Infrastructure for Economic Development and Poverty Reduction in Africa

8/7/2019 Infrastructure for Economic Development and Poverty Reduction in Africa

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INFRASTRUCTUREFOR ECONOMIC DEVELOPMENT

AND POVERTY REDUCTION

IN AFRICA


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United Nations Human Settlements ProgrammeNairobi 2011

INFRASTRUCTUREFOR ECONOMIC DEVELOPMENTAND POVERTY REDUCTIONIN AFRICA


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Te Global Urban Economic Dialogue SeriesInfrastructure for Economic Development and Poverty Reduction in Africa

First published in Nairobi in 2011 by UN-HABIA.Copyright United Nations Human Settlements Programme 2011

All rights reservedUnited Nations Human Settlements Programme (UN-HABIA)P. O. Box 30030, 00100 Nairobi GPO KENYAel: 254-020-7623120 (Central Office)

www.unhabitat.org

HS/192/10EISBN: 978-92-1-132027-5 (Series)

ISBN: 978-92-1-132293-4 (Volume)

Disclaimer

Te designations employed and the presentation of the material in this publication donot imply the expression of any opinion whatsoever on the part of the Secretariat ofthe United Nations concerning the legal status of any country, territory, city or areaor of its authorities, or concerning the delimitation of its frontiers of boundaries.

Views expressed in this publication do not necessarily reflect those of the UnitedNations Human Settlements Programme, the United Nations, or its Member States.

Excerpts may be reproduced without authorization,on condition that the source is indicated.

Cover photos: UN-HABIA

Acknowledgements:

Director: Oyebanji OyeyinkaPrincipal Editor and Manager: Xing Quan Zhang

Principal Author: Afeikhena JeromeInput: Gulelat KebedeEnglish Editor: Eric OrinaDesign and Layout: Andrew Ondoo


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U r b a n i z a t i o nis one of themost powerful,irreversible forcesin the world. Itis estimated that93 percent ofthe future urbanpopulation growth

will occur in thecities of Asia and

Africa, and to a lesser extent, Latin Americaand the Caribbean.

We live in a new urban era with most ofhumanity now living in towns and cities.

Global poverty is moving into cities, mostlyin developing countries, in a process we callthe urbanisation of poverty.

Te worlds slums are growing and growing

as are the global urban populations. Indeed,this is one of the greatest challenges we face inthe new millennium.

Te persistent problems of poverty and slumsare in large part due to weak urban economies.Urban economic development is fundamentalto UN-HABIAs mandate. Cities act asengines of national economic development.

Strong urban economies are essentialfor poverty reduction and the provision ofadequate housing, infrastructure, education,health, safety, and basic services.

Te Global Urban Economic Dialogue seriespresented here is a platform for all sectorsof the society to address urban economicdevelopment and particularly its contributionto addressing housing issues. Tis work carriesmany new ideas, solutions and innovativebest practices from some of the worlds

leading urban thinkers and practitionersfrom international organisations, nationalgovernments, local authorities, the privatesector, and civil society.

Tis series also gives us an interestinginsight and deeper understanding of the widerange of urban economic development andhuman settlements development issues. It willserve UN member States well in their quest

for better policies and strategies to addressincreasing global challenges in these areas

Joan ClosUnder-Secretary-General, United Nations

Executive Director, UN-HABIA

FOREWORD


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INFRASTRUCTURE FOR ECONOMIC DEVELOPMENT AND POVERTY REDUCTION IN AFRICA

CONTENTS

FOREWORD III

CONTENTS IV

LIST OF ABBREVIATIONS AND ACRONYMS VI

LIST OF TABLES VII

CHAPTER ONE: INTRODUCTION 1

1.1 Introduction 1

CHAPTER TWO: FRAMEWORK FOR INFRASTRUCTURE, POVERTY

REDUCTION AND ECONOMIC DEVELOPMENT 52.1 Definition/ Key Infrastructure Sectors 5

2.2 Infrastructure and the Millennium

Development Goals 6

2.3 The Concept of Poverty and the Poor 7

2.4 Infrastructure and Economic Development 9

2.4.1 Macroeconomic Evidence 9

2.4.2 Microeconomic Evidence 11

2.4.3 Micro-Level Studies on Mobile Phones 12

2.5 Poverty and Inequality 13

2.6 Randomized Field Experiments and

Impact Evaluation 15

2.6.1 Water and Sanitation 16

2.6.2 Transport 16

2.6.3 Irrigation 18

2.6.4 Power 18

CHAPTER THREE:AFRICAS INFRASTRUCTURE ENDOWMENT 19

3.1 Introduction 19

3.1 Energy 22

3.2 Renewable Energy 29

3.3 Transport 31

3.3.1 Roads 31

3.3.2. Railways 33

3.3.3 Maritime Transport 34

3.3.4 Airports 34

3.4 Information and Communications Technology 34

3.4.1 Telephones 34

3.4.2 Internet 37


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3.4.3 Bandwidth 38

3.5 Water and Sanitation 39

3.5.1 Water 40

3.5.2 Sanitation 43

CHAPTER FOUR:MODELS OF INFRASTRUCTURE FINANCING 47

4.1 Government Financing 47

4.2 Private Sector in Infrastructure Financing 47

4.3 Government Financing of Infrastructure in Africa 49

4.4 Current Investment Needs 50

CHAPTER FIVE: PRIVATE PARTICIPATION IN INFRASTRUCTUREIN AFRICA 53

5.1 The Record of Private Sector participation in

Africas Infrastructure 53

5.2 Water and Sanitation 58

5.3 Energy 58

5.4 Telecommunications 60

5.5. Transport 61

CHAPTER SIX: IMPACT OF INFRASTRUCTURE ON ECONOMICGROWTH AND POVERTY REDUCTION IN AFRICA 63

6.1 Africas Growth Performance 63

6.2 Poverty in Africa 64

6.3 Infrastructure and Growth in Africa 66

6.4 Infrastructure and Poverty Reduction in Africa 67

CHAPTER SEVEN: LESSONS, CONCLUSIONS ANDRECOMMENDATIONS 73

7.1 Key Lessons 73

7.2 Recommendations 74

7.2.1 Governments 74

7.2.2 Role of the Private Sector 747.2.3 Alternative Sources of Finance 75

7.3.4 Appropriate Regulation 75

7.3.5 Meeting the Rural Challenge 75

7.3.6 Meeting the needs of the Urban Poor 76

7.3.7 Regional Integration 76

REFERENCES 77

DATA APENDICES 85


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LIST OF ABBREVIATIONS AND ACRONYMS

AfDB African Development Bank

AICD African Infrastructure Country Diagnosis

BOT Build Operate Transfer

BOOT Build Own Operate Transfer

CD Capacity Development

DBFM Design, Build, Finance & Maintain

DFI Development Finance Institution

DFID Department for International Development (UK)

EAIF Emerging Africa Infrastructure Fund (PIDG)

EU European Union

FDI Foreign Direct Investment

GDP Gross Domestic Product

ICT Information and Communication Technology

IDA International Development Agency

IFC International Finance Corporation (WB)

IPP Independent Power Producers

MDGs Millennium Development Goals

MIGA Multilateral Investment Guarantee Agency (WB)

ODA Official Development Assistance

OECD Organisation for Economic Cooperation and Development

OLS Ordinary Least Squares

PPI Public-Private Investment

PPIAF Public-Private Infrastructure Advisory Facility (WB)

PPP Public-Private Partnership

PSP Private Sector Participation

SSA Sub-Saharan Africa

TA Technical Assistance

UN United Nations

WB World Bank

WiMAX Worldwide Interoperability for Microwave Access

WTO World Trade Organisation


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LISTS OF BOXES, FIGURES AND TABLES

LIST OF BOXES

Box 1: Africas Renewable Energy Potential 30

Box 2: Gautrain: Africas First High-Speed Rail Project Takes off 33

Box 3: M-PESA 36

Box 4: The Infrastructure Challenge of the Urban Poor 70

LIST OF FIGURES

Figure 1: Measures of Basic Infrastructure Provision: Sub-Saharan Africa versus other

Low Income Countries 19

Figure 2: Africas Known Exploitable Hydro-Power Potential 28

Figure 3: Installed Hydropower Capacity as Percentage of Known Exploitable Potential 29

Figure 4: ICT Penetration in Africa in 2009 35

Figure 5: ICT Development in Africa 35

Figure 7: Countries with the highest net additions of Internet users in Africa, 2000-2008 38

Figure 8: Internet users per 100 inhabitants in Africa, 2008 39

Figure 9: Regional Distribution of the 884 Million People Not Using Improved Drinking-Water Sources

in 2008, Population (Million) 41

Figure 10: Proportion of the Population with Access to Improved Water Sources in 2008 (Percentage) 42

Figure 11: Distribution of Who Usually Collects Drinking Water by Percentage 43Figure 12: Use of Sanitation facilities by MDG Regions (Percentage) 44

