How do they even come up with these numbers? That was the question that I wanted to answer. It was 2007 and I went to Zambia to do the 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 derelict state of the Central Statistical Office in Lusaka. The planned agricultural 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.
The 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 A short report on methodology had been pre- pared, but it was unpublished and was circulated internally as a manual for the national accountants.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 only on government finances and the copper sector. The entire agricultural sector was accounted for by observing trends in crop forecasts for eight agricultural commodities. For the rest of the economy there really was no usable data. The construction sector was assumed to grow at the same rate as cement production and imports. Retail, wholesale, and transport sec- tors were all assumed to grow at the same rate as agricultural and copper production, while business services were assumed to grow at the same rate as trade and transport.
Poor Numbers: How We Are Misled by African Development Statistics and What to Do About It
by Morten Jerven
Cornell Studies in Political Economy
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.
(sk)
「統計の数字がいい加減だということに驚く人がいる」ということに驚いてしまう。
いい加減なのは、なにもアフリカに限ったことではない。
統計を「作る」のがパブリック・セクターであるという本質を見て、それでも信頼するというのであれば、もう「勝手に信じてください」と言うしかない。
先進国が使う統計手法というものが、どういうふうにでも説明をできる道具だということを考えれば、統計が都合よく使われるのはごく自然のことといえる。
統計に騙されるのがいけないのではない。統計を信じるのがいけないのだ。