african development indicators ppt

Africa ugemty needs ch nations wider tad opportunities to reverse the crue effects ‘of the HIV/AIDS pandemic, civil wars, and persis teat lowe growl rates “The Word Bank atest annul repo

African

2-1, Gross domestic product mal — 15

Contents

2:12, Grose national savings — 26

2-18, GDP growhh 32

Prices and Exchange Rates 41

3-1 GDP deflator (local cumeney seie) — 42

5-7 Parllel market exchange rate

3-8 Rati of parle! marke oficial exchangerates 49

446 Discount ate ` cái

[Exports of total services (nonfactr and fcto)_74

Net private tansfers 76

Netofficil cungntưangfex—_ 77

5:36, Food import, growih_107

5-40, Fuel import, growth _1

5-42, Primary intermediate goods imports growth 113

5-48, Direction of wade matrix, imports, 1977 121

vi Contents

_Direton of wade matrix, expors, 2002133

Direction of ade matrix, curent US dollars 1997139

Direction of wade matrix curent U.S dollars, 2002142

65 Amortization: official concessional long-term loans _1S7

6-6 Amorization: offical nonconcesional long-term loans 158

168

s payments: long-term loans and IMF charges 164

4 Interest payment: short-term loans 166

‘Net lw long- and shar-tem loans, including IMF 167

‘Net lows: long-term ous, including IMF 168

transfers: longterm loans, including IME 170 Long-term debt: official concessional 171

‘Average terms of new commitment in 2002177

6-26, xterm debt and debt service ratios, 2002 178

_ Government deficivsuplus (including grants) — 186

7-2 Government defcvsurplus (excluding grants) 187

‘4 Government expenditure and lend

mes repayments 189

Content

193

“Taxes on income and profits _19

| nes on international ade and ansctions 195

Indirect taxes 196

[Nona revenue excluding grants 197

CGovemment expenditure: wages and salaries 198

CGovemment expenditure: rns in real wages and slries _199 Government expenditure: other goods and services 200,