Figure 13: Regional Distribution of the 2.6 Billion People Not Using Improved Sanitation in 2008,

Population (Million) 44

Figure 14: Sanitation Coverage in Africa in 2008 (Percentage) 46

Figure 15: Fiscal flows devoted to infrastructure 50

Figure 16: Economic Growth in Africa (1997 to 2009) 65

Figure 17: Evolution of Poverty in Africa (1990 to 2005) 65

Figure 18: Poverty Headcount by Region 66


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LIST OF TABLES

Table 1: Infrastructures Contribution to the Millennium Development Goals 7

Table 2: Africas Infrastructure Endowment Relative to other Regions 20

Table 3: Evolution of Access to Network Infrastructure, National Level (%) 23

Table 4: Quality Ratings of the Main Infrastructure Services in Africa (2002 Data) 25Table 5: Africas High Cost Infrastructure 26

Table 6: World Electricity Generation and Consumption, Most Recent Annual Estimates 2006 27

Table 7: Proportion of African Households Connected to Electricity Supply 27

Table 8: Characteristics of the Road Network in 14 African Cities 32

Table 9: Drinking Water Sources by MDG Regions (Percentage of Population) 40

Table 10: Urban/Rural Coverage of Drinking Water in Africa 42

Table 11: Sanitation Coverage in Africa 45

Table 12: Options for Private Sector Participation in Infrastructure 48

Table 13: Africas Annual Expenditure Needs to Meet the MDGs 51

Table 14: Private Sector in Infrastructure Projects by Region (1990-2007) 53

Table 15: Number of Private Sector Participation in Infrastructure Projects by Primary Sector

in Sub-Saharan Africa (1990-2007) 54

Table 16: Private Sector Investment in Infrastructure Projects by Primary Sector in Sub-Saharan Africa

(Total Investment Commitments in USD million) 55

Table 17: Total Projects by Primary Sector and Subsector (USD million) 56

Table 18: Number of Projects by Type 57

Table 19: Africas Top 15 Telecommunications Firms in 2008 61Table 20: Africa GDP Growth Rates, 1997 2007 (Cumulative annual average) 64

Table 21: How much faster Africa would have grown if it had enjoyed South Koreas infrastructure

stock and quality? 68

Table 22: Impact of Access to Water and Electricity on Poverty, Selected African Countries 69

Table 23: Access to infrastructure services by quintile of wealth, National level (%) 70

Table 24: Evolution of Access Rates to Networked Water and Electricity across Income Classes 71

Table A1: Africas Electricity Installed Capacity by Type, January 1, 2006 85

Table A2: Africas Total Net Electricity Generation 2003 to 2006 (Billion Kilowatt-hours) 86

Table A3: Progress on Sanitation in Africa (Percentage of Population) 88

Table A4: Improved Water Source in Africa (Percentage of Population) 89

Table A5 : ICT Development Index (IDI), 2002 and 2007, Africa 91

Table A6: Main (fixed) telephone lines 92

Table A7: Mobile Cellular Subscriptions in Africa 93

Table A8: Mobile cellular subscriptions (continuation) 94

Table A9: Internet Users 96

Table A10: International Internet Bandwidth 97


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CHAPTER 1 INTRODUCTION

1.1 Introduction

Te adequate supply of infrastructure serviceshas long been viewed as essential for economicdevelopment and poverty reduction, both inthe policy and academic realms. Over the lasttwo decades, considerable efforts have been

devoted to theoretical and empirical evaluationof the contribution of infrastructure to growthand economic development. More recently,increasing attention has also been shifting tothe impact of infrastructure on poverty andinequality (Ariyo and Jerome, 2004; Calderon,2008; Estache and Wodon, 2010; Ogun,2010). While the extant literature on these twotopics is far from unanimous, on the whole, aconsensus has emerged that, under the right

conditions, infrastructure development canplay a major role in promoting growth andequity and, through both channels, help toreduce poverty.

Paradoxically, in spite of this universallyacknowledged attributes and importance,sub Saharan Africa (SSA1) trails behind otherregions in infrastructure service delivery andquality, with the gap widening over time.

Tis is poignantly demonstrated in the energysector. With about 800 million citizens, the48 SSA countries produce collectively aboutas much power as Spain, which has only afraction (1/18th) of the population (AICD,2009). Despite its great potential in cleanenergy resources, such as hydropower, solar,

wind and geothermal, investment in newfacilities in SSA has been woefully inadequate,creating a chronic supply imbalance.

1 Due to the way data on infrastructure stocks are structured,there is overt reference to Sub Saharan Africa rather than Africa.Many of the indicators for North Africa are lumped with theMiddle East.

Investment in maintaining existinginfrastructure has also lagged behind, leavingmany African countries with degraded andinefficient infrastructure services; poor qualityroads, railways, and ports and an inadequateIC backbone.

Te bleak picture of infrastructure deficienciesin SSA is compounded by unprecedented urbangrowth whose consequences are reflected inthe explosion of informal settlements (slums)all over the continent (Binde and Mayor,2001; Pieterse, 2008). Urbanization in Africais faster than in any other region of the world.It is estimated that Africas urban population

will more than double the 2007 level of 373.4million as early as 2025, when 54 percent

of the population will be urban. In absoluteterms, there will be close to 800 million

African urban dwellers then, making it morethan todays total number of city dwellers inthe entire Western hemisphere (ibaijuka,2010). Due to inadequate investment in basicinfrastructure, the rapid rate of urbanizationin SSA is putting considerable strain on theregions limited infrastructure.

Another key characteristic of urbanization inAfrica is that in most countries it is happeningwithout or with limited development, resultingin a rapid increase in urban poverty. Perhaps,the most visible and enduring manifestationsof urban poverty is the formation andproliferation of slums (Arimah, 2010).


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In the context of economic stagnation, poorgovernance, and fragile public institutions, itis estimated that almost two-thirds of Africanurban dwellers are living in slums, characterisedby deficient infrastructure, unless current

approaches to urban development changeradically (Pieterse, 2008). Across Africa, rapidurban growth has been accompanied by ahost of problems, such as unemployment andunderemployment, a burgeoning informalsector, deteriorating infrastructure and servicedelivery capacity, overcrowding, environmentaldegradation, and an acute housing shortage.

Te lack of modern infrastructure is an

impediment to Africas economic developmentand a major constraint on poverty reduction,as well as the attainment of the MillenniumDevelopment Goals (MDGs). Availableevidence shows that lives and livelihoodsare suffering from the fragile state ofinfrastructure in SSA. Te lack of adequatetransport, power, communication networks,

water, sanitation and other infrastructure putssevere constraints on economic growth and

poverty reduction across the region. akenas a whole, these infrastructure constraintserode Africas competitiveness and makebringing African goods and services to the

world marketplace a challenge. Accordingto the World Banks 2009 Doing Business,most sub-Saharan African countries, with fewexceptions, rank in the bottom 40 percentof all countries in the trading across bordersindicator. Te needs for infrastructure in SSA

are enormous, hence the resurgence of interestin the regions infrastructure. From rural roads,railways and harbours, to irrigation systems,telecommunications, clean water, sanitation,energy and such basic social infrastructure ashealth, education, banking and commercialservices, hundreds of millions of Africans lackeven the most fundamental amenities. Tisis particularly true in rural areas, where themajority of the people live.

Te burden also falls most heavily on women,who, in the absence of electricity often mustspend hours collecting wood for cooking andheating.

Although the damaging economic and socialimpacts of Africas infrastructure deficiencieswere widely recognized, investment in Africaninfrastructure declined relative to otherpriorities during the 1990s. In part, there wasan incorrect assumption that private investors

would step in to finance the much neededinfrastructure. However, the private sector hasnot produced the massive investments anddramatically improved technical performance

hoped for (Jerome, 2009). Notable successesnotwithstanding, overall outcomes have fallenshort of expectations. Te results have beendisappointing, particularly in relation to

water and electricity needs, two areas criticalto the rapid economic development of Africa.

Available evidence shows that there has beenlimited mobilization of private financing; anumber of concessions have run into problems;in many countries, the cost of infrastructure

services has not diminished, and increases inquality and access rates have not occurred asanticipated.

Te investment needs in Africasinfrastructure are quite substantial. Te AfricaInfrastructure Country Diagnostic Study(AICD) estimates the cost of addressing Africasinfrastructure at about USD 93 billion a year,about 15 percent of GDP, one-third of which

is for maintenance. Te regions track recordof investment flows suggests that the privatesector by itself is unlikely to provide the kindof near-term funding needed to address theseshortcomings.

With Africas low levels of infrastructureinvestment in the face of rapidly growingneeds, the private sector appears capable ofsupplying only a fraction of the investmentneeds. Te current global economic andfinancial crisis poses a new threat to the role ofthe private sector in financing infrastructuredevelopment in Africa.


