The Problem with Empiricism

data-screenMark Twain’s coined phrase “there are lies, damn lies, and statistics” has the privilege of being used far too often and not nearly enough. The saying is invoked by people who see a genius in the mirror but are much too dense for their own good. They are the ones who feign skepticism while eagerly accepting whatever empirical evidence bolsters their own dogma.

These perpetrators of the crime against intellect are by and large statists, namely economists. They spend their days waiting to pounce on detractors on the first blip of data that justifies their collectivism. Unemployment inched up? Need more government stimulus! Unemployment falls slightly? Thank Heavens Washington is spending so much money to put people to work!

The key here is that any piece of data can be taken and spun into a web narrative to fit an agenda. Government-gathered statistics often provide a potpourri of easily-moldable fictions. And because the facts and figures come straight from the state’s mouth, they are often taken as Gospel. Anyone who thinks otherwise – that bureaucrats might have their own motives for possibly fudging information – is smeared as a tinfoil-chewing crank in need of immediate institutionalization.

The exception is when news breaks that some rogue public servant doctored stats for pure political purposes.

The New York Post, a paper not exactly known for its pride in accurate reporting, recently claimed the Census Bureau was aware manipulation of the employment report was going on in the run-up to the 2012 election. Just a few months out from when America put Sugar Daddy Obama back in the Oval Office, the national unemployment rate happened to fall from 8.1% to 7.8%. It wasn’t all that significant of a drop, but the talking heads sure made it sound like the Second Coming. The Post – which is relying on an unknown but “reliable source” – claims the figure was intentionally faked.

It goes without saying that unfounded claims based on a mysterious origin aren’t the most credible of sources. Even the everyday man on the street is wary about unnamed sources of information. He wants some kind of supporting evidence that isn’t just hearsay.

The Post report may be all smoke and no gun, but it’s not far from the realm of possibilities. Public sector workers have every incentive to keep their layabout jobs. In 2010, Census Department employee Julius Buckmon was fired for fudging results. He claims to have been given orders from higher-ups.

It also doesn’t help that the method the government uses to measure unemployment is already lackluster enough. Workers at the Bureau of Labor Statistics simply call up households and inquire about the inhabitants’ working situation. They don’t hook respondents up to a polygraph machine. The whole thing is based on the trustworthiness of the average schmuck. And even when the data is gathered the least severe measure of total employment, known as U3, is used as the headline number in media reports. The measure does not account for discouraged workers, who are tossed into the U6 bracket along with part-time workers seeking full-time employment. So the biochemist washing dishes at his local diner while scouring the classifieds each morning for a new position is left out. Since the beginning of America’s economic doldrums five years ago, the U6 unemployment rate has failed to drop below double-digits. But by highlighting only the “headline” number, the President and his press apparatchiks shine a light onto an otherwise dark employment picture.

Government manipulation of data is nothing new historically. Stalin famously had Western economists fooled for decades with erroneous reports on economic growth in his communist paradise. In 1989, Paul Samuelson, arguably the most influential academic economist of the late twentieth century, wrote in his famed textbook the “Soviet economy is proof that, contrary to what many skeptics had earlier believed, a socialist command economy can function and even thrive.” Two years later, the Union of Soviet Socialist Republics disintegrated. No mea culpa was ever issued.

Despite the philosophical shortcomings of pure empiricism, the great breadth of society has a fetish for data. The reason is simple. Numbers and statistics don’t just save us from having to make coherent arguments, they make it easy to not have to think very hard.

That’s the problem with radical scientism and empirics in general: the notion that logic is not needed to interpret information to fully understand the surrounding world. Stats and figures are malleable. They can be used to make the case for laissez faire, statism, interventionism, or whatever “ism” strikes your fancy.

Data is useless without a sound theory to interpret it. Otherwise, it may as well be a sheet of randomized numbers. Yet the empirical positivists are quick to dismiss the idea that things can be proved without observable evidence. As the late Murray Rothbard asked in his essay “In Defense of Extreme Apriorism”:

“what is the vaunted ‘evidence’ of the empiricists but the bringing of a hitherto obscure proposition into evident view?”

An evidence-only approach to the dismal science is destined to die on the mantle of popular methodology. Whatever the data may show, it can be easily explained away in empty pontificating and counterfactual hypothesizing. The adherents to scientism are left babbling in their own incoherent rationale. Basically, no amount of factual confirmation will convince the true believers of positive empiricism. They talk a good game of sensory verification, but have an excuse for their own canon under each sleeve.

It’s not paranoid gibberish to assume government bureaucrats would juice the numbers to make sure their preferred knight in shining armor stays in the White House. As much as Nancy Pelosi, Paul Krugman, and the New York Times editorial board would like to pretend, public servants are not boy scouts donned with merit badges as far as the eye can see. They are just as selfish and conniving as Wall Street traders.

Here is the most important lesson not taught in government 101: politicians and their over-paid henchmen lie. They’ll sell you lemon, break the warranty, set the bank loose on you, and then demand your undying loyalty. Everything they say should be taken with a grain of FDA-approved salt, including monthly data reports.

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One Response to “The Problem with Empiricism”

  1. James E. Miller says:

    Thank you for the thoughtful, though snarky, response Michael.

    Yes, I am defining radical empiricism as the mirror image to radical apriorism. Yes, many empiricists don't totally throw out theory and logic when it comes to solving the world's problems. But in my experience debating with some thinkers (John Aziz and Dan Bier the Skeptical Libertarian), they certainly come close to being pure adherents to scientism – that the scientific method can be used to solve all issues, regardless of logic.

    So I am not making any type of straw man. Theirs may not be the best of theories, but it certainly exists.

    It's clever you demean pure apriorism as a caricature of reality and then deny that the opposite does not exist whatsoever by the way.

    This article is not dedicated to upholding pure apriorism (to which I adhere) so I recommend Rothbard's essay on the topic from which I cite. Regardless, no theory, including empiricism, can at all exist first without the logical conclusion that data can, in fact, confirm someone's thought. In other words, data cannot prove itself true without some prior conclusion that it can do so. In a very brief, and admittedly simple, nutshell, that is the basis for radical apriorism.

    We are free to debate the origin of consciousness, though I remain unconvinced that our very mental cognition of ourselves and reality is the product of simple natural selection. Physicist and Nobel Prize winner Steven Weinberg recently had a piece in the New York Times Review of Books in which he postulated that much of the universe remains inexplicable to the human brain, and that we may never be able to understand it. Natural selection and evolutionary trends may explain this as well, but it seems there is something much more at work here.

    Of course, that’s all a much bigger question with bigger breadth that can be handled in a small comment section.

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