National

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Table 4.5: MPI, headcount ratio and intensity - Eastern Region 

Region MPI Incidence (%) Intensity (%) 

National 0.236 45.6 51.7 

Western 0.235 47.6 49.4 

Central 0.239 47.6 50.1 

Greater Accra  0.102 22.5 45.5 

Volta 0.306 58.2 52.7 

Eastern 0.217 44.0 49.3 

Ashanti 0.147 31.1 47.5 

Brong Ahafo 0.255 49.4 51.6 

Northern 0.491 80.8 60.7 

Upper East  0.359 68.1 52.8 

Upper West 0.348 65.5 53.1 

 

Between 2011 and 2017, the proportion of MPI poor people in the region reduced by 5.4 

percentage points, from 49.3 percent in 2011 to 44 percent in 2017. This reduction is however 

statistically insignificant. The decline represents a move out of poverty for nearly 178,000 people 

from the Eastern Region. The fall in MPI and intensity of poverty in the Eastern Region are also 

statistically insignificant. 

Figure 4.5: Percentage contribution by indicator - Eastern Region 

  

4.2 3.4
4.0 3.6

5.4 5.5

3.4 2.7
5.3

4.7

4.6
4.0

9.3
8.9

4.8
6.6

9.9 10.3

11.6 11.1

8.3 11.0

29.2 28.3

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20%

30%

40%

50%

60%

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90%

100%

Eastern National

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The Eastern Region recorded one statistically significant improvement in deprivation as depicted 

by the cooking fuel indicator. Among those who were cooking fuel poor, the percentage of poor 

people who no longer use solid fuels in enclosed spaces was about 16.3 percentage points. 

Although there were increases in the percentage of those who were poor in housing and school 

attendance, these were statistically insignificant.  

4.6 Ashanti Region 

The Ashanti Region is the second most developed region in the country after Greater Accra. It is 

therefore not surprising that it has the second lowest MPI after the capital region. With an MPI of 

0.147, it is about 0.089 below the national MPI and 0.045 above Greater Accra’s MPI. The 

headcount ratio of multidimensional poverty in the Ashanti Region is about 31.1 percent. This, 

therefore, implies that almost a third of the region’s population is multidimensionally poor. This 

is also significantly lower than the national average (45.6%) and greater than the nation’s capital 

(22.5%). The intensity of poverty in the Ashanti Region is about 47.5 percent, which means that 

those identified to be multidimensionally poor in the region are deprived in about 47.5 percent of 

the weighted indicators, on average. With a population of 1.84 million people, the Ashanti Region 

is the most populous and represents about 13 percent of all poor people in the nation.  

The results suggest that a third of households (33.1%) in the Ashanti Region are predominantly 

deprived in benefiting from health insurance. The deprivation in this area is lower than Greater 

Accra (35.5%) but higher than the national figure (28.3%). Similar to the Greater Accra Region, 

nutritional deprivation ranks second in the indicator contributions to the region’s MPI, at 11.6 

percent. Other relatively high contributors include school lag (10.0%), sanitation (9.8%), school 

attainment (9.3%) and overcrowding (6.4%). Access to potable water seems to be the least of the 

region’s problem with an MPI of approximately 2.0 percent.  

The Ashanti Region experienced a statistically significant fall multidimensionally poor people by 

14.6 percentage points from 45.6 percent to 31.1 percent between 2011 and 2017 respectively.  

Table 4.6: MPI, headcount ratio and intensity - Ashanti Region 

Region MPI Incidence (%) Intensity (%) 

National 0.236 45.6 51.7 

Western 0.235 47.6 49.4 

Central 0.239 47.6 50.1 

Greater Accra  0.102 22.5 45.5 

Volta 0.306 58.2 52.7 

Eastern 0.217 44.0 49.3 

Ashanti 0.147 31.1 47.5 

Brong Ahafo 0.255 49.4 51.6 

Northern 0.491 80.8 60.7 

Upper East  0.359 68.1 52.8 

Upper West 0.348 65.5 53.1 



35 

 

The reduction is statistically significant at 1% level.  From the estimated decline in poverty, about 

0.86 million people in the Ashanti Region w have been lifted out of poverty. The MPI also 

plummeted by 8.5 percentage points while the intensity of poverty decreased by 3.5 percentage 

points. Both estimates are significant at 1 percent and 5 percent respectively. 

The Ashanti Region is one of the two regions that experienced an improvement in all indicators 

between the period 2011 and 2017. However, progress noted in housing and assets deprivations 

were not significant. The highest reduction in living standard deprivation was due to a decline in 

the use of non-clean cooking fuels. This constituted about 17.5 percentage point difference.  

