Right to Work" snark hunt

I noticed that the "Right to Work" controversy has come up again in another thread. As some of you know, one of my "hobby horses" is econometrics, or the application of statistics to discussions of this type where objective data is available. [FWIW -- if objective data is *NOT* available, it is theology.]

For those of us that may be interested, I downloaded a list of the states, and dummy/binary coded the "right to work status" as 1 = "right to work", 0 = no "right to work, and from other sources downloaded family poverty rates, median household income and a measure of income distribution equality called the gini coefficient.

To download a copy of the data set click on

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Some quick spreadsheet work shows the un-nuanced data, i.e. "out of the box," not adjusted for anything, i.e. not population weighted, no logit/probit transformations etc. indicates the following:

Statement: Right to work states have higher family poverty rates. For RTW v family poverty rate in percent R square = 0.1153072619 F-RATIO = 1.42732643240265E-046 F-dist = 1.0000 Conclusion. NO SALE

Statement: Right to Work states have lower family incomes. For RTW v median family income R square = 0.1569634784 F-RATIO = 9.39707857939395E-192 F-dist = 1.0000 Conclusion: NO SALE

Statement: Right to Work states have higher disparity in income distribution as measured by the gini coefficient. For RTW v state gini coefficient R square = 1.02125374946014E-005 F-RATIO = 5.96807933525614E-058 F-dist = 1.0000 Conclusion: NO SALE

Cautions: As the calculations were not population weighted, the larger states such as California may have "swamped" the results, but this is highly doubtful as the split is c. 40% of the population lives in RTW states and 60% do not. D.C., P.R., the territories, etc. were omitted from the calculations. Not adjusted for family size. Other statistical tests such Kruskal?Wallis as may give different results. [Feel free to download data and "knock yourself out."]

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(you may find my LFTR01 proposal {pdf and odt format} in the drop box of interest also -- feel free to browse website)

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File uses the free OpenOffice suite which you can download at

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{current version

3.4.1} Many versions of MS Excel will also open the file.

For more info on R-squared to start see

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For info on the gini coefficient see

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Google on either or both terms for more than you want to know.

==>Now lets move on to something than means more than a p*** hole in the snow before the politicians/banksters bring the economy down around our ears.

Reply to
F. George McDuffee
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Interesting but actual poverty is what you can buy with what you have. Take someone from NY City and transplant them in MS or NM, they might be living high on the hog. Cost of living matters. I guess my question is, "Do high prices follow high wages? Or vice versa?"

Reply to
aasberry

...

...

The most important thing to remember about R^2 is that "correlation does _not_ imply causation"...

For such a simplistic measure of such a complex question, the number of confounding factors one can postulate is essentially unlimited...

Reply to
dpb

What it demonstrates is that "right to work" laws do not reduce poverty levels.

Reply to
PrecisionmachinisT

Indeed, but this only applies ==>if a correlation is detected.

Reply to
F. George McDuffee

On 10/29/2012 11:47 AM, PrecisionmachinisT wrote: ...

It also does not demonstrate that right to work laws have any causative bearing in preventing rise from poverty...

Reply to
dpb

causative

I never said it did.

However, the evidence strongly suggests it to be the case.

Reply to
PrecisionmachinisT

===============

While this seems plausible on its face, where is the data ==>and the analysis?

Reply to
F. George McDuffee

Except, upon analysis, there are some troubling facts..

For instance, one of the main purposes of collective bargaining is that of extracting higher wages from of an employer.

Reply to
PrecisionmachinisT

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