Data Don’t Speak for Themselves

Data Don’t Speak for Themselves

Check out this graph, data for which were drawn from the USDA and CDC:

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With a correlation coefficient of about -0.94, these data indicate that for the decade 2000-2009 there was a strong inverse relationship between per capita consumption of beef and the number of suicides by handgun. That is, this correlation seems to imply that the decline in total beef consumed per person over the course of the decade was linked to the number of suicides by handgun, which rose at virtually the same rate.

This proves that there’s a relationship between an individual’s meat consumption and his likelihood to commit suicide, right?

Of course not; this correlation is spurious. These data were not the result of a study that tracked the mental health and dietary habits of individuals over a decade. Rather, to demonstrate this idea of spurious correlation, the graph‘s maker, Tyler Vigen, took data from the CDC and USDA and laid them on top of one another. That they correlate for so long–and so closely–is entirely coincidental.

Absent some theoretical framework with which to interpret data–that is, if we let the data “speak for themselves”–data correlations can seem to deny true principles. For instance, roughly 87,000 flights occur daily in the United States, ostensibly defying the laws of gravity. But the laws of gravity aren’t contravened by the flight of giant metal birds with fixed wings. Rather, the interaction between airspeed, air pressure, wing shape, and direction creates the lift that allows aircraft to soar thousands of feet above the earth. The laws of gravity are entirely satisfied, and anyone claiming that these flights are evidence that the laws of gravity have been overturned would be ridiculed mercilessly by his peers.

This principle is just as true in economics as it is in physics. For example, economic theory tells us that demand curves are downward sloping–i.e. as price increases, fewer units of a good are consumed–but some studies purport to find that raising the cost of labor by means of a minimum wage causes no change in employers’ demand for labor. If the relationship between labor and the law of demand isn’t being disproved, what’s going on? 

At first glance, the law of demand would seem to imply that an increase in the cost of labor would induce employers to decrease the number of workers they hire. But if the minimum wage is only binding on certain individuals, and if employers don’t hire any such individuals, then employers won’t be impacted by the change. Likewise, for those making more than a proposed wage floor, a rise in the minimum wage won’t constitute a “raise” because, at best, their incomes will remain unaffected.

For example, according to PayScale the estimated average yearly earnings of someone who throws freight at WinCo Foods in Boise, ID, is $17,000. Assuming full-time status (2,080 working-hours annually), that amounts to a wage of roughly $8.17/hour. Idaho’s minimum wage reflects the national minimum wage of $7.25/hour, so any increase in their wage floor of up to $0.92/hour won’t be binding on any of WinCo’s Boise-based freight throwers, and, all things equal, WinCo’s employment level won’t be impacted.

But such a lack of response in employment isn’t evidence that minimum wage laws have no disemployment effects, or that the law of demand is irrelevant to labor. All it would demonstrate is that we must be more careful in determining the impacts of minimum wage hikes. Indeed, including workers who make more than the amount of a given proposal to raise the minimum wage is distortive of a study’s results, at best. At worst, their inclusion is highly disingenuous. 

Fortunately, the minimum wage is among the most studied policies in economics, so a great deal of work on its disemployment effects has already been done with low wage-earners in mind. A study out of Denmark [pdf], for example, assessed the impact of minimum wage increases on teenagers, for whom, by law, the minimum wage rises nearly 40 percent at age 18. 

The authors found that while those who keep their jobs see a significant increase in take-home pay, labor as a proportion of total input falls by nearly half. Furthermore, the overall employment rate for teens falls by a third as 18-year-old workers find themselves jobless. The upshot of these effects, taken together, is that the level of total wages paid by employers remains virtually unchanged—a result completely in line with the law of demand.

But there are other ways that employment is distorted by the institution of a new wage floor. Quite often, in fact, the law of demand is satisfied in ways that are less immediately visible. 

Recent studies from Seattle, the University of Illinois at Urbana-Champaign [pdf], and New York University [pdf] provide good examples. In the Seattle study, workers saw declines in hours that completely offset their gains in hourly pay, leaving them with less take-home pay. The NYU study found that higher productivity workers were substituted for lower productivity workers. In addition to such findings, the UIUC study also found that in low-skilled, labor-intensive industries a 10 percent increase in the minimum wage resulted in an increase of more than 24 percent in spending on capital, in line with concerns that minimum wage hikes lead to faster automation.