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CHAPTER ONE INTRODUCTION

Te effects of the crisis are already apparentin greater delays in financial closures, morecancellations, and higher financing costs for PPI(full) projects, despite the stimulus packagein response to the financial crisis in several

countries, often targeted at infrastructure.

However, unlike the debates on the reformsof the 1990s which were shaped by ideologicalorientation and blame game, there is graduallya coalescing of opinions on the reform agendain addressing Africas infrastructure despitethe wide variation and diversity in countriesand regions. A lot of learning has takenplace in the past two and a half decades and

substantial efforts have been invested in datain recent years2. Te choice is no longer simplya dichotomy between public and privateprovision, but how to forge mutual cooperationbetween these two sectors, defined by areas ofcompetence. Tere is growing consensus thatthe public sector must retain a much moreimportant role in financing than previouslyadmitted, while the private sector is expectedto help in meeting the significant needs

associated with infrastructure construction,operation, and, to some extent, financing insectors such as telecommunications, energygeneration, and transport services in whichcommercial and political risks are much lower.Small-scale operators are also assuming anincreasing, yet generally underestimated rolein catering to the needs of the populations notsupplied by the actors with higher visibility.

Access, affordability and quality of service

rendered by small providers are still not clearlyunderstood and deserve more research andanalysis.

2 The most comprehensive effort is the Africa InfrastructureCountry Diagnostic (AICD), a project designed to expand theworlds knowledge of physical infrastructure in Africa. Financing

for AICD is provided by a multi-donor trust fund to whichthe main contributors are the Department for InternationalDevelopment (United Kingdom), the Public Private Infrastructure

Advisory Facility, Agence Franaise de Dveloppement, and theEuropean Commission.

Tis report evaluates the role of infrastructurein promoting economic growth and povertyreduction in Africa. It is devoted to the studyof the complementary physical infrastructure -telecommunications, power, transport (roads,

railways, ports and airports), and water supply.Te report is presented in seven chapters.Chapter wo appraises the relationshipbetween infrastructure and development;Chapter Tree examines Africas infrastructureendowment; and Chapter Four evaluates thefinancing options. Te focus of Chapter Fiveis the record of private sector participationin Africa, while Chapter Six examines theinfrastructure/ development and poverty

nexus in Africa. Chapter Seven concludes.


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CHAPTER TWO FRAMEWORK FOR INFRASTRUCTURE, POVERTY REDUCTION AND ECONOMIC DEVELOPMENT

CHAPTER 2 FRAMEWORK FOR INFRASTRUCTURE,POVERTY REDUCTION ANDECONOMIC DEVELOPMENT

2.1 Definition/ KeyInfrastructure Sectors

Te last two years have witnessed a heightenedinterest in infrastructure in both developed anddeveloping countries, with emphasis on therole of infrastructure in mitigating the global

financial crisis through stimulus packagesin developed countries, and the recurringattention on its impact on growth and povertyreduction in developing countries (Jerome,2009). Tere is no iron clad definition ofinfrastructure. It is most commonly discussedin terms of its characteristics - longevity, scale,inflexibility, and higher investment costs - butthat is seldom seen as satisfactory.

Other characteristics describe infrastructureas:

essentially public goods, providing inprinciple, non-exclusive goods accessibleto all;

Fixed investments, bulky and lump-sumwith long (or no) payback periods;

having considerable variation in earning

power capacity (e.g. telecommunicationsversus water);

Output mostly paid for in local currency(less true for ports and airports);

Until recently, the public sector playing adominant role (finance, regulation);

Sensitive to corruption and politicalshifts.

Increasingly, the meaning of infrastructurehas been shifting from one focusing onphysical fixed assets such as roads, airports,sea ports, telecommunications systems, waterdistribution systems and sanitation (whatmight be called public utilities). It nowoften embodies notions of softer types of

infrastructure such as information systems andknowledge bases (Button, 2002). In general,infrastructure can be categorized into hardinfrastructure and soft infrastructure. Teformer refers to physical structures or facilitiesthat support the society and economy, such astransport (ports, roads and railways); energy(electricity generation, electrical grids, gas andoil pipelines); telecommunications (telephoneand internet); and, basic utilities (water supply,

hospitals and health clinics, schools, irrigation,etc.). Te latter refers to non-tangiblessupporting the development and operation ofhard infrastructure, such as policy, regulatory,and institutional frameworks; governancemechanisms; systems and procedures; socialnetworks; and transparency and accountabilityof financing and procurement systems(Bhattacharyay, 2008).

Broadly defined, therefore, infrastructurerefers to all basic inputs into and requirementsfor the proper functioning of the economy. Inspite of this, there are two generally acceptedcategories, namely, economic and socialinfrastructure.


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Economic infrastructure is also, at a givenpoint in time, part of an economys capitalstock used to facilitate economic production,or serve as inputs to production (e.g. electricity,roads, and ports). Tis helps to produce

items that are consumed by households (e.g.water, sanitation and electricity). Economicinfrastructure can further be subdivided intothree categories: utilities (power, piped gas,telecommunications, water and sanitation,sewerage and solid waste disposal), public

works (roads and water catchments in dams,irrigation and drainage) and other transportsub-sectors (railways, waterways and seaports,airports and urban transport systems). In

national accounts statistics, these are found intwo sub-headings of the gross domestic product(GDP): electricity, gas and water are located inthe secondary sector; while transport, storageand communication are found in the tertiarysector.

Social infrastructure, on the other hand,encompasses services such as health, educationand recreation. It has both a direct and indirect

impact on the quality of life. Directly, itenhances the level of productivity in economicactivities, indirectly, it streamlines activitiesand outcomes such as recreation, education,health and safety. Te indirect benefit ofimproved primary health care, for example,is improved productivity, which in turn leadsto higher economic growth and real incomes.Social infrastructure also facilitates investmentin human capital that ensures better utilization

by some of the economys physical capitalstock and thereby raises the productivityof the workforce. Te impact on growth issimilar to an increase in the supply of capital a higher capital to labour ratio which enablesa given number of workers to produce moreoutput per capita. It also enhances the qualityof life of the populace by empowering themeconomically, politically and socially, with theattendant positive effects on efficient use of

national resources and on poverty alleviation.

2.2. Infrastructure and theMillennium DevelopmentGoals

At the United Nations (UN) Millennium

Summit of September 2000, 189 nationsadopted the Millennium Declaration, out of

which grew a set of eight goals, 18 numericaltargets and 48 quantifiable indicators to beachieved over the 25-year period from 1990-2015. Te Millennium Development Goals(MDGs) commit the international communityto an expanded vision of poverty reductionand pro-poor growth and vigorously placehuman development at the centre of socialand economic progress in all countries. Teyseek to reduce the number of poor peoplein the world and specifically target the worstaspects of poverty.

Economic infrastructure essentially,transport, energy, information andcommunications technology, water, sanitationand irrigation is specifically identified in theMillennium Development Goals (MDGs),

only in respect of water and sanitation,telephones, personal computers and internetusers. Te transport sector has been largelyignored in the MDGs discourse; hence it is

widely referred to as the omitted MDG.

In many ways, infrastructure investmentsunderpin virtually all the MDGs, includinghalving poverty in the world by 2015 as shownin able 1. It is widely acknowledged that

the contribution of infrastructure to halvingincome poverty or MDG 1 is more significantthan the other goals (Willoughby, 2004).Infrastructure also affects non-income aspectsof poverty, contributing to improvementsin health, nutrition, education and socialcohesion. For example, roads contributesignificantly to lowering transaction costs(MDG I), raising girls school attendance(MDG II/III), improving access to hospitals

and medication (MDG IV/V/VI), andfostering international connectivity (MDGVIII).


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MDGs => I II III IV V VI VII VIII

Poverty Education Gender Mortality. Mat.Health

HIV Environment. Partnership

Infrastructure:Transport(local)

+++ ++ ++ + + + +

Transport(regional)

+++ + + ++ + + -- +++

Modernenergy

+++ + + ++ + + ++ +

Telecoms ++ + + + + + + ++

Water(private use)

++ ++ + +++ + + +++ +

Sanitation + + ++ + + + ++ +

Watermanagement

+++ + + ++

TABLE 1:Infrastructures Contribution to the Millennium Development Goals

Source: Willoughby 2004

aken in this context, infrastructure makesvaluable contributions to all the MDGs(Willoughby, 2004). Te many benefits ofinfrastructure have also been confirmed by the

United Nations Millennium Project (2005),which advocates for a major increase in basicinfrastructure investments, to assist countries(especially in Africa) escape the poverty trap.

2.3. The Concept of Povertyand the Poor

Te MDGs are focusing international

attention more sharply on poverty reduction.Te international target proposed by theMillennium Development Goal has been

widely adopted, namely in 2015 to reduce byhalf the proportion of people living in extremepoverty. But quite what this target might meanis obscured by the bewildering ambiguity with

which the term poverty is used, and by thepecuniary indicators proposed to monitor itlike the international poverty line of USD1

per day.

