Statistics

Gonorrhea, Wee P-values, and Tax Increases

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Adventurous reader Ted Poppke discovered a peer-reviewed paper that, according to the American Enterprise Institute (AEI), proved that increasing sales tax on booze “caused a 24% decrease in gonorrhea cases reported to the U.S. National Notifiable Disease Surveillance System, but had no effect on chlamydia.”

Caused. Strong word! The strongest there is in science. When a scientist says X causes Y, he has reached the pinnacle of Y-studies, for once we have learned the cause of Y, we have learned what most of what science can tell us of Y. Discovering cause is thus a terrible burden. Unfortunately, in many fields discovering a wee p-value has taken the place of discovering true cause, the consequences of which I detail in my just-in-time-for-Labor-Day Uncertainty: The Soul of Modeling, Probability & Statistics.

The paper is “Maryland Alcohol Sales Tax and Sexually Transmitted Infections: A Natural Experiment” in American Journal of Preventive Medicine by Stephanie A.S. Staras, Melvin D. Livingston, and Alexander C. Wagenaar. From the paper’s beginning:

Alcohol tax increases may decrease sexually transmitted infection rates overall and differentially across population subgroups by decreasing alcohol consumption in general and prior to sex, thus decreasing sexual risk taking and sexually transmitted infection acquisition…

Results strengthen the evidence from prior studies of alcohol taxes influencing gonorrhea rates and extend health prevention effects from alcohol excise to sales taxes. Alcohol tax increases may be an efficient strategy for reducing sexually transmitted infections.

To say “Alcohol tax increases may decrease sexually transmitted infection rates” is to invoke causal language. Somehow increasing the amount the government collects on bottles of beer will cause people who would have otherwise contracted gonorrhea to not contract gonorrhea.

Before examining the paper, think how this assertion can be proved. At least one man (or woman) who would have got gonorrhea when the sales tax was low would not have got it when the sales tax is high. How could raising a sales tax cause the absence of gonorrhea where that same gonorrhea would have necessarily been present under the low sales tax?

Obviously, a sales tax rate has no causative powers on gonorrhea, so the contention fails immediately. But the sales tax might have caused some other thing or things to happen, like setting off a chain of dominoes, which blocked the gonorrhea from setting up. And this is what the paper implies. A man who would have drank to excess and engaged in sex (or sex-like activities) with an infected woman (or vice versa) will now be stopped from drinking that little bit extra he would have under a cheaper tax, with the consequence he’ll now retain enough judgment to realize beer googles blur. Perhaps he’ll read a book instead.

Now the only way to tell this for sure is to run experiments on actual men and women, raising the tax for some, lowering it for others. But even this is dodgy, because we’ll always be left with a counterfactual question. Would this man had the sales tax been lower contracted the gonorrhea he safely avoided tonight when the tax was high? How can we ever know this? Answer: we cannot: we can only assume it.

This bewildering point is belabored and bothered to emphasize the over-certainty which is caused when mere correlations in external datasets take the place of (even imperfect) experiments. What the authors did was to collect gonorrhea and chlamydia rates before Maryland’s tax increase, and then collect them again after. Enter the statistical model, a regression-like creation with parameters for the state’s general tax rate, the state’s alcohol tax rate, a rate of gonorrhea and chlamydia infections for times and places other than in Maryland under the new rate, and an “ARIMA noise model”, which we can ignore.

The p-value associated with the alcohol tax rate parameter (under various manipulations) was wee for gonorrhea and not wee for chlamydia. What about parameter for rates of other sexually transmitted diseases? They didn’t check; or if they did, they remained silent about them (I’m guessing they didn’t check).

From the p-value weeness, they concluded “A 2011 Maryland 50% increase in alcohol-specific sales tax decreased statewide gonorrhea rates by an estimated 24%—preventing nearly 1,600 gonorrhea cases annually.”

Mighty bold claim. All gleaned from mixing databases and calculating a parameter inside a dicey statistical model.

The kicker was noticed by the AEI:

However, Staras et al. do not establish that alcohol consumption decreased as a result of the sales tax increase. In fact, the National Institute on Alcohol Abuse and Alcoholism, in Haughwout and colleagues, estimates that annual alcohol consumption per capita in Maryland increased by 0.03%, from 2.2058 gallons of ethanol in 2010 to 2.2065 gallons of ethanol in 2012 for people aged 14 years and older (the group studied by Staras et al.).