Other impacts from minimum wage hikes that aren’t immediately obvious include reductions in non-wage benefits for workers both at and just above the wage floor, higher consumer prices [pdf], substituting increased customer responsibility for unskilled labor [pdf], higher credential requirements for would-be employees [pdf], delayed teen and minority entry into the job market, and slower job growth for as long as eight years after the increase.

In spite of (methodologically questionable) recent challenges, the decades-old consensus remains on solid empirical ground. In a review of more than 100 studies of the minimum wage in countries across the globe, less than 8 percent found that increasing the minimum wage had the kind of positive impact on employment found in studies that challenge the consensus view. About two-thirds of the studies, by contrast, found negative employment effects. 

When the authors narrowed their evaluation to the best-quality evidence, 85 percent of studies found the expected disemployment effects, while “very few–if any–cases [were found in which] a study provide[d] convincing evidence of positive employment effects of minimum wages” on those most susceptible to employment displacement. 

In other words, despite donning a scientific veneer, the claims of those who hold that labor is not subject to the law of demand are nearly as baseless as those who might argue that the flight of airplanes disproves the law of gravity. Given the weight of evidence, we should be immediately skeptical upon hearing of studies that purport to find net-zero (or net-positive) impacts resulting from minimum wage hikes. 

But even if the literature were murkier on the empirical relationship between wage floors and employment, such skepticism would still be warranted. Intuitively, we know that if the price of a good rises, we respond to that change by reducing our consumption of that good. While the response depends on the individual consumer’s capacity and desire to consume at a given price level (that is, their demand elasticity), at some point the next increase in price causes everyone* to consume less. Interpreting data within this theoretical framework allows one to forego the mockery of anyone possessed of passing familiarity with economic principles.

In the end, economist David Henderson’s First Pillar of Economic Wisdom remains a true guiding principle: there ain’t no such thing as a free lunch. And, indeed, in the immortal words of Wesley, “Anyone who says differently is selling something.”

*The exception is in goods for which demand is perfectly inelastic, but, given the ease with which unskilled laborers can be found in the labor market, one would be hard-pressed to argue convincingly that unskilled labor constitutes such a good.

Reprinted from Ignore This.

Corruption at Amtrak

Randal O’Toole, Policy Analyst at the Cato Institute and blogger at The Antiplanner, published a policy brief today that details actions by Amtrak that, had they been taken by a private firm, would likely be considered securities fraud.

A press release from Amtrak claimed that 99.1% of its operating costs are covered by its revenues, but the release purposely neglected to include depreciation among its costs. In 2018, depreciation was nearly one-fifth of Amtrak’s operating costs, coming in at $807 million. The total for 2019 is expected to be some $50 million more.

Of course, Amtrak failing to account for the cost of infrastructure upkeep is nothing new, as the organization needs at least $33 billion (with a “B”) in backlogged maintenance. That number rises to as much as $92 billion when the costs of replacing passenger cars and maintaining tracks used, but not owned, by Amtrak are taken into account.

Amtrak’s press release also misrepresented their “passenger related revenue,” at least $235 million of which is pure state subsidies. Minus these subsidies and adding the cost of depreciation, real total losses in 2019 totaled more than $1 billion, or 35 times the annual loss-figure provided by Amtrak in its release. Notes O’Toole,

Similar premature information releases by Elon Musk led the Securities and Exchange Commission to charge him with fraud and force him to resign as Tesla’s CEO. Unfortunately, if any government agency has the power to charge Amtrak with fraud, none have bothered to do so.

Do look through the brief. It’s a relatively quick read and has plenty of source citations. Such thorough scholarship deserves to be appreciated.

This post originally appeared at Ignore This.

California’s Biometric Surveillance Moratorium

California recently passed Assembly Bill 1215, which prevents the use of biometric surveillance via body cameras worn by police officers. It’s nice to see the state not take on more power for once.

H/T to my good friend David McNaughtan of the Ledger Dispatch for the write-up.

Misinformed Voters

This will probably come as no surprise to regular readers of LI, but a 2018 survey on basic political knowledge revealed that the average American voter is not simply uninformed, but is systematically misinformed.