Government expenditure: intrest payments 201

Government expenditure: subsidies and curenttansers 202

‘Goverment expenditure: capital and net ending 203,

8 Agrcatore 211

Nominal producer pces 212

%2 Food price ini 218

$23 Food production index

8-4 Nonfood potucton index 220

85._Food production pe cap index 221

8:6._Volume of fod ouput, by major food cop _222

8-7 Valucof agricultural exports 226

9, Power, Communications and Transportation

9-2 Energy production and use 248

9-4 Personal computers and Internet use 280

9.7 Paved primary roads 283

9-8 Rail goods taffic-to-SPPP GDP ratio 254

vii Conents

Employment 267 [Number and gender structure of the labor force

“echnical notes 280

12, Aid ¬.ˆ

12-1, Net aid fom all donors, nominal_28

122, Netaid from DAC donors, nominal 286

fom all donors as share of recipient

10, Net aid from DAC donors as share of recipient GDP 294

“Marin and feshwatercathes, guaculue, balance of ade,

“CO, emissions from industrial processes, 1999381

Globally threatened species: mammals, is, nd higher plants, 1992-2002 — 352

‘National proection of natural areas, 2003388

Imerationl protected areas, 2002385

‘Grouping of African HIPC counties: tas as of July 2003365

External det service for individual Aican HIPCs that reached decison points,

Food price index, 2001238

~ Food and nonfood production index, 2002 240

Contents

12-2, Total et id per capita, 2002303,

13h, Life expactancy, 2001332

13-2 GDP per capita based on PPP, 2002 333

13-3 Lihan population asa percentage of al population, 2002,

Table des matiéres

Exportations de bens ot services (non facteurs, prix couramts 28

‘Croissance du PIB——_32

Revenu national brut parhabtant 33

Déflateur du PIB (sie en monnai locale)_42

—Taux de change officiel _45

3⁄6 Facteurde conversion des monies — 4i

Tauxd'escompte _ 61

“aux dbiteur des bangues commerciales _ 63

Exporiationstotales de services (nonfasteur et foteu) 74

Imporation \oales de services (nofiteur et faceur) 75

“eansfersprivés nts T6

“eansfers courant officiel ncts 77

Sold des transactions courts, hors ansfers nes en capital 78

Sold de transactions courts, hors transfers nes en caiai, PB — 79

Transfers nets en capital 80

Investissement dirss ness BI

Emprunts long terme nes 82

xiv Table des matres

5:33. Exponutions de produits manuficturés 104

5-36, _Importtons de produits alimentaires, aux de croissance 107

S1. Matrice de diestions du commerce, expotations, 1997 130

Table des mares w

5-54 _Matrice de directions du commerce, prix courant en dollar des Etats-Unis, 1997139

6-1 _Désaissements brut: pret offices concessions & long tee _ 153

62 Décaissements buts: pits ofiiels non coneessonnels long ierme 184

63 Décaissements buts: pris prvés lng terme 155

(6-10 _Paiements ditt: pelts officiels non concesionaels Along ere 162

(11 _Paiements dines: prétsprivés ong terme _163

6-19 Deted long tee: ofiilleconcesionaelle 17

6-24 Structure du service de a dete extériure—_175

`

10,

Recets non fieale, hơn đơn 197

3 Depenss publique: salies IUR

_Depensespubligues:tendanes ds sales els 199

Dépensespulgus:autes ies et services 200

Depetsespblques twee 201

_Depensespuigus dépensesea capital et pts ats 201

Depense publique: tndances des pens rss de dfese nationale 201 7-20, Depeses publiqs:Jepenses tes ducati par abiant 205

853, Indice dela production alimentaire _219,

Privatisation des entreprises publiques _ 260

Table des mates xi

Main oeuvre et structure par sexe 269

‘Travalleurs familia non rémunéré faisan partie des eavillews acifs 271

Sales dans

Salaies dans ls tansports, 'eaeposage eles communications 278

Sales dans le secteur soil et des services personnels

Aide au développement, nets, de tous les bileurs de fonds 285

‘Aide au développement, net, des bailleurs de fonds apparenant

pasauCAD 291

Ade au développement, nt, des bilers de fonds du CAD en poucentae da PIB,

‘Ade a développement, net, des ailleurs de fonds malate en pourcentge

Aide au développement, net, des bileurs de fonds du CAD en poucentage de

‘Aide au développement, net, des ailleurs de fonds

wii Table dee mares

3-14, Taued'analphabétsme 322

— >>

14 Indicateurs concernant Fenvironnenent—— 37

4-1 Ressoucesforestizes, 1980-2000 2

14.2, Ezosystme forestier, 1990-99385

UGL1, Protection nationale des zones naturclles, 2003384

[12 Zones prtéaées intematioales, 2002355,

‘Notes techniques 356

us

Table des mates

Intative pour alge endetement des pays paures rs endetés (PPTE):

tableau d'évoluton 364

ea

“

”

Ratio du sevice de la dete (ex post) 2002179

Ratio dete ttle PIB, 2002180

Indice dela production agricole, 2001238,

Indice dela production alimentaire par habitat, 2002 239

des pays bdtciaies,2002. 302

13:1 Esplrance de vie, 2001332

13-5 Moral matemell, 2001336

Foreword

Making headway against Afican poverty and meet

ing the Millersium Development Goals (MDGs) by

2005 are raising dificachllenges in most African

‘counties, Despite pockets of success, nary bal the

‘region’ popultion sil lives in exeme poverty, nd

ABien sil houses about three-fourths ofthe work!s

poorest countries Africa ugemty needs ch nations

wider tad opportunities to reverse the crue effects

‘of the HIV/AIDS pandemic, civil wars, and persis

teat lowe growl rates

“The Word Bank atest annul report on soa nd

‘economic conditions across the continent, Aiea

Development indicators ADI 2004, sounds a clear

‘warning thatthe pid spread of HIV/AIDS, anemic

threaten to undo some ofthe hard-fought gins of

‘Asi previous yeas, ADY 2004 assembles eco-

‘of soures to presenta roa picture of development

across Affea, There have been some key improne=

ment inthis volume—for example, macroeconomic

and oer data lags have been reduced, enabling ex-

ternal debt reporting up wo 2002, and there Rave been

nthe chapter on Household Welfare contin anew

307 per ead in SSA, exclaing South Ares rang ing from under 100 pe head inthe Democratic Re Public of Congo to oer 87,000 in Seyoheles At 28