This too is indirect evidence, because we don’t know if some who would have drank more drank less because of the tax increase, or those who would have drank even still more still drank enough. And so on.

Not for the last time I ask all to abjure all hypothesis tests.

Categories: Statistics

16 replies »

  1. increasing sales tax on booze “caused a 24% decrease in gonorrhea cases reported to the U.S. National Notifiable Disease Surveillance System

    Also caused, I’d wager, an increase in cell phone sales and the price of groceries.
    Has any state ever DECREASED a tax on booze?

  2. Ted: You take what you get, right? 🙂

    The first question I had was “Don’t people with chlamydia drink?” or “Does drukenness not affect the behaviour of those with chlamydia—say perhaps, they never use protection drunk or not?” I think that would have been a very important question to research before any proclamations were made. Otherewise, it just looks like nonsense wrapped up as science to get another tax increase—like anything is needed to do that…..if the results had been the other way around, wonder if they would have just tossed the study or “adjusted the data”…….

  3. If you’re gonna write a lengthy long rebuttal, at least be funny, otherwise, why not just get to the point & get it over with like the AEI study did that’s linked above.

    Based on a quick cursory search it appears that the two forms of VD cited, “G” and “C” both are very contagious in the same way. So for one to drop but not the other suggests something particular to the diseases is the factor as behavioral patterns were, insofar as drinking & the private festivities that followed, not substantially changed. (this is the kind of near-final-but-still-a-bit-tentative conclusion one can get from understanding the “physics” or in this case basic biology of the activity).

    Thus, its pretty easy to conclude that the relationship with tax increases is a form of coincidental correlation, not some unknown cause-effect link … unless those taxes were also associated with, perhaps, some parallel initiatives to treat G (in which latter case, taxes & reduced G WOULD be causally linked, sort of, with the correlation indicating a proxy measure [intervening variable] is involved).

    Clearly much more research into all these areas, and more, is needed to ferret out the correlations and then pin down the true causes & dismiss the coincidences.

  4. Don’t they know if they keep raising taxes they’ll just create a black market for gonorrhea? I’ve seen it happen a thousand times…

  5. So what’s wrong with the authors’ speculation (which Briggs quotes incompletely) below? No one has proved them wrong yet. It sure is possible that less alcohol consumption prior to sex decreases sexual risk behaviors.

    Alcohol tax increases may decrease sexually transmitted infection rates overall and differentially across population subgroups by decreasing alcohol consumption in general and prior to sex, thus decreasing sexual risk taking and sexually transmitted infection acquisition.

    Since the time series data collected in the paper are monthly data from January 2003 to December 2012—102 prior to and 18 months following the alcohol tax increase, AEI’s quoting aggregated data value from year 2010, as if it somehow shows the speculation is wrong, is meaningless.

    Not sure if you are taking any medications approved by FDA, the majority of them are the results of p-values.

  6. JH: Long ago many people gave up on the FDA approved drugs, as one by one they were removed from the market, etc. Anyone who read on the subject realized the studies were poorly done and that many studies were never even looked at if they showed no wee-p value. Only studies that showed significance were necessary and you could discard all the others. So, yes, I take medications approved by the FDA. The only other option is natural remedies and that won’t cut it for a Type 1 diabetic. Do I have any faith in the FDA—no. If there were practical alternatives, I’d look into them. Meantime, I read what I can on the medications and go with it.

  7. Sheri, all you need to admit is that you are taking FDA approved medications and those medications work. The rest is just garbage. FDA does not approved drug bases on p-values only… (This is not to claim that FDA is perfect.)

  8. “Not for the last time I ask all to abjure all hypothesis tests.”

    Somehow, I don’t think we have heard the last of Briggs on hypothesis tests.

  9. I just read a little more on it. I find it hard to believe raising the sales tax a few cents would lower a particular STD rate 20%. Apparently this is currently being reviewed. I get the feeling all we’ll see here is coincidence.

    I could see if the tax was raised say to 100%, literally doubling the cost of booze. But a raise from 6 percent to 9? No.

    JMJ

  10. So the hypothesized causal mechanism is, “by decreasing alcohol consumption in general and prior to sex, thus decreasing sexual risk taking and sexually transmitted infection acquisition…” and yet alcohol consumption went up. We don’t need statistics to reject the hypothesis.

  11. “The study also found that responders with cognitive impairment had lower education, were in non-law enforcement occupations (for example construction), smoked, and were of an older age compared to those without cognitive impairment.”

    That pretty much says everything you need to know.

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