Poverty often appears as an elusive concept,especially from the perspectives of researchersand policy makers in developing countries.Te best definition of poverty remains a

matter of considerable academic argument.Perhaps the only point of general agreementis that people who live in poverty must be ina state of deprivation; that is, a state in whichtheir standard of living falls below minimumacceptable standards.

Te concepts of poverty have developedrapidly over the last four decades. From ananalytical perspective, serious concern orthinking about poverty can be traced backto Rowntrees (1901) study. In the 1960s,the main focus was on the level of income,reflected in macro-economic indicators likeGross National Product (GNP) per head. Tis

was associated with an emphasis on growth,for example in the work of the PearsonCommission Partners in Development(1969). In the 1970s, concern about povertybecame more prominent, notably as a result ofRobert McNamaras celebrated speech to the

World Bank Board of Governors in Nairobiin 1973 on basic needs, and the subsequentpublication of Redistribution with Growth(Adelman, 1974).


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According to the World Bank (2001),poverty is pronounced deprivation in well-being, where well-being can be measured byan individuals possession of income, health,nutrition, education, assets, housing, and

certain rights in a society, such as freedomof speech. Poverty is also viewed as a lack ofopportunities, powerlessness, and vulnerability.Tis broadens the definition of poverty toinclude hunger, lack of shelter, being sick andnot being able to see a doctor, not being able togo to school and not knowing how to read, nothaving job, fear for the future, living one day ata time and losing a child to illness brought byunclean water. Poverty further entails lack of

representation and freedom. Indeed, the poorthemselves see powerlessness and voicelessnessas key aspects of their poverty (Narayan et al.,2000).

In general, poverty is a condition that isexperienced over time and is the outcome ofa process. While many are born into povertyand remain in it, others experience thecondition at one or more stages of their life

and move in and out of it. Fundamentally,poverty is a negative term denoting absenceor lack of material wealth. Such absence,however, is seldom absolute and the term isusually employed to describe the much morefrequent situation of insufficiency either in thepossession of wealth or in the flow of income(Green, 2008).

As Green (2008) suggests, poverty is often

embedded in social structures that exclude thepoor. Social exclusion can be understood asthose processes of discrimination that deprivepeople of their human rights and result ininequitable and fragmented societies. Genderdiscrimination is the most common formof discrimination worldwide. Te HumanDevelopment Report (2001) notes that 70percent of the worlds poor are female onaverage and that womens share of GDP in

developing countries is less than 50 percent ofmens.

Institutionalised racism, as in South Africa,is also responsible for extreme inequality inincome and land ownership (DFID, 2002).

Seen from this perspective, poverty is a multi-

dimensional phenomenon and experiencesof poverty are conceptually specific togeographical areas and groups. Many factorsconverge to make poverty an interlockingmulti- dimensional phenomenon. Tese comeout clearly in the criteria used to differentiatebetween categories of rich, average and poor.Te 2000/2001 World Development Report(World Bank 2001) identifies three broaddimensions of poverty relating to lack of

income, insecurity and lack of political voice.

In defining and measuring poverty, adistinction, thus, needs to be made betweenthe traditional uni-dimensional approach andmore recent multidimensional ones. Whereasthe traditional approach refers only to onevariable such as income or consumption,multidimensional ones, such as Sens capabilitytheory or studies derived from the concept of

fuzzy sets, extend the number of dimensionsalong which poverty is measured.

Te Oxford Poverty and HumanDevelopment Initiative recently unveiled aninnovative new multidimensional measureof people living in poverty, known as theMultidimensional Poverty Index or MPI. TeMPI features three deprivation dimensions-- health, education and standard of living.Using the Alkire Foster method, outcomes ofindividuals or households are measured againstmultiple criteria (ten in all) from each of thethree dimensions, thus providing a detailedpicture of not just who is poor, but in what

way they are poor. Te MPI will be featured inthe upcoming 20th-anniversary edition of theUNDP Human Development Report 2010.


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2.4. Infrastructure andEconomic Development

A recent body of research confirms theimportance of infrastructure service provision

to sustainable development. Te World Banks(1994) World Development Report landmarkstudy on infrastructure highlighted the criticalrole of infrastructure in the developmentprocess.

Te evidence in the World Bank reporton the vital role of infrastructure services ingrowth has been reinforced by subsequentresearch, especially that focusing on Africas

economic performance (Ndulu, 2006). Notonly does the development of infrastructureservices contribute to growth, but growth alsocontributes to infrastructure development, ina virtuous circle. Moreover, investments inhuman capital and in infrastructure interact,each increasing the returns to the other.

DFID (2002) identified the various channelsthrough which investment in infrastructure

can contribute to sustainable growth, asfollows:

Reducing transaction costs and facilitatingtrade flows within and across borders.

Enabling economic actors individuals,firms, governments to respond to newtypes of demand in different places;

Lowering the costs of inputs forentrepreneurs, or making existing

businesses more profitable;

Creating employment, including inpublic works (both as social protectionand as a counter-cyclical policy in times ofrecession);

Enhancing human capital, for exampleby improving access to schools and healthcentres; and,

Improving environmental conditions,which link to improved livelihoods, betterhealth and reduced vulnerability of thepoor

Empirically, research on the impact ofinfrastructure took off relatively recently,following the seminal work of Aschauer(1989), and has blossomed over the last twodecades.

In general, the evidence on the impactof infrastructure on poverty comes fromtwo types of studies. Te first focuseson the absolute impact of infrastructureon macroeconomic (production-related)indicators, the second is the microeconomicevidence both at the household and firm levels.

A recent development in the microeconomicliterature is the increasing use of randomized

evaluation to demonstrate impact as well asfocus on the dynamic and stochastic nature ofpoverty. Tis derives from the realization thatthat policy analyses based on static povertycan yield substantial inefficiencies in policyinterventions (Jalan and Ravallion 1998).

2.4.1 Macroeconomic Evidence

A considerable effort have been devoted

at the macroeconomic level to assessing theeffects of infrastructure on broad aggregatessuch as output, growth and productivity, usinga variety of data, empirical methodologies andinfrastructure measures. Literally hundredsof papers have been written on this subject.Te most popular approaches include theestimation of an aggregate production function(or its dual, the cost function), and empiricalgrowth regressions. Infrastructure is variously

measured in terms of physical stocks, spendingflows, or capital stocks. Estache (2006), Rompand de Haan (2007) and Straub (2007) offercomprehensive surveys of this literature.

Admittedly, more of these studies are based onthe experience of developed economies.

Aschauer (1989) opened the debate on themacro-economic impact of infrastructure whenhe found that the elasticity of national GDPto infrastructure is high in the United States,roughly 0.4 for total public capital and 0.24for core infrastructure. Such large estimateshave often been considered unrealistic and


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have triggered a large amount of subsequentresearch, which looks at different samplesor refining the techniques used. Subsequentstudies by Munnell (1990), and Nadiri andMamuneas (1994), confirm these results at

the national level. However, some researchers,including Garcia Mila and Mcguire (1992)and Morrison and Schwartz (1996), findthis elasticity to be lower, and sometimesinsignificant at the state or local level (Eberts1990, Hulten and Schwab 1991), Munnell(1990), for instance, found the elasticity to bearound 0.15 at the US metropolitan level.

A majority of this literature observes a

positive long-run effect of infrastructure onoutput, productivity, or their growth rate.More specifically, this is the case with almostall of the studies using physical indicatorsof infrastructure stocks. But the resultsare more mixed among the growth studiesusing measures of public capital stocks orinfrastructure spending flows than those thatdo not (Straub 2007).

Romp and de Haan (2005), while reviewingthe literature note that 32 of 39 studies ofOECD countries found a positive effect ofinfrastructure on some combination of output,efficiency, productivity, private investmentand employment. (Of the rest, three hadinconclusive results and four found a negligibleor negative impact of infrastructure). Teyalso review 12 studies that include developingcountries. Of these, nine find a significant

positive impact. Te three that find no impactrely on public spending data which is anotoriously imprecise measure, especially forcross-country analysis. Other meta-analysisalso shows a dominance of studies that point toa generally significant impact of infrastructureparticularly in developing countries. Calderonand Serven (2004) report that 16 out of 17studies of developing countries find a positiveimpact as do 21 of 29 studies of high income

countries. Briceo et al (2004) carry out asimilar review of about 102 papers and reachsimilar conclusions.

A strand of the literature has focused onthe development impact of infrastructure in

Africa. Ayogu (2007) provides a survey ofthe empirical literature. Most of the studiesdeal with the growth and productivity effects

of infrastructure development. For example,Estache, Speciale and Veredas (2005) presentpooled OLS growth regressions based onan augmented Solow model, including avariety of infrastructure indicators. Teirmain conclusion is that roads, power andtelecommunications infrastructure, with theexception of water and sanitation, contributesignificantly to long-run growth in Africa.Other studies based on the same production

function approach, such as those by Ayogu(1999), Boopen (2006) and Kamara (2006)make similar findings.