Figure 4.6: Percentage contribution by indicator - Ashanti Region 

  

 

4.7 Brong Ahafo Region 

The Brong Ahafo Region has an MPI of 0.255. This is just a little over the national MPI of 0.236. 

The headcount ratio of multidimensional poverty in the region is 49.4 percent which is about 3.8 

percent above the national MPI. Hence, the figure indicates that 49.4 percent of people in the 

region are multidimensionally poor. The intensity of poverty in the region is 51.6 percent. This 

means that among those that have been identified to be multidimensionally poor in the region, they 

2.5 3.4
1.9 3.63.8

5.5

2.8
2.76.4

4.7
4.2

4.0

9.8
8.9

4.6
6.6

9.3
10.3

9.9

11.1

11.6

11.0

33.1
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30%

40%

50%

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Ashanti National

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are deprived, on average, in 51.6 percent of the weighted indicators. The asset indicator contributes 

the least to the region’s MPI with 2.9 percent while insurance has the highest contribution of 27.8 

percent. Other indicators with a relatively higher contribution to the region’s MPI include school 

lag (11.2%), nutrition (11.0%), school attainment (10.7%) and sanitation (9.2%). Brong Ahafo is 

the fifth largest region in Ghana and almost 1.44 million MPI poor people reside in the region. 

This represents 10.2 percent of all the multidimensionally poor people in the country. 

Between 2011 and 2017, Brong Ahafo Region experienced a reduction in the incidence of 

multidimensional poverty by 11.2 percentage points, from 60.6 percent in 2011 to 49.4 percent in 

2017. This reduction is statistically significant at 5 percent level. The figure implies that nearly a 

third of a million people in the region have experienced significant improvement in their living 

standards, which removes them from the poverty bracket. There is also a statistically significant 

decrease in the MPI by 8.3 percentage points, as well as a statistically significant fall in the 

intensity of poverty by 4.1 percentage points. 

The Brong Ahafo Region was the second region to record an improvement in all indicators. Similar 

to the Ashanti Region, not all improvements in deprivations were significant. With the exception 

of housing and sanitation, the indicators which depicted a significant improvement in living 

standard are: electricity, cooking fuel, sanitation, school attainment, school lag and health 

insurance.  

Table 4.7: MPI, headcount ratio and intensity - Brong Ahafo Region 

Region MPI Incidence (%) Intensity (%) 

National 0.236 45.6 51.7 

Western 0.235 47.6 49.4 

Central 0.239 47.6 50.1 

Greater Accra  0.102 22.5 45.5 

Volta 0.306 58.2 52.7 

Eastern 0.217 44.0 49.3 

Ashanti 0.147 31.1 47.5 

Brong Ahafo 0.255 49.4 51.6 

Northern 0.491 80.8 60.7 

Upper East  0.359 68.1 52.8 

Upper West 0.348 65.5 53.1 

 

The greatest improvement in living standards is presented by the cooking fuel indicator, which 

suggests that the percentage of poor people who lack modern cooking methods reduced by 24 

percentage points. Over the period, access to electricity, school attainment, school lag and 

sanitation depicted an improvement of above 10 percentage points. 



37 

 

Figure 4.7: Percentage contribution by indicator - Brong Ahafo Region 

  

4.8 Northern Region 

The Northern Region has the highest multidimensional poverty in Ghana, with an MPI of 0.491. 

This is twice the national MPI (0.24) and 0.389 percentage points higher than the Greater Accra 

region, which has the lowest poverty. It is also the region with the highest MPI among the three 

northern regions. The incidence of multidimensional poverty in the Northern Region is 80.8 

percent which is also the largest among all the regions and greater than the national figure (45.6%). 

This estimate implies that eight out of every ten people in the region are multidimensionally poor. 

The intensity of poverty in the Northern Region is about 60.7 percent, meaning that the 

multidimensionally poor person in the region is deprived, on average in seven of the twelve 

weighted indicators. In Ghana, the average multidimensionally poor person is deprived in six of 

the weighted indicators; hence, the intensity of deprivation is higher in the Northern Region than 

nationwide. The Northern region is the sixth largest region in the country with almost 2.53 million 

4.6 3.4

3.7 3.6

5.5 5.5

2.9 2.7

5.0
4.7

3.0 4.0

9.2 8.9

5.6 6.6

10.7 10.3

11.2 11.1

11.0 11.0

27.8 28.3

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

Brong Ahafo National

P
er

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ta
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 c
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M
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electricity water housing assets

overcrowding cooking fuel sanitation school attendance

school attainment school lag nutrition health insurance



38 

 

MPI poor people. This represents approximately 17.9 percent of all multidimensionally poor 

people in the country. 

