not sure how accurate wikipedia is here, but I've seen this claim elsewhere
https://en.wikipedia.org/wiki/Disposable_and_discretionary_i...
Apparently what I meant above is discretionary income, which would include all fundamental bills/payments such as healthcare etc. Disposable income does not include those, it only includes income plus direct payments from the government.
What would interest me is discretionary income, which includes healthcare, mortgages etc. plus education, public transport, daycare, energy and I'm possibly forgetting some fundamental things.
"Disposable" is very much misleading here. If you have 1000$ "disposable" income but you still have to pay for or cannot afford all of the mentioned things then you are in worse shape than someone who has 500$ "disposable" income but can lean on public infrastructure and subsidies for those things. The difference can be quite massive.
The reason I'm specifically suspicious of the US here is that public infrastructure seems to be quite a bit behind and fundamental things like healthcare is substantially more expensive than in some of the most developed countries.
>The following table represents data from OECD's "median disposable income per person" metric, which includes all forms of income as well as taxes and transfers in kind from governments for benefits such as healthcare and education and is equivalised by dividing by the square root of household size. This metric, in addition to using a median rather than a mean, uses "data calculated according to the new OECD terms of reference"; compared to previous terms of reference, these "include a more detailed breakdown of current transfers received and paid by households as well as a revised definition of household income, including the value of goods produced for own consumption as an element of self-employed income." As OECD displays median disposable incomes in each country's respective currency, the values were converted here using the World Bank's PPP conversion factors, accounting for each country's cost of living in the year that the disposable median income was recorded. Unless noted otherwise, all data refers to 2019. Data are in United States dollars at current prices and current purchasing power parity for private consumption for the reference year.
[1,2,3,4,5,6,7,8,9,10]
[0,0,0,0,5,6,11,11,11,11]
Another example that I know fully well is Brazil: the mean is 8,560 BRL and the median is 8,220 BRL for monthly salaries, that is, very close. But these monthly salaries are known to vary widely from 2,170 BRL (USD 417) to 38,200 BRL (USD 7349), so hardly anyone is really making 8220 or close to that.
Yes, they do. I am a PhD mathematician with decades of work using these tools. I am quite clear on the meanings and shortcoming of all sorts of indicators. I am also aware how real world data trends instead of cooked up examples that don't match reality.
Median is a common value used by economists precisely because it more likely shows what a person makes as opposed to the mean, especially in cases of high inequality.
> If you don't believe
Yes, you can make up all sorts of nonsense. Not a single country follows the distributions you made up.
>Another example that I know fully well is Brazil:
You conclusion does not at all follow from your claim. Or from the actual data.
> so hardly anyone is really making [the median] or close to that
Well, by definition, over half of people make the median or more. Is that hardly anyone?
If you look at the data [1] (income by decile in Brazil), besides the 50% making median income or higher, another 30% of the people make within 30% of median. That leaves 20% of the people making under 70% of the median income.
What is your definition of "hardly anyone"?
Look at the data. Clearly median is much more accurate than mean for explaining how much people make, as this example showed.
[1] https://www.statista.com/statistics/1251075/average-monthly-...
???
Did you compute them? do you know how?
The Brazil data I just posted has median around 1383, mean of 2308.36, which is 65% larger.
An interesting test: compute with details the median and mean of the data I just posted. I already gave you the answers. I think you don't understand these terms.
That you don't like the outcome of the most two commonly used indicators is not the fault of the indicators - it's the result of you wanting to put things in the data that are not there.
Your claim about Brazil having "hardly anyone", which I showed was nonsense, shows exactly what you're trying to do - put things in data that simply are not there (and in the case of your claim, are mathematically invalid no matter the income distribution).
>Now, if you start using the percentiles as you're doing here, then you are looking deeper into the data
Percentiles have the exact same graph as dollars, or pesos, or anything you desire.
% = exact$ / total $.
So they have the exact same graph, merely a different label. Do you understand this? The % of total income versus income shows nothing different, there is no "deeper into the data" or "more accurate and reflective of reality" for this.
It's simply scaling ALL the numbers by a constant. No one changes place. No income compared to another changes in ratio. There is no subtle nuance pulled out of anywhere.
>which just proves my point.
Is your point that you don't know what any of these terms mean? Then yes, you proved your point. Mean, median, percent, ratio, decile, all the terms related to income - you have screwed them all up beyond reason.
Don't bother replying until you answer the questions I poste last time:
Do you admit 50% of people in Brazil make median income or more? What amount of people did you mean by "hardly anyone"?
Also answer: is the graph of income by % the same geometric shape as income by $, or yen, or peso, or any currency you care to pick, thereby giving no "looking deeper into the data"?
You're pretending to not understand what I said. The figure for median income of 8K is very different from what most people make in Brazil, because a lot of people will make less than that, and a lot make more than that. So, the median has little value, because there is just a small group that makes close to that figure compared to the other groups that make more or less. It is a society with large inequality that is polarized on the two sides, instead of concentrating on the middle. My point is that this measure is more useful for societies that have more equality, such as a few countries in Europe. For the US, the median is less and less useful to get a clear picture.
I see you've moved from "hardly any" to "a lot". Nice goal post move. I bet if you look at the actual data enough you might get to what the data shows.
The majority of people, for every country for which there is data, are close to the median income. End of story. You so far have posted so many simple math errors that it's hard to know where you got your understanding of these things.
> It is a society with large inequality that is polarized on the two sides, instead of concentrating on the middle.
There is no such country. Don't believe me? You can check this yourself:
[1] has all the data to check. Select the datasets showing income share. Select them, pick years, say 2016-2021. Download the CSV. There are 114 countries in the dataset for which all 5 quintiles of income are available for recent years.
For each compute the median. Then look at how close the middle 60% of the people are to the median.
If you really want to see that distributions are not what you believe, graph every single one. If you need tools, jupyterlab using python, pandas, and matplotlib make this task pretty easy.
In EVERY single one you will find the majority of people are decently close to the median. I just checked. Do it yourself so you stop believing all this mystical non-existent income distribution where people are not majority near the median.
I know you're convinced there are income distributions like those you made up, but there simply are not. It is empirical fact.
So, if you want to continue to claim what you are - do what I told you to do, pick the country you think best supports your claim, and post the actual data.
Until then you are simply wrong.
This is why economists, even those working in inequality, start with the median income when discussing income. It is the best point indicator of what the majority of people in a society earn.