In the same vein, Perkins, Fedderke andLuiz (2005) use a detailed database oninfrastructure investment and capital stocks,spanning as long as a hundred years, to test forthe existence of a long-run relation betweendifferent infrastructure measures and GDP.

Teir results suggest a bi-directional relationin most cases. Kularatne (2005) explores theeffects of infrastructure investment (as wellas social spending on health and education)on GDP. He also finds bi-directional effects,although the impact of infrastructureinvestment appears to occur indirectly throughprivate investment.

A more recent study by Caldern (2009)

provides a comprehensive assessment of theimpact of infrastructure development oneconomic growth in African countries. Basedon econometric estimates for a sample of136 countries over the period 19602005, itevaluates the impact of a faster accumulationof infrastructure stocks and an enhancementin the quality of infrastructure services oneconomic growth across African countries overthe 15-year study period. Te study findings

indicate that growth is positively affected bythe volume of infrastructure stocks and thequality of infrastructure services.


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Te simulation shows that if all Africancountries were to catch up with the regionsleader, Mauritius, in the infrastructure stockand quality, their rate of economic growth

would be enhancedon average by 2.2

percent per year, and ranging from 0.6 to 3.5percent.

Several broad generalizations can be deducedfrom the literature. First, there is increasingconsensus on the notion that infrastructuregenerally matters for growth and productioncosts, although its impact seems higher at lowerlevels of income. Nevertheless, the findingsremain tremendously varied, particularly in

relation to the magnitude of the effect, withstudies reporting widely varying returns andelasticity. Overall, the literature supports theview that infrastructure matters but does notunequivocally argue in favour of more or lessinfrastructure investments.

Second, the literature has been plaguedby numerous methodological issues thathave often clouded the robustness of the

conclusions

3

. Estimating the impact ofinfrastructure on growth is a complicatedendeavour, and papers vary in how carefullythey navigate the empirical and econometricpitfalls posed by network effects, endogeneity,heterogeneity and very poor quality data.

In general, most critiques of Aschauers(1989) pioneering work with its findings ofimplausibly high rates of return focus on afailure to appropriately correct for the possibilitythat an omitted variable is driving the results.Indeed, later studies (see Grammlich 1994 foran overview of this literature) attempted tocorrect this by introducing country (or region)fixed-effects and found much lower rates ofreturn.

3 See for example Estache and Fay (2007), Briceo-Garmendia andKlytchnikova (2006) and Briceo- Garmendia, Estache and Shafik(2004) for more elaboration on the methodological challenges inthe study of infrastructure.

However, the fixed-effect approach precludeslooking at the impact of other slow movingvariables, hence a number of authors prefernot to use it (e.g. Estache, Speciale andVeredas 2006). Even when studies have been

technically sound, they have suffered fromother limitations such as the nature of data.Infrastructure capital stocks are inadequateproxies to the growing private nature ofinfrastructure services, while physical indicatorsare still too coarse to really capture the flow ofservices to households and firms, and optimalstocks are unlikely to be ever identifiable atthe aggregation level of regions or countries.Tis is reflected in the wide variety of findings

in the now abundant empirical literature oninfrastructure and growth or productivity.

2.4.2 Microeconomic Evidence

Infrastructure, no doubt, has majorimplications for a variety of developmentoutcomes, both at the household level (health,education and social mobility), at the firmlevel (productivity, industrial development)

and at the global level (climate change). Temicroeconomic literature on infrastructureis, however, still evolving and far from robustbut with divergent results similar to themacroeconomic evidence.

In the micro-economic literature,considerable attention has been devoted toroads because of the perception that they willineluctably lead to poverty reduction and

income generation, especially in rural areas.Gibson and Rozelle (2003), for example,appraise the effect of access to roads in PapuaNew Guinea on poverty at the household level.Tey demonstrate that reducing access time toless than three hours where it was above thisthreshold, leads to a fall of 5.3 percent in thehead count poverty index.


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Using anzanian household survey data,Fan, Nyange and Rao (2005) look at theimpact of public investment and roads onhousehold level income and poverty and findvery positive effects, with a ratio of 1 to 9 in

the case of public capital investment. Bakht,Khandker and Koolwal (2009) estimate theimpact of two roads projects in Bangladesh onseven household outcomes by household fixed-effects method. For the two projects underconsideration, road development significantlyreduced the price of fertilizer. ransport costsalso decreased significantly. Going beyondmere access, Gachassin, E. al (2010) usethe second Cameroonian national household

survey (Enqute Camerounaise Auprs desMnages II, 2001) to address the impact ofroad access on poverty. Tey report that it isnot road availability per se that helps to reducepoverty, but the opportunities opened byroads, more specifically labour opportunities.

Another group of studies examines firm-level data. Reinikka and Svensson (2002)use unique microeconomic evidence to show

the effects of poor infrastructure services onprivate investment in Uganda. Tey surveyedUgandan firms to analyze how entrepreneurscope with deficient public capital. Teir studyfindings show that faced with unavailableand unpredictable services, many firms investin substitutes such as electricity generators.

According to Reinikka and Svensson, poorpublic capital, proxied by an unreliableand inadequate power supply, significantly

reduces productive private investment. As aresult, poor public capital crowds out privateinvestment. Teir findings are similar to thosefrom investment climate assessments, such as

Anas, Lee and Murray (1996) and Lee, Anasand Oh (1996) on Indonesia, Nigeria andTailand, and Alby and Straub (2007) oneight Latin American countries.

Without any doubt, drawbacks of themicroeconomic approach exist, the mainone being that since the contributions are bynature focused on specific cases and contexts,they may not always provide lessons that can

be generalized.

2.4.3 Micro-Level Studies on Mobile Phones

Te rapid adoption of mobile phones hasgenerated a great deal of studies on its effecton economic development and povertyeradication. Although the evidence on Africais quite recent, an emerging body of literatureidentifies the effect of mobile phones on

development outcomes, using mainly paneldata and the quasi-experimental nature of therollout of mobile phone service. Tese studiesprimarily focus on the relationship betweenmobile phone coverage and specific outcomes,such as price dispersion across markets (Akerand Mbiti, 2010), market agents behavior(Aker, 2008; Muto and Yamano, 2009) andproducer and consumer welfare (Aker, 2008).

Aker (2008) examines the impact of mobilephones on grain markets in Niger. He findsthat the introduction of mobile phones isassociated with increased consumer welfarethrough a reduction in the intra-annualcoefficient of variation, thereby subjectingconsumers to less intra-annual price risk.Mobile phones also increased traders welfare,primarily by increasing their sales prices, asthey were able to take advantage of spatial

arbitrage opportunities. Te net effect of thesechanges was an increase in average daily profits,equivalent to a 29 percent increase per year.

Aker and Mbiti (2010) also find thatthe introduction of mobile phones reducesdispersion of grain prices across markets by 10percent. Te effect is stronger for those marketpairs with higher transport costs, namely,those that are farther apart and linked bypoor quality roads. Te effect is also strongerover time, suggesting that there are networkseffects.


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Te primary mechanism through whichmobile phones improve market efficiency isa change in traders (middlemen) marketingbehaviour: grain traders operating in mobilephone markets search over a greater number of

markets, sell in more markets and have moremarket contacts as compared with their non-mobile phone counterparts.

Muto and Yamano (2009) estimate theimpact of mobile phones on agriculturalmarkets in Uganda, focusing on farmersmarket participation rather than marketefficiency. Using a panel dataset on farmhouseholds between 2003 and 2005, they find

that mobile phone coverage is associated witha 10 percent increase in farmers probabilityof market participation for bananas, althoughnot maize, thereby suggesting that mobilephones are more useful for perishable crops.Tis effect was greater for farmers located incommunities farther away from district centres.Te authors suggest that improved access toprice information reduced marketing costs,increased farm-gate prices and productive

efficiency though they did not empiricallyexplore the specific mechanisms driving theresults.

2.5 Poverty and Inequality

Te studies reviewed in the precedingsection all look at infrastructures contributionto economic growth rather than specifically

poverty and inequality. While there isconsiderable evidence that infrastructuredevelopment is correlated with economicgrowth, there is less evidence to support apositive impact on poverty. Some evidencesuggests that certain types of infrastructureservice provision, such as roads andtransport, have a potential contribution toagricultural output, and that infrastructureimprovements (in electricity supply, transport

and telecommunications) in small townscontribute significantly to industrial growthand employment.

At a community or individual level, benefitscan accrue to the poor if labour-intensivemethods of construction are used rather thancapital-intensive methods (Sida 1996).