Insurance (24.1%), nutrition (12.6%), school attainment (11.5%), school lag (10.2%) and school 

attendance (9.44%) are the indicators contributing more to multiple deprivation in the region. 

Similar to the trend found so far, insurance contributes the most to the region’s MPI, although, this 

is lower when compared to the national figure (28.3%). The number of people who own more than 

one small asset increased in the region and has the least share of total MPI of 1.8 percent.  

The Northern Region experienced a decrease in the MPI poor people by 2.7 percentage points from 

83.5 percent to 80.8 percent between 2011 and 2017 respectively. This fall was however 

statistically insignificant. The reduction represents about 83,000 people in the Northern Region 

who have been lifted out of poverty. The MPI also decreased by 3.2 percentage points while the 

intensity of poverty also fell by 1.9 percentage points but are however statistically insignificant. 

Table 4.8: MPI, headcount ratio, and intensity - Northern Region 

Region MPI Incidence (%) Intensity (%) 

National 0.236 45.6 51.7 

Western 0.235 47.6 49.4 

Central 0.239 47.6 50.1 

Greater Accra  0.102 22.5 45.5 

Volta 0.306 58.2 52.7 

Eastern 0.217 44.0 49.3 

Ashanti 0.147 31.1 47.5 

Brong Ahafo 0.255 49.4 51.6 

Northern 0.491 80.8 60.7 

Upper East  0.359 68.1 52.8 

Upper West 0.348 65.5 53.1 

 

Statistically significant improvements were made in access to electricity and school attainment 

deprivations in the Northern Region over the period 2011 and 2017. These deprivations reduced 

by 20.8 and 20.2 percentage points respectively. In contrast, the housing and overcrowding 

indicators depicted an increase in deprivations by 10.9 and 7.3 percentage points respectively.  

 

 



39 

 

Figure 4.8: Percentage contribution by indicator - Northern Region 

  

 

4.9 Upper East Region 

The Upper East Region is one of the three regions in the northern part of the country. It has the 

second highest MPI of 0.359 which is 0.132 points below poverty index of the Northern Region. 

The region’s MPI is 0.257 and 0.123 points above the Greater Accra region and the national MPI 

respectively. Incidence of multidimensional poverty in the Upper East region is 68.0 percent, also 

the second highest in the country. The figure implies that 68 percent of the population in the Upper 

East Region are multidimensionally poor, which is 22.4 percent higher than the national 

multidimensional poverty rate of 45.6 percent. The intensity of poverty in the Upper East region 

is 52.8 percent, which implies that those who are identified as multidimensionally poor are 

deprived, on average, in 52.8 percent of the weighted indicators. This, however, is the third-highest 

region after the Northern and Upper West Regions in terms of intensity of poverty. The Upper East 

3.8 3.4

5.1 3.6

7.0
5.5

1.8
2.7

3.0
4.7

3.9 4.0

7.6 8.9

9.4 6.6

11.5
10.3

10.2
11.1

12.6
11.0

24.1
28.3

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

Northern National

P
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M
P

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electricity water housing assets

overcrowding cooking fuel sanitation school attendance

school attainment school lag nutrition health insurance



40 

 

Region is the second least populated region in the country and has about 885,848 MPI poor people 

living in the region. This represents about 6.3 percent of all the MPI poor individuals in Ghana.  

Like the national scenario, not having a health insurance contribute the highest deprivation to the 

region’s multidimensional poverty (21.5%). However, the figure is relatively lower compared to 

its contribution to MPI at the national level (28.3%). Other indicators with concerning levels of 

deprivation in the region are school lag (14.0%), school attainment (13.9%), sanitation (9.0%), 

housing (8.4%) and nutrition (8.3%). Among all indicators, the lowest levels of deprivation were 

recorded by the assets (2.2%) and overcrowding (2.7%) indicators.  

Table 4.9: MPI, headcount ratio, and intensity - Upper East Region 

Region MPI Incidence (%) Intensity (%) 

National 0.236 45.6 51.7 

Western 0.235 47.6 49.4 

Central 0.239 47.6 50.1 

Greater Accra  0.102 22.5 45.5 

Volta 0.306 58.2 52.7 

Eastern 0.217 44.0 49.3 

Ashanti 0.147 31.1 47.5 

Brong Ahafo 0.255 49.4 51.6 

Northern 0.491 80.8 60.7 

Upper East  0.359 68.1 52.8 

Upper West 0.348 65.5 53.1 

 

Between 2011 and 2017, Upper East Region had a reduction in the proportion of MPI poor people 

by as much as 19.4 percentage points, from 87.4 percent to 68.1 percent. This reduction is 

statistically significant at 1 percent level. The noted reduction implies that nearly 253,000 people 

have been li