Economics today is a respected (for the most part) field of work, which has its own Nobel prizes, professors and specialized departments in every major university, learned journals and lengthy tomes in bookstores, pundits on the television and web, and so on. And much of the area of economics is sensible and necessary, and we have no better tool for analyzing and predicting economic outcomes. But some, perhaps much of this is but a house of cards and we’ll see the end of at least some of the discipline, soon. Or, at very least, we will see swept away the false constructs of a self-infatuated theoretical belief system, to be replaced only with analytics of the biggest of “big data”.
There can be few more important challenges to the standing of economics as a respected discipline than these, which I’ll touch on here:
- The increasing apparent weakness (some would say complete falsehood) of some of the founding precepts of economics
- The reactions of a core group of leading academics to the revelation that their analyses and theses were wrong, completely wrong, and based on inadequate data, incompletely analyzed.
- Nonsensical data being used – if only because there’s no substitute
- The increasing power of “big data” analytic tools - but I'll leave that for another time.
The title of this piece cites a saying ascribed to 1930s-era German theoretical physicist Wolfgang Pauli, whom upon reviewing a naïve, neophyte paper is said to have remarked: "Das ist nicht nur nicht richtig, es ist nicht einmal falsch!": this is not only not right, it is not even wrong. Meaning – there was nothing in the paper that could be considered to be verifiable, and thus the paper was utterly useless – or that its ideas were unconnected to any known reality. The saying seems particularly appropriate for the current state of some of orthodox economics, Nobel prizes and munificently-endowed university chairs notwithstanding.
1. Problems with the Precepts
You know a discipline is in trouble when some of its founding precepts are at once inviolate a priori assumptions and clearly on thin ice. In the case of economics, principles that were espoused as long ago as the 17th and 18th century falter when they’re used as rigorous mathematical or logical laws and fail the test.
Few assumptions are as central to orthodox economics than the law of supply and demand, the assumption that markets are efficient, the depiction of individuals as acting only in their rational self interest, economic equilibrium, …
The law of supply and demand is central to the modeling constructs of economics. As a common-sense argument it has been understood since at least the time of John Locke in the late 17th century, and perhaps much earlier. Locke’s statement: The price of any commodity rises or falls by the proportion of the number of buyer and sellers” and “that which regulates the price... [of goods] is nothing else but their quantity in proportion to their rent.” Makes sense! Or, at least, it MADE sense. Then, in an agrarian society, increasing demand meant that farmers had to grow crops with no increase in operational efficiency on farmland that was less fertile. Thus, the yields dropped and their marginal costs rose. Demand goes up, prices go up. By the time of the iPhone, in a mass-production system, as demand rises, yields in manufacture also increase and marginal costs drop. Demand goes up, prices go down. (And then there are application, content and related service markets, where the marginal cost is nearlyzero anyway.)
Yet the original ideas became articulated as specific mathematical rules so that economists can build mathematical models of economics. This is where we enter dangerous territory. Cutting through the complex but interesting arguments, the problem is that assumptions required to build out the tenets of supply-and-demand into an equilibrium model are logically inconsistent, except under implausible circumstances.
Similarly, since the time of Adam Smith, and with varying rigor since, economists have assumed that individuals act only in their rational, economic self interest. But how does this square with people who give to the poor, dedicate their lives to others – sometimes expressly contrary to the attainment of their highest financial success? How do we look at men and women who become soldiers, volunteer fire-fighters, artists and poets, scholars of ancient languages, mathematicians? And how do we deal with the many, many writings that espouse – as the noblest role in life – helping others? “there is no higher goal than serving humanity.” The unassailable and awkward answer is that humans don’t just act as economic robots.
2. The case of the dodgy deductions
There are few more compelling arguments against the validity of modern economics than the affair of the inadequate data and analysis by Harvard economists Carmen M. Reinhart and Kenneth Rogoff. In brief, Reinhart and Rogoff argued that expanding national debt had a strong, statistically significant impact on economic growth: “Our main result is that whereas the link between growth and debt seems relatively weak at “normal” debt levels, median growth rates for countries with public debt over roughly 90 percent of GDP are about one percent lower than otherwise; average (mean) growth rates are several percent lower. Surprisingly, the relationship between public debt and growth is remarkably similar across emerging markets and advanced economies.” This analysis became the centerpiece of arguments against Keynesian stimulus programs and unleashed a wave of austerity programs worldwide, and gave fodder to small-government arguments.
The first problem is: their analysis was wrong, badly wrong. The second problem is – the consequences for Reinhart and Rogoff were minimal – no visible chastisement from the field of economics, no calling to account by Harvard.
This in any other field should have been a career-ending blunder. A pair of strong advocates of a specific economic approach make THREE SEPARATE errors, all skewing the data's outcome in the same direction, all rather conveniently moving the analytical outcome in one direction that happens to coincide with their political aim. At very best, this is a combination of Confirmation Bias with sloppy data selection, entry and analysis. At very best. In normal firms or institutions these mistakes would be caught during internal review. They were not. Or in peer review- but there was none. One would hope that, in prestigious firms or institutions, these mistakes would have consequences. There were none.
Which all makes economics look more like a kind of religion, in which those who challenge orthodox statements from the field's leaders are banished from the church, where there was no way anyone with tenure or field honors at stake would challenge it. This episode, including the lack of any real consequences for a mistake that likely devastated the lives of tens of millions, casts into doubt the legitimacy of the entire field.
3. Bad data, but the only data we have
Some years ago, an analyst working for me observed that our firm’s ability to project Asian telecom expenditures was in trouble, because the Chinese data looked odd. Specifically, the annual totals of Chinese mobile subscribers increased each year by PRECISELY the percentage predicted in the then-current five-year plan. A little later, a research project ran into a similar roadblock: it is (or at least was) forbidden to do actual consumer surveys of Chinese citizens, except through official government bodies. The Chinese government seems so nervous about statistics about problems in the economy that external estimates of Chinese unemployment differ from official statistics by a factor of two or more. Indeed, Chinese government officials have acknowledged that their pronouncements on, and bodies of data describing, the Chinese economy, are “for guidance purposes only”.
So, here we are, with the Chinese economy now the world’s second largest and almost all the ‘data’ we have describing it are wrong or misleading or concocted or …
China is not the only nation that cooks the books in this way, although it may be the largest x the most egregious. (It’s widely believed, for example, that the requirement that the US Federal Government adjust certain expenditures for increases in the cost of living has had the effect of encouraging the government to under-report the rate of inflation.) Now, imagine the challenges of trying to build decent models of global economic behaviors when you KNOW that the second-largest data set is entirely bad data, and the only excuse anyone can offer is: “but they’re the only data we have”.
4. The rise of big data
This, I think, I’ll tackle another day …
 http://www.quora.com/Life/Im-16-And-I-want-to-serve-humanity-but-where-to-start/answer/George-Moromisato Not a famous writer, but it’s a nice line.
 scholar.harvard.edu/files/rogoff/files/growth_in_time_debt_aer.pdf from Google Books
 Thanks, Alie, for noticing this.