How is world population calculated? And how accurate is the number? Is it possible that the number can be entirely wrong?
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I always wonder how they count animal populations, especially small ones like ants. There’s no census, and who’s out there counting?
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How reliable would numbers from countries like China or North Korea? Do we actually get a number from NK?
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The truth is, we actually don’t know how accurate the estimate is because we’d have to know the near exact number in a sufficiently large representative area to compare it with the estimate. My guess is it can be several percentage points off, though certain undercounts (mentioned by others) can potentially be compensated by the folks with multiple citizenships that presumably are reported by each home country.
In general, information about the world population is aggregated from information about each country’s population. From there, each country usually either conducts regular censuses or has some form of national registration to track people (or both) as it’s a very important part of running a government.
These estimates are only updated so often though (IE, the US conduct it’s census only every 10 years), so there is a little math done to the number to get the current estimate. There are three big factors that matter when creating that current estimate: Mortality rate, Birth rate, and Migration. The first obviously creates downward pressure on the number, the second upward, and the third can be either depending on if the new flow is out of or into the nation.
How accurate is it? Well, the UN is one of the better sources, and they estimate their margin of error to within 1% or so for the entire world. It varies HIGHLY depending on the country though, with less developed nations and especially wartorn nations being incredibly difficult to estimate due to difficulties in conducting censuses, and highly developed nations being very accurate. Broadly speaking, you can trust the numbers though and there is very little to no chance that the number can be entirely wrong, unless you are getting a number from a shady source.
My understanding is there’s a roll-call every four years where everyone says their name and a guy with a clipboard writes it down. If a child is born, the parents call out “girl” or “boy” and if someone dies a relative calls out “dead one!”
Normally on these things what you are after is a trend. A certain number is not that relevant, just to have a ballpark will give enough information so humans can take decisions based on it. I hardly doub0t it is completely wrong, but trying to be more exact won’t provide much more relevant information for humans to make better decisions.
Population estimates are “guesses” with error factored in. Let’s say you had to estimate how many hairs were on your body. This is a seemingly impossible task…if you would like to be exact. Hairs are being added and removed by the second so to approach this problem we guess really a range of numbers.
To calculate that range you might pick a fixed unit (e.g. hairs per square inch of your body). You wake up one morning and you count the hairs on randomly selected square inches of your body. You do this several times under different conditions (e.g. time of day or area if your body).
You may find that some of the factors greatly impact the density of hair. These factors need to be collected too (e.g. proximity to your head). The factors can be used to weight you’re overall calculation and predict counts that are missing or you’re less sure about.
You can calculate how much your guesses vary under similar conditions. Let’s say one day you count 75 hairs/square-inch then another day 120 hairs/square-inch. You assume this is due to randomnesses. Now you can calculate an overall average and a range around that average (based on how much your sample estimates varied).
Now given you have an average estimate for your unit of analysis (hairs/square-inch), you meticulously calculate the number of square inches on your body (also an estimate with error). These are aggregated to determine the total number of hairs. However, this isn’t a single number, it’s a range based on how much your numbers varied when you collected data. We tend to communicate it as a single number because it’s easier to interpret.
Initial data collection is really important because if you aren’t identifying the factors that affect your estimates (let’s say you didn’t take different parts of the body into account) or aren’t appropriately sampling in a way that is representative of the population (if you only took measurements for your head as opposed to the different areas of the body)- your overall estimate will be flawed.
I’ve worked with census data (ACS data) and the measurement accuracy is questionable. The amount of personnel, expertise, and money needed is substantial, yet it’s clear the government doesn’t invest as they should.
This is extremely important because: 1) informs political polls and predictions (which have been subpar in terms of prediction); 2) Prediction of crime or domestic terrorism; 3) pretty much any prediction made about people on a macro-level.
I challenge all of the young-bloodz about to head of to college to look into measurement and statistics. We need more passionate minds in the field.
One thing not mentioned is that a lot of developing countries have a huge incentive to over-report their populations because the foreign aid they receive from more wealthy countries is linked to population. And, frankly, I’m not sure I trust the UN to do more than repeat what their member states say. So it depends on the source for the number. If it comes from the UN, you have this problem. If it comes from somewhere using formulas like the logistic differential equation mentioned here, it’s based on a guess of fertility rates that we don’t know is right. They all mostly agree, but their only source of ground truth is each other, so they could be agreeing with each other but not agreeing with reality. The estimates are probably mostly right, but probably off by more than their reported margins of error would have you believe.
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