The survey asked 24 questions to a sample of 1,000 American voters, 18 of which had dichotomous responses (e.g. True/False). If you were to blindfold a respondent, give them two buttons to signify their responses, and never ask them the questions, they would still be right, on average, about 50% of the time.

Compare that to the American voter, who correctly answered only 42.9% of the time. In other words, they did significantly worse than a blind, random guess.

Voters did about as well as a random guess on those questions with three possible responses, answering correctly 32.8% of the time.

Finally, there was one question with four possible answers, which was correctly answered by 34% of respondents.

Overall, the average American voter answered correctly only 40% of the time. More details at the link above.

Venezuelan Sanctions are a Bad Idea

The Trump administration recently enacted sanctions against Venezuela, citing human rights abuses among its justifications. But if violations of human rights are a legitimate concern for the administration, then pursuing economic sanctions is bad policy.

Research shows that such sanctions not only fail to achieve their stated goals seventy to eighty percent of the time, but also result in greater poverty and widespread malnutrition and starvation.

If preserving and improving the lives of the oppressed is an outcome for which we’re shooting, well, this ain’t it, chief. Instead, we should start developing solid trade relationships with Venezuela. After all, aside from enriching both countries, more economic interaction leads to fewer wars.

(H/T Jason Ditz)

Women’s Soccer is a Financial Loser

Women’s Soccer is a Financial Loser

On July 29, 2019, U.S. Soccer president Carlos Cordeiro released an open letter and fact sheet addressed to “Friends, Colleagues and Supporters of U.S. Soccer.” Though he spends much of the letter emphasizing the organization’s commitment to “equal pay for equal work,” Mr. Cordeiro indicates that the disparity in pay between the U.S. Men’s National Team (MNT) and U.S. Women’s National Team (WNT) is not what it seems at first blush.

Drawing on financial data from 2009 to 2019, “extensive analysis” reveals that from 2010 through 2018, MNT players were paid $26.4 million total, excluding FIFA prizes. By contrast, WNT players were paid a greater sum–$34.1 million total–despite the fact that the WNT was profitable in only two years (2016 and 2017), and, in fact, generated a net loss of $27.5 million.

The document also takes pains to point out the differences in pay structures between the MNT and WNT, which are the result of different collective bargaining agreements. Writes Cordeiro,

Under their CBA, the women have chosen to have a guaranteed salary; U.S. Soccer therefore pays each WNT contracted player a base salary of $100,000 per year. (In contrast, the men’s national team players have no guaranteed salary and are only paid for the training camps they attend and the games they play, plus game bonuses.)

Cordeiro also points out that WNT players have a guaranteed salary of between $67,500 and $72,500 for playing in the National Women’s Soccer League, which means that, all told, WNT players enjoy a guaranteed annual salary of at least $167,500. Beyond that guaranteed minimum, WNT players can, of course, earn bonuses for games and tournaments. “[A]lthough players on our Men’s National Team can earn larger bonuses,” writes Cordeiro, “they are guaranteed nothing; they have a different contract structure.”

Furthermore, WNT players enjoy “a robust package of benefits” that is not provided to MNT players. The package includes health, vision, and dental insurance, severance pay, a 401(k), and compensation for maternity leave and child care.

Cordeiro goes on to point that the common claim that WNT players are only paid $0.38 for every dollar earned by their male counterparts ignores WNT players’ benefits package, and is based upon “out-of-date numbers” and the unrealistic assumptions of twenty games played, twenty games won. Even so, concludes Cordeiro,

if the men and women ever did play in and win 20 friendlies in a year and were paid the average bonus amount, a women’s player would earn more from U.S. Soccer than the men’s player—the women’s player would earn at least $307,500 (WNT and NWSL salaries, plus game bonuses) and the men’s player would earn $263,333 (game bonuses only).

Cordeiro does acknowledge that prize money distributed by FIFA slants sharply in favor of men (which, as I’ve argued elsewhere, is neither surprising nor concerning), but, he says, “U.S. Soccer has and will continue to encourage FIFA to narrow this gap with an increase in the prize money that it awards to its Women’s World Cup champions as well as the total prize money it offers all women’s teams that compete.”

