Counting people is hard. Here are some readings I’ve come across recently on this, collected in one place for my own edification:
Oliver Kim’s How Much Should We Trust Developing Country GDP? is full of sobering quotes. Here’s one: “Hollowed out by years of state neglect, African statistical agencies are now often unable to conduct basic survey and sampling work… [e.g.] population figures [are] extrapolated from censuses that are decades-old”. The GDP anecdotes are even more heartbreaking
Have we vastly underestimated the total number of people on Earth? Quote: “Josias Láng-Ritter and his colleagues at Aalto University, Finland, were working to understand the extent to which dam construction projects caused people to be resettled, but while estimating populations, they kept getting vastly different numbers to official statistics. To investigate, they used data on 307 dam projects in 35 countries, including China, Brazil, Australia and Poland, all completed between 1980 and 2010, taking the number of people reported as resettled in each case as the population in that area prior to displacement. They then cross-checked these numbers against five major population datasets that break down areas into a grid of squares and estimate the number of people living in each square to arrive at totals… According to their analysis, the most accurate estimates undercounted the real number of people by 53 per cent on average, while the worst was 84 per cent out.”
David Nash’s Nigeria’s Missing 50 Million People argues that (quote) “Nigeria’s official population (~220-230 million) may be significantly inflated and could be closer to 170-180 million (another article claims 120 million) likely driven by political and financial incentives for states”. The comments are insightful too, e.g. David’s comment that Uganda and Burkina Faso have the opposite problem (“in Burkina Faso the issue was that GDP per capita numbers were calculated from industrial output divided by population estimates so in order to look good, local government had an incentive to underestimate population so they seemed richer”), and Sjlver’s comment comparing AMF’s population data from distributing bednets to every household to UNFPA data; I’ve copied their table below:
Counting people is hard. Here are some readings I’ve come across recently on this, collected in one place for my own edification:
Oliver Kim’s How Much Should We Trust Developing Country GDP? is full of sobering quotes. Here’s one: “Hollowed out by years of state neglect, African statistical agencies are now often unable to conduct basic survey and sampling work… [e.g.] population figures [are] extrapolated from censuses that are decades-old”. The GDP anecdotes are even more heartbreaking
Have we vastly underestimated the total number of people on Earth? Quote: “Josias Láng-Ritter and his colleagues at Aalto University, Finland, were working to understand the extent to which dam construction projects caused people to be resettled, but while estimating populations, they kept getting vastly different numbers to official statistics. To investigate, they used data on 307 dam projects in 35 countries, including China, Brazil, Australia and Poland, all completed between 1980 and 2010, taking the number of people reported as resettled in each case as the population in that area prior to displacement. They then cross-checked these numbers against five major population datasets that break down areas into a grid of squares and estimate the number of people living in each square to arrive at totals… According to their analysis, the most accurate estimates undercounted the real number of people by 53 per cent on average, while the worst was 84 per cent out.”
David Nash’s Nigeria’s Missing 50 Million People argues that (quote) “Nigeria’s official population (~220-230 million) may be significantly inflated and could be closer to 170-180 million (another article claims 120 million) likely driven by political and financial incentives for states”. The comments are insightful too, e.g. David’s comment that Uganda and Burkina Faso have the opposite problem (“in Burkina Faso the issue was that GDP per capita numbers were calculated from industrial output divided by population estimates so in order to look good, local government had an incentive to underestimate population so they seemed richer”), and Sjlver’s comment comparing AMF’s population data from distributing bednets to every household to UNFPA data; I’ve copied their table below:
Good links. My favorite example is Papua New Guinea, which doubled their population estimate after a UN Population Fund review. Chapter 1 of Fernand Braudel’s The Structures of Everyday Life is a good overview of the problem in historical perspective.
Wow, that’s nuts. Thanks for the pointer.