Poor Numbers: How We Are Misled by African Development Statistics and What to Do about It

209 Pages·2013·0.99 MB·English

by  Morten Jerven

Poor Numbers
A Volume in the Series
Cornell Studies in Political Economy
edited by Peter J. Katzenstein
A list of titles in this series is available at www.cornellpress.cornell.edu.
Poor Numbers
How We Are Misled by African Development
Statistics and What to Do about It
Morten Jerven
Cornell University Press
Ithaca and London
Cornell University Press gratefully acknowledges receipt of a subvention
from the University Publications Committee’s Rapid Response Fund, in
the Offi ce 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
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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 10 9 8 7 6 5 4 3 2 1
Paperback printing 10 9 8 7 6 5 4 3 2 1
Contents
List of Illustrations vii
Preface ix
Acknowledgments xv
Introduction 1
1. What Do We Know about Income and Growth in Africa? 8
2. Measuring African Wealth and Progress 33
3. Facts, Assumptions, and Controversy: Lessons from
the Datasets 55
4. Data for Development: Using and Improving
African Statistics 83
Conclusion: Development by Numbers 109
Appendix A. A Comparison of GDP Estimates from
the World Development Indicators Database and
Country Estimates 123
vi Contents
Appendix B. Details of Interviews and Questionnaires 139
Notes 141
References 163
Index 179
Illustrations
Tables
1.1. African economies ranked by per capita GDP
(in international USD) 18
1.2. Availability of national accounts data at statistical offi ces
in Africa and comparison of country-level GDP and
World Development Institute GDP 24
3.1. Nigerian population in census years (in millions) 59
3.2. Estimating Nigerian population growth (%) 60
3.3. Annual percentage growth in production of major food
crops in Nigeria, 1970–1982 62
3.4. Total food crop production in Nigeria, 1981–1990 (% growth) 63
3.5. Total cash crop production in Nigeria, 1981–1990 (% growth) 63
3.6. Estimated output of major agricultural crops in Nigeria
for the year 1993–1994 (in thousands of tonnes) 64
3.7. Estimated correlation matrix of annual growth rates
for Tanzania, 1961–2001 65
3.8. Average annual growth according to different data sources,
Tanzania, 1961–2000 67
viii Illustrations
3.9. Annual rate of economic growth in Tanzania
1985–1995 (%) 71
4.1. Summary of data provided in IMF and World Bank
reports on national statistical capacity in sub-Saharan Africa 101
Figures
3.1. Annual range of disagreement in GDP growth rate,
Tanzania, 1961–2001 67
3.2. GDP growth at constant prices, Tanzania, 1961–2001 68
Preface
H ow do they even come up with these numbers? That was the question
I wanted to answer. It was 2007 and I went to Zambia to do fi eldwork 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 Offi ce in Lusaka. The planned agricul-
tural crop survey was being delayed by the need for car repairs, most of
the offi ces 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 offi ce while I was visiting. No one at the offi ce 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.
T he data and methods used to estimate Zambian national income had
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