Datt and Ravallion (1998) analyze state-levelpoverty data from India for the period 19571991 and conclude that state-level differencesin poverty reduction can be attributed todifferences in initial conditions, particularlyirrigation infrastructure and human resources.Similarly, van de Walle (1996) uses theVietnam Living Standards Survey of 19921993 and estimated the poverty reductioneffect of irrigation infrastructure. With regard

to the impact of water supply projects onpoverty, Jalan and Ravallion (2003) provedthat the water supply system had a strongereconomic effect among poor householdsthan it did among non-poor households.Lokshin and Yemtsov (2004, 2005) estimatethe poverty reduction effect of community-level infrastructure improvement projects on

water supply systems that were implementedbetween 1998 and 2001 in Georgia. Jalan and

Ravallion (2003) investigate the role of watersupply and public health systems. Moreover,the role of irrigation and water relatedinfrastructure in poverty reduction has been

well documented in the literature.

A strand of the empirical literature focuseson the poverty effects of specific infrastructureprojects, using matching techniques thatcombine samples of beneficiaries with samples

drawn from regular household surveys. Onthe whole, the evidence shows that publicinvestment on infrastructure, especially onthe rehabilitation of rural roads, improveslocal community and market development.For example, rehabilitation of rural roadsraises male agricultural wages and aggregatecrop indices in poor villages of Bangladesh(Khandker et al. 2006). Likewise, in Vietnampublic investment in infrastructure has resulted

in an increase in the availability of food, thecompletion rates of primary school and the

wages of agricultural workers (Mu and van deWalle, 2007).


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In the same vein, other studies elsewherefind that access to new and improved roadsin rural areas enhances opportunities innon-agricultural activities in Peru (Escobaland Ponce, 2002) and in non-farm activities

among women in Georgia (Lokshin andYemtsov, 2005).

Given the controversy surrounding boththe theoretical and empirical literature on thedeterminants of poverty, Jalilian and Weiss(2004) explore the nexus between infrastructure,growth and poverty using samples of countriesfrom Africa, Asia and Latin America. Applyingdifferent theoretical and empirical techniques,

they obtain results from the estimation of thead hoc model showing that on average, aone per cent increase in infrastructure stockper capita, holding human capital constant, isassociated with a 0.35 per cent reduction inthe poverty ratio, when poverty is measuredby USD 1/day poverty headcount, or 0.52per cent when it is measured by USD 2/daypoverty headcount. Tis study suggests that,

while infrastructure investment in general has

a role to play in poverty reduction, physicalinfrastructure investment needs to be verysubstantial and must be supported by factorssuch as improvement in social infrastructureso as to promote rapid reductions in poverty.

However, relatively few empirical studieshave tackled directly the inequality impactof infrastructure at the macroeconomic level.Lpez (2004) and Caldern and Servn (2008)

are perhaps the two well known studies and theyboth use cross-country panel data. Lpez usestelephone density to proxy for infrastructure,

while Caldern and Servn employ syntheticindices of infrastructure quantity and quality.In both cases, the finding is that, other thingsbeing equal, infrastructure development isassociated with reduced income inequality.Indeed, for infrastructure development toreduce income inequality, it must help expand

access by the poor, as a key ingredient.

Combined with another finding thatinfrastructure appears to raise growth rates, theimplication would, therefore, be that with theright conditions, infrastructure developmentcan be a powerful tool for poverty reduction.

Te empirical literature suggests that thelink between infrastructure and povertyreduction is not linear. While the picture isbroadly positive, experience suggests thatthere is a complex set of variables that needattention if the development of infrastructureservices is to contribute to pro-poor growth.White elephant infrastructure projects are

well documented, while a variety of barriers

may prevent poor people from access toeconomic opportunities created. In particular,it should be noted that an inadequate focuson governance and institutional frameworkshas resulted in outcomes that are often lessthan anticipated. High levels of personaland political corruption, facilitated by weaksystems, have hindered a demand-led approach,distorted public investment choices, divertedbenefits from the poor, encouraged neglect of

maintenance and hindered the contributionto growth. oo often, there have been negativerather than positive consequences for poorpeople, including environmental damage to

which the poor are most vulnerable.

In general, non-poor households seemto benefit more from public infrastructureinvestments than non-poor households (WorldBank 1994). In Bangladesh, for example,

non-poor groups receive over 80 percent ofsubsidies on infrastructure (Kessides, 1993).Moreover, infrastructure development canhave negative impacts on specific social groupsdue to, among other factors, displacement,environmental pollution and health risks,and loss of livelihoods. Generally, the urbanpoor are increasingly situated at the peripheryof cities where access to city facilities and jobopportunities is restricted.


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2.6 Randomized FieldExperiments and ImpactEvaluation

Te last decade has witnessed an explosion

in the use of randomized field experiments ofthe Bannerjee-Duflo type (the same approachused by the medical industry to determine ifa drug or treatment does what it was designedto do) to poverty interventions to identify

whether or not a program is effective. Teexplosion has resulted from a convergenceof several forces- the increasing demand foraccountability and results by key stakeholdersincluding bilateral and multilateral donors,availability of high quality data, refinement inthe field and interest by academics amid someskeptics.

Experimental designs, also known asrandomization, are generally considered themost robust of the evaluation methodologies.By randomly allocating the interventionamong eligible beneficiaries, the assignmentprocess itself creates comparable treatment and

control groups that are statistically equivalentto one another, given appropriate samplesizes. Te outcome is very powerful because,in theory, the control groups generatedthrough random assignment serve as a perfectcounterfactual, free from the troublesomeselection bias issues that exist in all evaluations.Quasi-experimental (non-random) methodsare also used to carry out an evaluation whenit is not possible to construct treatment andcomparison groups through experimentaldesign. Tese techniques generate comparisongroups that resemble the treatment group,at least in observed characteristics througheconometric methodologies, which includematching methods, double differencemethods, instrumental variables methods,and reflexive comparisons. Te main benefitof quasi-experimental designs is that they candraw on existing data sources and are, thus,often quicker and cheaper to implement, andthey can be performed after a program has

been implemented, given sufficient existingdata. Te principal disadvantages of quasi-experimental techniques are that (a) thereliability of the results is often reduced as themethodology is less robust statistically; (b) the

methods can be statistically complex; and (c)there is a problem of selection bias.

While there is growing coverage of the sectorin evaluation efforts, published evaluationson infrastructure are still few as compared tohealth or education. Estache (2010) presentsan excellent review of the literature on impactevaluations on infrastructure derived mainlyfrom experimental and quasi-experimental

techniques and other methodologies whenthese techniques cannot be used. Te reviewtakes stock of the lessons of recent impactevaluations in energy, water and sanitationso far covered by evaluations based onrandomized experiments as well as the varioustransport subsectors (ports, railways, ruralroads and highways).

In all, modern evaluation techniques are

delivering on their promise to identify povertyrelated and distributional issues with many ofthe interventions considered in infrastructureactivities, whether projects, programs orpolicies. Whatever the form of evaluation,the research and practice of the last few yearshas provided many insights on why not allapparently comparable interventions havesometimes generated dissimilar impacts acrosslocations. Differences in institutions, legal

or social incentives and norms, access to andsources of financial resources, technologicalpreferences and choices or in initial conditionscan all explain quite convincingly differencesin impact.

In what follows, we succinctly appraisedevelopments in three infrastructure sectors

where the methodology is reasonablyadvanced:


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2.6.1 Water and Sanitation

Tere are several recent evaluationsconducted in water and sanitation, includingthe World Bank Dime initiative (Pouloset al. (2006), the World Bank EvaluationDepartment, (IEG, 2008) and a new thinktank (3ie) focusing on impact evaluations(Snilstveit and Waddington, 2009). Snilstveitand Waddington (2009), for example, which isthe most recent, is a synthetic review of impactevaluations examining effectiveness of water,sanitation and hygiene (WSH) interventionsin reducing childhood diarrhea. Te survey

was limited to rigorous impact evaluationtechniques, using experimental (randomisedassignment) and quasi-experimental methods,and which evaluated the impact of water,sanitation and/or hygiene interventions ondiarrhoea morbidity among children in low-and middle-income countries. It identified 65studies for quantitative synthesis, covering 71distinct interventions assessed across 130,000children in 35 developing countries duringthe past three decades.

According to the survey, studies typicallyvary from 6 to 19 months in duration ofcollection of water related disease data, withtheir average sample sizes varying from 327for point of use treatment to almost 6000 for

water supply. All studies found some impactfor each intervention type but there wassignificant diversity of efforts across studies.Te results, however, call into question somereceived wisdom, particularly with regard tothe sustainability of water quality interventionsand more limited effectiveness of sanitation.

Te main consensus in water and sanitationis:

Te questions posed by these studiesvalidate many of the common perceptionsregarding the desirability of meeting theMillennium Development Goals (MDGs)

soon. Water and sanitation are associatedwith other desirable MDG goals, namely,health, education, nutritional, employmentand income outcomes:

Tere is some variance in the eectivenessof the interventions aimed at reaching theMDGs. For instance, unless all connectionscome from piped water, water supplyinterventions tend to be less effective in

terms of health (although they can helpsave time) than water treatment at point ofuse interventions or than many sanitationand hygiene interventions. Assessmentsthus need to reflect quality of water andquality of service and not just the quantityresulting from the intervention;

Social norms are quite relevant inmaximizing the efforts to improve hygiene

and in ensuring the cooperation needed toguarantee the sustainability of interventionsin the sector; and,

Te policy and institutional context in whichthe evaluation is conducted is extremelyimportant. For example, educating waterusers can have high payoffs as well butthat the form of education matters a lotmore than many field workers sometimes

recognize. For instance, the effects can bevery different if the knowledge comes frompeers or if it comes from common formaltraining. Tere is however no clear rankingof approaches.

