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Poor Numbers

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Morten Jerven 作者
译者
2013-2-19 出版日期
187 页数
USD 22.95 价格
Cornell Studies in Political Economy 丛书系列
9780801478604 图书编码

Poor Numbers 在线电子书 图书标签: 经济学  经济  English  统计  社会学  英文原版  经管——经济管理  Morten   


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发表于2024-06-29


Poor Numbers 在线电子书 epub 下载 mobi 下载 pdf 下载 txt 下载 2024

Poor Numbers 在线电子书 epub 下载 mobi 下载 pdf 下载 txt 下载 2024

Poor Numbers 在线电子书 pdf 下载 txt下载 epub 下载 mobi 下载 2024



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非常有趣的内容了 从来没有想过数据背后的Credebility...

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非常有趣的内容了 从来没有想过数据背后的Credebility...

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非常有趣的内容了 从来没有想过数据背后的Credebility...

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非常有趣的内容了 从来没有想过数据背后的Credebility...

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非常有趣的内容了 从来没有想过数据背后的Credebility...

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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.

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