the growthoFitsrapialyuhanizng population (cities

ew at close to 5 percen), continuing the over end ofthe 1990s On average, output pe head has stagnated

Yet country performance has diverged widely in SSA —ideen have averaged more than percent growth forthe period 1995-2002, while afew Several have seen thet economies contrat, avai ably esa reat of severe civil confit On average, investment and trade tends have besa sad, with a slight increase in the overall curent account dei

were heavily concentrated in ol exporting counties

sn Sous Aiea,

‘Accossto ICT isi linia bu increasing a 2002, there were about 12 personal computers per thous sand population i SSA, over 30 percet rise fom:

wit Foreword

2000 and 16 percent fom 2001 In Nosth Afia,

‘computer ownership was somewhat higher t about

17 per thousand le wei sng sharp but of

‘he 6.2 millon records Ilere ser in SSA, about

half were in South Aftia Hover, these data may

ot filly account for mutiple wer saves

‘ie wanspor tas declined abit fom 200010 2001

All Africa recorded about 30.9 milion passengers in

bby North and Sout Aca,

Nef aid to Africa rose about 35 percent in 2002

because of higher DAC and multilateral flows, buton

per capita basis it is sil fa below ($27 in 2002)

what ie was in 1992 ($40) Aid flow was $28 per

head for SSA As of July 2003, 16 counties had

reached HIPC decision points ad ? had reached

completion points Total debe service rele reprevented

shut $43 billion, and pro-poar expires had be-

{gun fo increase ia most of the couttes However,

rine counties, mostly coalitafTesod, had ot yet

reached the HIPC decision poi,

Ta SSA, death ates have continued to ise because

of the HIV/AIDS pandemic, causing life expectancy

st bit ofall rom SO in 1990 to 46 in 2002 AIDS-

felted deaths were 2.2 milion 2001 (for com

lage tet close 0 20 milion Almost 10 milion were

infected and 11 milion were orphase, ineluding a

rillon each in Nigeria and Ehipia, Under S moral

iy too at 169 por thousand for SSA; in mie couse

tres it exceeded 200 per thousand, Only haf ofthe

cfildrnin SSA were immunized Heath expenitres

averaged only STS pet headin SSA, excluding South

‘Alia, an were below $10 per head in 16 countries

But these averages in social indicators conceal wide sarason between counties Material mortal for xml, ranges fom 8s ow 3845 pe 100,00 bits

1 2.300, Education trends were somewhat moe fi

‘orale, ith steady fli literacy, fom 42 pr zat ia 1997 9 37 person in 2002, Although there is slo of eatching-up to do at 8 percent, Boss pe

in 1980 (80 percent), Socal indicators were more favorable in Nomh iia, with fife expectancy a 70 {in 2002 nd immunization rates ner 0 percent

“ADI 2005 draws g#enlon to Afica ich enim mental resources, bt la to theses that envio rent is coming under, Many’ counties have large numbers of endangered species, and each year 0.7 percent of forest cover is being ost

“The deoilal World Hank Attica Database 2004, consisting of almost 1,200 indisor, including the

‘World Bank's “Country ata Glance” Tables and an lection copy of AD! 200, alo being nade avail: able on CD-ROM, together witha user-fnendly ia- terface wo facilitate dowloading and analysis Dice- tions fr obaining both the blicaion andthe CD- ROM can be found onthe World Bank’ external web site (wou woridbank ong) With iereased demand Forinformasiont monte Pavers Retion St

ny Papers (PRS), national development proarans

Su the Mileniany Developmen Goal, a access

to electronic media widening in Aiea, ADI is ex posted io evolve further, with the goal of offering the