Now, if inequality of pay is a “social injustice,” why is it we aren’t concerned about the disparity when it favors women over men, as in this case, or in other cases, like professional modeling? If economic inequality is inexcusable when women are at the disadvantage, doesn’t logical consistency demand such inequality is likewise inexcusable when women are the beneficiaries? For those concerned with unequal economic outcomes, this seems a hard question to answer.

But to those who see economic outcomes as the result of processes which take place in a complex network of human interaction, such outcomes are of little or no concern. After all, insofar as people are voluntarily exchanging their own property (including their productive labor) and are not being arbitrarily hampered by violent coercion relative to others (as by the state), then the outcomes, disparate though they may be, are necessarily just.

Indeed, given that the WNT represents a net loss for U.S. Soccer, it should be abundantly clear that the pay received by women’s soccer players is not only just, but extremely (and, by their own logic, unjustifiably) generous.

Reprinted from Ignore This.

Minding the (Wage) Gap

April has come and gone, and, with it, the highly publicized Equal Pay Day.  It’s the day of the year on which women are said to have finally reached pay parity with men from the previous year; women working full-time, it turns out, only earn 77%, 78%, or 79% of what full-time male workers earn.
But there’s a problem with those figures, no matter which you choose: they account for exactly one confounding factor.
In economics, there’s this great, smart-sounding, Latin phrase, ceteris paribus, which means “with other conditions remaining the same.” It’s a quick way of communicating the idea that we’re trying to figure out exactly how much impact one factor has in determining an outcome.
(It’s also fun because injecting Latin words into an article like this really makes the author look like he knows some stuff; but I digress.)
Back to our numbers: we’re trying to discover just how much influence sexist discrimination has on women’s earnings relative to men’s, we’ve controlled for full-time status, and now we’re saying that–ceteris paribus–sexism alone accounts for a gap of 21% to 23% between men and women?
Come on.
Granted, controlling for full-time status is important, but surely we can do better than one measly factor. I mean, there are a ton of other things that play into comparing the earnings of men and women, right?
For example, shouldn’t we try to compare women and men who studied the same things in college and selected careers in the same fields? Seems relatively important–and when we do that, the American Association of University Women finds that women actually make 93% of their male coworkers.
What about comparing work experience?  Lengthy career interruptions? And, heck, what about overtime?  Controlling for those things, a report prepared for the US Department of Labor found that women actually make 95% as much as their male coworkers.
I’d say a rise in women’s pay from 77% to 95% is quite an improvement, wouldn’t you agree?
But wait, there’s more!
Starting a family makes up a large (and growing) proportion of the total wage gap, and women tend to accept “family-friendly fringe benefits” (flexible hours, child-care, and parental leave, for example) in lieu of higher wages. When we account for these kinds of non-wage compensation, the gap in total compensation falls to 3.6%.
Neat, right?
Clearly, controlling for confounding factors is important; but as encouraging as all of these numbers are, we should take a step back and analyze some assumptions behind these comparisons.
For one thing, we seem content to uncritically accept the notion that, at some point, when we’ve controlled for everything we can possibly think of, the remaining disparity will necessarily indicate discrimination; but it’s not obvious that this is the case.  Stanford economist Thomas Sowell writes, “Where there are very significant differences in known factors between one group and another, it would be reckless to assume that all remaining unknown factors are the same.”
Another questionable assumption is that people–not just women–are single-mindedly concerned with maximizing their income, but that, too, is far from obvious.  In fact, individual success is subjective and multidimensional.  Using relative income as a means to compare men and women doesn’t tell us as much as we might wish it would because it ignores the complexity of success.
But even if we accept that comparing wages is a useful means of measuring sexual discrimination, we’re dealing with averages here, and while it’s important to understand what these numbers are telling us, it’s just as important for us to understand what they’re not telling us.
Take this study published in the American Economic Review, which finds that, when controlling for a host of relevant factors, women earn 97.5% of what men earn.  Are we supposed to believe that that number is telling us that every female worker makes precisely 97.5% of what her male co-workers earn?  
Not at all–but it does give us insight into the fact that there’s considerable wage variation between individuals.  
Let’s say that the average male income is $50,000 per year, meaning that an average adjusted female income of 97.5% is $48,750. Sure, half of these women make less than $48,750, but the other half makes more than that. It’s the same thing with men:  while half make more than $50,000 per year, the other half makes less.
This means that among the half of women who make more than $48,750 and the half of men who make less than $50,000, there’s considerable overlap, with a not inconsequential number of women out-earning men.
Given this overlap, sexual discrimination as an explanation for disparities in income loses some of its intellectual appeal–after all, if Jack makes more than Jill, what accounts for Jane, who makes more than Jack?  What about John, who makes less than Jill?
A more comprehensive explanation of the data might be that men and women make different choices on the basis of differences in values–and, empirically, there’s actually very good reason to believe that this is the case. Research shows that men and women differ widely in choice of major while attending college. As a result, fewer women than men enter certain fields–STEM, for instance–while the converse is also true–nursing is just under 9% male.
Furthermore, a recent study found that women choose to enter STEM fields less often in countries where they enjoy a higher degree of gender equality.  Coupled with research that finds that men and women in countries with more gender equality diverge more widely in personality–even as they converge in valuing self-actualization–these facts suggest that empowered women tend to prefer pursuing careers they enjoy over jobs that merely pay them well.  
University of Chicago economist Steven D. Levitt puts it this way: “Rather than interpreting women’s lower wages as a failure, perhaps it should be seen as a sign that a higher wage simply isn’t as meaningful an incentive for women as it is for men.”
Don’t get me wrong, here: none of this should be taken to mean that sexism doesn’t exist–it most certainly does–but the data, and especially this analysis, should be encouraging to those of us who are concerned about the economic well-being of women in 2018.

