May 20, 2016

Right to Work, more recent data

So, what's the argument over?

Do Right-to-Work laws fulfill their claimed benefits to workers? (Executive summary: They don't). Arguments in favor of right-to-work (RTW) boil down to claiming a better overall life for ordinary workers in a state. I'm going to explain my personal bias: No law should ever be made without compelling need. Thus, the entire burden of proof is not that a law will not make things any worse, it is that a law must make things better. This is why I'm not explicitly testing anti-right-to-work claims. Anti-any-law automatically is favored as the "null hypothesis". Of course, some laws are trivial to justify. The damage done to people and society by practices such as child prostitution are so enormous, and the moral issue so clear-cut, that it is trivial to show an overriding social need for a law against such practices. When it comes to labor law, things can start to become less immediately clear-cut.

Let's Talk Money

All State Differences
Median Income
Orange: Right-to-work state does better.
Blue: Non-RTW state does better.

One conventional measurement that dominates the argument about right-to-work is income. If you know me, though, you'll already know that I will not look at them in conventional ways. Attempts to attack or defend RTW based on "average" incomes are just plain silly. It's easy to see how. The "average" is only a good representation if income is evenly distributed, which it isn't. A very small portion of Americans in any state have much higher incomes than most of that state does. Instead of average, I will use median. The median is literally the number in the middle. Half of the households in a state makes no more than the median, half make no less than the median. Thus, it represents a truer estimate when the data is highly skewed.

Okay, so now that I've chosen median income (for 2014, since all data for 2015 isn't finalized, yet at the US Census) as the basis of comparison (conveniently available from the Burea of Labor Statistics, how to compare? One way is to aggregate the two groups of states (RTW vs. non-RTW), subtract one aggregation from the other, et voila! But "simple" isn't always so simple. If there is a difference between the two, is that difference meaningful? The data covers all the possible comparisons (all 50 states for that year). What aggregation should be used?

There are only 50 states. Of these 24 were RTW in 2014, 26 were not. That's not much. That's only 624 pairwise comparisons of states. We have spreadsheets in the modern day, so 624 subtractions are nothing. Okay, so I can do 624 subtractions of one state's median wage from another's, then what? Aggregate the subtractions and present column charts with error bars and all kinds of statistical gobbie-goo?

I could, but it would only hide more than reveal. After all, when I've got that few points of data, why not just present them all and let the reader see directly? That's what I did. The first figure displays every single comparison, grouped in "income difference" brackets. Orange columns are where an RTW state had a higher median income than a non-RTW state. Blue columns are the other way around. Orange = RTW better. Blue = RTW worse. If you mouse over, you'll see the limits of each bracket and the actual number of comparisons that fell into that bracket. Overall, an RTW state was better in 145 comparisons. A non-RTW state was better in 479 comparisons. So, that's a 73% disadvantage to RTW. Does that mean anything?

Let's look at it another way, what is the possibility that this difference could occur by random chance? If it is likely to have just been random chance, then we shouldn't let the difference lead us to any conclusions. I used a method called "bootstrapping" to estimate the probability that this outcome was by random chance. You can look up bootstrapping in any statistics textbook if you are really into the nuts and bolts. To make a long story shorter, it turns out that the probability of this outcome just being random chance is roughly 0.0004. Statistical "significance" begins when probability is equal to or less than 0.05. We can safely exclude random chance from explaining this outcome

All State Differences
Cost-of-Living Adjusted Median Income
Orange: Right-to-work state does better.
Blue: Non-RTW state does better.

But money goes out, too.

However, as Mark Twain long ago tried to point out in A Connecticut Yankee, income is only half the story of individual prosperity. If you make twice as much money as the cobbler in the next village but have to pay twice as much for everything, you're no better off than the cobbler in the next village, no matter how big your income might look before you pay your bills. A more accurate idea of the effect of RTW is to factor in cost of living as a relative state ratio. Thus, a more expensive state (New York) would have a 2014 cost of living at 1.316, while a cheaper state (Oklahoma) would have one of 0.921. What this means is that an income of $50,000 in New York would be roughly equivalent to an income of $35,000 in Oklahoma. The New Yorker might make more money on paper, but he'd be no better off than a Sooner making $15,000 less a year! That's a pretty important factor. I do have to caution that statewide costs of living are very approximate, and it is easy to find exceptions. Manhattan would be even worse, for example.

When we factor in cost of living to median income, the picture changes. RTW states now have a slight advantage. Cost-of-living adjusted median wages are better in 55% of the comparisons (554 out of 612). However, bootstrapping showed a 45% probability that this was just due to random chance. In other words, the effect of RTW on cost-of-living adjusted wages is a toss-up, almost 50-50. So, it seems that the RTW advocates may be right on one thing: States without RTW will have a higher cost of living. The opponents of RTW are also correct: RTW goes hand-in-hand with lower wages. In short, it's a wash. In terms of income including expenses, RTW has no net effect.

All State Differences
Median Wages Adjusted by
Employment, Population, and Cost of Living
Orange: Right-to-work state does better.
Blue: Non-RTW state does better.

Let's Talk Money and Jobs

The tale is not told, though. After all, what if RTW states (like Texas) happen to be very populous states and non-RTW states (like Alaska) are sparsely populated? Then, even though on a pure state-by-state basis, RTW might not do well, in terms of overall prosperity of human beings, it might shine! But how to measure that? If we are thinking primarily of ordinary people—and we should, since the arguments about RTW always get down to whether it helps ordinary people, we can start with median income, again. If everyone were making the median income, the median income would not change. Then multiply the median income by the number of employed people in a state to get an aggregate income estimate. We also have to take into account that a state may have a lot more people to support on top of those who are working. Divide the aggregate income by the state's total population. This "population-adjusted income" can give us an idea of how well each state does vs. another in terms of the comfort of its mass of people.

Let us not forget cost of living, since higher wages are passed on to consumers by the businesses paying them. What does that give us? You've probably already been looking over the last graph. As you can see, RTW does slightly worse than non-RTW in terms of income, adjusted by employment, population, and cost of living. In 292 comparisons, an RTW state did better than a non-RTW state, but in 332 comparisons, a non-RTW state did better than an RTW state. Bootstrapping tells us, though, that this is probably (70%) just random chance. That is, when you get down to the wire, RTW makes no overall difference.

What does this ultimately mean? The claim I tested is "Right to work improves the lot of the worker". In the end, taking into account cost of living, or combined cost of living, employment and population, it's a toss-up. While Right to work might not guarantee misery, it also does nothing to improve the overall condition of the vast majority of Americans. What it tells me, personally, is that Right to Work is a failure. It does not benefit ordinary workers in any way that cannot be just as easily explained by random chance.

What is the take-home? Given the data at hand, a compelling worker-benefit based argument in favor of enacting or maintaining RTW cannot be made. By and large, RTW is not a policy that produces enough benefit to an ordinary worker to be worthy of being kept as law, not even when macro-economic factors such as overall employment are taken into account.