‘host relevant information to moitor development

ail electronic forms We welcome ser fedhack an suggestions for improving ADY in fare yous,

0)

Kian Harolé Geto ChiTFeonomid,Afi Region

Acknowledgments

‘This volume was produces by the Operations! Qual

lity and Knowledge Services ofthe Afi Region, in

callaboation with the Development Data Group of

‘he Development Bconomics Vie Presidency

‘The volume was prepared by team fed by Taga

1 Khan and comprising Joss Detour, Rose Mung,

‘Kara Nou, Joan Pandit, Christophe Reckmoe, and

VildanVerbeck-Desniraydin Valuable guidance was

provide by the Africa Chief Esonomist office The

chapters on national accoums, balance of payments,

trade, and goverment finance draw heey on the

‘work of Word Bank Afise county desks The chap

‘ers on poner, communications and tansporation,

‘orld DeveloprentIndzators database, The chap-

‘ero external debt easily daw fromthe Debt

Reporting System (DRS) of the Mod Bank, while

the chapsr ow environment was eepareé with data

fom the World Resouces Inst, The update for

the chapter on privatization of public enterprises was

provided by Nikolay Madinga, andthe upate thề

Rows The HIVIAIDS tele was prepared with data from the Joi United Navons Programme on HIV AIDS (UNAIDS) In addition, many World Bank tf?

‘rovided information on thei counties or thei 20 omic or sectoral pecaies,

‘Lawrence Masti provided assistance in ein and odacing the volume, while the Worid Bank Omize

‘of the Publisher—in articular Richard A Crabbe, Mary Fisk, and Monika Lynde—prepared and coor inated ial production ofthe book Ore sta sided and ads on be design ant conten of his vole

“ADI 2004 was prodced primarily using the dats

tem Ths too! was programmed fo generate auto- tically ll de table in this volume and ean be used for other publications, Using data warehousing ology, the LDB instamly ecleuates al indicators and aggregates tem once new information is aail- able, This guaranes thatthe most recent data are reflected in his an ature volumes

Preface

Arian Development Indicators 2004 eontinaes the

‘data publican series started bythe Woe Bank in

1999 with African Economic and Financial Data

‘published joiny with the United Nations Develop-

Indicators 1992, 199495, 1998, 1997, 199899, 2000,

2001, 2002, and 2003, These data volumes are in

tended to provide Afticans and thse imtresed in

monitor development programs and ad flows inthe

‘eon, Each ssessive volume provides acess to

tment inthe quality and availabilty ofthe dats

‘The data inthis volune drive foe a vatity of

soures In most ese, the orginal soure is national

sttistial services in Aca Inaditon, many iter-

rational agencies collector compile dat on Arica

and organize atonal data in standardized fame:

‘work This volume draws hemi from such sources

state to help adress problems of ising or ir-

‘consistent dia fom standard soures, Some ofthe

‘wtimaion methods used here cfr from methods used in ote sources This volume azeses these differences in methodologies in the caper ints tions and in the technical nots

In the radon ofthe frst nine volumes, tis data collection is itended to serve asa prime source of

‘cam and non-A salyka and polcymakert vả

‘ontibate to a beter understanding of Africa and ta

Lhe

Gerard A Byam Ditctr, Operations! Quay and Keowiedge Services

‘ia Region

Acronyms and Abbreviations

‘Worl Rank

xếi Acronyms and ABbrevations

—

Introduction

said awa egies sc empirical ta a

be realy used by analy This puiteaton

by Apieon Developme Indicator (D1) 192, 1994

95.1986, 1997, 199809 3000 2001, 2002, 82005

‘smeaopeovide uti point ul tha tsk

previous volumes in this Seis Chit

* Most macroeconomic data (in particular, ational

sccouns, balance of payments, government finaee

ste and trade) reflect daa mained by Work!