Subjective Success and Deceptive Statistics

Subjective Success and Deceptive Statistics

One of my best friends–a mother of three–loves to talk about her children, and my wife and I love to hear about them.  They’re three of the most adorable little girls you could ever hope to meet, and they’re constantly saying or doing or being in some way cute and precocious.  My friend could not be more proud of them.

A full-time mother, she also works part time in the evening to help her husband (also my friend) meet the financial needs of their family.  You can imagine the logistics:  he works during the day while she stays home with the girls.  When he gets home, they get some time together (around four hours) before she goes off to work, at which point they switch roles.  This way, she reaps the benefits of both raising her own children and having time with her husband, while also having the opportunity to spend time away from them to avoid becoming worn out.

She has a bachelor’s degree, but she neither works in her field (music) nor holds a particularly high-profile position where she does work.  Of course, neither of these facts are especially significant to her; her stated passion, her greatest personal desire, is to be a loving mother.  Because she gets to spend the majority of her time pursuing her dream, tempered by time to herself, she sees herself as being quite successful.  I agree, wholeheartedly; not everyone would.

So… what?

It may be as plainly evident to you as it is to me that each man and woman thinks of success differently.  You may even be tempted to abandon ship here and spend your time more productively in scrolling through Facebook.  But before you weigh anchor, here’s what I’m getting at:  individual definitions of success are given little love in statistics that aim to compare outcomes between groups, and even less so within certain narratives those statistics are used to support.

“And?” you ask, as you reach to navigate elsewhere.

Hold that finger just a moment longer.

Imagine you’re a social scientist.  As a social scientist, your job is to study human relationships and society.  When you set out to study something–say, the impact of discrimination on the income and career outcomes of men and women–you know you must account for every conceivable confounding factor, or else you wind up with distorted, inaccurate results.  Because you want to be as accurate as possible in your findings, let’s say you decide to compile a list of things for which you might need to control.

Education?  Check.

Career field?  Check.

Continuous years of experience?  Check.

Average hours worked per week?  Bueno.

Job title and responsibilities?  Yes.

Size of employer?  Uh-huh.

Employer market share?  Sure.

Marital status?  Yep.

Family plans?  Excellent.

Now, where, in all of this, are differing individual definitions of success accounted for?  Don’t get me wrong, it’s a great list, and it’ll produce results that are far more accurate and useful in comparing wage rates than simply taking the average of gross wage statistics; but if, in interpreting your results, you, the truth-seeking social scientist, don’t find a way to account for subjective success, your analysis still reflects unexamined acceptance of a crucial, confounding bias: that pay is the best, or most important, or at least a particularly useful, definition of success.  Your results may indicate in what ways things are different, but they say nothing of whether anyone cares about the differences, nor do they provide any basis for why anyone should care.