2.6.2 Transport

ransport does pose special challenges thatlimit the possibility to assume randomness.

While many small scale or rural transportprojects can be evaluated using real or quasitrials, large projects such as highways, ports,airports and railways are not easily amenableto experimental and quasi-experimentaltechniques. For example, to perform a purelyrandomized experimental approach, one

would need two or more similar areas in termsof their geography and economic situation.Investments are sometimes based on demandforecasts with 20-30 years lead time. Tepayoffs to many infrastructure interventionstend to be slow to show up.


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Estache (2010), thus, recommends the use ofother feasible approximations such as generalequilibrium and other structural models toobtain an evaluation (propensity scores) butthey are not simple either.

van de Walle (2009) offers a very thoroughoverview of the technical dimensions of impactevaluations of rural road projects. She observesthat very few of the many aid-financed ruralroad projects in developing countries havebeen subject to evaluations. Te reason beingthat they are simply hard to do using (quasi-)randomized evaluation techniques. Te mostchallenging characteristic of road projects in

terms of the techniques approximating randomtrials is that they have no natural comparisongroup. It is, indeed, hard to find two similarregions in all the relevant characteristics suchas the initial conditions in the compositionand level of production activities, compositionand levels of skills of workers, the number ofusers, access to other transport modes, accessto schools or any variable that may influencethe evolution of the derived demand for the

road and hence the comparability of theevolution of regions with and without theroad project. In addition, evaluators have ahard time addressing all relevant spillovereffects as well as time dimensions associated

with many road PPPs. Tis is why it is stillcommon to see assessments of the impact ofrural roads interventions conducted throughgeneral equilibrium modeling (Estache,2010). Despite the challenges, there are a few

well known top quality evaluations. Banerjee,Duflo and Qian (2009) for China, Jacoby(2001) on Nepal, van de Walle and Mu (2007)on Vietnam, Gibson and Rozelle (2003) onPapua New-Guinea), Khandaker et al. (2006)on Bangladesh and Dercon et al. (2007) onEthiopia.

Banerjee, Duflo and Qian (2009), forexample, estimate the effect of accessto transportation networks on regionaldemographic and economic outcomes acrosscounties in China during 1986-2003. Tey

go beyond the trade related impacts andassess the effects of greater factor mobility,better access to education, health care andfinance, and other effects of diffusion ofideas, technologies, etc. Teir results are stillpreliminary and somewhat surprising. Teydo not find a significant effect on GDP levels,population, or the composition of population.However, with a few important caveats, theyfind a distributional impact across space from

distance to railways. On average, increasingdistance from railroads by one percentdecreases annual GDP growth by 0.12-0.28percent across sectors. In other words, a policy

which randomly places transportationinfrastructure will have a positive economiceffect on those areas.

Te conclusion and overall policy messageof these papers is quite robust. Rural roads

provide substantial benefits to households inlow-income countries, especially the poorest.But not all roads beneficiaries get the samebenefits. Tere is a wide range of outcomes,including situations in which a specificoutcome is present in one project and notin another one within the same country.Moreover, they also show that rural roads arenot a panacea for poverty alleviation and themechanics of poverty alleviation can vary quite

a lot across projects.


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2.6.3 Irrigation

Very few evaluations have been conductedfor irrigation. A recent study by Sawada,et al. (2010) evaluates the role of irrigationinfrastructure in mitigating the negativeimpact of poverty dynamics using householdpanel data from Sri Lanka.

A unique monthly household panel data setwas collected in Sri Lanka through extensivefield surveys using standard questionnairesto derive household accessibility to irrigationinfrastructure. Tey then employ propensityscore matching to quantify the impacts ofirrigation infrastructure access on individual

livelihoods and the various channels throughwhich irrigation reduces chronic and transientpoverty.

Te point estimates derived by the propensityscore matching method show that withirrigation accessibility, per capita income andper capita food and non-food consumptionexpenditures increase by around 17.8, 12.2and 37.6 percent respectively, when evaluated

at the average level among the treated, and thatthe probability of binding credit constraint isreduced by 5.6 percent during the dry season.Te results provide evidence in support of therole of infrastructure in reducing both chronicand transient poverty.

2.6.4 Power

Tere are very few publications on the

impact of electricity interventions as in thecase of water and roads, impact evaluationstend to focus a lot more on rural populations.Estache (2010), however, indicates thatthere are several ongoing evaluations (in

Afghanistan, Bangladesh, El Salvador,Ethiopia, Mozambique, Pakistan, Peru,anzania, and Vietnam) but it is too early todraw major conclusions from these projects.

Using Chinese data from 1970-97, Fan etal. (2002) show that, for every 10,000 yuanspent on electricity development, 2.3 personsare brought out of poverty. Balisacan et al.(2002) did a similar analysis for Indonesia

in 1990 and concluded that a 10 percentimprovement in access to a compositetechnology measure (including electricity ina village) raised the income of the poor byroughly 2 percent. aylor (2005) and Escobaland orero (2005) also conducted similarassessments for Guatemala and Peru and drewvery similar positive conclusions on the gainsfrom electrification. Balisacan and Pernia(2002) use Filipino data from 1985-1997 to

argue that the rich tend to benefit more fromincreased access to electricity.

However, the above studies suffer from amajor econometric deficiency, the inabilityto fully address the causality between theintervention and the impact. Tey also do notaccount for the fact that electricity is ofteninstalled first in areas with the greatest potentialfor economic growth (Estache, 2010).

Dinkelman (2008) provides insights intothe impact of rural electrification on cookingtechnologies and employment. Tese effectsare identified by exploiting variation inelectricity project placement and timing fromSouth Africas mass roll-out of rural householdelectricity. She finds that within five years,treated areas substitute sharply towardselectricity in cooking. She also finds a 13.5 per

cent increase in women employment but noeffect on male employment. Tis employmenteffect is driven by the switch to electricityfrom cooking wood that is usually collectedby women.


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CHAPTER THREE AFRICAS INFRASTRUCTURE ENDOWMENT

CHAPTER 3 AFRICAS INFRASTRUCTUREENDOWMENT

3.1 Introduction

By any conceivable measure, Africalags considerably behind other regions ofthe developing world, both in terms ofinfrastructure service quality and quantity.Tis observation holds sway across a wide

range of indicators, including the density ofroad networks and paved roads, per capita

capacity to generate electricity, and householdaccess to electricity, water, and sanitation(see Figure 1). Moreover, there is abundantevidence to show that many countries arenot keeping up with the rapid demographicgrowth, including rapid urbanization and ifthe current trends prevail, the gap is likely to

widen even further.

326

78

134

41

211

51

76

72

0 35030025020015010050

Other Low Income Countries

SSA Low Income Countries

FIGURE 1: Measures of Basic Infrastructure Provision: Sub-Saharan Africa versusother Low Income Countries

Source: Adapted from World Bank (2009), Africas infrastructure: Time for Transformation.

Te dismal infrastructure picture in Africa ispoignantly painted in able 1 which presentsthe continents endowment relative to otherregions of the world. As indicated in the table,the data, though not recent in some sectors,suggests that electricity is accessible to as low as18 percent of sub-Saharan Africas population,relative to 44 percent in South Asia, the next-lowest region.

Access to an improved water source is 58percent in SSA compared to 87 percent forSouth Asia and East Asia and the Pacificrespectively. Access to improved sanitation,at 31 percent, is comparable to that in South

Asia at 33 percent, but well below the 66percent reported for East Asia and the Pacific.Moreover, access to a flush toilet (connectingto a sewer or septic tank) is only 6 percent inSSA.


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Tese aggregate figures, however, maskconsiderable country variations and the rural/urban dichotomy. Coverage rates in urbanareas are much higher than in rural areas. osome extent, Africas low overall access rates

are partly explained by negligible servicecoverage in rural areas, where the bulk ofthe population still resides. When broadermeasures of improved water and sanitation

are considered, the discrepancies are still largeand stark. About 63 percent of the urbanpopulation has access to an improved watersource, compared with about 14 percent ofthe rural population. Similarly, about 42

percent of the urban population has access toimproved sanitation versus about 7 percent ofthe rural population, and only 12 percent ofrural households have access to electricity.