"Đenkceunry desks often refered ax operons dt

‘Thewe dala ae ofen tne up wo dte sod offer beer

country coverage than the data stored inthe Banks

‘Analysis Database (SIMA), which were used ìn

publicton Before 1998, SIMA is large database that

‘conan some but ual daa pred Bank sta

produced by UN agencies

+ The soverge of many ofthe dla series has een

joweve,subtantaldaa gaps rem, aeably in yeas such as public emerpeses, gener, and labor

——DẦẦẦDẦ

is an ongoing process, and greater effors and ination support willbe required i eubstantat ma."

‘This volume presents the available relevant dats for 1980-2002, groped in 16 shapes: background at; ational accounts; prices and exchange rte: money an! Baking extra sector extra det comumuniation an ransportion pubic enerpenes labo free and eloymont a ws sea aeons: andenszenmentalndcatrs Char enone) indicators) was once agaie taken fiom the World Resouces Institute's Horld Resources 2002-2004: Decisions for Eank: Balance, Tee and Power

nature ofthe da followed by aso of charts, satisial lables, and technical otes These notes define the mm

2 Iiraducton

companion CD-ROM, known a World Bank Arca

hips bck to 1980, These series wl vide snalyets

with dat coded lp plac thermos recent years ina

steal conten

The data inthis volume inconporate numerous

revisions t ote published previously inthe ei

“There ae several ens fr this

‘hearer voles have Bsn epic with pdt

stil ts or improved estimates In mos cans,

‘hese changes eflest revisions mad by the orga

includes conection of eee ia previous vores

+ Dasa series expressed incon U.S dolla and

exchange rte ue base Yer of 1998; previous

‘Dis were bsedon 1987 exchange rates andre,

+ Some series expressed in constant prices have

been revised a reslt of updated or revised

eta,

5 Astnthe 2003 vung macrosononi dtl

county desk iaformation The diferene is mst

Figures ree consolidated government data sca

[anh cea government data

Considerable effort has est mado stan nd

to harmonize related data rts drawn from diverse

fod definitions difer widely among soures, fll

compaabliycamotbs ensued nthe indeatos mus

be intepeted with care In addition, the stastial

systems in many developing economies are sil weak

“ibich fete the svaiBifY su ai oF he data

‘hoy port Morcover,trcounty ad steers)

compariaons always involve complex techaiesl

asiderabe maryns of enor To provide reasonably

timely data required for meaning! monitoring, the

‘World Bank, the lưernatonal Monetary Fund (IMF),

and other agencies sometimes make estimates onthe

‘pin natonalepetng.eperially Sr the mort reeat

yar, when dita cannot be ey proce hy nations

indicators, and some countries are covered only

—

i using the data and interpreting the indicators, Particularly when makieg comparisons across

srenghened sata! systems throughout the region Asana aid ts interetton an cross-county compan, furs for slevtedndiators reine

with enon in patscuar i cross coaney analysis the chats

Throughout this volume (except when otherwise stated), the symbol *." ndicates that data ate not available or not applicable zero (0) indicates sither zo value oF an insignificant value, that i Jest than one-lf of the smalls unit showa, The abbreviation "MR" indicates “most recent year

‘svalble” Ia Chapter 13, columos headed by a priod (orceae 1993-97 show data forthe lites able

To eitae eon compasions ths book as converted values of many aatlonal series fom the rational esrecistoUS, dollars, sing the Mord Bank Ais mets

Indicators in this volume every fallow standard finns as far spouse and cover year through

3002, depending on the chapter Data Tor 2002 ae -elimanary and thefre maya itera opisnt Xthinandaero# account and dat ay note valle

the tistics Here may be dierent fom hase in other

— E111

‘ice series when ross dost product (GDP) inused {the denominator for there clkvlaHuns, is alweys

‘capresied at market prices (excep in Figure 23) Tal but the Fiat chap, the data are arnged by indieaor to fclitteerourctunty comparisons For country-specific werk, dala est be aranged to sow indicators togetier foreach county

In this volume, the stati tables ae usually srranged a6 time series, Ay country and by country

