A Short History of Stupid

by Helen Razer

  As for the ‘fastest growing crime’ tag, the FBI used that description of cybercrime in the US a decade ago, and they haven’t used it since (because it’s not true), but it has taken on a life of its own since then, an unkillable factoid still to be found in politicians’ speeches, law enforcement statements and media reports.

  And the Stupid gets worse—much, much worse—when it comes to one specific type of ‘cybercrime’: software and content ‘piracy’. File sharing has by itself generated a mini-industry dedicated to proving its profoundly damaging economic effects, despite content industries continuing to perform strongly. The US broadcasting industry’s revenue has risen 22 per cent since 2009 to hit a record US$121 billion in 2012. Worldwide movie ticket sales have soared in recent years—in 2013 they set a new global record of US$36 billion and ticket sales have risen 22 per cent since 2009—and while the music industry has seen steady decline in sales of recorded music in recent years, global live music sales have smashed previous highs, with an all-time record $4.8 billion spent in concert ticket sales in 2013, a 30 per cent increase on 2012. But according to a litany of industry-funded studies, file sharing is on the verge of destroying those industries. According to a study prepared by an economics firm for an Australian film studio body in 2010,* file sharing would result in the loss of more than 8000 Australians jobs in content industries that year and cost those industries $900 million. ‘Nation of unrepentant pirates costs $900m’ was the scolding headline in an ensuing media report.

  But some basic checking would have raised significant questions about the report. Rather than falling, employment in both the creative and performing arts and motion picture and sound recording industry subsectors had, according to data from the Australian Bureau of Statistics, steadily risen over the decade to 2010, despite the alleged impact of movie piracy (first via pirated DVDs—a now almost-forgotten form of crime, like wreckers luring ships onto rocks—then online). In 1999, employment in Australia’s creative industries averaged 27,000 people over the year and motion picture production 22,000. In 2013, they averaged 41,000 and 27,000 jobs respectively. More Australians are employed making films and in the creative industries now than when, courtesy of a dirt-cheap Australian dollar, George Lucas made those wretched Star Wars prequels here.† Further, the numbers were different to those in another report by another economics firm for another content industry group mere months earlier, which concluded movie piracy cost Australia $551 million and caused the loss of 6000 jobs across the whole economy.

  Okay, so you say 6000, I say 8000—there’s not such a big difference . . . but there had been another report four years earlier showing piracy cost the Australian movie industry just $230 million annually in Australia. However, the US authors of that report later admitted they’d got some basic calculations wrong and inflated their estimates. And when that first report, the 8000 jobs one, was eventually released for public scrutiny—the journalist who wrote the story at the time hadn’t seen the report, just been told what was in it—it was revealed the report was simply the application of data from a European report to Australia, without any attempt to use local data or take local circumstances into account. Worse, the source report—the European report, yes, I know it’s hard to keep track, but as I said, there’s an entire mini-industry producing these—had been discredited, particularly its prediction that piracy would cause the loss of 1.2 million jobs in creative industries in Europe. In 2013, the EU was lauding its creative industries as an important and, for the Europeans, all too rare, source of economic growth.

  All right, all right, the blur of numbers is getting too much. And a generous soul, seeking to explain such inconsistencies, might think that there’s just something innately difficult to calculate about the internet, what with it being cyber and virtual and borderless and everything having to be calculated, presumably, in binary numbers. But increasingly we have a broader environment of all kinds of public debate in which statistics and economic data are routinely invented or manipulated, and contrary data ignored, in the service of a preferred narrative that suits specific interests, including the media’s. Across dozens of diverse public policy issues, we’re awash in all kinds of rubbish numbers about jobs and costs gleaned from misused data, absurd economic modelling and nonsensical reports produced by vested interests and handed to a gullible or collusive media for reporting.

  Like ever-rising levels of crime, there are some numerical claims that draw their strength from being incessantly repeated despite being contradicted by reality, and these routinely feature in the media and in political polemic. Like crime, suicide is regularly claimed by the media to be rising to ‘epidemic’ levels, when, as we have seen, it has fallen dramatically in Australia over the last two decades in the non-indigenous community, and remained at about the same (far too high) level among indigenous people. Since the Howard government’s hard-line industrial relations regime was replaced by a more employee-friendly system by a Labor government in 2008, employer groups and conservative politicians have been regularly warning that it would lead to fewer jobs, lower productivity, unsustainable wage rises and union militancy. In fact, 2010 and 2013 both saw the second-lowest level of industrial disputes since records began in the 1980s; labour productivity grew significantly faster under the new system compared to under the Howard government, when it stagnated or fell; 2013 was the lowest year for wages growth in Australia on record; and over 700,000 jobs had been created under the new system. Nonetheless, the claims continue to be made regardless of their inaccuracy, with claims of a ‘productivity crisis’ and ‘wages explosion’.