Think back to my friend.  For her, success is about motherhood, family relationships, and a balanced life, not how much she makes at work, or how much she makes compared to someone else.

For my mother–an angel if I ever knew one–success means acting with integrity, working hard, loving and serving others, forgiving willingly, and creating beauty to share with the world.  To use her words, “It’s not so much what I’ve done, or how much I’ve earned, but how I’ve done it.”

A rare politician worthy of my admiration, Rep. Justin Amash (R-MI), recently related his father’s definition of success in an interview with Reason:  “Success is not about being really rich, it’s about being able to make decisions for your own life and provide for your family.”

A friend and colleague I’ve known since age eleven expressed to me recently that her definition of success has a lot to do with both personal relationships and integrity of character, with the additional component of ongoing intellectual growth.  Moreover, she said, her views on success have evolved:

“I care more about being mentally healthy and having good balance in my life.  Five years ago, I was pretty willing to trade all of that off for achievement/respect/attention in economics.  I now have a much lower … tolerance for career and education demands that make me unhappy or are likely to mess with my self-esteem.”

I could go on.

And on.

But I won’t.

Instead, I’ll say that, while it isn’t unimportant, pay is, at best, a one-dimensional proxy for something that is probably better thought of as an ordered list whose sequence–though sometimes fluid–is not without consequence.  For many, the rate of their pay (especially as compared to others) may not even make their top five.  And the further down the list it is, the less likely it is to be relevant to one’s happiness.

Personally, I can’t see myself being happy or feeling successful working 80+ hours per week in a high stress job, leaving my family relationships to wilt and having no time for personal growth.  The difference in pay between myself and someone who takes that route says very little about how successful each of us feel we are.  As such, it is a useless means of comparison and irrelevant to the question of what “should be.”

And what of comparing outcomes between those who do seek success in long hours and neglected relationships?  Fundamentally, argues Stanford economist Thomas Sowell in his most recent book, Discrimination and Disparities, outcomes are based upon complex, interrelated factors and necessary combinations of prerequisites.  Thus (big breath, now),

“The seemingly invincible fallacy of assuming an even or random distribution of outcomes as something to expect, in the absence of such complicating causes as genes or discrimination, can make many statistics that show very disparate outcomes be seen as indicating something fundamentally wrong in the real world, rather than something fundamentally wrong with the assumptions behind the norms to which those outcomes are being compared. Neither logic nor empirical evidence provides a compelling reason for expecting either equal or random outcomes among individuals, groups, institutions, or nations.”

In other words, even when two individuals have the same idea of what constitutes success, it’s irrational to expect equality in achieving that success.  One may be willing to work harder, or stay at work longer, or forego more leisure, or remain more aloof from family, or give up more friendships, or sacrifice more health.  F. A. Hayek, a prominent 20th century economist and Nobel laureate, conveyed this insight in his 1960 work, The Constitution of Liberty:

“From the fact that people are very different it follows that, if we treat them equally [under the law], the result must be inequality in their actual position, and that the only way to place them in an equal position would be to treat them differently [under the law].”

If you’ve been hoping this whole time for a TL;DR version of my point, I’ve saved it until the very end:  we unduly bias our results from the get-go by assuming that every individual wants exactly the same thing, regardless of cost. In effect, we’re superimposing a single definition of success upon millions of individuals to whom it does not apply.  In doing so, their feelings of subjective success are ignored, and they can thus be used against their will as statistics in the interest of padding a narrative that insists that they are, in fact, victims.

I don’t have to be (or even want to be) the richest, best looking, or smartest person I know.  I just want to be happy, and achieving happiness involves being the kind of man that my wife (and future children, whenever they arrive) deserve to be with.  I am most successful when I have happiness at home, and, frankly, comparing myself to others makes me unhappy.

Thanks for sticking around.  You can stop holding that finger now.

A Brush with the Epistemology of Truth

I have no problem with the concept of objective truth.  In fact, I strongly believe in it.  As I see it, to say, “there’s no such thing as objective truth” is to spiral into philosophical oblivion.

Think about it–if the statement “there’s no such thing as objective truth” is objectively true, then the true-ness of that statement falsifies itself and, because of the strong, binary nature of the claim, necessitates that its opposite is true.