Inmoaiuelon 3

groups The largest country group is All Africa

consisting of two subgroups: North Africa and

Sub-Sabaran Africa group i shows, excluding South

‘Mica and Nigeria, These two ce sbgrops withing

the SSA group, and correspond tothe Sub-Saharan

Altea and Sub Saharan fica exuding Nigeria groups

shown isthe AEE and D1 1992, whore South Mex

listed separately

‘Annual data sown for country groups a tt

sveages, or medias forth counties iced inthe

soup, asindiested onthe tale These group agrees

ane citer simple arihiesio—wher missng dts ate

rep ot ormising counties Intelatercase, when

‘ales are mibsing for a cout ora yes estimates are

‘ade mina the same sony compostin ofthe

‘rope trove time However, the implicit estate

tnd the agrogatestatsties ae shown only ifthe

coupes or which dats ae availble for a ven year

by benchmarks in 1995, Ths proved is tnd or

may Worl Bank sts! pobsatons

felis importance ef the eounes i the arp ttl

for that indicator, based on simple addition across

counties when the indicator i expressed in easanably

comparable unis Growp averages for anal ratios

(for example, impons 10 GOP) canbe either neghied

or simple (arithnetie)- Usually they ae calevlted fro

the group totals for bob the numerator and the

denominator, which is snsytically equivalent 10

‘slewing weighed averages, where the weight foreach

country is its share in the group total for the

denominator, Smet, ever, whens appropiate

leering represent alu forthe group, these

cual weigh

series levels, aos, growt ates, or means for batt

‘counties and county groups, They ate ether simple verges or average annual peeerige growth ets

“These growth ates abways wee least-squares method andar vtally compote rom reales, In his publication, the east gues growth aes ar compte

‘sing the eel forthe year before the fst year shown

`

LeletAe pelod More speeifiil the eegtession

‘uation tkesthe orm: fog =e +e, whee hiss

‘nations isthe variable, atime anda =Tog¥ and log (1 +a the paactes to bests 5 the

ro enn IF she lensesquares estat of ben

{09} Land multipiedby 10m expressitiaprcentae terms The least-squares growth rate dampens the

sane signa rescu in th ine snes

‘Tyoughout this volume, data for Etioia iach tre tp to 1982, excep when osorwise indicated Mauss data are reported for Hal years ening June

$30 The data are published under the second yar of the

Pbiched under 2001 Therefore, n some ees 6 overnment finance) das for Masri may appear 3 Year compared 2 la yeas pcan, whore dla

‘ere publsed under he fit euro be epring psd

Selected Background Data

ie fst two tables of the volume provide e-_indzators, of some ofthe more important indicators

Selected Background Data 5

Figure 1-1 Development diamonds for all African countries, 2002*

Figure 1-1 (coninued)

9

change)

lo Selected Background Data

Technical notes

Tables

“Table 1-1, Masi indicators The data for his table

age from the World Bank's Satie Information

Management ac Analysis Database (SIMA), except

for aid flows, which are fom tbe Orzansation for

Economic Co-operation and Development (OECD),

‘Geographic Disinbution of Aid Flows to Developing

‘Countries database (see tecrical notes 19 Chapter

12)- Regional aggrezates foc GNP per eat, if ex-

tan and education are weighted by popslation

Population estimate for mi-2002 are Word Bonk

recent population censuses or surveys (aos fom

‘county of byl are geacaly considered 0 be pat

‘ofthe population of ther counry of origin (soe tech

ical oes to Tables 131, 13-4 and 135)

Land area refers othe and warfice ares of coun

‘ny excluding inland waters

‘Gros ational income (GND) per capita figures in

US dollars are calculted according to the Mor

Bonk Ada meshod described below, GNI meses

the total domestic and foreign vale ade claimed

by sen It eomprises GDP (defined inthe note

for Tale 25) plus net factor income from abroad,

hich i the income residents receive from abroad

rents made to aonresidents who contebuted co the

domewic economy The dat se am the Food and

“Agriculture Organization FA)

