Monday 14 October 2013

[U156.Ebook] Ebook Download Poor Numbers: How We Are Misled

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Poor Numbers: How We Are Misled

Poor Numbers: How We Are Misled



Poor Numbers: How We Are Misled

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Poor Numbers: How We Are Misled

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.

  • Sales Rank: #727452 in Books
  • Brand: imusti
  • Published on: 2013-02-19
  • Released on: 2013-01-24
  • Original language: English
  • Number of items: 1
  • Dimensions: 9.00" h x .52" w x 6.00" l, .62 pounds
  • Binding: Paperback
  • 176 pages
Features
  • Cornell University Press

Review

"Increasingly, scientists turn to the large statistical databases of international bodies when testing favoured hypotheses to control for growth and economic development. They might hesitate after reading Poor Numbers. . . . This book offers fascinating, disturbing insights for anyone interested in the role of numbers in the social sciences. For those using global economic databases, it should be required reading."―Nature (11 July 2013)



"This important book attempts to systematize what most quantitative practitioners in Africa generally understand: African macroeconomic data are poor. . . . Using a variety of sources that include current surveys of in-country statistical collection agencies and firsthand historical accounts, Jerven outlines several root causes of the data problem, which include Africa's colonial heritage and the more recent, structural adjustment policies. He continues his analysis by exploring how data are consciously shaped by both local and international politics and international aid agencies. Specifically, Jerven is critical of World Bank transparency and its unwillingness to provide him with quantitative methodologies of its official data compilation. . . . This volume opens up a venue for a research paradigm that could lead to much-needed improvements in the collection of African data. Summing Up: Highly recommended."―Choice (August 2013)



"Poor Numbers is a powerful little book…, highlighting the risks of making political inferences solely based on statistical analysis… Although an economist by training, Jerven's clear prose without jargon helps make Poor Numbers reach a wider readership. It is imperative to note that his is not a simple criticism of quantitative methodology, but of the confidence one has in the findings of quantitative analysis without due attention to the quality of the data. In this sense, even those who have no scholarly interest in African development economics would find the findings and conclusions pertinent to the foundational debates on the role of methodology and theory in political science."―Jan Erk, European Political Science (November 2014)



"[Poor Numbers]is a useful reminder of the dubious information content of economic indicators generated by national accounting systems of sub-Saharan African states. I recommend the book to all scholars and researchers who contemplate the use of data generated by national accounting systems of sub-Saharan African countries."―Rolf A.E. Mueller,Quarterly Journal of International Agriculture(2015)



"I found Poor Numbers illuminating and disturbing at the same time―I think that is exactly what Morten Jerven intended. It is well written, even elegant in some places. Jerven's recommendation that more funding be put into statistical services to do baseline surveys and field-based data collection makes a lot of sense."―Carol Lancaster, Dean of the School of Foreign Service and Professor of Politics, Georgetown University, author of Aid to Africa: So Little Done, So Much to Do



"In Poor Numbers, Morten Jerven takes on the issue of inaccurate macroeconomic data in Sub-Saharan Africa. First, by describing collection methods, he shows quite convincingly that the data are pretty dreadful, and perhaps more damning, that they may include systematic and predictable flaws linked to the way in which they are collected and aggregated. Jerven demonstrates that basic national accounts data are too poor to assess very basic characteristics of African economic performance since independence. This short elegant book is fascinating and strikes me as a must-read for any social scientist interested in African political economy and policy."―Nicolas van de Walle, Cornell University, author of African Economies and the Politics of Permanent Crisis, 1979–1999

About the Author

Morten Jerven is Assistant Professor in the School for International Studies at Simon Fraser University.

Most helpful customer reviews

4 of 4 people found the following review helpful.
Bad data
By Dascholar
Bravo to Morten Jervens on a fine and informative book. May the stats get better!!!!

I just finished reading this book. Since I had read other things by author, I did not discover anything that I did not already know. For those who are not aware of his work, this book will come as quite informative and for some hopefully a wake up call. My only quibble with the book is that it too nice. Probably, this is a question of personality and style. He references epistemological and methodological problems that arise from using bad data (bad plus noisy data is, in my view, a priori junk); however, he does not, borrowing from a Seinfeld episode, bother to name names as much as I think he should have. In my view, there is no justification for someone who is methodologically sophisticated using bad data to draw inferences about whether institutions/regime types impact economic development and public goods distribution. There is no basis for claiming that there is a positive and robust relationship between post-structural adjustment, democratization and an uptick in economic growth in Africa based on national income data. As Jerven shows clearly, the problems with the data is just too much to rest such an inferential oomph onto. Even with pristine data, this proposition is problematic. It is down right silly with bad data! In a nutshell, I like the book a lot and see it as having a major impact but I would have liked it to have been more forceful in its criticism of those who have used bad data and should have known better

2 of 2 people found the following review helpful.
Necessary work on data quality and its implications
By Leo
Since Morgenstern, few works have examined extensively the accuracy of economic observations. This book do it for Africa, but only for national accounting. It deals with the (extreme) deficiencies of african GDP estimations, and how these (should) affect the (in)conclusions about development. If you plan to use african data, this is a mandatory reading. If you do not plan to use african data, but you do work with cross section macro variables from FMI, WB or Penn Tables, you still should read this to get a real feel of how unreliable these datasets can be.

0 of 0 people found the following review helpful.
Statistics are Used to Make Judgements; Unfortunately, Many of them are Little Better than Guesswork
By Al Miller
This is an essential book for anyone interested in Africa. We make judgements all the time based on what are at best "guesstimates." This books gives the inside story on how statistics are arrived at by the experts. It makes one wonder about how African policy is decided on by the various foreign offices in developing countries. .

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