Poverty Rate Versus Continuous Tax Burden

I’ve received several e-mails about possible distortions that can arise from plotting a true continuous variable (the relative poverty rate) versus an ordinal rank, and if it’s possible to re-plot the data against the data used to create the ranks. Of concern is that ranks can have different meanings at different points on a scale; the difference between slots 1 and 2 might be much larger and much more significant, for instance, than the difference between slots 20 and 30.

Fortunately, with the data available on the Tax Foundation website, I can express the yearly tax-burden of Rhode Island residents using the same method applied to the poverty rate, in terms of a percentage of the national average. The correlation is as strong as in the continuous-versus-rank plot

PvRtVsTxBr3.JPG


(Tax burden numbers are from the Tax Foundation, poverty numbers are from the U.S. Census Bureau)…
































YearRI
Tax Burden
US
Tax Burden
RI Relative
Tax Burden
RI Relative
Poverty Rate
19809.7%9.5%102.1%82.3%
19819.7%9.3%104.3%83.6%
19829.9%9.3%106.5%88.7%
198310.1%9.4%107.4%95.4%
198410.1%9.7%104.1%88.9%
19859.8%9.7%101.0%66.2%
19869.7%9.7%100.0%65.0%
198710.1%9.9%102.0%60.4%
198810.0%9.8%102.0%75.4%
19899.7%9.8%99.0%52.3%
199010.0%9.9%101.0%55.6%
199110.1%9.9%102.0%73.2%
199210.6%10.1%105.0%83.8%
199310.6%10.2%103.9%74.2%
199410.6%10.2%103.9%71.0%
199510.7%10.2%104.9%76.8%
199610.5%10.0%105.0%80.3%
199710.5%9.8%107.1%95.5%
199810.5%9.7%108.2%91.3%
199910.3%9.6%107.3%84.0%
200010.2%9.5%107.4%90.3%
200110.5%9.5%110.5%82.1%
200210.3%9.5%108.4%90.9%
200310.6%9.7%109.3%92.0%
200411.0%9.8%112.2%90.6%
200511.2%9.8%114.3%96.0%
200610.9%9.9%110.1%85.4%
200710.5%9.9%106.1%76.0%
200810.2%9.7%105.2%

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Thomas Schmeling
Thomas Schmeling
12 years ago

Interesting. I would also ask, however, why you are using relative poverty and tax rates? Those depend not only on changes in RI, but changes elsewhere. (RI’s relative poverty rate goes down if Texas’ actually poverty rate goes up). I suspect that at least some of the relationship here is an artifact of these relative measures.
What happens when you plot the actual RI poverty rate against the lagged (or two-year average) RI tax rate? Isn’t this what you’re really interested in?

leo
leo
12 years ago

Answer:
Rhode Island raised the minimum wage
Higher wages=less poverty
States that have the,much lower Federal minimum wage have the highest poverty rates
Low Minimum wage=more poverty

Monique
Editor
12 years ago

Leo, can you show some data for your hypothesis? First of all, the minimum wage is not a living wage and was not intended to be. Further, as the minimum wage went up in this state, so did the cost of living – especially housing. I would bet the cost of living outpaced the increase in the minimum wage and, therefore, the increase in the minimum wage was not a factor in the decrease in poverty.
If you’ve got data and analysis that demonstrates otherwise, bring it forward.

Thomas Schmeling
Thomas Schmeling
12 years ago

Andrew, I agree with your impulse to try to factor out the effects of global influences on RI poverty rates to determine the relation of tax and poverty rates, but a) I don’t think that can be done with just one data transformation, b) I don’t think it can be done with any 2-variable scattergram and c) I’m pretty sure what you’ve done doesn’t accomplish it. On the last point, try this for a check: If your approach succeeds in “controlling for” those global effects, you should find that the “RI relative poverty rate” is not correlated with the US poverty rate. If they are correlated, global effects still contaminate your measure. A quick pass through the data makes it appear that this is the case, because there is in fact a strong positive correlation between the two variables. I think you can verify this with a graphic, though a simple regression makes it clearer. I’m not stating this more emphatically because I’m not sure your poverty data is the same as mine. I used the data at the link below, but I doubt it makes a difference. http://www.census.gov/hhes/www/poverty/histpov/hstpov21.html …. As I say above, your measure means that, even if the RI tax-to-poverty relation stays the same over time, your measure will cause it to appear to change if poverty levels or tax rates change in other states. That obviously makes it impossible to make statements about the RI relation. In short, it is just not possible to draw the conclusion you want to from this 2-variable analysis. There’s more to be said…for instance that I don’t agree at all that your “relative tax” measure makes sense, that it’s not clear whether your poverty rates are “before transfer” or “after transfer”, that it matters more how tax dollars are spent… Read more »

Thomas Schmeling
Thomas Schmeling
12 years ago

Andrew, Here’s a response. .Your statements are in italics “You use the term “empirical”, yet the approach you are taking towards a correlation between variables normed to national averages that is stronger than a correlation between absolute variables is that you a-priori don’t like the normed variables, so let’s ignore them. That’s not an “empirical” approach.” Andrew, I’m sorry to say it, but the above statement is complete nonsense. I used the data to look at the correlation between the US poverty rate and the “RI relative poverty rate” . It is positive, fairly strong, and statistically significant. That correlation indicates that you have NOT successfully removed the effect of global influences on the RI poverty rate. I may be right and I may be wrong, but the conclusion is based on data, so In what way is that conclusion “a priori” and “not empirical”? This correlations present in this and the previous post exist. Yes, the correlations exist, but that doesn’t necessarily tell us much, if anything. There’s an (apocryphal?) story in the stats literature about a researcher who found a strong positive correlation between teacher salaries and champagne sales, and concluded that giving teachers raises was a waste because they would only spend it on booze. The correlation did in fact exist, but the conclusion was obviously nonsense. Once you control for the rise in real wages across all professions, there turns out to be no separate effect for teachers. Higher wages overall lead to higher teacher salaries and higher wages overall create more disposible income and higher liquor sales. There are a lot of zero-order correlations like this that disappear, or even reverse sign (go from positive to negative or the reverse), when you properly control for other variables. Relative measures are valid — even necessary —… Read more »

Thomas Schmeling
Thomas Schmeling
12 years ago

This may not be necessary, but I feel compelled to point out that the paragraph above that begins “OK,; but now try this…” contains a lot of italicized text that is NOT Andrew’s words, but my own.

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