"The World Bank Atlas method uses a thee-year

average of conversion factors to convert GNI dita,

expressed in dtferent national currencies, 0 com:

‘moa denomination, conventionally U.S, dallas The

“Alda conversion actor for any yea isthe average of

the oficial exchange rat (Tele 3-4) or altenative

conversion factor (Table 3-6) for tat year and for

‘he oo preceding years, fe adjusting them fora

‘rence in eave inflaton between that courtyard

‘he United Stats This three-year average smoothes fluctuations in prices and exchange rates for cack county The resulting GNU in US dolla is divided

by the midyear popaltion forthe latest of the three years to derive GNI per capa

“The folowing formulas describe the procedures for

fect ome (8) and for calelting pr eapta GNI in U.S dollars for

ve

bà Y/N) Hehe

wher E.= cm 0NI ea ans) fo year z= ON dein fr sae men option fir yea and P= US GNI detor or gert

Growth rates of GNI per capita for this table are Shovan in real terms They bwve been calculated by the least-squares meted sng constant GNI pe ait series in 1995 pies in rational urrency (Weld Bank, SIMA) (See also technical notes for Tale 2-19) Life expectaney at birth indicates the number of eem: newborn infnt wold ive f prevailing pat

‘main the ste throughout ts if Figures are World Bank estimates based on date from the UN Popula-

statistical offices Primacy school enrollment i the ratio of eilaren

‘ofall ages eveled in primary school to the popula: tion of children of primary schon age While many

‘counties consider the primary school age w be 6 10

11 yeas thers use diferent age groups These if

Selected Background Dat "

ferent country practices ae also reflect ia the ra-

‘ios Gross eacellment may be reported in excess af

10 percent if some pupils are younger o older han

the country’ standard range of primary schoo age

In practice, caroliment dos not necesaily qual a=

tenance, noe docs remain consan thoughout the

year Data ae foo the United Nations Education,

Scintif, and Carl Organization (UNESCO)

‘Secondary school enrollment isthe ratio of ch:

‘ren of al ages ena in secondary school 0 the

Population of chilren of secondary school age The

definition of secondary school age differs among

counties [ts most commonly considered 1 be 12

1 17 years Data ae fom UNESCO

‘ous net ODA per capita consists of net disburse

sent of fans and grants fom al ffical sources on

concessional financial terns, divided by the midyear

‘Table 1-2, Population Average annval percentage growth shown in this able was called using the least-squares metho

Figures

Figwes in his chapter Figure Il, Life expectaney Table 1-1): access 0 safe wate (Table 13-1); GNI per capita Table 2-19); primary’ school enrollment (Table 1-1,

Figure 1-2, Lisracy rate (Table 13-14); GNI per

‘capita (Table 2-19); populasion growth (Table 1-2)

2 Sideted Background Data

Methodology used for regional aggregations and period averages in Chapter 1

National Accounts

atonal acounts data provide the broadest pic

ture of nation’ economic performance Ne-

tional ageounts give information on the sie-

(GDP) and its components by indasta rigin, GDP

and its components by expedite, an information

‘ovation economic reations withthe outside wal

‘These key sates ae used fr assessing & nation

‘economic condition aa given ie or the ends ina

tions economic performance ove time National

forecasting and policymaking an as such are used

‘Widely by analysts and poieymakes

‘GDP and its components by india origin ae

compile following the widely sed Syste of Na-

‘inal Accounts (SNA) The SNA metho aecunts

fo vewaly all actives penn othe proc of

s0ods andthe provision of services in an economy

by residents and nonresidents, regardless of the all-

‘ation © domestic and foreign claims GDP doesnot

account forthe depeeiaton of ied cata

“Ther are thee mths of compiling GDP figures

Income, expenditure, and production methods Bo-

‘mathod isnot used in most developing court this

volume, GDP and its components by industria origin

se compiled using the production method The three

inagriultie, vale adden inary and valve det

in services (See the technical notes atthe end of this chapter) The national accounts reconstructed

in national esrrencies and in curent prices, Fires reported in this chapter are, hoes, in US dlls,