Sub-SaharanAfrica

South Asia East Asia andPacific

Europe andCentral Asia

LatinAmerica andCaribbean

Middle Eastand North

Africa

Population (2007) 561 312 800 1,522 1912 446

Sector and measure

Transport

Paved roads (% ofTotal - 2006)

11.9 56.9 11.4 n.a 22 81

Information andcommunicationtechnology

Fixed Line andMobile Subscribers

per 100 people(2007)

25 26 67 121 85 68

PCs per 1000people (2007)

1.8 3.3 5.6 10.6 11.3 6.3

Energy

Electricalgenerating capacity(MW per 1 millionpeople, 2003)

70 154 231 970 464 496

Access to electricity(% of householdswith access, 2004)

18 44 57 79 88

Water and sanitation

Water(% of populationwith to improvedwater source,2006)

58 87 87 95 91 89

Sanitation(% of populationwith accessto improvedsanitation facili ties,2006)

31 33 66 89 78 77

TABLE 2:Africas Infrastructure Endowment Relative to other Regions

Sources: 2009 World Development Indicators, World Bank, April 20, 2009; except for energy which is sourcedfrom AICDs and Energy Information Agency, US Department of Energy.


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Post-conflict countries also sufferdisproportionately from lack of basicinfrastructure. During war, a countrysphysical infrastructure is likely to have beensignificantly damaged or disassembled.

Frequently, the neglect of basic maintenanceis an even greater problem than destructionand vandalism. During a lengthy conflict,a cumulative lack of maintenance results ininfrastructure that must be reconstructedbecause it is beyond salvaging.

Africas 15 landlocked countries, home toabout 40 of the regions overall population,also face special challenges. Being landlocked

adds, on average, four days to land distributionof exports and nine days to imports comparedwith equivalent distances within the seaportcountry4. Te geographic disadvantages resultsin high transport costs which hamper intraand inter-regional trade, as variously shown byElbadawi, Mengistae and Zeufack (2006), andBehar and Manners (2008). Reduced opennessto trade emerges as the main factor behind therobust empirical finding that other things

equal landlocked countries tend to growmore slowly than the rest.

able 2 provides an estimate of trends inaccess rates to basic infrastructure servicesin sub-Saharan Africa by households atthe national level. It includes piped water,flush toilets, electricity, and landline phonesobtained from Demographic and HouseholdSurveys (DHS). A cursory examination of the

table indicates that access is generally low forall the countries. Only South Africa (pipedwater and electricity) and Gabon (electricity)have an access rate that is greater than 50 percent at any point.

4 Goods bound for Uganda, Rwanda, and Burundi spend, onaverage, five days more (25 versus 20 days) in Tanzanias DarEs Salaam port than domestically bound goods. The same istrue for goods shipped through Mombasa, Kenya. Inefficient

port processes in Douala, Cameroon, contribute to the delaysand high cost of transporting goods to Ndjamena in Chad,

2,000 km from the sea. The five-week journey over rail androad requires seven documents and suffers from poor andfragmented trucking services, widespread rent-seeking resultingin many checkpoints, security problems, and weak customsadministration in Chad.

Further, there is clearly a discernablerelationship between access rates and economicdevelopment. In relatively poor countries suchas Burkina Faso, Burundi, Chad, Ethiopia,Kenya, Madagascar, Malawi, Mozambique,

Niger, Rwanda, Sierra Leone, anzania, andUganda, less than 20 percent of the populationhas access to any modern infrastructure serviceat any time. At the other extreme is middleincome Gabon where only 15 percent of thehouseholds do not have electricity. Te tworichest countries (South Africa and Gabon)have the highest access rates to piped waterand electricity. South Africa also has thehighest coverage rate for flush toilets and

landline phones.

Te average Africa-wide annual growthrates in coverage for the different services inthe countries in the sample is 5.0 percent forelectricity, 1.4 percent for piped water, 7.0percent for flush toilet, and 12 percent forlandline telephones during the period 1996-2005. It is striking that for piped water andflush toilets, around a quarter of the countries

in the sample actually show evidence ofnegative growth rates in coverage, whileanother third report only modest growth ratesof 0-4 percent per year. Furthermore, beyondbroad averages, a large number of countries arefailing to ensure that service expansion keepspace with population growth. For piped waterand flush toilet, close to half of the countriesare expanding too slowly to keep pace withdemographic growth. In the case of electricity

and landline telephones, around 80 percent ofthe countries are managing to expand coveragefaster than they are expanding population. Buteven for these countries, under a continuationof current trends, it would take perhaps until2050 to reach universal access for water andbeyond 2050 for other services.


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Tere is still lack of objective data on thetechnical quality of Africas infrastructure suchas chemical quality of water delivered. able3, thus, presents some rough indicators of thequality of Africas infrastructure benchmarked

against the performance of low, middle andhigh income countries. Over all, the servicequality for Africa is poor across all infrastructuresectors but compares favourably with what isobtainable in low income countries (LICs).

While Africa is at par with other LICs inwater, it seems to be slightly technicallybetter in electricity and telecommunications.Tis, however, should be interpreted withcaution in view of the limitation of the

indicators utilized. For example, in transportand communication, the data covers onlysix countries. On perceptions, Africa faredrelatively worse off in all the indicators exceptfor mobile phones and this should be a concernto policy makers.

Africas infrastructure networks are not onlydeficient in coverage and quality, but the priceof the services provided are also exceptionally

high, by global standards, as revealed byAICD (able 3). Whether for power, water,road freight, mobile telephones, or Internetservices, the tariffs paid in Africa are severalmultiples of those paid in other parts of thedeveloping world. Te explanation for thisstate is sometimes due to genuine higher costs,and other times due to high profit margins.For example, Nigerias leading mobile provider,MN Nigeria, spends in excess of USD 5.55m

on diesel to power its 6,000 generator plantsacross the country monthly. Zain Nigeria alsoruns back up power generators in the bulk ofits 3,600 base stations in the country due tocontinual national electricity supply problems.Te power sector, however, provides the clearestexample of infrastructure of genuine highercosts in Africa than elsewhere. Many smallercountries have national power systems belowthe 500-megawatt threshold and therefore

often rely on small diesel generation that cancost up to USD 0.35 per kilowatt-hour to run(AICD, 2008).

Below we highlight some sector specificdetails.

3.1 Energy

Te wide-ranging role of energy in economicdevelopment and poverty alleviation is widelyacknowledged. Expanded provision and useof energy services is strongly associated witheconomic development. Tis makes energyalso central to reducing poverty and hunger,increasing literacy and education and reducinginfant and maternal mortality.

Africas largest infrastructure deficiency ismore pronounced in the energy sector, whethermeasured in terms of energy consumption,generation capacity or security of supply.Te energy sector in most parts of Africa ischaracterized by a lack of access (especially inrural areas), low purchasing power, low energyefficiency and over-dependence on traditionalbiomass for meeting basic energy needs.Biomass accounts for as much as two-thirdsof total African final energy consumption. Incomparison, biomass accounts for about 3percent of final energy consumption in OECDcountries. Wood, including charcoal, is themost common and the most environmentallydetrimental biomass energy source in SSA.Firewood accounts for about 65 percent ofbiomass use, and charcoal accounts for about3.0 percent. Health impairment and anunacceptable high rate of mortality in the order

of 400,000 deaths from respiratory diseases peryear are linked to exposure to indoor pollutionfrom dirty fuels in poorly ventilated dwellings(African Development Bank, 2008). A largesegment of the continents population, thuslives in conditions of acute energy poverty.


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Country

1990

95

1996

00

2001

-

05

1990

95

1996

00

2001-

05

1990

95

1996

00

2001-

05

1990

95

1996

00

2001

-

05

Benin

23.1

5

28.7

4

2.3

9

14.

39

21.9

6

4.3

8

BurkinaFaso

5.6

4

3.6

2

5.8

9

0.8

9

0.5

8

1.8

6

6.2

3

6.

06

10.1

6

1.7

9

3.7

2

CAR

2.6

5

1.1

1

5.0

4

1.4

9

Cameroon

12.0

7

11.3

4

12.9

5

6.5

6

6.4

1

8.0

7

31.2

8

41.

52

45.7

6

2.5

5

2.3

3

Chad

3.3

6

4.4

5

0.2

4

1.8

3

2.

76

4.3

3

0.4

5

0.8

8

Comoros

22.6

7

2.9

3

30.

47

3.2

Congo(Bra

zzaville)

25.8

1

5.3

3

34.8

6

1.2

7

CotedIvoire

23.9

8

27.9

3

14.0

3

12.4

5

38.

59

49.7

4

6.5

5

Ethiopia

4.2

1

5.9

8

0.3

4

2.1

3

11.

28

12.0

4

1.5

6

4.4

1

Gabon

43.0

3

24.5

75.

18

15.2

6

Ghana

13.6

5

15.3

8

15.0

8

5.9

4

7.5

7

10.2

8

27.8

5

39.

36

44.2

6

2.4

7.5

Guinea

9.6

2

9.1

3

-

2.6

5

2.6

2

17.

41

20.9

3

2.4

2

7.1

7

Documents

Infrastructure for Economic Development and Poverty Reduction in Africa