  But the primary abuse of numbers in public debate relates to their manipulation and invention. And so persistent and widespread is this form of Stupid that we can list the dodgy techniques that are used over and over again in public debate by those who try to use numbers in their own interests. These are just a few:

  The reverse magic pudding

  Norman Lindsay’s beloved Magic Pudding would always re-form into a pudding no matter how often he was eaten, providing a handy metaphor for generations of Australian economists and politicians, who would often accuse their opponents of ‘Magic Pudding economics’. But a staple of bogus economic numbers is a reversal of this—a peculiar form of commerce in which money lost from one industry (invariably, the industry that has paid for the report concerned) never goes anywhere else, but instead entirely vanishes from the economy, a pudding that magically consumes itself if no one else does.

  Thus, the money lost from content industries because of piracy, for example, is assumed to simply disappear, unspent. A consumer who had downloaded something for free rather than paying the content industry’s inflated prices forever retains the money they might have spent buying the CD or DVD or going to the cinema. They don’t put it in the bank, where it might add to savings that can be used for investment; they don’t spend it watching other movies or buying other music (in fact, there’s evidence file sharers spend considerably more money buying music than those who don’t also download it for free), nor do they spend it elsewhere, creating jobs and growth in other industries. It just sits there in their pockets, never touched again, or perhaps they bury it every time they download something, so it never flows to any other part of the industry or the economy.

  A variant on the reverse magic pudding is the type of report that argues government spending in a particular area would create thousands of new jobs both in that industry and, because of multipliers, in other industries as well—without mentioning that similar spending in other areas or industries might via other multipliers create more jobs, or that there may be greater benefits for the economy in governments reducing support for industries, curbing expenditure or cutting taxes.

  Economists debate the issue to this day, but some say multipliers are a branch of . . .

  Major event mathematics

  This is a special branch of applied mathematics, studied closely not in the halls of academe but in consultancies working for
governments and sporting bodies. This area deals with the remarkable properties of major event numbers, which do not comply with the ordinary laws of maths but instead have, rather like the additional dimensions of string theory, further layers of multiplication and an innate capacity to erase negative symbols. This is because, unlike conventional maths, major event maths works backwards from the answer you want to give you the numbers you need.

  Only in the arcane world of major event mathematics, for example, can the Melbourne Formula One grand prix, which costs the state of Victoria $50 million a year, somehow generate a net $30 million in economic benefits. Likewise, by employing major event mathematics, bidding cities always ignore the fact that nearly every host city ends up spending at least twice more than budgeted to host the Olympic Games and loses money doing so. It’s major event maths when builders of big road projects start from the traffic levels they need to make the project viable, then work backwards to their traffic forecasts. And when FIFA announces that 26 billion people have watched a soccer tournament on a planet with only 7 billion people, them’s major event numbers, presumably delighting advertisers who are reaching not merely every human on earth, but tens of billions of aliens as well.

  The inapt comparison

  This trick’s a clever one, because spotting it requires quite specialist knowledge or a willingness to go digging for information: use a comparison to make your case for you while not explaining all the ways in which the comparison is meaningless. Say you want to argue that costs in Australia’s construction industry are too high. But too high compared to what? Comparing them to Chinese or African building costs will alert even casual readers that you’re making a dodgy comparison. Why not the United States? It’s a developed country, just like Australia, and will make your point that Australia should reduce wages and introduce greater ‘workplace flexibility’. The only problem will be if someone bothers to check and spots that you’re comparing costs in something entirely inappropriate. You might compare Australian construction costs to costs in the Texas building industry, which is half the size of the entire Australian industry and thus benefits from huge economies of scale, and which relies on immigrant labour, much of it illegal, for more than a third of its workforce, and which has a workplace death rate many times higher than Australia’s. The comparison in fact is a proposal that Australia massively scale up its construction sector using illegal immigrants whom we don’t mind seeing killed.

  On the other hand, there are times when industries insist that it’s everyone else who is making the inapt comparisons. In response to a parliamentary inquiry into why software, content and IT products cost more in Australia—often 50 per cent more—than in the United States and other markets, companies like Microsoft, Apple and Adobe and the copyright industry argued that international comparisons, even for software and content that could be delivered online, were meaningless. Such comparisons were, in the words of Microsoft, ‘of limited use, as prices differ from country to country and across channels due to a range of factors’. There’s no point comparing prices internationally, you see, because they might be different.*

  The unrepresentative poll

  You’re an industry body eager to influence policy, but unfortunately you just can’t get the numbers to work for you, even with a reverse magic pudding or major event maths or using an inapt comparison. What to do? There’s always the opinions of your own members, which can be sampled at minimal expense if you’ve got their contact details: surveys of business executives on their expectations inevitably yield concerns about the rising cost of regulation, taxes and wages. That’s even the case when it is businesses themselves that have been bidding up the cost of labour, as happened during Australia’s resources boom, when resources firms competed with each other for a limited pool of skilled labour to build new mining and extraction projects.