‘sully converted fom nation eumeny sees tte official exchange rte ihe official exchange rate +

sowsexreme voi, the fea cureny is converte into US dollars by using an atemave conversion fc- toc The comeson factors ued fr this purpose are presented in Table 3-6 Reporting curences in 2

‘common denominator fsa cross county co parisons and aggregations in omy groups

In addition, estimate of GDP and it somponents

by indus origin are converted ito constant ies Reporting figures in constant prices ls eset for

‘monitoring eal changes inthe structure of produce

‘Constant pce series is US, dolarsusea 1995 base year and are convettd fom the national cursney series using 1995 exchange ates As his volume es tublshes a common base year fr all counties, aa-

<< based om years other than 1995 have been partly rebased to 1995 by rescaling constant price series of comporents of GDP

“ Natoma Acconns

sings single base year ase problems when there

fn elative prices, For example, values expessed in

constant U.S, dollars necessarily reflect the exchange

‘ates prevailing dung the base year Whetesubse-

quent exchange rte changes have been substantia

1s they have for many African counties since 1980,

‘comparisons among counties and aggregate trends

willbe atfected, Fo this reason lane, the data should

‘be used with considerable euton,

‘Monitoring resource allocations across sectors in

any given point in tie requires the use of eument

prices, Accordingly, in addition to GDP in eoasant

Brice, GDP in curent prices is provided Following

‘GDP in curent prices are components of GDP by

expenditre Data on consumption investment, and

savings are constructed using the SNA’s convention

‘Conespealy al income is eitier consumed of ved

‘8 such the sum of tal consumption ad gross do-

‘est sving equals GDP

‘When viewed from a production pot of view, by

Aefinition savings equals investment, Investment

‘wheter it represents adios to he stock of capt

cor merely replenishes depreciated capital stock plus

‘et change in the level of ivetores tis Financed

iter through domestic savings or by drawing 00 tbe

‘Savings of foreigner, Data on gros domestic invest

ment a gross domestic savings thus sed ight not

‘only on the natre ofthe domestic inter Aerapeal r=

sostee allocation bt also onthe sie of the resource

2p Gros nation savings, however, indicates the

amount of savings generated by a nation’s residents

"Although this volume icles & eheper on iner-

rational tad, the at that bale of pyres is an

integra pat ofthe national accounts warrant the n=

lusion of the resource balance and its compoaents in

this chapter Moreover, a closer examination ofthe

Fifh edition of the IMF's Balance of Payments

Mana (1993) reflects ditfereacesin concep, de-

nitions, ad lassficatons fromthe UNS SNA geide lines Foe instance, i the SNA factor services tea dered by residents of anocher county ae excluded fom goods and services, but this practice snot mi verally followed, The tables on resource balance, and on values of exports (fee on board {f and mon (cot, insurance, fviht {cif} of goods tnd nonfoctor services i curent US, dlls pro vide a comprehensive and systematic framework for

‘macroeconomic alysis in general, Those interested Jina more specialized and rigorous sty of ttea- tional trade transitions should use the data provided

in Chapter 5

The rate af growth of eal domestic product i an

{is widely monitored Becaure these growth rites are calcolated from nana series, they ae suitable for bth eom-contry comparisons and tend analy or Individual counties Aggregate vakes and trends, however elect the choie of the hase yeas, a8 e8° Plaine above

(Gross national income (GND per capla, Nhi GDP per capita adjusted for changes i interational terms of trge and which include et factor come fom abroad, and total consumption per capita are also widely monitored indicators of economic

‘ropress, When expressed in cument US dallas to facilitate comparison and agereztio, however, the values for these indicators aecessirlyreflet ex change rate fucaations a8 wells underlying eo nomic and demographic changes These fndestors ray be used! with caution for erosscountry om: patson daring any single year They require special sttention when used for td analy,

ate for Chaper 2 re rom the World Bank's coun try desks Estimates are hase on data obained fom

‘who review th quali of national accounts dats a Jnsome instances, help adjust the ion series