It bids one recall that old mind-bender that pops up every once in a while on social media, shared by people who feel especially clever for having thought of it:

  1. The following statement is true.
  2. The previous statement is false.

(Now, clench your buttocks…)

If the first statement is true, then the second statement must be true; but if the second statement is true, then the first must be false and, owing to the binary nature of the claim, the opposite must necessarily be true; but if the opposite of the first statement is true, then the original second statement is false and, again, necessitates that its opposite is true; but if the opposite of the second statement is true, then the opposite of the first statement is false, and the cycle begins again, continuing ad nauseam until eventually the metaphysical superstructure of reality fails and the entire universe implodes.

(Or, you know, somewhat less dramatically, a priceless bust of Immanuel Kant suddenly sublimates somewhere.)

“Okay,” you say, rubbing your temples, “but one could easily get around such a logical hangup by taking the weak position of disbelieving in objective truth.”

Ah, but could you?  …one?

See, to hold a belief is to accept (at some level) that it’s more accurate than some competing belief, relatively speaking. But unless there’s some objective truth against which to measure the relative accuracy of competing beliefs, there’s no such thing as relative truth. In other words, hedging your philosophical bets by weakly disbelieving in (or, weaker still, merely being uncertain of) the existence of objective truth assumes at least one objective truth, which is that–

“The only objective truth is that there are no objective truths aside from the truth that there are no other truths.”

Yes, my friend, you’re a quick one; though perhaps you could’ve summed it up a bit nicer–might I suggest, “there are no objective truths other than this one”?

Or maybe, “the only truth is truth’s absence.”

Any way you want to word it, the idea is demonstrably untrue.

We know, for example, when it’s objectively true to say that a human being is dead–there aren’t an overabundance of bare skeletons frequenting the local coffee shop, after all.

We can also fairly assert that, objectively speaking, the chemical formula of carbon dioxide is one carbon atom and two oxygen atoms at all times and in all places.

Heck, one could list numerous objective truths, and each addition to that list would further undermine the idea of truth-as-lack-of-truth.

And, frankly, the truth-of-non-truth assertion is a lot to ask. If the only objective truth is that there are no other truths, then relative truth exists only as it relates to the question of the existence of objective truth, rendering unrelated any other question of philosophy; and, because other philosophical questions are disconnected from the question of truth, every philosophy is, of necessity, morally equivalent to every other.

That would put Ted Bundy at moral parity with Mother Theresa. The progressive eradication of global poverty by a trend toward economic liberalism would be morally no better than the intentional murder and unintentional starvation of a hundred million people under twentieth century Communism. Paul Krugman would be equal to Bob Murphy.

Needless to say, it’s not an attractive proposition.

None of this is to say that everything is objectively true, of course. Nor is it to claim that we possess every objective truth. But it can serve as a launching point for discussion and a point of fundamental agreement.

Now, if you’ll forgive me, I think I might have pulled something throughout the writing of this article.


Reflections on Voting, Incentives, and the State

As much as they might want to deny it, I think people recognize–at some level, anyway–that their individual vote has only a fraction of a fraction (of a fraction) of an impact upon the outcome of a given election.  Keeping up with current events, economics, and foreign policy exacts a cost on voters that far outweighs their individual impact.  Sure, we might like to think that our vote “makes a difference,” but the truth is that one-person-one-vote simply doesn’t register individual preference very forcefully.

The upshot of this cost-benefit mismatch is that voters choose to remain ignorant of many critical issues.  Rather than expending the time and energy otherwise necessary to remain informed, voters choose–understandably–to vote on the basis of what sounds good, what feels right, and what gives them a sense of “helping.”  But even if such voting behavior is understandable, it also perpetuates the re-election of very unpopular politicians at shockingly high rates, and, more to the point, the terrible policies of said politicians thrive.  This is one reason why libertarians generally favor strictly limiting the power of governments.

History and economics tell us that perverse incentives seem to have a direct, positive relationship to state power: the more powerful the state, the greater the probability of economic agents responding to perverse incentives like rent-seeking.  A political environment where rights are protected, contracts are upheld, and state power is limited, by contrast, tends to limit perverse incentives.  Voting in such a limited state may not be any more effective at an individual level–the chances that a single vote makes any difference is still limited to the very rare occurrence of a tie–but fewer lousy politicians and myopic policies are likely to stick around.

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