please note original question was asking about how accurate is the articles data and that is partly what my answer is answering. I am also working on the assumption that the question means: "Does the data the answer finds imply poor Americans are actually better off than average citizens of most other wealthy nations?" rather than asking if the article is implying poor people in America are richer on average than the average person of other wealthy nations. because the article is clearly stating and implying that the American poor is wealthier than the average person in almost all other wealthy nations. I personally don't see a good reason to take the articles data which agrees with the article to then prove the article is using it's own data correctly. In short I think the original question is asking if the data found by the answerer comes to the same conclusion as the article.
This answer looks at the specific claim in the article that:
US low-income households greatly underreport both their income and non-cash benefits in such surveys.
That is false.
The reason I cite this is because this study THE DISTRIBUTION OF UNDERREPORTED INCOME: WHAT WE CAN LEARN FROM THE NRP (February 2023) research for which was conducted while the authors were, employees at the U.S.
Department of the Treasury and the Internal Revenue Service.
The above quoted text is proven false by the following quote from the linked research paper:
While the likelihood of having underreported income increases at higher reported income levels, the average ratio of underreported to reported income actually declines as reported income increases. In addition, underreporting of business income is substantially greater than that of income subject to information reporting and is especially concentrated among taxpayers reporting business losses.
Please Note: as wages decrease, making a rounding error or mistake will increase the disparity % between reported and underreported incomes. The important point is that the poorer a demographic is, the fewer people per capita underreport.
To give an example: if you made $1000 but simply didn't bother to file taxes, or are homeless and just didn't bother to file, then the ratio of unreported income will be 100%. If you make $10,000 and accidentally stuffed a decimal on your calculator and reported only $1,000 you will be underreporting by 90%. On the flip side if someone who made $1,000,000 fails to report 10 times more money than the $10k individual made all year, a mere $100,000, they would only show a 10% discrepancy between their total and unreported incomes. This percentile shrinks further the more money is made.
One must also consider that people in the bottom 0-20 quintile are not going to have the same resources at tax time as people in the higher quintiles and so may be more prone to innocent mistakes. This is demonstrated in the following graph from the cited study:
What the Just Facts article quote doesn't take into account is the fact that poorer people are going to fall into incomes that are auto auditable by agencies such as the IRS. They (the IRS) have the systems in place to cross reference monies and services given by federal agencies, banks, credit cards, and employment reporting from employers. These people are also far less likely to be engaged in money generating ventures that are harder for the IRS to automatically track such as privately owned businesses, property rent income and royalties, as shown in the following chart:
There is additional supporting evidence that the original article is not based on reliable data. The below chart shows the unreported net income of different income levels and makes it clear that poor people account for very little unreported income.
Average Net Unreported Income Discovered in TCMP and NRP Audits, 1988-2013
Notes: Figures are based on the averages of the 1988 TCMP file, and the 2001 and 2006 through 2013 NRP files and converted to 2013 levels using per capita personal income.. Black lines show the results when returns are ranked by reported total income. Grey lines show the results when returns are ranked by corrected total income. Dashed lines show the results when returns are ranked by total positive income. Returns with negative total incomes are a subset of the bottom quintile, the rest of which is in the group labeled 0-20. Average dollar values in Figure 1D are for tax returns with a change in reported income.
This next chart is probably the best one, showing that both bottom quintiles are the most accurate per capita in reporting their incomes.
Please note that negative income usually means someone is running a business or starting a business or having a bad year while in business or dealing with business debt or trying to scam the IRS by writing off their brand new yacht / mansion / Ferrari as a business expense. None of that category should be confused with the 0-20 and 20-40 bottom quintiles.
That one phrase in particular in the posted article stood out to me and I wanted to see what, if anything, it could be based on. I found that it is twisted and/or based on unreliable data at best or at worst simply fabricated. This certainly doesn't bode well for an article based off a website called "Just Facts". I do know I put in a lot of effort to debunk that one phrase however what I gathered is the gist of their article, and one of the main points to @Horrendous Hexapods' question, stating there is a ton of unrecorded money that the US poor population has hidden somewhere, thoroughly debunked by a cursory examination of official data.
One thing I was trying to (but was unable to) find is concrete data that homeless people do not get counted in the money calculations and slip through the cracks, becoming undocumented poor people.
Please note there is a lot more data including the original numbers used for their calculations in the article I cited.
The above data addresses "The study also cites other studies which state that apparently there is a sharp rise in low-income households underreporting their income." that portion of the question and "I just wanted to ask how reliable this study is." that portion proving the articles data is unreliable and the phrase from the original question false.