  Or you’re a PR firm looking for a cheap’n’cheerful way to generate some coverage for a client. How about a quick survey of their customers, preferably on something inanely ‘fun’ or related to sex so that the media will pick it up? Who knows, it might be a slow news day or get picked up on social media and ‘go viral’.

  Not that such exercises have to be the preserve of hard-up industry bodies or inspirationless PR firms. The prestigious World Economic Forum Competitiveness Report is regularly cited by chin-stroking business figures and commentators from around the world as an important insight into how different economies compare when it comes to how governments can make life easier for business. What’s never mentioned is that much of the report is based on the responses of a handful of business executives in each country, rather than any objective assessment of regulatory practices. This meant that in the 2012 report, a small number (fewer than seventy) Australian executives rated Australia, then under a Labor government, worse for government nepotism than Saudi Arabia, which is run by a single family; they rated Australia lower on ‘trust in government’ than Bahrain, where anti-government protesters are butchered and jailed; and they rated Australia’s judiciary as less independent than that of Qatar. Of course, given that senior Gulf state business executives are usually related to, or are themselves, key government figures, such results aren’t surprising.

  Adventures in time

  Want to discredit a policy that has no significant impacts in the short term? Two of the most widely used tricks in Australia involve time-travel economics. Don’t be intimidated, it’s dead easy: compare the industry employment outcomes from a modelled scenario with a business-as-usual scenario (employing the reverse magic pudding of course) and declare that a particular policy will ‘cost thousands of jobs’, as though thousands of workers in an industry will be sacked tomorrow, even when the relevant industry will in fact grow, just at a slightly lower rate than under the business-as-usual scenario and thus produce slightly fewer additional future jobs than otherwise.

  Alternatively, compare the GDP outcomes from the modelled scenario with the GDP outcome of the business-as-usual scenario, do so over a period long enough to generate a substantial difference—say, fifty years—and then use the difference in GDP fifty years hence to claim that a policy will ‘shrink the economy by X per cent’, as though we’ll immediately enter a prolonged recession rather than have a minutely slower growth path over decades.

  Better yet, the really clever will calculate the per capita or per household GDP ‘loss’ and use that figure to warn that a policy will cost each household—cost you!—thousands of dollars, giving the impression families will somehow be stripped of income or have assets seized in a midnight raid.

  Both of these tricks have been repeatedly used to attack climate change policies in Australia, and have made a comeback under Australia’s new climate change denialist conservative government, which since its election in 2013 has claimed a carbon price will reduce GDP by $1 trillion ‘over the next few decades’—without mentioning that’s actually a difference of 1–2 per cent of total GDP between now and 2050.

  Social costs

  Jealous that business groups and large companies were having all the fun with dodgy modelling, in recent years NGOs, research institutes and non-profit lobby groups decided to get into the action themselves and created a new sub-industry around modelling the ‘social costs’ of various undesirable things such as alcohol or illnesses deemed not to be attracting sufficient research funding from governments. ‘Social costs’ in this instance isn’t used in the narrow economic sense, but consists of a more nebulous mix of externalities, economic costs (lost productivity, mainly), fiscal costs to taxpayers via the health system or criminal justice system, estimates of economic loss associated with illness and premature death, and reverse magic pudding costs that are actually expenditure for other sectors of the economy—out-of-pocket medical costs for unfunded treatment for illnesses, for example.

  In Australia, economists working for public health groups have thus estimated that the costs of various problems run into the many hundreds of billions. Drug use, for ex
ample, is said to cost Australia $56 billion a year. Eating disorders have been estimated to cost $70 billion a year; obesity was calculated to cost over $50 billion a year in ‘lost wellbeing’ (the comparable US estimate was $190 billion). Alzheimer’s disease is predicted to cost Australia over $ 80 billion a year in the 2060s (adventures-in-time alert!). Depression costs $13 billion a year, illiteracy is said to cost $18 billion, stress nearly $15 billion—even insomnia costs nearly $15 billion, we’re told.

  All of these are real problems affecting the lives of people and, indeed, possibly reducing their productivity or sending them to early graves. But the procession of claims about their ‘social cost’ has the cumulative effect of suggesting that the best way to massively expand the GDPs of Western economies would be to send the entire population to the gym and counsellors.

  The politics of political arithmetic

  Concerns about this form of Stupid long predate the emergence of economic modelling and polling in the twentieth century. As the quote from Adam Smith that begins this chapter indicates, the provenance and accuracy of the calculation of statistics have been disputed almost from their inception. Moreover, the original name, ‘political arithmetic’, was enormously significant—‘statistics’ as a name didn’t catch on until an enterprising Scotsman, John Sinclair, rebranded ‘political arithmetic’ using a German term for qualitative (as opposed to quantitative) descriptions of the characteristics of states (states . . . statistics . . . geddit?).