Poor Numbers

Morten Jerven

Description

One of the most urgent challenges in African economic development is to devise a strategy for improving statistical capacity. Reliable statistics, including estimates of economic growth rates and per-capita income, are basic to the operation of governments in developing countries and vital to nongovernmental organizations and other entities that provide financial aid to them. Rich countries and international financial institutions such as the World Bank allocate their development resources on the basis of such data. The paucity of accurate statistics is not merely a technical problem; it has a massive impact on the welfare of citizens in developing countries.Where do these statistics originate? How accurate are they? Poor Numbers is the first analysis of the production and use of African economic development statistics. Morten Jerven's research shows how the statistical capacities of sub-Saharan African economies have fallen into disarray. The numbers substantially misstate the actual state of affairs. As a result, scarce resources are misapplied. Development policy does not deliver the benefits expected. Policymakers' attempts to improve the lot of the citizenry are frustrated. Donors have no accurate sense of the impact of the aid they supply. Jerven's findings from sub-Saharan Africa have far-reaching implications for aid and development policy. As Jerven notes, the current catchphrase in the development community is "evidence-based policy," and scholars are applying increasingly sophisticated econometric methods-but no statistical techniques can substitute for partial and unreliable data.

Sujets

• Political economy

Informations

• Publié par: Cornell University Press
• Date de parution: 24 janvier 2013
• Nombre de lectures: 0
• EAN13: 9780801467615
• Langue: English
• Poids de l'ouvrage: 1 Mo

Extrait

PoorNumbers

AVolumeintheSeries CornellStudiesinPoliticalEconomy edited byPeter J. Katzenstein Alistoftitlesinthisseriesisavailableatwww.cornellpress.cornell.edu.

PoorNumbers

HowWeAreMisledbyAfricanDevelopment Statistics and What to Do about It

MortenJerven

CornellUniversityPress IthacaandLondon

Cornell University Press gratefully acknowledges receipt of a subvention from the University Publications Committee’s Rapid Response Fund, in the Office of the VicePresident for Research, Simon Fraser University, which assisted in the publication of this book.

Copyright © 2013 by Cornell University

All rights reserved. Except for brief quotations in a review, this book, or parts thereof, must not be reproduced in any form without permission in writing from the publisher. For information, address Cornell University Press, Sage House, 512 East State Street, Ithaca, New York 14850.

First published 2013 by Cornell University Press First printing, Cornell Paperbacks, 2013 Printed in the United States of America

Library of Congress CataloginginPublication Data

Jerven, Morten, 1978–  Poor numbers : how we are misled by African development statistics and what to do about it / Morten Jerven.  p. cm  Includes bibliographical references and index.  ISBN 9780801451638 (cloth : alk. paper)  ISBN 9780801478604 (pbk. : alk. paper)  1. Economic development—Africa, SubSaharan—Statistics. 2. National income—Africa, Southern—Accounting. 3. Economic indicators—Africa, SubSaharan. 4. Africa, SubSaharan—Economic conditions—Statistics. 5. Africa, SubSaharan—Statistical services. I. Title.  HC800.J47 2013  338.967—dc23 2012045248

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Cloth printing Paperback printing

10 9 8 7 6 5 4 3 2 1 10 9 8 7 6 5 4 3 2 1

ListofIllustrations Preface Acknowledgments

Introduction

Contents

1.WhatDoWeKnowaboutIncomeandGrowthinAfrica?

2.MeasuringAfricanWealthandProgress

3.Facts,Assumptions,andControversy:Lessonsfrom the Datasets

4.DataforDevelopment:UsingandImproving African Statistics

Conclusion:DevelopmentbyNumbers

AppendixA.AComparisonofGDPEstimatesfrom the World Development Indicators Database and Country Estimates

vii ix xv

1 8 33

55

83 109

123

v i C o n t e n t s

AppendixB.DetailsofInterviewsandQuestionnaires

Notes References Index

139 141 163 179

Illustrations

Tables 1.1.AfricaneconomiesrankedbypercapitaGDP (in international USD) 1.2.Availabilityofnationalaccountsdataatstatisticaloffices in Africa and comparison of countrylevel GDP and World Development Institute GDP 3.1.Nigerianpopulationincensusyears(inmillions) 3.2.EstimatingNigerianpopulationgrowth(%) 3.3.Annualpercentagegrowthinproductionofmajorfood crops in Nigeria, 1970–1982 3.4.TotalfoodcropproductioninNigeria,1981–1990(%growth) 3.5.TotalcashcropproductioninNigeria,1981–1990(%growth) 3.6.EstimatedoutputofmajoragriculturalcropsinNigeria for the year 1993–1994 (in thousands of tonnes) 3.7.Estimatedcorrelationmatrixofannualgrowthrates for Tanzania, 1961–2001 3.8.Averageannualgrowthaccordingtodifferentdatasources, Tanzania, 1961–2000

18

24 59 60

62 63 63

64

65

67

v i i i I l l u s t r a t i o n s

3.9.AnnualrateofeconomicgrowthinTanzania 1985–1995 (%) 4.1.SummaryofdataprovidedinIMFandWorldBank reports on national statistical capacity in subSaharan Africa

Figures 3.1.AnnualrangeofdisagreementinGDPgrowthrate, Tanzania, 1961–2001 3.2.GDPgrowthatconstantprices,Tanzania,1961–2001

71

101

67 68

Preface

Howdotheyevencomeupwiththesenumbers?Thatwasthequestion I wanted to answer. It was 2007 and I went to Zambia to do fieldwork for my doctoral thesis in economic history. I wanted to examine how national income estimates were made in African countries. I was struck by the der elict state of the Central Statistical Office in Lusaka. The planned agricul tural crop survey was being delayed by the need for car repairs, most of the offices were dark, and the computers were either missing or very old. The national accounts division had three employees, of whom only one was regularly in the office while I was visiting. No one at the office could account for how the income estimates had been made more than a decade ago. In the library there was a dearth of publications and no record of any activity that may or may not have taken place in the late 1970s, the 1980s, and the early 1990s. ThedataandmethodsusedtoestimateZambiannationalincomehad last been revised in 1994. A short report on methodology had been pre pared, but it was unpublished and was circulated internally as a manual for the national accountants. It revealed the real state of affairs of national income statistics in Zambia. I was surprised by the lack of basic data and the rudimentary methods in use. Regular and reliable data were available