This section is going to increase the data showing how unreliable the data in the Just Facts article is. We will be looking at the headline of the article "The Poorest 20% of Americans Are Richer on Average Than Most European Nations" and "if the US “poor” were a nation, it would be one of the world’s richest." and "In reality, the US is so economically exceptional that the poorest 20 percent of Americans are richer than many of the world’s most affluent nations."
please note I chose 2017 for the following data since the article posted in the question was published august 2019 and should have had access to the following data at that time. I am not cherry picking any particular point in time I am simply using data that is at least 1 year older than the articles publishing date and at the end of that year as most things are calculated using the end of the year.
the chart below is showing the total wealth of the population in the first income quintile using data from https://www.federalreserve.gov/releases/z1/dataviz/dfa/distribute/chart/#quarter:135;series:Net%20worth;demographic:income;population:11;units:levels;range:2011.4,2023.3
as you can see the total wealth for the us population was 2.5 trillion usd at that point in time
the below images are from https://databank.worldbank.org/source/wealth-accounts/Type/TABLE/preview/on and are sorted to show countries total wealth from wealthiest to least wealthy in 2017 set to constant 2018 usd.
please note I am unsure if the previous graph is using constant 2018 usd ($2.5T) or 2017 usd ($2.56T) or 2017 usd inflation adjusted to match todays dollar ($2.05T) for the sake of argument I will use the number that makes the article look best $2.56T (that is $2.5T 2017 usd adjusted to match the 2018 usd list below) for comparison purposes. Also i may be incorrectly understanding what constant 2018 usd means please correct me if I am as I just looked it up.
as you can see thee fictitious nation of the poor would fall between Qatar and Portugal and be the new 47th nation falling far short of beating out most of the worlds wealthiest nations. However comparing these statistics in this way is flawed due to the fact that there is a population discrepancy. To give an explanation if I had made a nation consisting of 300 trillion individuals who all had $1 usd to their name this new fictitious nation would beat out the us in total wealth. This data isnt very useful when you are trying to compare like data to like data. instead we need to calculate per capita wealth. If we do that with my fictitious 300 trilling $1 strong army we have the poorest country per capita out of every single one of them. so lets see what we get when we calculate wealth per capita.
we are going to use 2017 data from https://www.census.gov/data/tables/time-series/demo/income-poverty/cps-hinc/hinc-05.2017.html#list-tab-1611581443 however they calculate how many households are in each income bracket and do not give total population of each bracket and i could not find population number for this but this only favors the original article because if we calculate the data in the spreadsheet from census.gov we will come up with a population that is less than the total meaning wealth per capita will be higher than what it really is due to the missing data. Below is Percent Distribution of Households, by Selected Characteristics Within Income Quintile and Top 5 Percent in 2017 (Data reflect the implementation of an updated CPS ASEC processing system addresses) [<1.0 MB] opened in google sheets please note there is text that doesn't show up correctly during googles conversion and i fixed this manually by copying and pasting the data back into the first column for the data rows we will be using, I then minimized the rows we will not be using. Feel free to download the spreadsheet to see all the data for yourself it contains info by age race and a bunch of other data.
so we can see No earners, One earner, Two earners or more, ..Two earners, ..Three earners, ..Four earners (on later copies of this file it states 4 earners or more). these rows indicate households with a number of earners in them. we can then take the numbers from the lowest fifth column and multiply it by the number of earners. we also know there needs to be a minimum of 1 individual per household so no earners we will just count as a single person. this is where we are going to be missing some of the population since some households might have 0 earners but 5 people in them same with 1 earner and a family of 3 but this is the best data i could find and less population = higher worth per population which can only benefit the article in question. I just realized if a household has a bunch of earners those individual earners might all be poor but the household might get bumped to a higher quintile. say you had 10 earners in a household all making $12k per year each individual is in the first quintile of the poverty charts but the household would be bringing in $120,000 and that might stick it in a higher quintile on the spreadsheet removing those individuals from this population count increasing individual wealth in this equation even further.
here is the data we need typed out:
no earners x 16,175 = 16,175
one earner x 8,268 = 8,268
two earners x 1,020 = 2,040
three earners x 66 = 198
four earners x 6 = 24
add those all up to get total minimum population we can glean from this data: 16,175 + 8,268 + 2,040 + 198 + 24 = 26,705 and since this chart is in thousands 26,705 * 1,000 = 26,705,000 now we divide the 2,560,000,000,000 by 26,705,000 giving us a wealth per capita of $95,862.20 sticking this made up nation of the poor between Turkmenistan and Surinam at position 56 out of 146 or rather in this case 147 since we made a fake nation. however we can make this number even worse by taking the average number of people per household from 2017 and multiplying it by the number of households in the first quintile. this will still give us an under reported population since as i stated above there could be multiple poor people working in a household but the combined income bumps the household into a higher quintile.
so we will be using this spreadsheet https://www2.census.gov/programs-surveys/cps/tables/hinc-01/2018/bridge/hinc01_1.xls to get the average number of people per household which is 2.53
then we take the total households in the lowest quintile from the first spreadsheet 25,534 and multiply it by the 2.53 average to get 64601.02 then multiply that by 1000 and you now have a more accurate population number totaling 64,601,020 people in the lowest income quintile. so to get wealth per capita we divide 2,560,000,000,000 by 64,601,020 and get $39,627.86 wealth per person which puts us at position 86 out of 147 nestled between Turkey and Guatemala
below is the entire sheet of data used from https://databank.worldbank.org/source/wealth-accounts/Type/TABLE/preview/on#advancedDownloadOptions
if someone has more accurate first income quintile population data please let me know and I will redo this portion but even with the most generous calculations with the data I was able to find we can see that even the title of the article is a false statement not to mention the other statements within.
The next item im going to address is all the social stuff the poor get and i will try to add taht into the equations to see if the article can make a comeback from the current slew of data against it. However its 7am so good morning its time for me to go to sleep!